close()
Close httplib2 connections.
- delete(projectId, datasetId, deleteContents=None)
delete(projectId, datasetId, deleteContents=None, x__xgafv=None)
Deletes the dataset specified by the datasetId value. Before you can delete a dataset, you must delete all its tables, either manually or by specifying deleteContents. Immediately after deletion, you can create another dataset with the same name.
- get(projectId, datasetId, datasetView=None)
get(projectId, datasetId, datasetView=None, x__xgafv=None)
Returns the dataset specified by datasetID.
- insert(projectId, body=None)
insert(projectId, body=None, x__xgafv=None)
Creates a new empty dataset.
- list(projectId, all=None, filter=None, maxResults=None, pageToken=None)
Lists all datasets in the specified project to which you have been granted the READER dataset role.
+list(projectId, all=None, filter=None, maxResults=None, pageToken=None, x__xgafv=None)
+Lists all datasets in the specified project to which the user has been granted the READER dataset role.
Retrieves the next page of results.
- patch(projectId, datasetId, body=None)
Updates information in an existing dataset. The update method replaces the entire dataset resource, whereas the patch method only replaces fields that are provided in the submitted dataset resource. This method supports patch semantics.
+patch(projectId, datasetId, body=None, x__xgafv=None)
+Updates information in an existing dataset. The update method replaces the entire dataset resource, whereas the patch method only replaces fields that are provided in the submitted dataset resource. This method supports RFC5789 patch semantics.
- update(projectId, datasetId, body=None)
undelete(projectId, datasetId, body=None, x__xgafv=None)
+Undeletes a dataset which is within time travel window based on datasetId. If a time is specified, the dataset version deleted at that time is undeleted, else the last live version is undeleted.
+
+ update(projectId, datasetId, body=None, x__xgafv=None)
Updates information in an existing dataset. The update method replaces the entire dataset resource, whereas the patch method only replaces fields that are provided in the submitted dataset resource.
delete(projectId, datasetId, deleteContents=None)
+ delete(projectId, datasetId, deleteContents=None, x__xgafv=None)
Deletes the dataset specified by the datasetId value. Before you can delete a dataset, you must delete all its tables, either manually or by specifying deleteContents. Immediately after deletion, you can create another dataset with the same name. Args: - projectId: string, Project ID of the dataset being deleted (required) - datasetId: string, Dataset ID of dataset being deleted (required) + projectId: string, Required. Project ID of the dataset being deleted (required) + datasetId: string, Required. Dataset ID of dataset being deleted (required) deleteContents: boolean, If True, delete all the tables in the dataset. If False and the dataset contains tables, the request will fail. Default is False + x__xgafv: string, V1 error format. + Allowed values + 1 - v1 error format + 2 - v2 error format
get(projectId, datasetId, datasetView=None)
+ get(projectId, datasetId, datasetView=None, x__xgafv=None)
Returns the dataset specified by datasetID.
Args:
- projectId: string, Project ID of the requested dataset (required)
- datasetId: string, Dataset ID of the requested dataset (required)
- datasetView: string, Specifies the view that determines which dataset information is returned. By default, metadata and ACL information are returned. Allowed values: METADATA, ACL, FULL.
+ projectId: string, Required. Project ID of the requested dataset (required)
+ datasetId: string, Required. Dataset ID of the requested dataset (required)
+ datasetView: string, Optional. Specifies the view that determines which dataset information is returned. By default, metadata and ACL information are returned.
+ Allowed values
+ DATASET_VIEW_UNSPECIFIED - The default value. Default to the FULL view.
+ METADATA - Includes metadata information for the dataset, such as location, etag, lastModifiedTime, etc.
+ ACL - Includes ACL information for the dataset, which defines dataset access for one or more entities.
+ FULL - Includes both dataset metadata and ACL information.
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
Returns:
An object of the form:
{
- "access": [ # [Optional] An array of objects that define dataset access for one or more entities. You can set this property when inserting or updating a dataset in order to control who is allowed to access the data. If unspecified at dataset creation time, BigQuery adds default dataset access for the following entities: access.specialGroup: projectReaders; access.role: READER; access.specialGroup: projectWriters; access.role: WRITER; access.specialGroup: projectOwners; access.role: OWNER; access.userByEmail: [dataset creator email]; access.role: OWNER;
- {
- "dataset": { # [Pick one] A grant authorizing all resources of a particular type in a particular dataset access to this dataset. Only views are supported for now. The role field is not required when this field is set. If that dataset is deleted and re-created, its access needs to be granted again via an update operation.
- "dataset": { # [Required] The dataset this entry applies to.
- "datasetId": "A String", # [Required] A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- "projectId": "A String", # [Optional] The ID of the project containing this dataset.
+ "access": [ # Optional. An array of objects that define dataset access for one or more entities. You can set this property when inserting or updating a dataset in order to control who is allowed to access the data. If unspecified at dataset creation time, BigQuery adds default dataset access for the following entities: access.specialGroup: projectReaders; access.role: READER; access.specialGroup: projectWriters; access.role: WRITER; access.specialGroup: projectOwners; access.role: OWNER; access.userByEmail: [dataset creator email]; access.role: OWNER;
+ { # An object that defines dataset access for an entity.
+ "dataset": { # Grants all resources of particular types in a particular dataset read access to the current dataset. Similar to how individually authorized views work, updates to any resource granted through its dataset (including creation of new resources) requires read permission to referenced resources, plus write permission to the authorizing dataset. # [Pick one] A grant authorizing all resources of a particular type in a particular dataset access to this dataset. Only views are supported for now. The role field is not required when this field is set. If that dataset is deleted and re-created, its access needs to be granted again via an update operation.
+ "dataset": { # The dataset this entry applies to
+ "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "projectId": "A String", # Optional. The ID of the project containing this dataset.
},
- "targetTypes": [
+ "targetTypes": [ # Which resources in the dataset this entry applies to. Currently, only views are supported, but additional target types may be added in the future.
"A String",
],
},
"domain": "A String", # [Pick one] A domain to grant access to. Any users signed in with the domain specified will be granted the specified access. Example: "example.com". Maps to IAM policy member "domain:DOMAIN".
"groupByEmail": "A String", # [Pick one] An email address of a Google Group to grant access to. Maps to IAM policy member "group:GROUP".
"iamMember": "A String", # [Pick one] Some other type of member that appears in the IAM Policy but isn't a user, group, domain, or special group.
- "role": "A String", # [Required] An IAM role ID that should be granted to the user, group, or domain specified in this access entry. The following legacy mappings will be applied: OWNER roles/bigquery.dataOwner WRITER roles/bigquery.dataEditor READER roles/bigquery.dataViewer This field will accept any of the above formats, but will return only the legacy format. For example, if you set this field to "roles/bigquery.dataOwner", it will be returned back as "OWNER".
- "routine": { # [Pick one] A routine from a different dataset to grant access to. Queries executed against that routine will have read access to views/tables/routines in this dataset. Only UDF is supported for now. The role field is not required when this field is set. If that routine is updated by any user, access to the routine needs to be granted again via an update operation.
+ "role": "A String", # An IAM role ID that should be granted to the user, group, or domain specified in this access entry. The following legacy mappings will be applied: OWNER <=> roles/bigquery.dataOwner WRITER <=> roles/bigquery.dataEditor READER <=> roles/bigquery.dataViewer This field will accept any of the above formats, but will return only the legacy format. For example, if you set this field to "roles/bigquery.dataOwner", it will be returned back as "OWNER".
+ "routine": { # Id path of a routine. # [Pick one] A routine from a different dataset to grant access to. Queries executed against that routine will have read access to views/tables/routines in this dataset. Only UDF is supported for now. The role field is not required when this field is set. If that routine is updated by any user, access to the routine needs to be granted again via an update operation.
"datasetId": "A String", # Required. The ID of the dataset containing this routine.
"projectId": "A String", # Required. The ID of the project containing this routine.
"routineId": "A String", # Required. The ID of the routine. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 256 characters.
},
"specialGroup": "A String", # [Pick one] A special group to grant access to. Possible values include: projectOwners: Owners of the enclosing project. projectReaders: Readers of the enclosing project. projectWriters: Writers of the enclosing project. allAuthenticatedUsers: All authenticated BigQuery users. Maps to similarly-named IAM members.
"userByEmail": "A String", # [Pick one] An email address of a user to grant access to. For example: fred@example.com. Maps to IAM policy member "user:EMAIL" or "serviceAccount:EMAIL".
- "view": { # [Pick one] A view from a different dataset to grant access to. Queries executed against that view will have read access to tables in this dataset. The role field is not required when this field is set. If that view is updated by any user, access to the view needs to be granted again via an update operation.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "view": { # [Pick one] A view from a different dataset to grant access to. Queries executed against that view will have read access to views/tables/routines in this dataset. The role field is not required when this field is set. If that view is updated by any user, access to the view needs to be granted again via an update operation.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
},
],
- "creationTime": "A String", # [Output-only] The time when this dataset was created, in milliseconds since the epoch.
- "datasetReference": { # [Required] A reference that identifies the dataset.
- "datasetId": "A String", # [Required] A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- "projectId": "A String", # [Optional] The ID of the project containing this dataset.
+ "creationTime": "A String", # Output only. The time when this dataset was created, in milliseconds since the epoch.
+ "datasetReference": { # Required. A reference that identifies the dataset.
+ "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "projectId": "A String", # Optional. The ID of the project containing this dataset.
},
- "defaultCollation": "A String", # [Output-only] The default collation of the dataset.
- "defaultEncryptionConfiguration": {
+ "defaultCollation": "A String", # Optional. Defines the default collation specification of future tables created in the dataset. If a table is created in this dataset without table-level default collation, then the table inherits the dataset default collation, which is applied to the string fields that do not have explicit collation specified. A change to this field affects only tables created afterwards, and does not alter the existing tables. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.
+ "defaultEncryptionConfiguration": { # The default encryption key for all tables in the dataset. Once this property is set, all newly-created partitioned tables in the dataset will have encryption key set to this value, unless table creation request (or query) overrides the key.
"kmsKeyName": "A String", # Optional. Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key.
},
- "defaultPartitionExpirationMs": "A String", # [Optional] The default partition expiration for all partitioned tables in the dataset, in milliseconds. Once this property is set, all newly-created partitioned tables in the dataset will have an expirationMs property in the timePartitioning settings set to this value, and changing the value will only affect new tables, not existing ones. The storage in a partition will have an expiration time of its partition time plus this value. Setting this property overrides the use of defaultTableExpirationMs for partitioned tables: only one of defaultTableExpirationMs and defaultPartitionExpirationMs will be used for any new partitioned table. If you provide an explicit timePartitioning.expirationMs when creating or updating a partitioned table, that value takes precedence over the default partition expiration time indicated by this property.
- "defaultRoundingMode": "A String", # [Output-only] The default rounding mode of the dataset.
- "defaultTableExpirationMs": "A String", # [Optional] The default lifetime of all tables in the dataset, in milliseconds. The minimum value is 3600000 milliseconds (one hour). Once this property is set, all newly-created tables in the dataset will have an expirationTime property set to the creation time plus the value in this property, and changing the value will only affect new tables, not existing ones. When the expirationTime for a given table is reached, that table will be deleted automatically. If a table's expirationTime is modified or removed before the table expires, or if you provide an explicit expirationTime when creating a table, that value takes precedence over the default expiration time indicated by this property.
- "description": "A String", # [Optional] A user-friendly description of the dataset.
- "etag": "A String", # [Output-only] A hash of the resource.
- "externalDatasetReference": { # [Optional] Information about the external metadata storage where the dataset is defined. Filled out when the dataset type is EXTERNAL.
- "connection": "A String", # [Required] The connection id that is used to access the external_source. Format: projects/{project_id}/locations/{location_id}/connections/{connection_id}
- "externalSource": "A String", # [Required] External source that backs this dataset.
- },
- "friendlyName": "A String", # [Optional] A descriptive name for the dataset.
- "id": "A String", # [Output-only] The fully-qualified unique name of the dataset in the format projectId:datasetId. The dataset name without the project name is given in the datasetId field. When creating a new dataset, leave this field blank, and instead specify the datasetId field.
- "isCaseInsensitive": True or False, # [Optional] Indicates if table names are case insensitive in the dataset.
- "kind": "bigquery#dataset", # [Output-only] The resource type.
+ "defaultPartitionExpirationMs": "A String", # This default partition expiration, expressed in milliseconds. When new time-partitioned tables are created in a dataset where this property is set, the table will inherit this value, propagated as the `TimePartitioning.expirationMs` property on the new table. If you set `TimePartitioning.expirationMs` explicitly when creating a table, the `defaultPartitionExpirationMs` of the containing dataset is ignored. When creating a partitioned table, if `defaultPartitionExpirationMs` is set, the `defaultTableExpirationMs` value is ignored and the table will not be inherit a table expiration deadline.
+ "defaultRoundingMode": "A String", # Optional. Defines the default rounding mode specification of new tables created within this dataset. During table creation, if this field is specified, the table within this dataset will inherit the default rounding mode of the dataset. Setting the default rounding mode on a table overrides this option. Existing tables in the dataset are unaffected. If columns are defined during that table creation, they will immediately inherit the table's default rounding mode, unless otherwise specified.
+ "defaultTableExpirationMs": "A String", # Optional. The default lifetime of all tables in the dataset, in milliseconds. The minimum lifetime value is 3600000 milliseconds (one hour). To clear an existing default expiration with a PATCH request, set to 0. Once this property is set, all newly-created tables in the dataset will have an expirationTime property set to the creation time plus the value in this property, and changing the value will only affect new tables, not existing ones. When the expirationTime for a given table is reached, that table will be deleted automatically. If a table's expirationTime is modified or removed before the table expires, or if you provide an explicit expirationTime when creating a table, that value takes precedence over the default expiration time indicated by this property.
+ "description": "A String", # Optional. A user-friendly description of the dataset.
+ "etag": "A String", # Output only. A hash of the resource.
+ "externalDatasetReference": { # Configures the access a dataset defined in an external metadata storage. # Optional. Information about the external metadata storage where the dataset is defined. Filled out when the dataset type is EXTERNAL.
+ "connection": "A String", # Required. The connection id that is used to access the external_source. Format: projects/{project_id}/locations/{location_id}/connections/{connection_id}
+ "externalSource": "A String", # Required. External source that backs this dataset.
+ },
+ "friendlyName": "A String", # Optional. A descriptive name for the dataset.
+ "id": "A String", # Output only. The fully-qualified unique name of the dataset in the format projectId:datasetId. The dataset name without the project name is given in the datasetId field. When creating a new dataset, leave this field blank, and instead specify the datasetId field.
+ "isCaseInsensitive": True or False, # Optional. TRUE if the dataset and its table names are case-insensitive, otherwise FALSE. By default, this is FALSE, which means the dataset and its table names are case-sensitive. This field does not affect routine references.
+ "kind": "bigquery#dataset", # Output only. The resource type.
"labels": { # The labels associated with this dataset. You can use these to organize and group your datasets. You can set this property when inserting or updating a dataset. See Creating and Updating Dataset Labels for more information.
"a_key": "A String",
},
- "lastModifiedTime": "A String", # [Output-only] The date when this dataset or any of its tables was last modified, in milliseconds since the epoch.
- "location": "A String", # The geographic location where the dataset should reside. The default value is US. See details at https://cloud.google.com/bigquery/docs/locations.
- "maxTimeTravelHours": "A String", # [Optional] Number of hours for the max time travel for all tables in the dataset.
- "satisfiesPzs": True or False, # [Output-only] Reserved for future use.
- "selfLink": "A String", # [Output-only] A URL that can be used to access the resource again. You can use this URL in Get or Update requests to the resource.
- "storageBillingModel": "A String", # [Optional] Storage billing model to be used for all tables in the dataset. Can be set to PHYSICAL. Default is LOGICAL.
- "tags": [ # [Optional]The tags associated with this dataset. Tag keys are globally unique.
- {
- "tagKey": "A String", # [Required] The namespaced friendly name of the tag key, e.g. "12345/environment" where 12345 is org id.
- "tagValue": "A String", # [Required] Friendly short name of the tag value, e.g. "production".
+ "lastModifiedTime": "A String", # Output only. The date when this dataset was last modified, in milliseconds since the epoch.
+ "linkedDatasetSource": { # A dataset source type which refers to another BigQuery dataset. # Optional. The source dataset reference when the dataset is of type LINKED. For all other dataset types it is not set. This field cannot be updated once it is set. Any attempt to update this field using Update and Patch API Operations will be ignored.
+ "sourceDataset": { # The source dataset reference contains project numbers and not project ids.
+ "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "projectId": "A String", # Optional. The ID of the project containing this dataset.
+ },
+ },
+ "location": "A String", # The geographic location where the dataset should reside. See https://cloud.google.com/bigquery/docs/locations for supported locations.
+ "maxTimeTravelHours": "A String", # Optional. Defines the time travel window in hours. The value can be from 48 to 168 hours (2 to 7 days). The default value is 168 hours if this is not set.
+ "satisfiesPzs": True or False, # Output only. Reserved for future use.
+ "selfLink": "A String", # Output only. A URL that can be used to access the resource again. You can use this URL in Get or Update requests to the resource.
+ "storageBillingModel": "A String", # Optional. Updates storage_billing_model for the dataset.
+ "tags": [ # Output only. Tags for the Dataset.
+ { # A global tag managed by Resource Manager. https://cloud.google.com/iam/docs/tags-access-control#definitions
+ "tagKey": "A String", # Required. The namespaced friendly name of the tag key, e.g. "12345/environment" where 12345 is org id.
+ "tagValue": "A String", # Required. The friendly short name of the tag value, e.g. "production".
},
],
+ "type": "A String", # Output only. Same as `type` in `ListFormatDataset`. The type of the dataset, one of: * DEFAULT - only accessible by owner and authorized accounts, * PUBLIC - accessible by everyone, * LINKED - linked dataset, * EXTERNAL - dataset with definition in external metadata catalog. -- *BIGLAKE_METASTORE - dataset that references a database created in BigLakeMetastore service. --
}
insert(projectId, body=None)
+ insert(projectId, body=None, x__xgafv=None)
Creates a new empty dataset.
Args:
- projectId: string, Project ID of the new dataset (required)
+ projectId: string, Required. Project ID of the new dataset (required)
body: object, The request body.
The object takes the form of:
{
- "access": [ # [Optional] An array of objects that define dataset access for one or more entities. You can set this property when inserting or updating a dataset in order to control who is allowed to access the data. If unspecified at dataset creation time, BigQuery adds default dataset access for the following entities: access.specialGroup: projectReaders; access.role: READER; access.specialGroup: projectWriters; access.role: WRITER; access.specialGroup: projectOwners; access.role: OWNER; access.userByEmail: [dataset creator email]; access.role: OWNER;
- {
- "dataset": { # [Pick one] A grant authorizing all resources of a particular type in a particular dataset access to this dataset. Only views are supported for now. The role field is not required when this field is set. If that dataset is deleted and re-created, its access needs to be granted again via an update operation.
- "dataset": { # [Required] The dataset this entry applies to.
- "datasetId": "A String", # [Required] A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- "projectId": "A String", # [Optional] The ID of the project containing this dataset.
+ "access": [ # Optional. An array of objects that define dataset access for one or more entities. You can set this property when inserting or updating a dataset in order to control who is allowed to access the data. If unspecified at dataset creation time, BigQuery adds default dataset access for the following entities: access.specialGroup: projectReaders; access.role: READER; access.specialGroup: projectWriters; access.role: WRITER; access.specialGroup: projectOwners; access.role: OWNER; access.userByEmail: [dataset creator email]; access.role: OWNER;
+ { # An object that defines dataset access for an entity.
+ "dataset": { # Grants all resources of particular types in a particular dataset read access to the current dataset. Similar to how individually authorized views work, updates to any resource granted through its dataset (including creation of new resources) requires read permission to referenced resources, plus write permission to the authorizing dataset. # [Pick one] A grant authorizing all resources of a particular type in a particular dataset access to this dataset. Only views are supported for now. The role field is not required when this field is set. If that dataset is deleted and re-created, its access needs to be granted again via an update operation.
+ "dataset": { # The dataset this entry applies to
+ "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "projectId": "A String", # Optional. The ID of the project containing this dataset.
},
- "targetTypes": [
+ "targetTypes": [ # Which resources in the dataset this entry applies to. Currently, only views are supported, but additional target types may be added in the future.
"A String",
],
},
"domain": "A String", # [Pick one] A domain to grant access to. Any users signed in with the domain specified will be granted the specified access. Example: "example.com". Maps to IAM policy member "domain:DOMAIN".
"groupByEmail": "A String", # [Pick one] An email address of a Google Group to grant access to. Maps to IAM policy member "group:GROUP".
"iamMember": "A String", # [Pick one] Some other type of member that appears in the IAM Policy but isn't a user, group, domain, or special group.
- "role": "A String", # [Required] An IAM role ID that should be granted to the user, group, or domain specified in this access entry. The following legacy mappings will be applied: OWNER roles/bigquery.dataOwner WRITER roles/bigquery.dataEditor READER roles/bigquery.dataViewer This field will accept any of the above formats, but will return only the legacy format. For example, if you set this field to "roles/bigquery.dataOwner", it will be returned back as "OWNER".
- "routine": { # [Pick one] A routine from a different dataset to grant access to. Queries executed against that routine will have read access to views/tables/routines in this dataset. Only UDF is supported for now. The role field is not required when this field is set. If that routine is updated by any user, access to the routine needs to be granted again via an update operation.
+ "role": "A String", # An IAM role ID that should be granted to the user, group, or domain specified in this access entry. The following legacy mappings will be applied: OWNER <=> roles/bigquery.dataOwner WRITER <=> roles/bigquery.dataEditor READER <=> roles/bigquery.dataViewer This field will accept any of the above formats, but will return only the legacy format. For example, if you set this field to "roles/bigquery.dataOwner", it will be returned back as "OWNER".
+ "routine": { # Id path of a routine. # [Pick one] A routine from a different dataset to grant access to. Queries executed against that routine will have read access to views/tables/routines in this dataset. Only UDF is supported for now. The role field is not required when this field is set. If that routine is updated by any user, access to the routine needs to be granted again via an update operation.
"datasetId": "A String", # Required. The ID of the dataset containing this routine.
"projectId": "A String", # Required. The ID of the project containing this routine.
"routineId": "A String", # Required. The ID of the routine. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 256 characters.
},
"specialGroup": "A String", # [Pick one] A special group to grant access to. Possible values include: projectOwners: Owners of the enclosing project. projectReaders: Readers of the enclosing project. projectWriters: Writers of the enclosing project. allAuthenticatedUsers: All authenticated BigQuery users. Maps to similarly-named IAM members.
"userByEmail": "A String", # [Pick one] An email address of a user to grant access to. For example: fred@example.com. Maps to IAM policy member "user:EMAIL" or "serviceAccount:EMAIL".
- "view": { # [Pick one] A view from a different dataset to grant access to. Queries executed against that view will have read access to tables in this dataset. The role field is not required when this field is set. If that view is updated by any user, access to the view needs to be granted again via an update operation.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "view": { # [Pick one] A view from a different dataset to grant access to. Queries executed against that view will have read access to views/tables/routines in this dataset. The role field is not required when this field is set. If that view is updated by any user, access to the view needs to be granted again via an update operation.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
},
],
- "creationTime": "A String", # [Output-only] The time when this dataset was created, in milliseconds since the epoch.
- "datasetReference": { # [Required] A reference that identifies the dataset.
- "datasetId": "A String", # [Required] A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- "projectId": "A String", # [Optional] The ID of the project containing this dataset.
+ "creationTime": "A String", # Output only. The time when this dataset was created, in milliseconds since the epoch.
+ "datasetReference": { # Required. A reference that identifies the dataset.
+ "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "projectId": "A String", # Optional. The ID of the project containing this dataset.
},
- "defaultCollation": "A String", # [Output-only] The default collation of the dataset.
- "defaultEncryptionConfiguration": {
+ "defaultCollation": "A String", # Optional. Defines the default collation specification of future tables created in the dataset. If a table is created in this dataset without table-level default collation, then the table inherits the dataset default collation, which is applied to the string fields that do not have explicit collation specified. A change to this field affects only tables created afterwards, and does not alter the existing tables. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.
+ "defaultEncryptionConfiguration": { # The default encryption key for all tables in the dataset. Once this property is set, all newly-created partitioned tables in the dataset will have encryption key set to this value, unless table creation request (or query) overrides the key.
"kmsKeyName": "A String", # Optional. Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key.
},
- "defaultPartitionExpirationMs": "A String", # [Optional] The default partition expiration for all partitioned tables in the dataset, in milliseconds. Once this property is set, all newly-created partitioned tables in the dataset will have an expirationMs property in the timePartitioning settings set to this value, and changing the value will only affect new tables, not existing ones. The storage in a partition will have an expiration time of its partition time plus this value. Setting this property overrides the use of defaultTableExpirationMs for partitioned tables: only one of defaultTableExpirationMs and defaultPartitionExpirationMs will be used for any new partitioned table. If you provide an explicit timePartitioning.expirationMs when creating or updating a partitioned table, that value takes precedence over the default partition expiration time indicated by this property.
- "defaultRoundingMode": "A String", # [Output-only] The default rounding mode of the dataset.
- "defaultTableExpirationMs": "A String", # [Optional] The default lifetime of all tables in the dataset, in milliseconds. The minimum value is 3600000 milliseconds (one hour). Once this property is set, all newly-created tables in the dataset will have an expirationTime property set to the creation time plus the value in this property, and changing the value will only affect new tables, not existing ones. When the expirationTime for a given table is reached, that table will be deleted automatically. If a table's expirationTime is modified or removed before the table expires, or if you provide an explicit expirationTime when creating a table, that value takes precedence over the default expiration time indicated by this property.
- "description": "A String", # [Optional] A user-friendly description of the dataset.
- "etag": "A String", # [Output-only] A hash of the resource.
- "externalDatasetReference": { # [Optional] Information about the external metadata storage where the dataset is defined. Filled out when the dataset type is EXTERNAL.
- "connection": "A String", # [Required] The connection id that is used to access the external_source. Format: projects/{project_id}/locations/{location_id}/connections/{connection_id}
- "externalSource": "A String", # [Required] External source that backs this dataset.
- },
- "friendlyName": "A String", # [Optional] A descriptive name for the dataset.
- "id": "A String", # [Output-only] The fully-qualified unique name of the dataset in the format projectId:datasetId. The dataset name without the project name is given in the datasetId field. When creating a new dataset, leave this field blank, and instead specify the datasetId field.
- "isCaseInsensitive": True or False, # [Optional] Indicates if table names are case insensitive in the dataset.
- "kind": "bigquery#dataset", # [Output-only] The resource type.
+ "defaultPartitionExpirationMs": "A String", # This default partition expiration, expressed in milliseconds. When new time-partitioned tables are created in a dataset where this property is set, the table will inherit this value, propagated as the `TimePartitioning.expirationMs` property on the new table. If you set `TimePartitioning.expirationMs` explicitly when creating a table, the `defaultPartitionExpirationMs` of the containing dataset is ignored. When creating a partitioned table, if `defaultPartitionExpirationMs` is set, the `defaultTableExpirationMs` value is ignored and the table will not be inherit a table expiration deadline.
+ "defaultRoundingMode": "A String", # Optional. Defines the default rounding mode specification of new tables created within this dataset. During table creation, if this field is specified, the table within this dataset will inherit the default rounding mode of the dataset. Setting the default rounding mode on a table overrides this option. Existing tables in the dataset are unaffected. If columns are defined during that table creation, they will immediately inherit the table's default rounding mode, unless otherwise specified.
+ "defaultTableExpirationMs": "A String", # Optional. The default lifetime of all tables in the dataset, in milliseconds. The minimum lifetime value is 3600000 milliseconds (one hour). To clear an existing default expiration with a PATCH request, set to 0. Once this property is set, all newly-created tables in the dataset will have an expirationTime property set to the creation time plus the value in this property, and changing the value will only affect new tables, not existing ones. When the expirationTime for a given table is reached, that table will be deleted automatically. If a table's expirationTime is modified or removed before the table expires, or if you provide an explicit expirationTime when creating a table, that value takes precedence over the default expiration time indicated by this property.
+ "description": "A String", # Optional. A user-friendly description of the dataset.
+ "etag": "A String", # Output only. A hash of the resource.
+ "externalDatasetReference": { # Configures the access a dataset defined in an external metadata storage. # Optional. Information about the external metadata storage where the dataset is defined. Filled out when the dataset type is EXTERNAL.
+ "connection": "A String", # Required. The connection id that is used to access the external_source. Format: projects/{project_id}/locations/{location_id}/connections/{connection_id}
+ "externalSource": "A String", # Required. External source that backs this dataset.
+ },
+ "friendlyName": "A String", # Optional. A descriptive name for the dataset.
+ "id": "A String", # Output only. The fully-qualified unique name of the dataset in the format projectId:datasetId. The dataset name without the project name is given in the datasetId field. When creating a new dataset, leave this field blank, and instead specify the datasetId field.
+ "isCaseInsensitive": True or False, # Optional. TRUE if the dataset and its table names are case-insensitive, otherwise FALSE. By default, this is FALSE, which means the dataset and its table names are case-sensitive. This field does not affect routine references.
+ "kind": "bigquery#dataset", # Output only. The resource type.
"labels": { # The labels associated with this dataset. You can use these to organize and group your datasets. You can set this property when inserting or updating a dataset. See Creating and Updating Dataset Labels for more information.
"a_key": "A String",
},
- "lastModifiedTime": "A String", # [Output-only] The date when this dataset or any of its tables was last modified, in milliseconds since the epoch.
- "location": "A String", # The geographic location where the dataset should reside. The default value is US. See details at https://cloud.google.com/bigquery/docs/locations.
- "maxTimeTravelHours": "A String", # [Optional] Number of hours for the max time travel for all tables in the dataset.
- "satisfiesPzs": True or False, # [Output-only] Reserved for future use.
- "selfLink": "A String", # [Output-only] A URL that can be used to access the resource again. You can use this URL in Get or Update requests to the resource.
- "storageBillingModel": "A String", # [Optional] Storage billing model to be used for all tables in the dataset. Can be set to PHYSICAL. Default is LOGICAL.
- "tags": [ # [Optional]The tags associated with this dataset. Tag keys are globally unique.
- {
- "tagKey": "A String", # [Required] The namespaced friendly name of the tag key, e.g. "12345/environment" where 12345 is org id.
- "tagValue": "A String", # [Required] Friendly short name of the tag value, e.g. "production".
+ "lastModifiedTime": "A String", # Output only. The date when this dataset was last modified, in milliseconds since the epoch.
+ "linkedDatasetSource": { # A dataset source type which refers to another BigQuery dataset. # Optional. The source dataset reference when the dataset is of type LINKED. For all other dataset types it is not set. This field cannot be updated once it is set. Any attempt to update this field using Update and Patch API Operations will be ignored.
+ "sourceDataset": { # The source dataset reference contains project numbers and not project ids.
+ "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "projectId": "A String", # Optional. The ID of the project containing this dataset.
+ },
+ },
+ "location": "A String", # The geographic location where the dataset should reside. See https://cloud.google.com/bigquery/docs/locations for supported locations.
+ "maxTimeTravelHours": "A String", # Optional. Defines the time travel window in hours. The value can be from 48 to 168 hours (2 to 7 days). The default value is 168 hours if this is not set.
+ "satisfiesPzs": True or False, # Output only. Reserved for future use.
+ "selfLink": "A String", # Output only. A URL that can be used to access the resource again. You can use this URL in Get or Update requests to the resource.
+ "storageBillingModel": "A String", # Optional. Updates storage_billing_model for the dataset.
+ "tags": [ # Output only. Tags for the Dataset.
+ { # A global tag managed by Resource Manager. https://cloud.google.com/iam/docs/tags-access-control#definitions
+ "tagKey": "A String", # Required. The namespaced friendly name of the tag key, e.g. "12345/environment" where 12345 is org id.
+ "tagValue": "A String", # Required. The friendly short name of the tag value, e.g. "production".
},
],
+ "type": "A String", # Output only. Same as `type` in `ListFormatDataset`. The type of the dataset, one of: * DEFAULT - only accessible by owner and authorized accounts, * PUBLIC - accessible by everyone, * LINKED - linked dataset, * EXTERNAL - dataset with definition in external metadata catalog. -- *BIGLAKE_METASTORE - dataset that references a database created in BigLakeMetastore service. --
}
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
Returns:
An object of the form:
{
- "access": [ # [Optional] An array of objects that define dataset access for one or more entities. You can set this property when inserting or updating a dataset in order to control who is allowed to access the data. If unspecified at dataset creation time, BigQuery adds default dataset access for the following entities: access.specialGroup: projectReaders; access.role: READER; access.specialGroup: projectWriters; access.role: WRITER; access.specialGroup: projectOwners; access.role: OWNER; access.userByEmail: [dataset creator email]; access.role: OWNER;
- {
- "dataset": { # [Pick one] A grant authorizing all resources of a particular type in a particular dataset access to this dataset. Only views are supported for now. The role field is not required when this field is set. If that dataset is deleted and re-created, its access needs to be granted again via an update operation.
- "dataset": { # [Required] The dataset this entry applies to.
- "datasetId": "A String", # [Required] A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- "projectId": "A String", # [Optional] The ID of the project containing this dataset.
+ "access": [ # Optional. An array of objects that define dataset access for one or more entities. You can set this property when inserting or updating a dataset in order to control who is allowed to access the data. If unspecified at dataset creation time, BigQuery adds default dataset access for the following entities: access.specialGroup: projectReaders; access.role: READER; access.specialGroup: projectWriters; access.role: WRITER; access.specialGroup: projectOwners; access.role: OWNER; access.userByEmail: [dataset creator email]; access.role: OWNER;
+ { # An object that defines dataset access for an entity.
+ "dataset": { # Grants all resources of particular types in a particular dataset read access to the current dataset. Similar to how individually authorized views work, updates to any resource granted through its dataset (including creation of new resources) requires read permission to referenced resources, plus write permission to the authorizing dataset. # [Pick one] A grant authorizing all resources of a particular type in a particular dataset access to this dataset. Only views are supported for now. The role field is not required when this field is set. If that dataset is deleted and re-created, its access needs to be granted again via an update operation.
+ "dataset": { # The dataset this entry applies to
+ "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "projectId": "A String", # Optional. The ID of the project containing this dataset.
},
- "targetTypes": [
+ "targetTypes": [ # Which resources in the dataset this entry applies to. Currently, only views are supported, but additional target types may be added in the future.
"A String",
],
},
"domain": "A String", # [Pick one] A domain to grant access to. Any users signed in with the domain specified will be granted the specified access. Example: "example.com". Maps to IAM policy member "domain:DOMAIN".
"groupByEmail": "A String", # [Pick one] An email address of a Google Group to grant access to. Maps to IAM policy member "group:GROUP".
"iamMember": "A String", # [Pick one] Some other type of member that appears in the IAM Policy but isn't a user, group, domain, or special group.
- "role": "A String", # [Required] An IAM role ID that should be granted to the user, group, or domain specified in this access entry. The following legacy mappings will be applied: OWNER roles/bigquery.dataOwner WRITER roles/bigquery.dataEditor READER roles/bigquery.dataViewer This field will accept any of the above formats, but will return only the legacy format. For example, if you set this field to "roles/bigquery.dataOwner", it will be returned back as "OWNER".
- "routine": { # [Pick one] A routine from a different dataset to grant access to. Queries executed against that routine will have read access to views/tables/routines in this dataset. Only UDF is supported for now. The role field is not required when this field is set. If that routine is updated by any user, access to the routine needs to be granted again via an update operation.
+ "role": "A String", # An IAM role ID that should be granted to the user, group, or domain specified in this access entry. The following legacy mappings will be applied: OWNER <=> roles/bigquery.dataOwner WRITER <=> roles/bigquery.dataEditor READER <=> roles/bigquery.dataViewer This field will accept any of the above formats, but will return only the legacy format. For example, if you set this field to "roles/bigquery.dataOwner", it will be returned back as "OWNER".
+ "routine": { # Id path of a routine. # [Pick one] A routine from a different dataset to grant access to. Queries executed against that routine will have read access to views/tables/routines in this dataset. Only UDF is supported for now. The role field is not required when this field is set. If that routine is updated by any user, access to the routine needs to be granted again via an update operation.
"datasetId": "A String", # Required. The ID of the dataset containing this routine.
"projectId": "A String", # Required. The ID of the project containing this routine.
"routineId": "A String", # Required. The ID of the routine. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 256 characters.
},
"specialGroup": "A String", # [Pick one] A special group to grant access to. Possible values include: projectOwners: Owners of the enclosing project. projectReaders: Readers of the enclosing project. projectWriters: Writers of the enclosing project. allAuthenticatedUsers: All authenticated BigQuery users. Maps to similarly-named IAM members.
"userByEmail": "A String", # [Pick one] An email address of a user to grant access to. For example: fred@example.com. Maps to IAM policy member "user:EMAIL" or "serviceAccount:EMAIL".
- "view": { # [Pick one] A view from a different dataset to grant access to. Queries executed against that view will have read access to tables in this dataset. The role field is not required when this field is set. If that view is updated by any user, access to the view needs to be granted again via an update operation.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "view": { # [Pick one] A view from a different dataset to grant access to. Queries executed against that view will have read access to views/tables/routines in this dataset. The role field is not required when this field is set. If that view is updated by any user, access to the view needs to be granted again via an update operation.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
},
],
- "creationTime": "A String", # [Output-only] The time when this dataset was created, in milliseconds since the epoch.
- "datasetReference": { # [Required] A reference that identifies the dataset.
- "datasetId": "A String", # [Required] A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- "projectId": "A String", # [Optional] The ID of the project containing this dataset.
+ "creationTime": "A String", # Output only. The time when this dataset was created, in milliseconds since the epoch.
+ "datasetReference": { # Required. A reference that identifies the dataset.
+ "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "projectId": "A String", # Optional. The ID of the project containing this dataset.
},
- "defaultCollation": "A String", # [Output-only] The default collation of the dataset.
- "defaultEncryptionConfiguration": {
+ "defaultCollation": "A String", # Optional. Defines the default collation specification of future tables created in the dataset. If a table is created in this dataset without table-level default collation, then the table inherits the dataset default collation, which is applied to the string fields that do not have explicit collation specified. A change to this field affects only tables created afterwards, and does not alter the existing tables. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.
+ "defaultEncryptionConfiguration": { # The default encryption key for all tables in the dataset. Once this property is set, all newly-created partitioned tables in the dataset will have encryption key set to this value, unless table creation request (or query) overrides the key.
"kmsKeyName": "A String", # Optional. Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key.
},
- "defaultPartitionExpirationMs": "A String", # [Optional] The default partition expiration for all partitioned tables in the dataset, in milliseconds. Once this property is set, all newly-created partitioned tables in the dataset will have an expirationMs property in the timePartitioning settings set to this value, and changing the value will only affect new tables, not existing ones. The storage in a partition will have an expiration time of its partition time plus this value. Setting this property overrides the use of defaultTableExpirationMs for partitioned tables: only one of defaultTableExpirationMs and defaultPartitionExpirationMs will be used for any new partitioned table. If you provide an explicit timePartitioning.expirationMs when creating or updating a partitioned table, that value takes precedence over the default partition expiration time indicated by this property.
- "defaultRoundingMode": "A String", # [Output-only] The default rounding mode of the dataset.
- "defaultTableExpirationMs": "A String", # [Optional] The default lifetime of all tables in the dataset, in milliseconds. The minimum value is 3600000 milliseconds (one hour). Once this property is set, all newly-created tables in the dataset will have an expirationTime property set to the creation time plus the value in this property, and changing the value will only affect new tables, not existing ones. When the expirationTime for a given table is reached, that table will be deleted automatically. If a table's expirationTime is modified or removed before the table expires, or if you provide an explicit expirationTime when creating a table, that value takes precedence over the default expiration time indicated by this property.
- "description": "A String", # [Optional] A user-friendly description of the dataset.
- "etag": "A String", # [Output-only] A hash of the resource.
- "externalDatasetReference": { # [Optional] Information about the external metadata storage where the dataset is defined. Filled out when the dataset type is EXTERNAL.
- "connection": "A String", # [Required] The connection id that is used to access the external_source. Format: projects/{project_id}/locations/{location_id}/connections/{connection_id}
- "externalSource": "A String", # [Required] External source that backs this dataset.
- },
- "friendlyName": "A String", # [Optional] A descriptive name for the dataset.
- "id": "A String", # [Output-only] The fully-qualified unique name of the dataset in the format projectId:datasetId. The dataset name without the project name is given in the datasetId field. When creating a new dataset, leave this field blank, and instead specify the datasetId field.
- "isCaseInsensitive": True or False, # [Optional] Indicates if table names are case insensitive in the dataset.
- "kind": "bigquery#dataset", # [Output-only] The resource type.
+ "defaultPartitionExpirationMs": "A String", # This default partition expiration, expressed in milliseconds. When new time-partitioned tables are created in a dataset where this property is set, the table will inherit this value, propagated as the `TimePartitioning.expirationMs` property on the new table. If you set `TimePartitioning.expirationMs` explicitly when creating a table, the `defaultPartitionExpirationMs` of the containing dataset is ignored. When creating a partitioned table, if `defaultPartitionExpirationMs` is set, the `defaultTableExpirationMs` value is ignored and the table will not be inherit a table expiration deadline.
+ "defaultRoundingMode": "A String", # Optional. Defines the default rounding mode specification of new tables created within this dataset. During table creation, if this field is specified, the table within this dataset will inherit the default rounding mode of the dataset. Setting the default rounding mode on a table overrides this option. Existing tables in the dataset are unaffected. If columns are defined during that table creation, they will immediately inherit the table's default rounding mode, unless otherwise specified.
+ "defaultTableExpirationMs": "A String", # Optional. The default lifetime of all tables in the dataset, in milliseconds. The minimum lifetime value is 3600000 milliseconds (one hour). To clear an existing default expiration with a PATCH request, set to 0. Once this property is set, all newly-created tables in the dataset will have an expirationTime property set to the creation time plus the value in this property, and changing the value will only affect new tables, not existing ones. When the expirationTime for a given table is reached, that table will be deleted automatically. If a table's expirationTime is modified or removed before the table expires, or if you provide an explicit expirationTime when creating a table, that value takes precedence over the default expiration time indicated by this property.
+ "description": "A String", # Optional. A user-friendly description of the dataset.
+ "etag": "A String", # Output only. A hash of the resource.
+ "externalDatasetReference": { # Configures the access a dataset defined in an external metadata storage. # Optional. Information about the external metadata storage where the dataset is defined. Filled out when the dataset type is EXTERNAL.
+ "connection": "A String", # Required. The connection id that is used to access the external_source. Format: projects/{project_id}/locations/{location_id}/connections/{connection_id}
+ "externalSource": "A String", # Required. External source that backs this dataset.
+ },
+ "friendlyName": "A String", # Optional. A descriptive name for the dataset.
+ "id": "A String", # Output only. The fully-qualified unique name of the dataset in the format projectId:datasetId. The dataset name without the project name is given in the datasetId field. When creating a new dataset, leave this field blank, and instead specify the datasetId field.
+ "isCaseInsensitive": True or False, # Optional. TRUE if the dataset and its table names are case-insensitive, otherwise FALSE. By default, this is FALSE, which means the dataset and its table names are case-sensitive. This field does not affect routine references.
+ "kind": "bigquery#dataset", # Output only. The resource type.
"labels": { # The labels associated with this dataset. You can use these to organize and group your datasets. You can set this property when inserting or updating a dataset. See Creating and Updating Dataset Labels for more information.
"a_key": "A String",
},
- "lastModifiedTime": "A String", # [Output-only] The date when this dataset or any of its tables was last modified, in milliseconds since the epoch.
- "location": "A String", # The geographic location where the dataset should reside. The default value is US. See details at https://cloud.google.com/bigquery/docs/locations.
- "maxTimeTravelHours": "A String", # [Optional] Number of hours for the max time travel for all tables in the dataset.
- "satisfiesPzs": True or False, # [Output-only] Reserved for future use.
- "selfLink": "A String", # [Output-only] A URL that can be used to access the resource again. You can use this URL in Get or Update requests to the resource.
- "storageBillingModel": "A String", # [Optional] Storage billing model to be used for all tables in the dataset. Can be set to PHYSICAL. Default is LOGICAL.
- "tags": [ # [Optional]The tags associated with this dataset. Tag keys are globally unique.
- {
- "tagKey": "A String", # [Required] The namespaced friendly name of the tag key, e.g. "12345/environment" where 12345 is org id.
- "tagValue": "A String", # [Required] Friendly short name of the tag value, e.g. "production".
+ "lastModifiedTime": "A String", # Output only. The date when this dataset was last modified, in milliseconds since the epoch.
+ "linkedDatasetSource": { # A dataset source type which refers to another BigQuery dataset. # Optional. The source dataset reference when the dataset is of type LINKED. For all other dataset types it is not set. This field cannot be updated once it is set. Any attempt to update this field using Update and Patch API Operations will be ignored.
+ "sourceDataset": { # The source dataset reference contains project numbers and not project ids.
+ "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "projectId": "A String", # Optional. The ID of the project containing this dataset.
+ },
+ },
+ "location": "A String", # The geographic location where the dataset should reside. See https://cloud.google.com/bigquery/docs/locations for supported locations.
+ "maxTimeTravelHours": "A String", # Optional. Defines the time travel window in hours. The value can be from 48 to 168 hours (2 to 7 days). The default value is 168 hours if this is not set.
+ "satisfiesPzs": True or False, # Output only. Reserved for future use.
+ "selfLink": "A String", # Output only. A URL that can be used to access the resource again. You can use this URL in Get or Update requests to the resource.
+ "storageBillingModel": "A String", # Optional. Updates storage_billing_model for the dataset.
+ "tags": [ # Output only. Tags for the Dataset.
+ { # A global tag managed by Resource Manager. https://cloud.google.com/iam/docs/tags-access-control#definitions
+ "tagKey": "A String", # Required. The namespaced friendly name of the tag key, e.g. "12345/environment" where 12345 is org id.
+ "tagValue": "A String", # Required. The friendly short name of the tag value, e.g. "production".
},
],
+ "type": "A String", # Output only. Same as `type` in `ListFormatDataset`. The type of the dataset, one of: * DEFAULT - only accessible by owner and authorized accounts, * PUBLIC - accessible by everyone, * LINKED - linked dataset, * EXTERNAL - dataset with definition in external metadata catalog. -- *BIGLAKE_METASTORE - dataset that references a database created in BigLakeMetastore service. --
}
list(projectId, all=None, filter=None, maxResults=None, pageToken=None)
- Lists all datasets in the specified project to which you have been granted the READER dataset role. +list(projectId, all=None, filter=None, maxResults=None, pageToken=None, x__xgafv=None)+Lists all datasets in the specified project to which the user has been granted the READER dataset role. Args: - projectId: string, Project ID of the datasets to be listed (required) + projectId: string, Required. Project ID of the datasets to be listed (required) all: boolean, Whether to list all datasets, including hidden ones - filter: string, An expression for filtering the results of the request by label. The syntax is "labels.<name>[:<value>]". Multiple filters can be ANDed together by connecting with a space. Example: "labels.department:receiving labels.active". See Filtering datasets using labels for details. - maxResults: integer, The maximum number of results to return + filter: string, An expression for filtering the results of the request by label. The syntax is \"labels.<name>[:<value>]\". Multiple filters can be ANDed together by connecting with a space. Example: \"labels.department:receiving labels.active\". See [Filtering datasets using labels](/bigquery/docs/labeling-datasets#filtering_datasets_using_labels) for details. + maxResults: integer, The maximum number of results to return in a single response page. Leverage the page tokens to iterate through the entire collection. pageToken: string, Page token, returned by a previous call, to request the next page of results + x__xgafv: string, V1 error format. + Allowed values + 1 - v1 error format + 2 - v2 error format Returns: An object of the form: - { + { # Response format for a page of results when listing datasets. "datasets": [ # An array of the dataset resources in the project. Each resource contains basic information. For full information about a particular dataset resource, use the Datasets: get method. This property is omitted when there are no datasets in the project. - { + { # A dataset resource with only a subset of fields, to be returned in a list of datasets. "datasetReference": { # The dataset reference. Use this property to access specific parts of the dataset's ID, such as project ID or dataset ID. - "datasetId": "A String", # [Required] A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. - "projectId": "A String", # [Optional] The ID of the project containing this dataset. + "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. + "projectId": "A String", # Optional. The ID of the project containing this dataset. }, - "friendlyName": "A String", # A descriptive name for the dataset, if one exists. + "friendlyName": "A String", # An alternate name for the dataset. The friendly name is purely decorative in nature. "id": "A String", # The fully-qualified, unique, opaque ID of the dataset. - "kind": "bigquery#dataset", # The resource type. This property always returns the value "bigquery#dataset". + "kind": "A String", # The resource type. This property always returns the value "bigquery#dataset" "labels": { # The labels associated with this dataset. You can use these to organize and group your datasets. "a_key": "A String", }, - "location": "A String", # The geographic location where the data resides. + "location": "A String", # The geographic location where the dataset resides. }, ], - "etag": "A String", # A hash value of the results page. You can use this property to determine if the page has changed since the last request. - "kind": "bigquery#datasetList", # The list type. This property always returns the value "bigquery#datasetList". + "etag": "A String", # Output only. A hash value of the results page. You can use this property to determine if the page has changed since the last request. + "kind": "bigquery#datasetList", # Output only. The resource type. This property always returns the value "bigquery#datasetList" "nextPageToken": "A String", # A token that can be used to request the next results page. This property is omitted on the final results page. + "unreachable": [ # A list of skipped locations that were unreachable. For more information about BigQuery locations, see: https://cloud.google.com/bigquery/docs/locations. Example: "europe-west5" + "A String", + ], }
patch(projectId, datasetId, body=None)
- Updates information in an existing dataset. The update method replaces the entire dataset resource, whereas the patch method only replaces fields that are provided in the submitted dataset resource. This method supports patch semantics. +patch(projectId, datasetId, body=None, x__xgafv=None)+Updates information in an existing dataset. The update method replaces the entire dataset resource, whereas the patch method only replaces fields that are provided in the submitted dataset resource. This method supports RFC5789 patch semantics. Args: - projectId: string, Project ID of the dataset being updated (required) - datasetId: string, Dataset ID of the dataset being updated (required) + projectId: string, Required. Project ID of the dataset being updated (required) + datasetId: string, Required. Dataset ID of the dataset being updated (required) body: object, The request body. The object takes the form of: { - "access": [ # [Optional] An array of objects that define dataset access for one or more entities. You can set this property when inserting or updating a dataset in order to control who is allowed to access the data. If unspecified at dataset creation time, BigQuery adds default dataset access for the following entities: access.specialGroup: projectReaders; access.role: READER; access.specialGroup: projectWriters; access.role: WRITER; access.specialGroup: projectOwners; access.role: OWNER; access.userByEmail: [dataset creator email]; access.role: OWNER; - { - "dataset": { # [Pick one] A grant authorizing all resources of a particular type in a particular dataset access to this dataset. Only views are supported for now. The role field is not required when this field is set. If that dataset is deleted and re-created, its access needs to be granted again via an update operation. - "dataset": { # [Required] The dataset this entry applies to. - "datasetId": "A String", # [Required] A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. - "projectId": "A String", # [Optional] The ID of the project containing this dataset. + "access": [ # Optional. An array of objects that define dataset access for one or more entities. You can set this property when inserting or updating a dataset in order to control who is allowed to access the data. If unspecified at dataset creation time, BigQuery adds default dataset access for the following entities: access.specialGroup: projectReaders; access.role: READER; access.specialGroup: projectWriters; access.role: WRITER; access.specialGroup: projectOwners; access.role: OWNER; access.userByEmail: [dataset creator email]; access.role: OWNER; + { # An object that defines dataset access for an entity. + "dataset": { # Grants all resources of particular types in a particular dataset read access to the current dataset. Similar to how individually authorized views work, updates to any resource granted through its dataset (including creation of new resources) requires read permission to referenced resources, plus write permission to the authorizing dataset. # [Pick one] A grant authorizing all resources of a particular type in a particular dataset access to this dataset. Only views are supported for now. The role field is not required when this field is set. If that dataset is deleted and re-created, its access needs to be granted again via an update operation. + "dataset": { # The dataset this entry applies to + "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. + "projectId": "A String", # Optional. The ID of the project containing this dataset. }, - "targetTypes": [ + "targetTypes": [ # Which resources in the dataset this entry applies to. Currently, only views are supported, but additional target types may be added in the future. "A String", ], }, "domain": "A String", # [Pick one] A domain to grant access to. Any users signed in with the domain specified will be granted the specified access. Example: "example.com". Maps to IAM policy member "domain:DOMAIN". "groupByEmail": "A String", # [Pick one] An email address of a Google Group to grant access to. Maps to IAM policy member "group:GROUP". "iamMember": "A String", # [Pick one] Some other type of member that appears in the IAM Policy but isn't a user, group, domain, or special group. - "role": "A String", # [Required] An IAM role ID that should be granted to the user, group, or domain specified in this access entry. The following legacy mappings will be applied: OWNER roles/bigquery.dataOwner WRITER roles/bigquery.dataEditor READER roles/bigquery.dataViewer This field will accept any of the above formats, but will return only the legacy format. For example, if you set this field to "roles/bigquery.dataOwner", it will be returned back as "OWNER". - "routine": { # [Pick one] A routine from a different dataset to grant access to. Queries executed against that routine will have read access to views/tables/routines in this dataset. Only UDF is supported for now. The role field is not required when this field is set. If that routine is updated by any user, access to the routine needs to be granted again via an update operation. + "role": "A String", # An IAM role ID that should be granted to the user, group, or domain specified in this access entry. The following legacy mappings will be applied: OWNER <=> roles/bigquery.dataOwner WRITER <=> roles/bigquery.dataEditor READER <=> roles/bigquery.dataViewer This field will accept any of the above formats, but will return only the legacy format. For example, if you set this field to "roles/bigquery.dataOwner", it will be returned back as "OWNER". + "routine": { # Id path of a routine. # [Pick one] A routine from a different dataset to grant access to. Queries executed against that routine will have read access to views/tables/routines in this dataset. Only UDF is supported for now. The role field is not required when this field is set. If that routine is updated by any user, access to the routine needs to be granted again via an update operation. "datasetId": "A String", # Required. The ID of the dataset containing this routine. "projectId": "A String", # Required. The ID of the project containing this routine. "routineId": "A String", # Required. The ID of the routine. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 256 characters. }, "specialGroup": "A String", # [Pick one] A special group to grant access to. Possible values include: projectOwners: Owners of the enclosing project. projectReaders: Readers of the enclosing project. projectWriters: Writers of the enclosing project. allAuthenticatedUsers: All authenticated BigQuery users. Maps to similarly-named IAM members. "userByEmail": "A String", # [Pick one] An email address of a user to grant access to. For example: fred@example.com. Maps to IAM policy member "user:EMAIL" or "serviceAccount:EMAIL". - "view": { # [Pick one] A view from a different dataset to grant access to. Queries executed against that view will have read access to tables in this dataset. The role field is not required when this field is set. If that view is updated by any user, access to the view needs to be granted again via an update operation. - "datasetId": "A String", # [Required] The ID of the dataset containing this table. - "projectId": "A String", # [Required] The ID of the project containing this table. - "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. + "view": { # [Pick one] A view from a different dataset to grant access to. Queries executed against that view will have read access to views/tables/routines in this dataset. The role field is not required when this field is set. If that view is updated by any user, access to the view needs to be granted again via an update operation. + "datasetId": "A String", # Required. The ID of the dataset containing this table. + "projectId": "A String", # Required. The ID of the project containing this table. + "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`. }, }, ], - "creationTime": "A String", # [Output-only] The time when this dataset was created, in milliseconds since the epoch. - "datasetReference": { # [Required] A reference that identifies the dataset. - "datasetId": "A String", # [Required] A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. - "projectId": "A String", # [Optional] The ID of the project containing this dataset. + "creationTime": "A String", # Output only. The time when this dataset was created, in milliseconds since the epoch. + "datasetReference": { # Required. A reference that identifies the dataset. + "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. + "projectId": "A String", # Optional. The ID of the project containing this dataset. }, - "defaultCollation": "A String", # [Output-only] The default collation of the dataset. - "defaultEncryptionConfiguration": { + "defaultCollation": "A String", # Optional. Defines the default collation specification of future tables created in the dataset. If a table is created in this dataset without table-level default collation, then the table inherits the dataset default collation, which is applied to the string fields that do not have explicit collation specified. A change to this field affects only tables created afterwards, and does not alter the existing tables. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior. + "defaultEncryptionConfiguration": { # The default encryption key for all tables in the dataset. Once this property is set, all newly-created partitioned tables in the dataset will have encryption key set to this value, unless table creation request (or query) overrides the key. "kmsKeyName": "A String", # Optional. Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key. }, - "defaultPartitionExpirationMs": "A String", # [Optional] The default partition expiration for all partitioned tables in the dataset, in milliseconds. Once this property is set, all newly-created partitioned tables in the dataset will have an expirationMs property in the timePartitioning settings set to this value, and changing the value will only affect new tables, not existing ones. The storage in a partition will have an expiration time of its partition time plus this value. Setting this property overrides the use of defaultTableExpirationMs for partitioned tables: only one of defaultTableExpirationMs and defaultPartitionExpirationMs will be used for any new partitioned table. If you provide an explicit timePartitioning.expirationMs when creating or updating a partitioned table, that value takes precedence over the default partition expiration time indicated by this property. - "defaultRoundingMode": "A String", # [Output-only] The default rounding mode of the dataset. - "defaultTableExpirationMs": "A String", # [Optional] The default lifetime of all tables in the dataset, in milliseconds. The minimum value is 3600000 milliseconds (one hour). Once this property is set, all newly-created tables in the dataset will have an expirationTime property set to the creation time plus the value in this property, and changing the value will only affect new tables, not existing ones. When the expirationTime for a given table is reached, that table will be deleted automatically. If a table's expirationTime is modified or removed before the table expires, or if you provide an explicit expirationTime when creating a table, that value takes precedence over the default expiration time indicated by this property. - "description": "A String", # [Optional] A user-friendly description of the dataset. - "etag": "A String", # [Output-only] A hash of the resource. - "externalDatasetReference": { # [Optional] Information about the external metadata storage where the dataset is defined. Filled out when the dataset type is EXTERNAL. - "connection": "A String", # [Required] The connection id that is used to access the external_source. Format: projects/{project_id}/locations/{location_id}/connections/{connection_id} - "externalSource": "A String", # [Required] External source that backs this dataset. - }, - "friendlyName": "A String", # [Optional] A descriptive name for the dataset. - "id": "A String", # [Output-only] The fully-qualified unique name of the dataset in the format projectId:datasetId. The dataset name without the project name is given in the datasetId field. When creating a new dataset, leave this field blank, and instead specify the datasetId field. - "isCaseInsensitive": True or False, # [Optional] Indicates if table names are case insensitive in the dataset. - "kind": "bigquery#dataset", # [Output-only] The resource type. + "defaultPartitionExpirationMs": "A String", # This default partition expiration, expressed in milliseconds. When new time-partitioned tables are created in a dataset where this property is set, the table will inherit this value, propagated as the `TimePartitioning.expirationMs` property on the new table. If you set `TimePartitioning.expirationMs` explicitly when creating a table, the `defaultPartitionExpirationMs` of the containing dataset is ignored. When creating a partitioned table, if `defaultPartitionExpirationMs` is set, the `defaultTableExpirationMs` value is ignored and the table will not be inherit a table expiration deadline. + "defaultRoundingMode": "A String", # Optional. Defines the default rounding mode specification of new tables created within this dataset. During table creation, if this field is specified, the table within this dataset will inherit the default rounding mode of the dataset. Setting the default rounding mode on a table overrides this option. Existing tables in the dataset are unaffected. If columns are defined during that table creation, they will immediately inherit the table's default rounding mode, unless otherwise specified. + "defaultTableExpirationMs": "A String", # Optional. The default lifetime of all tables in the dataset, in milliseconds. The minimum lifetime value is 3600000 milliseconds (one hour). To clear an existing default expiration with a PATCH request, set to 0. Once this property is set, all newly-created tables in the dataset will have an expirationTime property set to the creation time plus the value in this property, and changing the value will only affect new tables, not existing ones. When the expirationTime for a given table is reached, that table will be deleted automatically. If a table's expirationTime is modified or removed before the table expires, or if you provide an explicit expirationTime when creating a table, that value takes precedence over the default expiration time indicated by this property. + "description": "A String", # Optional. A user-friendly description of the dataset. + "etag": "A String", # Output only. A hash of the resource. + "externalDatasetReference": { # Configures the access a dataset defined in an external metadata storage. # Optional. Information about the external metadata storage where the dataset is defined. Filled out when the dataset type is EXTERNAL. + "connection": "A String", # Required. The connection id that is used to access the external_source. Format: projects/{project_id}/locations/{location_id}/connections/{connection_id} + "externalSource": "A String", # Required. External source that backs this dataset. + }, + "friendlyName": "A String", # Optional. A descriptive name for the dataset. + "id": "A String", # Output only. The fully-qualified unique name of the dataset in the format projectId:datasetId. The dataset name without the project name is given in the datasetId field. When creating a new dataset, leave this field blank, and instead specify the datasetId field. + "isCaseInsensitive": True or False, # Optional. TRUE if the dataset and its table names are case-insensitive, otherwise FALSE. By default, this is FALSE, which means the dataset and its table names are case-sensitive. This field does not affect routine references. + "kind": "bigquery#dataset", # Output only. The resource type. "labels": { # The labels associated with this dataset. You can use these to organize and group your datasets. You can set this property when inserting or updating a dataset. See Creating and Updating Dataset Labels for more information. "a_key": "A String", }, - "lastModifiedTime": "A String", # [Output-only] The date when this dataset or any of its tables was last modified, in milliseconds since the epoch. - "location": "A String", # The geographic location where the dataset should reside. The default value is US. See details at https://cloud.google.com/bigquery/docs/locations. - "maxTimeTravelHours": "A String", # [Optional] Number of hours for the max time travel for all tables in the dataset. - "satisfiesPzs": True or False, # [Output-only] Reserved for future use. - "selfLink": "A String", # [Output-only] A URL that can be used to access the resource again. You can use this URL in Get or Update requests to the resource. - "storageBillingModel": "A String", # [Optional] Storage billing model to be used for all tables in the dataset. Can be set to PHYSICAL. Default is LOGICAL. - "tags": [ # [Optional]The tags associated with this dataset. Tag keys are globally unique. - { - "tagKey": "A String", # [Required] The namespaced friendly name of the tag key, e.g. "12345/environment" where 12345 is org id. - "tagValue": "A String", # [Required] Friendly short name of the tag value, e.g. "production". + "lastModifiedTime": "A String", # Output only. The date when this dataset was last modified, in milliseconds since the epoch. + "linkedDatasetSource": { # A dataset source type which refers to another BigQuery dataset. # Optional. The source dataset reference when the dataset is of type LINKED. For all other dataset types it is not set. This field cannot be updated once it is set. Any attempt to update this field using Update and Patch API Operations will be ignored. + "sourceDataset": { # The source dataset reference contains project numbers and not project ids. + "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. + "projectId": "A String", # Optional. The ID of the project containing this dataset. + }, + }, + "location": "A String", # The geographic location where the dataset should reside. See https://cloud.google.com/bigquery/docs/locations for supported locations. + "maxTimeTravelHours": "A String", # Optional. Defines the time travel window in hours. The value can be from 48 to 168 hours (2 to 7 days). The default value is 168 hours if this is not set. + "satisfiesPzs": True or False, # Output only. Reserved for future use. + "selfLink": "A String", # Output only. A URL that can be used to access the resource again. You can use this URL in Get or Update requests to the resource. + "storageBillingModel": "A String", # Optional. Updates storage_billing_model for the dataset. + "tags": [ # Output only. Tags for the Dataset. + { # A global tag managed by Resource Manager. https://cloud.google.com/iam/docs/tags-access-control#definitions + "tagKey": "A String", # Required. The namespaced friendly name of the tag key, e.g. "12345/environment" where 12345 is org id. + "tagValue": "A String", # Required. The friendly short name of the tag value, e.g. "production". }, ], + "type": "A String", # Output only. Same as `type` in `ListFormatDataset`. The type of the dataset, one of: * DEFAULT - only accessible by owner and authorized accounts, * PUBLIC - accessible by everyone, * LINKED - linked dataset, * EXTERNAL - dataset with definition in external metadata catalog. -- *BIGLAKE_METASTORE - dataset that references a database created in BigLakeMetastore service. -- } + x__xgafv: string, V1 error format. + Allowed values + 1 - v1 error format + 2 - v2 error format Returns: An object of the form: { - "access": [ # [Optional] An array of objects that define dataset access for one or more entities. You can set this property when inserting or updating a dataset in order to control who is allowed to access the data. If unspecified at dataset creation time, BigQuery adds default dataset access for the following entities: access.specialGroup: projectReaders; access.role: READER; access.specialGroup: projectWriters; access.role: WRITER; access.specialGroup: projectOwners; access.role: OWNER; access.userByEmail: [dataset creator email]; access.role: OWNER; - { - "dataset": { # [Pick one] A grant authorizing all resources of a particular type in a particular dataset access to this dataset. Only views are supported for now. The role field is not required when this field is set. If that dataset is deleted and re-created, its access needs to be granted again via an update operation. - "dataset": { # [Required] The dataset this entry applies to. - "datasetId": "A String", # [Required] A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. - "projectId": "A String", # [Optional] The ID of the project containing this dataset. + "access": [ # Optional. An array of objects that define dataset access for one or more entities. You can set this property when inserting or updating a dataset in order to control who is allowed to access the data. If unspecified at dataset creation time, BigQuery adds default dataset access for the following entities: access.specialGroup: projectReaders; access.role: READER; access.specialGroup: projectWriters; access.role: WRITER; access.specialGroup: projectOwners; access.role: OWNER; access.userByEmail: [dataset creator email]; access.role: OWNER; + { # An object that defines dataset access for an entity. + "dataset": { # Grants all resources of particular types in a particular dataset read access to the current dataset. Similar to how individually authorized views work, updates to any resource granted through its dataset (including creation of new resources) requires read permission to referenced resources, plus write permission to the authorizing dataset. # [Pick one] A grant authorizing all resources of a particular type in a particular dataset access to this dataset. Only views are supported for now. The role field is not required when this field is set. If that dataset is deleted and re-created, its access needs to be granted again via an update operation. + "dataset": { # The dataset this entry applies to + "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. + "projectId": "A String", # Optional. The ID of the project containing this dataset. }, - "targetTypes": [ + "targetTypes": [ # Which resources in the dataset this entry applies to. Currently, only views are supported, but additional target types may be added in the future. "A String", ], }, "domain": "A String", # [Pick one] A domain to grant access to. Any users signed in with the domain specified will be granted the specified access. Example: "example.com". Maps to IAM policy member "domain:DOMAIN". "groupByEmail": "A String", # [Pick one] An email address of a Google Group to grant access to. Maps to IAM policy member "group:GROUP". "iamMember": "A String", # [Pick one] Some other type of member that appears in the IAM Policy but isn't a user, group, domain, or special group. - "role": "A String", # [Required] An IAM role ID that should be granted to the user, group, or domain specified in this access entry. The following legacy mappings will be applied: OWNER roles/bigquery.dataOwner WRITER roles/bigquery.dataEditor READER roles/bigquery.dataViewer This field will accept any of the above formats, but will return only the legacy format. For example, if you set this field to "roles/bigquery.dataOwner", it will be returned back as "OWNER". - "routine": { # [Pick one] A routine from a different dataset to grant access to. Queries executed against that routine will have read access to views/tables/routines in this dataset. Only UDF is supported for now. The role field is not required when this field is set. If that routine is updated by any user, access to the routine needs to be granted again via an update operation. + "role": "A String", # An IAM role ID that should be granted to the user, group, or domain specified in this access entry. The following legacy mappings will be applied: OWNER <=> roles/bigquery.dataOwner WRITER <=> roles/bigquery.dataEditor READER <=> roles/bigquery.dataViewer This field will accept any of the above formats, but will return only the legacy format. For example, if you set this field to "roles/bigquery.dataOwner", it will be returned back as "OWNER". + "routine": { # Id path of a routine. # [Pick one] A routine from a different dataset to grant access to. Queries executed against that routine will have read access to views/tables/routines in this dataset. Only UDF is supported for now. The role field is not required when this field is set. If that routine is updated by any user, access to the routine needs to be granted again via an update operation. "datasetId": "A String", # Required. The ID of the dataset containing this routine. "projectId": "A String", # Required. The ID of the project containing this routine. "routineId": "A String", # Required. The ID of the routine. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 256 characters. }, "specialGroup": "A String", # [Pick one] A special group to grant access to. Possible values include: projectOwners: Owners of the enclosing project. projectReaders: Readers of the enclosing project. projectWriters: Writers of the enclosing project. allAuthenticatedUsers: All authenticated BigQuery users. Maps to similarly-named IAM members. "userByEmail": "A String", # [Pick one] An email address of a user to grant access to. For example: fred@example.com. Maps to IAM policy member "user:EMAIL" or "serviceAccount:EMAIL". - "view": { # [Pick one] A view from a different dataset to grant access to. Queries executed against that view will have read access to tables in this dataset. The role field is not required when this field is set. If that view is updated by any user, access to the view needs to be granted again via an update operation. - "datasetId": "A String", # [Required] The ID of the dataset containing this table. - "projectId": "A String", # [Required] The ID of the project containing this table. - "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. + "view": { # [Pick one] A view from a different dataset to grant access to. Queries executed against that view will have read access to views/tables/routines in this dataset. The role field is not required when this field is set. If that view is updated by any user, access to the view needs to be granted again via an update operation. + "datasetId": "A String", # Required. The ID of the dataset containing this table. + "projectId": "A String", # Required. The ID of the project containing this table. + "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`. }, }, ], - "creationTime": "A String", # [Output-only] The time when this dataset was created, in milliseconds since the epoch. - "datasetReference": { # [Required] A reference that identifies the dataset. - "datasetId": "A String", # [Required] A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. - "projectId": "A String", # [Optional] The ID of the project containing this dataset. + "creationTime": "A String", # Output only. The time when this dataset was created, in milliseconds since the epoch. + "datasetReference": { # Required. A reference that identifies the dataset. + "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. + "projectId": "A String", # Optional. The ID of the project containing this dataset. }, - "defaultCollation": "A String", # [Output-only] The default collation of the dataset. - "defaultEncryptionConfiguration": { + "defaultCollation": "A String", # Optional. Defines the default collation specification of future tables created in the dataset. If a table is created in this dataset without table-level default collation, then the table inherits the dataset default collation, which is applied to the string fields that do not have explicit collation specified. A change to this field affects only tables created afterwards, and does not alter the existing tables. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior. + "defaultEncryptionConfiguration": { # The default encryption key for all tables in the dataset. Once this property is set, all newly-created partitioned tables in the dataset will have encryption key set to this value, unless table creation request (or query) overrides the key. "kmsKeyName": "A String", # Optional. Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key. }, - "defaultPartitionExpirationMs": "A String", # [Optional] The default partition expiration for all partitioned tables in the dataset, in milliseconds. Once this property is set, all newly-created partitioned tables in the dataset will have an expirationMs property in the timePartitioning settings set to this value, and changing the value will only affect new tables, not existing ones. The storage in a partition will have an expiration time of its partition time plus this value. Setting this property overrides the use of defaultTableExpirationMs for partitioned tables: only one of defaultTableExpirationMs and defaultPartitionExpirationMs will be used for any new partitioned table. If you provide an explicit timePartitioning.expirationMs when creating or updating a partitioned table, that value takes precedence over the default partition expiration time indicated by this property. - "defaultRoundingMode": "A String", # [Output-only] The default rounding mode of the dataset. - "defaultTableExpirationMs": "A String", # [Optional] The default lifetime of all tables in the dataset, in milliseconds. The minimum value is 3600000 milliseconds (one hour). Once this property is set, all newly-created tables in the dataset will have an expirationTime property set to the creation time plus the value in this property, and changing the value will only affect new tables, not existing ones. When the expirationTime for a given table is reached, that table will be deleted automatically. If a table's expirationTime is modified or removed before the table expires, or if you provide an explicit expirationTime when creating a table, that value takes precedence over the default expiration time indicated by this property. - "description": "A String", # [Optional] A user-friendly description of the dataset. - "etag": "A String", # [Output-only] A hash of the resource. - "externalDatasetReference": { # [Optional] Information about the external metadata storage where the dataset is defined. Filled out when the dataset type is EXTERNAL. - "connection": "A String", # [Required] The connection id that is used to access the external_source. Format: projects/{project_id}/locations/{location_id}/connections/{connection_id} - "externalSource": "A String", # [Required] External source that backs this dataset. - }, - "friendlyName": "A String", # [Optional] A descriptive name for the dataset. - "id": "A String", # [Output-only] The fully-qualified unique name of the dataset in the format projectId:datasetId. The dataset name without the project name is given in the datasetId field. When creating a new dataset, leave this field blank, and instead specify the datasetId field. - "isCaseInsensitive": True or False, # [Optional] Indicates if table names are case insensitive in the dataset. - "kind": "bigquery#dataset", # [Output-only] The resource type. + "defaultPartitionExpirationMs": "A String", # This default partition expiration, expressed in milliseconds. When new time-partitioned tables are created in a dataset where this property is set, the table will inherit this value, propagated as the `TimePartitioning.expirationMs` property on the new table. If you set `TimePartitioning.expirationMs` explicitly when creating a table, the `defaultPartitionExpirationMs` of the containing dataset is ignored. When creating a partitioned table, if `defaultPartitionExpirationMs` is set, the `defaultTableExpirationMs` value is ignored and the table will not be inherit a table expiration deadline. + "defaultRoundingMode": "A String", # Optional. Defines the default rounding mode specification of new tables created within this dataset. During table creation, if this field is specified, the table within this dataset will inherit the default rounding mode of the dataset. Setting the default rounding mode on a table overrides this option. Existing tables in the dataset are unaffected. If columns are defined during that table creation, they will immediately inherit the table's default rounding mode, unless otherwise specified. + "defaultTableExpirationMs": "A String", # Optional. The default lifetime of all tables in the dataset, in milliseconds. The minimum lifetime value is 3600000 milliseconds (one hour). To clear an existing default expiration with a PATCH request, set to 0. Once this property is set, all newly-created tables in the dataset will have an expirationTime property set to the creation time plus the value in this property, and changing the value will only affect new tables, not existing ones. When the expirationTime for a given table is reached, that table will be deleted automatically. If a table's expirationTime is modified or removed before the table expires, or if you provide an explicit expirationTime when creating a table, that value takes precedence over the default expiration time indicated by this property. + "description": "A String", # Optional. A user-friendly description of the dataset. + "etag": "A String", # Output only. A hash of the resource. + "externalDatasetReference": { # Configures the access a dataset defined in an external metadata storage. # Optional. Information about the external metadata storage where the dataset is defined. Filled out when the dataset type is EXTERNAL. + "connection": "A String", # Required. The connection id that is used to access the external_source. Format: projects/{project_id}/locations/{location_id}/connections/{connection_id} + "externalSource": "A String", # Required. External source that backs this dataset. + }, + "friendlyName": "A String", # Optional. A descriptive name for the dataset. + "id": "A String", # Output only. The fully-qualified unique name of the dataset in the format projectId:datasetId. The dataset name without the project name is given in the datasetId field. When creating a new dataset, leave this field blank, and instead specify the datasetId field. + "isCaseInsensitive": True or False, # Optional. TRUE if the dataset and its table names are case-insensitive, otherwise FALSE. By default, this is FALSE, which means the dataset and its table names are case-sensitive. This field does not affect routine references. + "kind": "bigquery#dataset", # Output only. The resource type. "labels": { # The labels associated with this dataset. You can use these to organize and group your datasets. You can set this property when inserting or updating a dataset. See Creating and Updating Dataset Labels for more information. "a_key": "A String", }, - "lastModifiedTime": "A String", # [Output-only] The date when this dataset or any of its tables was last modified, in milliseconds since the epoch. - "location": "A String", # The geographic location where the dataset should reside. The default value is US. See details at https://cloud.google.com/bigquery/docs/locations. - "maxTimeTravelHours": "A String", # [Optional] Number of hours for the max time travel for all tables in the dataset. - "satisfiesPzs": True or False, # [Output-only] Reserved for future use. - "selfLink": "A String", # [Output-only] A URL that can be used to access the resource again. You can use this URL in Get or Update requests to the resource. - "storageBillingModel": "A String", # [Optional] Storage billing model to be used for all tables in the dataset. Can be set to PHYSICAL. Default is LOGICAL. - "tags": [ # [Optional]The tags associated with this dataset. Tag keys are globally unique. + "lastModifiedTime": "A String", # Output only. The date when this dataset was last modified, in milliseconds since the epoch. + "linkedDatasetSource": { # A dataset source type which refers to another BigQuery dataset. # Optional. The source dataset reference when the dataset is of type LINKED. For all other dataset types it is not set. This field cannot be updated once it is set. Any attempt to update this field using Update and Patch API Operations will be ignored. + "sourceDataset": { # The source dataset reference contains project numbers and not project ids. + "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. + "projectId": "A String", # Optional. The ID of the project containing this dataset. + }, + }, + "location": "A String", # The geographic location where the dataset should reside. See https://cloud.google.com/bigquery/docs/locations for supported locations. + "maxTimeTravelHours": "A String", # Optional. Defines the time travel window in hours. The value can be from 48 to 168 hours (2 to 7 days). The default value is 168 hours if this is not set. + "satisfiesPzs": True or False, # Output only. Reserved for future use. + "selfLink": "A String", # Output only. A URL that can be used to access the resource again. You can use this URL in Get or Update requests to the resource. + "storageBillingModel": "A String", # Optional. Updates storage_billing_model for the dataset. + "tags": [ # Output only. Tags for the Dataset. + { # A global tag managed by Resource Manager. https://cloud.google.com/iam/docs/tags-access-control#definitions + "tagKey": "A String", # Required. The namespaced friendly name of the tag key, e.g. "12345/environment" where 12345 is org id. + "tagValue": "A String", # Required. The friendly short name of the tag value, e.g. "production". + }, + ], + "type": "A String", # Output only. Same as `type` in `ListFormatDataset`. The type of the dataset, one of: * DEFAULT - only accessible by owner and authorized accounts, * PUBLIC - accessible by everyone, * LINKED - linked dataset, * EXTERNAL - dataset with definition in external metadata catalog. -- *BIGLAKE_METASTORE - dataset that references a database created in BigLakeMetastore service. -- +}+
undelete(projectId, datasetId, body=None, x__xgafv=None)
+ Undeletes a dataset which is within time travel window based on datasetId. If a time is specified, the dataset version deleted at that time is undeleted, else the last live version is undeleted.
+
+Args:
+ projectId: string, Required. Project ID of the dataset to be undeleted (required)
+ datasetId: string, Required. Dataset ID of dataset being deleted (required)
+ body: object, The request body.
+ The object takes the form of:
+
+{ # Request format for undeleting a dataset.
+ "deletionTime": "A String", # Optional. The exact time when the dataset was deleted. If not specified, it will undelete the most recently deleted version.
+}
+
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
+
+Returns:
+ An object of the form:
+
{
- "tagKey": "A String", # [Required] The namespaced friendly name of the tag key, e.g. "12345/environment" where 12345 is org id.
- "tagValue": "A String", # [Required] Friendly short name of the tag value, e.g. "production".
+ "access": [ # Optional. An array of objects that define dataset access for one or more entities. You can set this property when inserting or updating a dataset in order to control who is allowed to access the data. If unspecified at dataset creation time, BigQuery adds default dataset access for the following entities: access.specialGroup: projectReaders; access.role: READER; access.specialGroup: projectWriters; access.role: WRITER; access.specialGroup: projectOwners; access.role: OWNER; access.userByEmail: [dataset creator email]; access.role: OWNER;
+ { # An object that defines dataset access for an entity.
+ "dataset": { # Grants all resources of particular types in a particular dataset read access to the current dataset. Similar to how individually authorized views work, updates to any resource granted through its dataset (including creation of new resources) requires read permission to referenced resources, plus write permission to the authorizing dataset. # [Pick one] A grant authorizing all resources of a particular type in a particular dataset access to this dataset. Only views are supported for now. The role field is not required when this field is set. If that dataset is deleted and re-created, its access needs to be granted again via an update operation.
+ "dataset": { # The dataset this entry applies to
+ "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "projectId": "A String", # Optional. The ID of the project containing this dataset.
+ },
+ "targetTypes": [ # Which resources in the dataset this entry applies to. Currently, only views are supported, but additional target types may be added in the future.
+ "A String",
+ ],
+ },
+ "domain": "A String", # [Pick one] A domain to grant access to. Any users signed in with the domain specified will be granted the specified access. Example: "example.com". Maps to IAM policy member "domain:DOMAIN".
+ "groupByEmail": "A String", # [Pick one] An email address of a Google Group to grant access to. Maps to IAM policy member "group:GROUP".
+ "iamMember": "A String", # [Pick one] Some other type of member that appears in the IAM Policy but isn't a user, group, domain, or special group.
+ "role": "A String", # An IAM role ID that should be granted to the user, group, or domain specified in this access entry. The following legacy mappings will be applied: OWNER <=> roles/bigquery.dataOwner WRITER <=> roles/bigquery.dataEditor READER <=> roles/bigquery.dataViewer This field will accept any of the above formats, but will return only the legacy format. For example, if you set this field to "roles/bigquery.dataOwner", it will be returned back as "OWNER".
+ "routine": { # Id path of a routine. # [Pick one] A routine from a different dataset to grant access to. Queries executed against that routine will have read access to views/tables/routines in this dataset. Only UDF is supported for now. The role field is not required when this field is set. If that routine is updated by any user, access to the routine needs to be granted again via an update operation.
+ "datasetId": "A String", # Required. The ID of the dataset containing this routine.
+ "projectId": "A String", # Required. The ID of the project containing this routine.
+ "routineId": "A String", # Required. The ID of the routine. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 256 characters.
+ },
+ "specialGroup": "A String", # [Pick one] A special group to grant access to. Possible values include: projectOwners: Owners of the enclosing project. projectReaders: Readers of the enclosing project. projectWriters: Writers of the enclosing project. allAuthenticatedUsers: All authenticated BigQuery users. Maps to similarly-named IAM members.
+ "userByEmail": "A String", # [Pick one] An email address of a user to grant access to. For example: fred@example.com. Maps to IAM policy member "user:EMAIL" or "serviceAccount:EMAIL".
+ "view": { # [Pick one] A view from a different dataset to grant access to. Queries executed against that view will have read access to views/tables/routines in this dataset. The role field is not required when this field is set. If that view is updated by any user, access to the view needs to be granted again via an update operation.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ },
+ ],
+ "creationTime": "A String", # Output only. The time when this dataset was created, in milliseconds since the epoch.
+ "datasetReference": { # Required. A reference that identifies the dataset.
+ "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "projectId": "A String", # Optional. The ID of the project containing this dataset.
+ },
+ "defaultCollation": "A String", # Optional. Defines the default collation specification of future tables created in the dataset. If a table is created in this dataset without table-level default collation, then the table inherits the dataset default collation, which is applied to the string fields that do not have explicit collation specified. A change to this field affects only tables created afterwards, and does not alter the existing tables. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.
+ "defaultEncryptionConfiguration": { # The default encryption key for all tables in the dataset. Once this property is set, all newly-created partitioned tables in the dataset will have encryption key set to this value, unless table creation request (or query) overrides the key.
+ "kmsKeyName": "A String", # Optional. Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key.
+ },
+ "defaultPartitionExpirationMs": "A String", # This default partition expiration, expressed in milliseconds. When new time-partitioned tables are created in a dataset where this property is set, the table will inherit this value, propagated as the `TimePartitioning.expirationMs` property on the new table. If you set `TimePartitioning.expirationMs` explicitly when creating a table, the `defaultPartitionExpirationMs` of the containing dataset is ignored. When creating a partitioned table, if `defaultPartitionExpirationMs` is set, the `defaultTableExpirationMs` value is ignored and the table will not be inherit a table expiration deadline.
+ "defaultRoundingMode": "A String", # Optional. Defines the default rounding mode specification of new tables created within this dataset. During table creation, if this field is specified, the table within this dataset will inherit the default rounding mode of the dataset. Setting the default rounding mode on a table overrides this option. Existing tables in the dataset are unaffected. If columns are defined during that table creation, they will immediately inherit the table's default rounding mode, unless otherwise specified.
+ "defaultTableExpirationMs": "A String", # Optional. The default lifetime of all tables in the dataset, in milliseconds. The minimum lifetime value is 3600000 milliseconds (one hour). To clear an existing default expiration with a PATCH request, set to 0. Once this property is set, all newly-created tables in the dataset will have an expirationTime property set to the creation time plus the value in this property, and changing the value will only affect new tables, not existing ones. When the expirationTime for a given table is reached, that table will be deleted automatically. If a table's expirationTime is modified or removed before the table expires, or if you provide an explicit expirationTime when creating a table, that value takes precedence over the default expiration time indicated by this property.
+ "description": "A String", # Optional. A user-friendly description of the dataset.
+ "etag": "A String", # Output only. A hash of the resource.
+ "externalDatasetReference": { # Configures the access a dataset defined in an external metadata storage. # Optional. Information about the external metadata storage where the dataset is defined. Filled out when the dataset type is EXTERNAL.
+ "connection": "A String", # Required. The connection id that is used to access the external_source. Format: projects/{project_id}/locations/{location_id}/connections/{connection_id}
+ "externalSource": "A String", # Required. External source that backs this dataset.
+ },
+ "friendlyName": "A String", # Optional. A descriptive name for the dataset.
+ "id": "A String", # Output only. The fully-qualified unique name of the dataset in the format projectId:datasetId. The dataset name without the project name is given in the datasetId field. When creating a new dataset, leave this field blank, and instead specify the datasetId field.
+ "isCaseInsensitive": True or False, # Optional. TRUE if the dataset and its table names are case-insensitive, otherwise FALSE. By default, this is FALSE, which means the dataset and its table names are case-sensitive. This field does not affect routine references.
+ "kind": "bigquery#dataset", # Output only. The resource type.
+ "labels": { # The labels associated with this dataset. You can use these to organize and group your datasets. You can set this property when inserting or updating a dataset. See Creating and Updating Dataset Labels for more information.
+ "a_key": "A String",
+ },
+ "lastModifiedTime": "A String", # Output only. The date when this dataset was last modified, in milliseconds since the epoch.
+ "linkedDatasetSource": { # A dataset source type which refers to another BigQuery dataset. # Optional. The source dataset reference when the dataset is of type LINKED. For all other dataset types it is not set. This field cannot be updated once it is set. Any attempt to update this field using Update and Patch API Operations will be ignored.
+ "sourceDataset": { # The source dataset reference contains project numbers and not project ids.
+ "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "projectId": "A String", # Optional. The ID of the project containing this dataset.
+ },
+ },
+ "location": "A String", # The geographic location where the dataset should reside. See https://cloud.google.com/bigquery/docs/locations for supported locations.
+ "maxTimeTravelHours": "A String", # Optional. Defines the time travel window in hours. The value can be from 48 to 168 hours (2 to 7 days). The default value is 168 hours if this is not set.
+ "satisfiesPzs": True or False, # Output only. Reserved for future use.
+ "selfLink": "A String", # Output only. A URL that can be used to access the resource again. You can use this URL in Get or Update requests to the resource.
+ "storageBillingModel": "A String", # Optional. Updates storage_billing_model for the dataset.
+ "tags": [ # Output only. Tags for the Dataset.
+ { # A global tag managed by Resource Manager. https://cloud.google.com/iam/docs/tags-access-control#definitions
+ "tagKey": "A String", # Required. The namespaced friendly name of the tag key, e.g. "12345/environment" where 12345 is org id.
+ "tagValue": "A String", # Required. The friendly short name of the tag value, e.g. "production".
},
],
+ "type": "A String", # Output only. Same as `type` in `ListFormatDataset`. The type of the dataset, one of: * DEFAULT - only accessible by owner and authorized accounts, * PUBLIC - accessible by everyone, * LINKED - linked dataset, * EXTERNAL - dataset with definition in external metadata catalog. -- *BIGLAKE_METASTORE - dataset that references a database created in BigLakeMetastore service. --
}
update(projectId, datasetId, body=None)
+ update(projectId, datasetId, body=None, x__xgafv=None)
Updates information in an existing dataset. The update method replaces the entire dataset resource, whereas the patch method only replaces fields that are provided in the submitted dataset resource.
Args:
- projectId: string, Project ID of the dataset being updated (required)
- datasetId: string, Dataset ID of the dataset being updated (required)
+ projectId: string, Required. Project ID of the dataset being updated (required)
+ datasetId: string, Required. Dataset ID of the dataset being updated (required)
body: object, The request body.
The object takes the form of:
{
- "access": [ # [Optional] An array of objects that define dataset access for one or more entities. You can set this property when inserting or updating a dataset in order to control who is allowed to access the data. If unspecified at dataset creation time, BigQuery adds default dataset access for the following entities: access.specialGroup: projectReaders; access.role: READER; access.specialGroup: projectWriters; access.role: WRITER; access.specialGroup: projectOwners; access.role: OWNER; access.userByEmail: [dataset creator email]; access.role: OWNER;
- {
- "dataset": { # [Pick one] A grant authorizing all resources of a particular type in a particular dataset access to this dataset. Only views are supported for now. The role field is not required when this field is set. If that dataset is deleted and re-created, its access needs to be granted again via an update operation.
- "dataset": { # [Required] The dataset this entry applies to.
- "datasetId": "A String", # [Required] A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- "projectId": "A String", # [Optional] The ID of the project containing this dataset.
+ "access": [ # Optional. An array of objects that define dataset access for one or more entities. You can set this property when inserting or updating a dataset in order to control who is allowed to access the data. If unspecified at dataset creation time, BigQuery adds default dataset access for the following entities: access.specialGroup: projectReaders; access.role: READER; access.specialGroup: projectWriters; access.role: WRITER; access.specialGroup: projectOwners; access.role: OWNER; access.userByEmail: [dataset creator email]; access.role: OWNER;
+ { # An object that defines dataset access for an entity.
+ "dataset": { # Grants all resources of particular types in a particular dataset read access to the current dataset. Similar to how individually authorized views work, updates to any resource granted through its dataset (including creation of new resources) requires read permission to referenced resources, plus write permission to the authorizing dataset. # [Pick one] A grant authorizing all resources of a particular type in a particular dataset access to this dataset. Only views are supported for now. The role field is not required when this field is set. If that dataset is deleted and re-created, its access needs to be granted again via an update operation.
+ "dataset": { # The dataset this entry applies to
+ "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "projectId": "A String", # Optional. The ID of the project containing this dataset.
},
- "targetTypes": [
+ "targetTypes": [ # Which resources in the dataset this entry applies to. Currently, only views are supported, but additional target types may be added in the future.
"A String",
],
},
"domain": "A String", # [Pick one] A domain to grant access to. Any users signed in with the domain specified will be granted the specified access. Example: "example.com". Maps to IAM policy member "domain:DOMAIN".
"groupByEmail": "A String", # [Pick one] An email address of a Google Group to grant access to. Maps to IAM policy member "group:GROUP".
"iamMember": "A String", # [Pick one] Some other type of member that appears in the IAM Policy but isn't a user, group, domain, or special group.
- "role": "A String", # [Required] An IAM role ID that should be granted to the user, group, or domain specified in this access entry. The following legacy mappings will be applied: OWNER roles/bigquery.dataOwner WRITER roles/bigquery.dataEditor READER roles/bigquery.dataViewer This field will accept any of the above formats, but will return only the legacy format. For example, if you set this field to "roles/bigquery.dataOwner", it will be returned back as "OWNER".
- "routine": { # [Pick one] A routine from a different dataset to grant access to. Queries executed against that routine will have read access to views/tables/routines in this dataset. Only UDF is supported for now. The role field is not required when this field is set. If that routine is updated by any user, access to the routine needs to be granted again via an update operation.
+ "role": "A String", # An IAM role ID that should be granted to the user, group, or domain specified in this access entry. The following legacy mappings will be applied: OWNER <=> roles/bigquery.dataOwner WRITER <=> roles/bigquery.dataEditor READER <=> roles/bigquery.dataViewer This field will accept any of the above formats, but will return only the legacy format. For example, if you set this field to "roles/bigquery.dataOwner", it will be returned back as "OWNER".
+ "routine": { # Id path of a routine. # [Pick one] A routine from a different dataset to grant access to. Queries executed against that routine will have read access to views/tables/routines in this dataset. Only UDF is supported for now. The role field is not required when this field is set. If that routine is updated by any user, access to the routine needs to be granted again via an update operation.
"datasetId": "A String", # Required. The ID of the dataset containing this routine.
"projectId": "A String", # Required. The ID of the project containing this routine.
"routineId": "A String", # Required. The ID of the routine. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 256 characters.
},
"specialGroup": "A String", # [Pick one] A special group to grant access to. Possible values include: projectOwners: Owners of the enclosing project. projectReaders: Readers of the enclosing project. projectWriters: Writers of the enclosing project. allAuthenticatedUsers: All authenticated BigQuery users. Maps to similarly-named IAM members.
"userByEmail": "A String", # [Pick one] An email address of a user to grant access to. For example: fred@example.com. Maps to IAM policy member "user:EMAIL" or "serviceAccount:EMAIL".
- "view": { # [Pick one] A view from a different dataset to grant access to. Queries executed against that view will have read access to tables in this dataset. The role field is not required when this field is set. If that view is updated by any user, access to the view needs to be granted again via an update operation.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "view": { # [Pick one] A view from a different dataset to grant access to. Queries executed against that view will have read access to views/tables/routines in this dataset. The role field is not required when this field is set. If that view is updated by any user, access to the view needs to be granted again via an update operation.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
},
],
- "creationTime": "A String", # [Output-only] The time when this dataset was created, in milliseconds since the epoch.
- "datasetReference": { # [Required] A reference that identifies the dataset.
- "datasetId": "A String", # [Required] A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- "projectId": "A String", # [Optional] The ID of the project containing this dataset.
+ "creationTime": "A String", # Output only. The time when this dataset was created, in milliseconds since the epoch.
+ "datasetReference": { # Required. A reference that identifies the dataset.
+ "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "projectId": "A String", # Optional. The ID of the project containing this dataset.
},
- "defaultCollation": "A String", # [Output-only] The default collation of the dataset.
- "defaultEncryptionConfiguration": {
+ "defaultCollation": "A String", # Optional. Defines the default collation specification of future tables created in the dataset. If a table is created in this dataset without table-level default collation, then the table inherits the dataset default collation, which is applied to the string fields that do not have explicit collation specified. A change to this field affects only tables created afterwards, and does not alter the existing tables. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.
+ "defaultEncryptionConfiguration": { # The default encryption key for all tables in the dataset. Once this property is set, all newly-created partitioned tables in the dataset will have encryption key set to this value, unless table creation request (or query) overrides the key.
"kmsKeyName": "A String", # Optional. Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key.
},
- "defaultPartitionExpirationMs": "A String", # [Optional] The default partition expiration for all partitioned tables in the dataset, in milliseconds. Once this property is set, all newly-created partitioned tables in the dataset will have an expirationMs property in the timePartitioning settings set to this value, and changing the value will only affect new tables, not existing ones. The storage in a partition will have an expiration time of its partition time plus this value. Setting this property overrides the use of defaultTableExpirationMs for partitioned tables: only one of defaultTableExpirationMs and defaultPartitionExpirationMs will be used for any new partitioned table. If you provide an explicit timePartitioning.expirationMs when creating or updating a partitioned table, that value takes precedence over the default partition expiration time indicated by this property.
- "defaultRoundingMode": "A String", # [Output-only] The default rounding mode of the dataset.
- "defaultTableExpirationMs": "A String", # [Optional] The default lifetime of all tables in the dataset, in milliseconds. The minimum value is 3600000 milliseconds (one hour). Once this property is set, all newly-created tables in the dataset will have an expirationTime property set to the creation time plus the value in this property, and changing the value will only affect new tables, not existing ones. When the expirationTime for a given table is reached, that table will be deleted automatically. If a table's expirationTime is modified or removed before the table expires, or if you provide an explicit expirationTime when creating a table, that value takes precedence over the default expiration time indicated by this property.
- "description": "A String", # [Optional] A user-friendly description of the dataset.
- "etag": "A String", # [Output-only] A hash of the resource.
- "externalDatasetReference": { # [Optional] Information about the external metadata storage where the dataset is defined. Filled out when the dataset type is EXTERNAL.
- "connection": "A String", # [Required] The connection id that is used to access the external_source. Format: projects/{project_id}/locations/{location_id}/connections/{connection_id}
- "externalSource": "A String", # [Required] External source that backs this dataset.
- },
- "friendlyName": "A String", # [Optional] A descriptive name for the dataset.
- "id": "A String", # [Output-only] The fully-qualified unique name of the dataset in the format projectId:datasetId. The dataset name without the project name is given in the datasetId field. When creating a new dataset, leave this field blank, and instead specify the datasetId field.
- "isCaseInsensitive": True or False, # [Optional] Indicates if table names are case insensitive in the dataset.
- "kind": "bigquery#dataset", # [Output-only] The resource type.
+ "defaultPartitionExpirationMs": "A String", # This default partition expiration, expressed in milliseconds. When new time-partitioned tables are created in a dataset where this property is set, the table will inherit this value, propagated as the `TimePartitioning.expirationMs` property on the new table. If you set `TimePartitioning.expirationMs` explicitly when creating a table, the `defaultPartitionExpirationMs` of the containing dataset is ignored. When creating a partitioned table, if `defaultPartitionExpirationMs` is set, the `defaultTableExpirationMs` value is ignored and the table will not be inherit a table expiration deadline.
+ "defaultRoundingMode": "A String", # Optional. Defines the default rounding mode specification of new tables created within this dataset. During table creation, if this field is specified, the table within this dataset will inherit the default rounding mode of the dataset. Setting the default rounding mode on a table overrides this option. Existing tables in the dataset are unaffected. If columns are defined during that table creation, they will immediately inherit the table's default rounding mode, unless otherwise specified.
+ "defaultTableExpirationMs": "A String", # Optional. The default lifetime of all tables in the dataset, in milliseconds. The minimum lifetime value is 3600000 milliseconds (one hour). To clear an existing default expiration with a PATCH request, set to 0. Once this property is set, all newly-created tables in the dataset will have an expirationTime property set to the creation time plus the value in this property, and changing the value will only affect new tables, not existing ones. When the expirationTime for a given table is reached, that table will be deleted automatically. If a table's expirationTime is modified or removed before the table expires, or if you provide an explicit expirationTime when creating a table, that value takes precedence over the default expiration time indicated by this property.
+ "description": "A String", # Optional. A user-friendly description of the dataset.
+ "etag": "A String", # Output only. A hash of the resource.
+ "externalDatasetReference": { # Configures the access a dataset defined in an external metadata storage. # Optional. Information about the external metadata storage where the dataset is defined. Filled out when the dataset type is EXTERNAL.
+ "connection": "A String", # Required. The connection id that is used to access the external_source. Format: projects/{project_id}/locations/{location_id}/connections/{connection_id}
+ "externalSource": "A String", # Required. External source that backs this dataset.
+ },
+ "friendlyName": "A String", # Optional. A descriptive name for the dataset.
+ "id": "A String", # Output only. The fully-qualified unique name of the dataset in the format projectId:datasetId. The dataset name without the project name is given in the datasetId field. When creating a new dataset, leave this field blank, and instead specify the datasetId field.
+ "isCaseInsensitive": True or False, # Optional. TRUE if the dataset and its table names are case-insensitive, otherwise FALSE. By default, this is FALSE, which means the dataset and its table names are case-sensitive. This field does not affect routine references.
+ "kind": "bigquery#dataset", # Output only. The resource type.
"labels": { # The labels associated with this dataset. You can use these to organize and group your datasets. You can set this property when inserting or updating a dataset. See Creating and Updating Dataset Labels for more information.
"a_key": "A String",
},
- "lastModifiedTime": "A String", # [Output-only] The date when this dataset or any of its tables was last modified, in milliseconds since the epoch.
- "location": "A String", # The geographic location where the dataset should reside. The default value is US. See details at https://cloud.google.com/bigquery/docs/locations.
- "maxTimeTravelHours": "A String", # [Optional] Number of hours for the max time travel for all tables in the dataset.
- "satisfiesPzs": True or False, # [Output-only] Reserved for future use.
- "selfLink": "A String", # [Output-only] A URL that can be used to access the resource again. You can use this URL in Get or Update requests to the resource.
- "storageBillingModel": "A String", # [Optional] Storage billing model to be used for all tables in the dataset. Can be set to PHYSICAL. Default is LOGICAL.
- "tags": [ # [Optional]The tags associated with this dataset. Tag keys are globally unique.
- {
- "tagKey": "A String", # [Required] The namespaced friendly name of the tag key, e.g. "12345/environment" where 12345 is org id.
- "tagValue": "A String", # [Required] Friendly short name of the tag value, e.g. "production".
+ "lastModifiedTime": "A String", # Output only. The date when this dataset was last modified, in milliseconds since the epoch.
+ "linkedDatasetSource": { # A dataset source type which refers to another BigQuery dataset. # Optional. The source dataset reference when the dataset is of type LINKED. For all other dataset types it is not set. This field cannot be updated once it is set. Any attempt to update this field using Update and Patch API Operations will be ignored.
+ "sourceDataset": { # The source dataset reference contains project numbers and not project ids.
+ "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "projectId": "A String", # Optional. The ID of the project containing this dataset.
+ },
+ },
+ "location": "A String", # The geographic location where the dataset should reside. See https://cloud.google.com/bigquery/docs/locations for supported locations.
+ "maxTimeTravelHours": "A String", # Optional. Defines the time travel window in hours. The value can be from 48 to 168 hours (2 to 7 days). The default value is 168 hours if this is not set.
+ "satisfiesPzs": True or False, # Output only. Reserved for future use.
+ "selfLink": "A String", # Output only. A URL that can be used to access the resource again. You can use this URL in Get or Update requests to the resource.
+ "storageBillingModel": "A String", # Optional. Updates storage_billing_model for the dataset.
+ "tags": [ # Output only. Tags for the Dataset.
+ { # A global tag managed by Resource Manager. https://cloud.google.com/iam/docs/tags-access-control#definitions
+ "tagKey": "A String", # Required. The namespaced friendly name of the tag key, e.g. "12345/environment" where 12345 is org id.
+ "tagValue": "A String", # Required. The friendly short name of the tag value, e.g. "production".
},
],
+ "type": "A String", # Output only. Same as `type` in `ListFormatDataset`. The type of the dataset, one of: * DEFAULT - only accessible by owner and authorized accounts, * PUBLIC - accessible by everyone, * LINKED - linked dataset, * EXTERNAL - dataset with definition in external metadata catalog. -- *BIGLAKE_METASTORE - dataset that references a database created in BigLakeMetastore service. --
}
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
Returns:
An object of the form:
{
- "access": [ # [Optional] An array of objects that define dataset access for one or more entities. You can set this property when inserting or updating a dataset in order to control who is allowed to access the data. If unspecified at dataset creation time, BigQuery adds default dataset access for the following entities: access.specialGroup: projectReaders; access.role: READER; access.specialGroup: projectWriters; access.role: WRITER; access.specialGroup: projectOwners; access.role: OWNER; access.userByEmail: [dataset creator email]; access.role: OWNER;
- {
- "dataset": { # [Pick one] A grant authorizing all resources of a particular type in a particular dataset access to this dataset. Only views are supported for now. The role field is not required when this field is set. If that dataset is deleted and re-created, its access needs to be granted again via an update operation.
- "dataset": { # [Required] The dataset this entry applies to.
- "datasetId": "A String", # [Required] A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- "projectId": "A String", # [Optional] The ID of the project containing this dataset.
+ "access": [ # Optional. An array of objects that define dataset access for one or more entities. You can set this property when inserting or updating a dataset in order to control who is allowed to access the data. If unspecified at dataset creation time, BigQuery adds default dataset access for the following entities: access.specialGroup: projectReaders; access.role: READER; access.specialGroup: projectWriters; access.role: WRITER; access.specialGroup: projectOwners; access.role: OWNER; access.userByEmail: [dataset creator email]; access.role: OWNER;
+ { # An object that defines dataset access for an entity.
+ "dataset": { # Grants all resources of particular types in a particular dataset read access to the current dataset. Similar to how individually authorized views work, updates to any resource granted through its dataset (including creation of new resources) requires read permission to referenced resources, plus write permission to the authorizing dataset. # [Pick one] A grant authorizing all resources of a particular type in a particular dataset access to this dataset. Only views are supported for now. The role field is not required when this field is set. If that dataset is deleted and re-created, its access needs to be granted again via an update operation.
+ "dataset": { # The dataset this entry applies to
+ "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "projectId": "A String", # Optional. The ID of the project containing this dataset.
},
- "targetTypes": [
+ "targetTypes": [ # Which resources in the dataset this entry applies to. Currently, only views are supported, but additional target types may be added in the future.
"A String",
],
},
"domain": "A String", # [Pick one] A domain to grant access to. Any users signed in with the domain specified will be granted the specified access. Example: "example.com". Maps to IAM policy member "domain:DOMAIN".
"groupByEmail": "A String", # [Pick one] An email address of a Google Group to grant access to. Maps to IAM policy member "group:GROUP".
"iamMember": "A String", # [Pick one] Some other type of member that appears in the IAM Policy but isn't a user, group, domain, or special group.
- "role": "A String", # [Required] An IAM role ID that should be granted to the user, group, or domain specified in this access entry. The following legacy mappings will be applied: OWNER roles/bigquery.dataOwner WRITER roles/bigquery.dataEditor READER roles/bigquery.dataViewer This field will accept any of the above formats, but will return only the legacy format. For example, if you set this field to "roles/bigquery.dataOwner", it will be returned back as "OWNER".
- "routine": { # [Pick one] A routine from a different dataset to grant access to. Queries executed against that routine will have read access to views/tables/routines in this dataset. Only UDF is supported for now. The role field is not required when this field is set. If that routine is updated by any user, access to the routine needs to be granted again via an update operation.
+ "role": "A String", # An IAM role ID that should be granted to the user, group, or domain specified in this access entry. The following legacy mappings will be applied: OWNER <=> roles/bigquery.dataOwner WRITER <=> roles/bigquery.dataEditor READER <=> roles/bigquery.dataViewer This field will accept any of the above formats, but will return only the legacy format. For example, if you set this field to "roles/bigquery.dataOwner", it will be returned back as "OWNER".
+ "routine": { # Id path of a routine. # [Pick one] A routine from a different dataset to grant access to. Queries executed against that routine will have read access to views/tables/routines in this dataset. Only UDF is supported for now. The role field is not required when this field is set. If that routine is updated by any user, access to the routine needs to be granted again via an update operation.
"datasetId": "A String", # Required. The ID of the dataset containing this routine.
"projectId": "A String", # Required. The ID of the project containing this routine.
"routineId": "A String", # Required. The ID of the routine. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 256 characters.
},
"specialGroup": "A String", # [Pick one] A special group to grant access to. Possible values include: projectOwners: Owners of the enclosing project. projectReaders: Readers of the enclosing project. projectWriters: Writers of the enclosing project. allAuthenticatedUsers: All authenticated BigQuery users. Maps to similarly-named IAM members.
"userByEmail": "A String", # [Pick one] An email address of a user to grant access to. For example: fred@example.com. Maps to IAM policy member "user:EMAIL" or "serviceAccount:EMAIL".
- "view": { # [Pick one] A view from a different dataset to grant access to. Queries executed against that view will have read access to tables in this dataset. The role field is not required when this field is set. If that view is updated by any user, access to the view needs to be granted again via an update operation.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "view": { # [Pick one] A view from a different dataset to grant access to. Queries executed against that view will have read access to views/tables/routines in this dataset. The role field is not required when this field is set. If that view is updated by any user, access to the view needs to be granted again via an update operation.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
},
],
- "creationTime": "A String", # [Output-only] The time when this dataset was created, in milliseconds since the epoch.
- "datasetReference": { # [Required] A reference that identifies the dataset.
- "datasetId": "A String", # [Required] A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- "projectId": "A String", # [Optional] The ID of the project containing this dataset.
+ "creationTime": "A String", # Output only. The time when this dataset was created, in milliseconds since the epoch.
+ "datasetReference": { # Required. A reference that identifies the dataset.
+ "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "projectId": "A String", # Optional. The ID of the project containing this dataset.
},
- "defaultCollation": "A String", # [Output-only] The default collation of the dataset.
- "defaultEncryptionConfiguration": {
+ "defaultCollation": "A String", # Optional. Defines the default collation specification of future tables created in the dataset. If a table is created in this dataset without table-level default collation, then the table inherits the dataset default collation, which is applied to the string fields that do not have explicit collation specified. A change to this field affects only tables created afterwards, and does not alter the existing tables. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.
+ "defaultEncryptionConfiguration": { # The default encryption key for all tables in the dataset. Once this property is set, all newly-created partitioned tables in the dataset will have encryption key set to this value, unless table creation request (or query) overrides the key.
"kmsKeyName": "A String", # Optional. Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key.
},
- "defaultPartitionExpirationMs": "A String", # [Optional] The default partition expiration for all partitioned tables in the dataset, in milliseconds. Once this property is set, all newly-created partitioned tables in the dataset will have an expirationMs property in the timePartitioning settings set to this value, and changing the value will only affect new tables, not existing ones. The storage in a partition will have an expiration time of its partition time plus this value. Setting this property overrides the use of defaultTableExpirationMs for partitioned tables: only one of defaultTableExpirationMs and defaultPartitionExpirationMs will be used for any new partitioned table. If you provide an explicit timePartitioning.expirationMs when creating or updating a partitioned table, that value takes precedence over the default partition expiration time indicated by this property.
- "defaultRoundingMode": "A String", # [Output-only] The default rounding mode of the dataset.
- "defaultTableExpirationMs": "A String", # [Optional] The default lifetime of all tables in the dataset, in milliseconds. The minimum value is 3600000 milliseconds (one hour). Once this property is set, all newly-created tables in the dataset will have an expirationTime property set to the creation time plus the value in this property, and changing the value will only affect new tables, not existing ones. When the expirationTime for a given table is reached, that table will be deleted automatically. If a table's expirationTime is modified or removed before the table expires, or if you provide an explicit expirationTime when creating a table, that value takes precedence over the default expiration time indicated by this property.
- "description": "A String", # [Optional] A user-friendly description of the dataset.
- "etag": "A String", # [Output-only] A hash of the resource.
- "externalDatasetReference": { # [Optional] Information about the external metadata storage where the dataset is defined. Filled out when the dataset type is EXTERNAL.
- "connection": "A String", # [Required] The connection id that is used to access the external_source. Format: projects/{project_id}/locations/{location_id}/connections/{connection_id}
- "externalSource": "A String", # [Required] External source that backs this dataset.
- },
- "friendlyName": "A String", # [Optional] A descriptive name for the dataset.
- "id": "A String", # [Output-only] The fully-qualified unique name of the dataset in the format projectId:datasetId. The dataset name without the project name is given in the datasetId field. When creating a new dataset, leave this field blank, and instead specify the datasetId field.
- "isCaseInsensitive": True or False, # [Optional] Indicates if table names are case insensitive in the dataset.
- "kind": "bigquery#dataset", # [Output-only] The resource type.
+ "defaultPartitionExpirationMs": "A String", # This default partition expiration, expressed in milliseconds. When new time-partitioned tables are created in a dataset where this property is set, the table will inherit this value, propagated as the `TimePartitioning.expirationMs` property on the new table. If you set `TimePartitioning.expirationMs` explicitly when creating a table, the `defaultPartitionExpirationMs` of the containing dataset is ignored. When creating a partitioned table, if `defaultPartitionExpirationMs` is set, the `defaultTableExpirationMs` value is ignored and the table will not be inherit a table expiration deadline.
+ "defaultRoundingMode": "A String", # Optional. Defines the default rounding mode specification of new tables created within this dataset. During table creation, if this field is specified, the table within this dataset will inherit the default rounding mode of the dataset. Setting the default rounding mode on a table overrides this option. Existing tables in the dataset are unaffected. If columns are defined during that table creation, they will immediately inherit the table's default rounding mode, unless otherwise specified.
+ "defaultTableExpirationMs": "A String", # Optional. The default lifetime of all tables in the dataset, in milliseconds. The minimum lifetime value is 3600000 milliseconds (one hour). To clear an existing default expiration with a PATCH request, set to 0. Once this property is set, all newly-created tables in the dataset will have an expirationTime property set to the creation time plus the value in this property, and changing the value will only affect new tables, not existing ones. When the expirationTime for a given table is reached, that table will be deleted automatically. If a table's expirationTime is modified or removed before the table expires, or if you provide an explicit expirationTime when creating a table, that value takes precedence over the default expiration time indicated by this property.
+ "description": "A String", # Optional. A user-friendly description of the dataset.
+ "etag": "A String", # Output only. A hash of the resource.
+ "externalDatasetReference": { # Configures the access a dataset defined in an external metadata storage. # Optional. Information about the external metadata storage where the dataset is defined. Filled out when the dataset type is EXTERNAL.
+ "connection": "A String", # Required. The connection id that is used to access the external_source. Format: projects/{project_id}/locations/{location_id}/connections/{connection_id}
+ "externalSource": "A String", # Required. External source that backs this dataset.
+ },
+ "friendlyName": "A String", # Optional. A descriptive name for the dataset.
+ "id": "A String", # Output only. The fully-qualified unique name of the dataset in the format projectId:datasetId. The dataset name without the project name is given in the datasetId field. When creating a new dataset, leave this field blank, and instead specify the datasetId field.
+ "isCaseInsensitive": True or False, # Optional. TRUE if the dataset and its table names are case-insensitive, otherwise FALSE. By default, this is FALSE, which means the dataset and its table names are case-sensitive. This field does not affect routine references.
+ "kind": "bigquery#dataset", # Output only. The resource type.
"labels": { # The labels associated with this dataset. You can use these to organize and group your datasets. You can set this property when inserting or updating a dataset. See Creating and Updating Dataset Labels for more information.
"a_key": "A String",
},
- "lastModifiedTime": "A String", # [Output-only] The date when this dataset or any of its tables was last modified, in milliseconds since the epoch.
- "location": "A String", # The geographic location where the dataset should reside. The default value is US. See details at https://cloud.google.com/bigquery/docs/locations.
- "maxTimeTravelHours": "A String", # [Optional] Number of hours for the max time travel for all tables in the dataset.
- "satisfiesPzs": True or False, # [Output-only] Reserved for future use.
- "selfLink": "A String", # [Output-only] A URL that can be used to access the resource again. You can use this URL in Get or Update requests to the resource.
- "storageBillingModel": "A String", # [Optional] Storage billing model to be used for all tables in the dataset. Can be set to PHYSICAL. Default is LOGICAL.
- "tags": [ # [Optional]The tags associated with this dataset. Tag keys are globally unique.
- {
- "tagKey": "A String", # [Required] The namespaced friendly name of the tag key, e.g. "12345/environment" where 12345 is org id.
- "tagValue": "A String", # [Required] Friendly short name of the tag value, e.g. "production".
+ "lastModifiedTime": "A String", # Output only. The date when this dataset was last modified, in milliseconds since the epoch.
+ "linkedDatasetSource": { # A dataset source type which refers to another BigQuery dataset. # Optional. The source dataset reference when the dataset is of type LINKED. For all other dataset types it is not set. This field cannot be updated once it is set. Any attempt to update this field using Update and Patch API Operations will be ignored.
+ "sourceDataset": { # The source dataset reference contains project numbers and not project ids.
+ "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "projectId": "A String", # Optional. The ID of the project containing this dataset.
+ },
+ },
+ "location": "A String", # The geographic location where the dataset should reside. See https://cloud.google.com/bigquery/docs/locations for supported locations.
+ "maxTimeTravelHours": "A String", # Optional. Defines the time travel window in hours. The value can be from 48 to 168 hours (2 to 7 days). The default value is 168 hours if this is not set.
+ "satisfiesPzs": True or False, # Output only. Reserved for future use.
+ "selfLink": "A String", # Output only. A URL that can be used to access the resource again. You can use this URL in Get or Update requests to the resource.
+ "storageBillingModel": "A String", # Optional. Updates storage_billing_model for the dataset.
+ "tags": [ # Output only. Tags for the Dataset.
+ { # A global tag managed by Resource Manager. https://cloud.google.com/iam/docs/tags-access-control#definitions
+ "tagKey": "A String", # Required. The namespaced friendly name of the tag key, e.g. "12345/environment" where 12345 is org id.
+ "tagValue": "A String", # Required. The friendly short name of the tag value, e.g. "production".
},
],
+ "type": "A String", # Output only. Same as `type` in `ListFormatDataset`. The type of the dataset, one of: * DEFAULT - only accessible by owner and authorized accounts, * PUBLIC - accessible by everyone, * LINKED - linked dataset, * EXTERNAL - dataset with definition in external metadata catalog. -- *BIGLAKE_METASTORE - dataset that references a database created in BigLakeMetastore service. --
}
- cancel(projectId, jobId, location=None)
cancel(projectId, jobId, location=None, x__xgafv=None)
Requests that a job be cancelled. This call will return immediately, and the client will need to poll for the job status to see if the cancel completed successfully. Cancelled jobs may still incur costs.
Close httplib2 connections.
- delete(projectId, jobId, location=None)
delete(projectId, jobId, location=None, x__xgafv=None)
Requests the deletion of the metadata of a job. This call returns when the job's metadata is deleted.
- get(projectId, jobId, location=None)
get(projectId, jobId, location=None, x__xgafv=None)
Returns information about a specific job. Job information is available for a six month period after creation. Requires that you're the person who ran the job, or have the Is Owner project role.
-Retrieves the results of a query job.
+getQueryResults(projectId, jobId, formatOptions_useInt64Timestamp=None, location=None, maxResults=None, pageToken=None, startIndex=None, timeoutMs=None, x__xgafv=None)
+RPC to get the results of a query job.
Retrieves the next page of results.
- insert(projectId, body=None, media_body=None, media_mime_type=None)
Starts a new asynchronous job. Requires the Can View project role.
+insert(projectId, body=None, media_body=None, media_mime_type=None, x__xgafv=None)
+Starts a new asynchronous job. This API has two different kinds of endpoint URIs, as this method supports a variety of use cases. * The *Metadata* URI is used for most interactions, as it accepts the job configuration directly. * The *Upload* URI is ONLY for the case when you're sending both a load job configuration and a data stream together. In this case, the Upload URI accepts the job configuration and the data as two distinct multipart MIME parts.
+list(projectId, allUsers=None, maxCreationTime=None, maxResults=None, minCreationTime=None, pageToken=None, parentJobId=None, projection=None, stateFilter=None, x__xgafv=None)
Lists all jobs that you started in the specified project. Job information is available for a six month period after creation. The job list is sorted in reverse chronological order, by job creation time. Requires the Can View project role, or the Is Owner project role if you set the allUsers property.
Retrieves the next page of results.
+query(projectId, body=None, x__xgafv=None)
Runs a BigQuery SQL query synchronously and returns query results if the query completes within a specified timeout.
cancel(projectId, jobId, location=None)
+ cancel(projectId, jobId, location=None, x__xgafv=None)
Requests that a job be cancelled. This call will return immediately, and the client will need to poll for the job status to see if the cancel completed successfully. Cancelled jobs may still incur costs.
Args:
- projectId: string, [Required] Project ID of the job to cancel (required)
- jobId: string, [Required] Job ID of the job to cancel (required)
- location: string, The geographic location of the job. Required except for US and EU. See details at https://cloud.google.com/bigquery/docs/locations#specifying_your_location.
+ projectId: string, Required. Project ID of the job to cancel (required)
+ jobId: string, Required. Job ID of the job to cancel (required)
+ location: string, The geographic location of the job. You must specify the location to run the job for the following scenarios: - If the location to run a job is not in the `us` or the `eu` multi-regional location - If the job's location is in a single region (for example, `us-central1`) For more information, see https://cloud.google.com/bigquery/docs/locations#specifying_your_location.
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
Returns:
An object of the form:
- {
+ { # Describes format of a jobs cancellation response.
"job": { # The final state of the job.
- "configuration": { # [Required] Describes the job configuration.
- "copy": { # [Pick one] Copies a table.
- "createDisposition": "A String", # [Optional] Specifies whether the job is allowed to create new tables. The following values are supported: CREATE_IF_NEEDED: If the table does not exist, BigQuery creates the table. CREATE_NEVER: The table must already exist. If it does not, a 'notFound' error is returned in the job result. The default value is CREATE_IF_NEEDED. Creation, truncation and append actions occur as one atomic update upon job completion.
+ "configuration": { # Required. Describes the job configuration.
+ "copy": { # JobConfigurationTableCopy configures a job that copies data from one table to another. For more information on copying tables, see [Copy a table](https://cloud.google.com/bigquery/docs/managing-tables#copy-table). # [Pick one] Copies a table.
+ "createDisposition": "A String", # Optional. Specifies whether the job is allowed to create new tables. The following values are supported: * CREATE_IF_NEEDED: If the table does not exist, BigQuery creates the table. * CREATE_NEVER: The table must already exist. If it does not, a 'notFound' error is returned in the job result. The default value is CREATE_IF_NEEDED. Creation, truncation and append actions occur as one atomic update upon job completion.
"destinationEncryptionConfiguration": { # Custom encryption configuration (e.g., Cloud KMS keys).
"kmsKeyName": "A String", # Optional. Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key.
},
- "destinationExpirationTime": "", # [Optional] The time when the destination table expires. Expired tables will be deleted and their storage reclaimed.
- "destinationTable": { # [Required] The destination table
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "destinationExpirationTime": "A String", # Optional. The time when the destination table expires. Expired tables will be deleted and their storage reclaimed.
+ "destinationTable": { # [Required] The destination table.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
- "operationType": "A String", # [Optional] Supported operation types in table copy job.
+ "operationType": "A String", # Optional. Supported operation types in table copy job.
"sourceTable": { # [Pick one] Source table to copy.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
"sourceTables": [ # [Pick one] Source tables to copy.
{
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
],
- "writeDisposition": "A String", # [Optional] Specifies the action that occurs if the destination table already exists. The following values are supported: WRITE_TRUNCATE: If the table already exists, BigQuery overwrites the table data. WRITE_APPEND: If the table already exists, BigQuery appends the data to the table. WRITE_EMPTY: If the table already exists and contains data, a 'duplicate' error is returned in the job result. The default value is WRITE_EMPTY. Each action is atomic and only occurs if BigQuery is able to complete the job successfully. Creation, truncation and append actions occur as one atomic update upon job completion.
+ "writeDisposition": "A String", # Optional. Specifies the action that occurs if the destination table already exists. The following values are supported: * WRITE_TRUNCATE: If the table already exists, BigQuery overwrites the table data and uses the schema and table constraints from the source table. * WRITE_APPEND: If the table already exists, BigQuery appends the data to the table. * WRITE_EMPTY: If the table already exists and contains data, a 'duplicate' error is returned in the job result. The default value is WRITE_EMPTY. Each action is atomic and only occurs if BigQuery is able to complete the job successfully. Creation, truncation and append actions occur as one atomic update upon job completion.
},
- "dryRun": True or False, # [Optional] If set, don't actually run this job. A valid query will return a mostly empty response with some processing statistics, while an invalid query will return the same error it would if it wasn't a dry run. Behavior of non-query jobs is undefined.
- "extract": { # [Pick one] Configures an extract job.
- "compression": "A String", # [Optional] The compression type to use for exported files. Possible values include GZIP, DEFLATE, SNAPPY, and NONE. The default value is NONE. DEFLATE and SNAPPY are only supported for Avro. Not applicable when extracting models.
- "destinationFormat": "A String", # [Optional] The exported file format. Possible values include CSV, NEWLINE_DELIMITED_JSON, PARQUET or AVRO for tables and ML_TF_SAVED_MODEL or ML_XGBOOST_BOOSTER for models. The default value for tables is CSV. Tables with nested or repeated fields cannot be exported as CSV. The default value for models is ML_TF_SAVED_MODEL.
+ "dryRun": True or False, # Optional. If set, don't actually run this job. A valid query will return a mostly empty response with some processing statistics, while an invalid query will return the same error it would if it wasn't a dry run. Behavior of non-query jobs is undefined.
+ "extract": { # JobConfigurationExtract configures a job that exports data from a BigQuery table into Google Cloud Storage. # [Pick one] Configures an extract job.
+ "compression": "A String", # Optional. The compression type to use for exported files. Possible values include DEFLATE, GZIP, NONE, SNAPPY, and ZSTD. The default value is NONE. Not all compression formats are support for all file formats. DEFLATE is only supported for Avro. ZSTD is only supported for Parquet. Not applicable when extracting models.
+ "destinationFormat": "A String", # Optional. The exported file format. Possible values include CSV, NEWLINE_DELIMITED_JSON, PARQUET, or AVRO for tables and ML_TF_SAVED_MODEL or ML_XGBOOST_BOOSTER for models. The default value for tables is CSV. Tables with nested or repeated fields cannot be exported as CSV. The default value for models is ML_TF_SAVED_MODEL.
"destinationUri": "A String", # [Pick one] DEPRECATED: Use destinationUris instead, passing only one URI as necessary. The fully-qualified Google Cloud Storage URI where the extracted table should be written.
"destinationUris": [ # [Pick one] A list of fully-qualified Google Cloud Storage URIs where the extracted table should be written.
"A String",
],
- "fieldDelimiter": "A String", # [Optional] Delimiter to use between fields in the exported data. Default is ','. Not applicable when extracting models.
- "printHeader": true, # [Optional] Whether to print out a header row in the results. Default is true. Not applicable when extracting models.
- "sourceModel": { # A reference to the model being exported.
+ "fieldDelimiter": "A String", # Optional. When extracting data in CSV format, this defines the delimiter to use between fields in the exported data. Default is ','. Not applicable when extracting models.
+ "modelExtractOptions": { # Options related to model extraction. # Optional. Model extract options only applicable when extracting models.
+ "trialId": "A String", # The 1-based ID of the trial to be exported from a hyperparameter tuning model. If not specified, the trial with id = [Model](/bigquery/docs/reference/rest/v2/models#resource:-model).defaultTrialId is exported. This field is ignored for models not trained with hyperparameter tuning.
+ },
+ "printHeader": true, # Optional. Whether to print out a header row in the results. Default is true. Not applicable when extracting models.
+ "sourceModel": { # Id path of a model. # A reference to the model being exported.
"datasetId": "A String", # Required. The ID of the dataset containing this model.
"modelId": "A String", # Required. The ID of the model. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
"projectId": "A String", # Required. The ID of the project containing this model.
},
"sourceTable": { # A reference to the table being exported.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
- "useAvroLogicalTypes": True or False, # [Optional] If destinationFormat is set to "AVRO", this flag indicates whether to enable extracting applicable column types (such as TIMESTAMP) to their corresponding AVRO logical types (timestamp-micros), instead of only using their raw types (avro-long). Not applicable when extracting models.
+ "useAvroLogicalTypes": True or False, # Whether to use logical types when extracting to AVRO format. Not applicable when extracting models.
},
- "jobTimeoutMs": "A String", # [Optional] Job timeout in milliseconds. If this time limit is exceeded, BigQuery may attempt to terminate the job.
- "jobType": "A String", # [Output-only] The type of the job. Can be QUERY, LOAD, EXTRACT, COPY or UNKNOWN.
+ "jobTimeoutMs": "A String", # Optional. Job timeout in milliseconds. If this time limit is exceeded, BigQuery might attempt to stop the job.
+ "jobType": "A String", # Output only. The type of the job. Can be QUERY, LOAD, EXTRACT, COPY or UNKNOWN.
"labels": { # The labels associated with this job. You can use these to organize and group your jobs. Label keys and values can be no longer than 63 characters, can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. Label values are optional. Label keys must start with a letter and each label in the list must have a different key.
"a_key": "A String",
},
- "load": { # [Pick one] Configures a load job.
- "allowJaggedRows": True or False, # [Optional] Accept rows that are missing trailing optional columns. The missing values are treated as nulls. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. Only applicable to CSV, ignored for other formats.
+ "load": { # JobConfigurationLoad contains the configuration properties for loading data into a destination table. # [Pick one] Configures a load job.
+ "allowJaggedRows": True or False, # Optional. Accept rows that are missing trailing optional columns. The missing values are treated as nulls. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. Only applicable to CSV, ignored for other formats.
"allowQuotedNewlines": True or False, # Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false.
- "autodetect": True or False, # [Optional] Indicates if we should automatically infer the options and schema for CSV and JSON sources.
- "clustering": { # [Beta] Clustering specification for the destination table. Must be specified with time-based partitioning, data in the table will be first partitioned and subsequently clustered.
- "fields": [ # [Repeated] One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. When you cluster a table using multiple columns, the order of columns you specify is important. The order of the specified columns determines the sort order of the data.
+ "autodetect": True or False, # Optional. Indicates if we should automatically infer the options and schema for CSV and JSON sources.
+ "clustering": { # Configures table clustering. # Clustering specification for the destination table.
+ "fields": [ # One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. The ordering of the clustering fields should be prioritized from most to least important for filtering purposes. Additional information on limitations can be found here: https://cloud.google.com/bigquery/docs/creating-clustered-tables#limitations
"A String",
],
},
- "connectionProperties": [ # Connection properties.
- {
- "key": "A String", # [Required] Name of the connection property to set.
- "value": "A String", # [Required] Value of the connection property.
+ "connectionProperties": [ # Optional. Connection properties which can modify the load job behavior. Currently, only the 'session_id' connection property is supported, and is used to resolve _SESSION appearing as the dataset id.
+ { # A connection-level property to customize query behavior. Under JDBC, these correspond directly to connection properties passed to the DriverManager. Under ODBC, these correspond to properties in the connection string. Currently supported connection properties: * **dataset_project_id**: represents the default project for datasets that are used in the query. Setting the system variable `@@dataset_project_id` achieves the same behavior. For more information about system variables, see: https://cloud.google.com/bigquery/docs/reference/system-variables * **time_zone**: represents the default timezone used to run the query. * **session_id**: associates the query with a given session. * **query_label**: associates the query with a given job label. If set, all subsequent queries in a script or session will have this label. For the format in which a you can specify a query label, see labels in the JobConfiguration resource type: https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#jobconfiguration Additional properties are allowed, but ignored. Specifying multiple connection properties with the same key returns an error.
+ "key": "A String", # The key of the property to set.
+ "value": "A String", # The value of the property to set.
},
],
- "createDisposition": "A String", # [Optional] Specifies whether the job is allowed to create new tables. The following values are supported: CREATE_IF_NEEDED: If the table does not exist, BigQuery creates the table. CREATE_NEVER: The table must already exist. If it does not, a 'notFound' error is returned in the job result. The default value is CREATE_IF_NEEDED. Creation, truncation and append actions occur as one atomic update upon job completion.
- "createSession": True or False, # If true, creates a new session, where session id will be a server generated random id. If false, runs query with an existing session_id passed in ConnectionProperty, otherwise runs the load job in non-session mode.
- "decimalTargetTypes": [ # [Optional] Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown. Example: Suppose the value of this field is ["NUMERIC", "BIGNUMERIC"]. If (precision,scale) is: (38,9) -> NUMERIC; (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits); (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits); (76,38) -> BIGNUMERIC; (77,38) -> BIGNUMERIC (error if value exeeds supported range). This field cannot contain duplicate types. The order of the types in this field is ignored. For example, ["BIGNUMERIC", "NUMERIC"] is the same as ["NUMERIC", "BIGNUMERIC"] and NUMERIC always takes precedence over BIGNUMERIC. Defaults to ["NUMERIC", "STRING"] for ORC and ["NUMERIC"] for the other file formats.
+ "createDisposition": "A String", # Optional. Specifies whether the job is allowed to create new tables. The following values are supported: * CREATE_IF_NEEDED: If the table does not exist, BigQuery creates the table. * CREATE_NEVER: The table must already exist. If it does not, a 'notFound' error is returned in the job result. The default value is CREATE_IF_NEEDED. Creation, truncation and append actions occur as one atomic update upon job completion.
+ "createSession": True or False, # Optional. If this property is true, the job creates a new session using a randomly generated session_id. To continue using a created session with subsequent queries, pass the existing session identifier as a `ConnectionProperty` value. The session identifier is returned as part of the `SessionInfo` message within the query statistics. The new session's location will be set to `Job.JobReference.location` if it is present, otherwise it's set to the default location based on existing routing logic.
+ "decimalTargetTypes": [ # Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown. Example: Suppose the value of this field is ["NUMERIC", "BIGNUMERIC"]. If (precision,scale) is: * (38,9) -> NUMERIC; * (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits); * (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits); * (76,38) -> BIGNUMERIC; * (77,38) -> BIGNUMERIC (error if value exeeds supported range). This field cannot contain duplicate types. The order of the types in this field is ignored. For example, ["BIGNUMERIC", "NUMERIC"] is the same as ["NUMERIC", "BIGNUMERIC"] and NUMERIC always takes precedence over BIGNUMERIC. Defaults to ["NUMERIC", "STRING"] for ORC and ["NUMERIC"] for the other file formats.
"A String",
],
- "destinationEncryptionConfiguration": { # Custom encryption configuration (e.g., Cloud KMS keys).
+ "destinationEncryptionConfiguration": { # Custom encryption configuration (e.g., Cloud KMS keys)
"kmsKeyName": "A String", # Optional. Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key.
},
"destinationTable": { # [Required] The destination table to load the data into.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- },
- "destinationTableProperties": { # [Beta] [Optional] Properties with which to create the destination table if it is new.
- "description": "A String", # [Optional] The description for the destination table. This will only be used if the destination table is newly created. If the table already exists and a value different than the current description is provided, the job will fail.
- "expirationTime": "A String", # [Internal] This field is for Google internal use only.
- "friendlyName": "A String", # [Optional] The friendly name for the destination table. This will only be used if the destination table is newly created. If the table already exists and a value different than the current friendly name is provided, the job will fail.
- "labels": { # [Optional] The labels associated with this table. You can use these to organize and group your tables. This will only be used if the destination table is newly created. If the table already exists and labels are different than the current labels are provided, the job will fail.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ "destinationTableProperties": { # Properties for the destination table. # Optional. [Experimental] Properties with which to create the destination table if it is new.
+ "description": "A String", # Optional. The description for the destination table. This will only be used if the destination table is newly created. If the table already exists and a value different than the current description is provided, the job will fail.
+ "expirationTime": "A String", # Internal use only.
+ "friendlyName": "A String", # Optional. Friendly name for the destination table. If the table already exists, it should be same as the existing friendly name.
+ "labels": { # Optional. The labels associated with this table. You can use these to organize and group your tables. This will only be used if the destination table is newly created. If the table already exists and labels are different than the current labels are provided, the job will fail.
"a_key": "A String",
},
},
- "encoding": "A String", # [Optional] The character encoding of the data. The supported values are UTF-8 or ISO-8859-1. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the quote and fieldDelimiter properties.
- "fieldDelimiter": "A String", # [Optional] The separator for fields in a CSV file. The separator can be any ISO-8859-1 single-byte character. To use a character in the range 128-255, you must encode the character as UTF8. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. BigQuery also supports the escape sequence "\t" to specify a tab separator. The default value is a comma (',').
- "fileSetSpecType": "A String", # [Optional] Specifies how source URIs are interpreted for constructing the file set to load. By default source URIs are expanded against the underlying storage. Other options include specifying manifest files. Only applicable to object storage systems.
- "hivePartitioningOptions": { # [Optional] Options to configure hive partitioning support.
- "fields": [ # [Output-only] For permanent external tables, this field is populated with the hive partition keys in the order they were inferred. The types of the partition keys can be deduced by checking the table schema (which will include the partition keys). Not every API will populate this field in the output. For example, Tables.Get will populate it, but Tables.List will not contain this field.
+ "encoding": "A String", # Optional. The character encoding of the data. The supported values are UTF-8, ISO-8859-1, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the `quote` and `fieldDelimiter` properties. If you don't specify an encoding, or if you specify a UTF-8 encoding when the CSV file is not UTF-8 encoded, BigQuery attempts to convert the data to UTF-8. Generally, your data loads successfully, but it may not match byte-for-byte what you expect. To avoid this, specify the correct encoding by using the `--encoding` flag. If BigQuery can't convert a character other than the ASCII `0` character, BigQuery converts the character to the standard Unicode replacement character: �.
+ "fieldDelimiter": "A String", # Optional. The separator character for fields in a CSV file. The separator is interpreted as a single byte. For files encoded in ISO-8859-1, any single character can be used as a separator. For files encoded in UTF-8, characters represented in decimal range 1-127 (U+0001-U+007F) can be used without any modification. UTF-8 characters encoded with multiple bytes (i.e. U+0080 and above) will have only the first byte used for separating fields. The remaining bytes will be treated as a part of the field. BigQuery also supports the escape sequence "\t" (U+0009) to specify a tab separator. The default value is comma (",", U+002C).
+ "fileSetSpecType": "A String", # Optional. Specifies how source URIs are interpreted for constructing the file set to load. By default, source URIs are expanded against the underlying storage. You can also specify manifest files to control how the file set is constructed. This option is only applicable to object storage systems.
+ "hivePartitioningOptions": { # Options for configuring hive partitioning detect. # Optional. When set, configures hive partitioning support. Not all storage formats support hive partitioning -- requesting hive partitioning on an unsupported format will lead to an error, as will providing an invalid specification.
+ "fields": [ # Output only. For permanent external tables, this field is populated with the hive partition keys in the order they were inferred. The types of the partition keys can be deduced by checking the table schema (which will include the partition keys). Not every API will populate this field in the output. For example, Tables.Get will populate it, but Tables.List will not contain this field.
"A String",
],
- "mode": "A String", # [Optional] When set, what mode of hive partitioning to use when reading data. The following modes are supported. (1) AUTO: automatically infer partition key name(s) and type(s). (2) STRINGS: automatically infer partition key name(s). All types are interpreted as strings. (3) CUSTOM: partition key schema is encoded in the source URI prefix. Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported types include: AVRO, CSV, JSON, ORC and Parquet.
- "requirePartitionFilter": True or False, # [Optional] If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. Note that this field should only be true when creating a permanent external table or querying a temporary external table. Hive-partitioned loads with requirePartitionFilter explicitly set to true will fail.
- "sourceUriPrefix": "A String", # [Optional] When hive partition detection is requested, a common prefix for all source uris should be supplied. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout. gs://bucket/path_to_table/dt=2019-01-01/country=BR/id=7/file.avro gs://bucket/path_to_table/dt=2018-12-31/country=CA/id=3/file.avro When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/ (trailing slash does not matter).
- },
- "ignoreUnknownValues": True or False, # [Optional] Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names
- "jsonExtension": "A String", # [Optional] If sourceFormat is set to newline-delimited JSON, indicates whether it should be processed as a JSON variant such as GeoJSON. For a sourceFormat other than JSON, omit this field. If the sourceFormat is newline-delimited JSON: - for newline-delimited GeoJSON: set to GEOJSON.
- "maxBadRecords": 42, # [Optional] The maximum number of bad records that BigQuery can ignore when running the job. If the number of bad records exceeds this value, an invalid error is returned in the job result. This is only valid for CSV and JSON. The default value is 0, which requires that all records are valid.
- "nullMarker": "A String", # [Optional] Specifies a string that represents a null value in a CSV file. For example, if you specify "\N", BigQuery interprets "\N" as a null value when loading a CSV file. The default value is the empty string. If you set this property to a custom value, BigQuery throws an error if an empty string is present for all data types except for STRING and BYTE. For STRING and BYTE columns, BigQuery interprets the empty string as an empty value.
- "parquetOptions": { # [Optional] Options to configure parquet support.
- "enableListInference": True or False, # [Optional] Indicates whether to use schema inference specifically for Parquet LIST logical type.
- "enumAsString": True or False, # [Optional] Indicates whether to infer Parquet ENUM logical type as STRING instead of BYTES by default.
- },
- "preserveAsciiControlCharacters": True or False, # [Optional] Preserves the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\x00' to '\x1F') when loading from CSV. Only applicable to CSV, ignored for other formats.
+ "mode": "A String", # Optional. When set, what mode of hive partitioning to use when reading data. The following modes are supported: * AUTO: automatically infer partition key name(s) and type(s). * STRINGS: automatically infer partition key name(s). All types are strings. * CUSTOM: partition key schema is encoded in the source URI prefix. Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported formats are: JSON, CSV, ORC, Avro and Parquet.
+ "requirePartitionFilter": false, # Optional. If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. Note that this field should only be true when creating a permanent external table or querying a temporary external table. Hive-partitioned loads with require_partition_filter explicitly set to true will fail.
+ "sourceUriPrefix": "A String", # Optional. When hive partition detection is requested, a common prefix for all source uris must be required. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout: gs://bucket/path_to_table/dt=2019-06-01/country=USA/id=7/file.avro gs://bucket/path_to_table/dt=2019-05-31/country=CA/id=3/file.avro When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/. CUSTOM detection requires encoding the partitioning schema immediately after the common prefix. For CUSTOM, any of * gs://bucket/path_to_table/{dt:DATE}/{country:STRING}/{id:INTEGER} * gs://bucket/path_to_table/{dt:STRING}/{country:STRING}/{id:INTEGER} * gs://bucket/path_to_table/{dt:DATE}/{country:STRING}/{id:STRING} would all be valid source URI prefixes.
+ },
+ "ignoreUnknownValues": True or False, # Optional. Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names in the table schema Avro, Parquet, ORC: Fields in the file schema that don't exist in the table schema.
+ "jsonExtension": "A String", # Optional. Load option to be used together with source_format newline-delimited JSON to indicate that a variant of JSON is being loaded. To load newline-delimited GeoJSON, specify GEOJSON (and source_format must be set to NEWLINE_DELIMITED_JSON).
+ "maxBadRecords": 42, # Optional. The maximum number of bad records that BigQuery can ignore when running the job. If the number of bad records exceeds this value, an invalid error is returned in the job result. The default value is 0, which requires that all records are valid. This is only supported for CSV and NEWLINE_DELIMITED_JSON file formats.
+ "nullMarker": "A String", # Optional. Specifies a string that represents a null value in a CSV file. For example, if you specify "\N", BigQuery interprets "\N" as a null value when loading a CSV file. The default value is the empty string. If you set this property to a custom value, BigQuery throws an error if an empty string is present for all data types except for STRING and BYTE. For STRING and BYTE columns, BigQuery interprets the empty string as an empty value.
+ "parquetOptions": { # Parquet Options for load and make external tables. # Optional. Additional properties to set if sourceFormat is set to PARQUET.
+ "enableListInference": True or False, # Optional. Indicates whether to use schema inference specifically for Parquet LIST logical type.
+ "enumAsString": True or False, # Optional. Indicates whether to infer Parquet ENUM logical type as STRING instead of BYTES by default.
+ },
+ "preserveAsciiControlCharacters": True or False, # Optional. When sourceFormat is set to "CSV", this indicates whether the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\x00' to '\x1F') are preserved.
"projectionFields": [ # If sourceFormat is set to "DATASTORE_BACKUP", indicates which entity properties to load into BigQuery from a Cloud Datastore backup. Property names are case sensitive and must be top-level properties. If no properties are specified, BigQuery loads all properties. If any named property isn't found in the Cloud Datastore backup, an invalid error is returned in the job result.
"A String",
],
- "quote": """, # [Optional] The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ('"'). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true.
- "rangePartitioning": { # [TrustedTester] Range partitioning specification for this table. Only one of timePartitioning and rangePartitioning should be specified.
- "field": "A String", # [TrustedTester] [Required] The table is partitioned by this field. The field must be a top-level NULLABLE/REQUIRED field. The only supported type is INTEGER/INT64.
- "range": { # [TrustedTester] [Required] Defines the ranges for range partitioning.
- "end": "A String", # [TrustedTester] [Required] The end of range partitioning, exclusive.
- "interval": "A String", # [TrustedTester] [Required] The width of each interval.
- "start": "A String", # [TrustedTester] [Required] The start of range partitioning, inclusive.
+ "quote": """, # Optional. The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ('"'). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true. To include the specific quote character within a quoted value, precede it with an additional matching quote character. For example, if you want to escape the default character ' " ', use ' "" '. @default "
+ "rangePartitioning": { # Range partitioning specification for the destination table. Only one of timePartitioning and rangePartitioning should be specified.
+ "field": "A String", # Required. [Experimental] The table is partitioned by this field. The field must be a top-level NULLABLE/REQUIRED field. The only supported type is INTEGER/INT64.
+ "range": { # [Experimental] Defines the ranges for range partitioning.
+ "end": "A String", # [Experimental] The end of range partitioning, exclusive.
+ "interval": "A String", # [Experimental] The width of each interval.
+ "start": "A String", # [Experimental] The start of range partitioning, inclusive.
},
},
- "referenceFileSchemaUri": "A String", # User provided referencing file with the expected reader schema, Available for the format: AVRO, PARQUET, ORC.
- "schema": { # [Optional] The schema for the destination table. The schema can be omitted if the destination table already exists, or if you're loading data from Google Cloud Datastore.
+ "referenceFileSchemaUri": "A String", # Optional. The user can provide a reference file with the reader schema. This file is only loaded if it is part of source URIs, but is not loaded otherwise. It is enabled for the following formats: AVRO, PARQUET, ORC.
+ "schema": { # Schema of a table # Optional. The schema for the destination table. The schema can be omitted if the destination table already exists, or if you're loading data from Google Cloud Datastore.
"fields": [ # Describes the fields in a table.
- {
- "categories": { # [Optional] The categories attached to this field, used for field-level access control.
- "names": [ # A list of category resource names. For example, "projects/1/taxonomies/2/categories/3". At most 5 categories are allowed.
+ { # A field in TableSchema
+ "categories": { # Deprecated.
+ "names": [ # Deprecated.
"A String",
],
},
- "collation": "A String", # Optional. Collation specification of the field. It only can be set on string type field.
- "defaultValueExpression": "A String", # Optional. A SQL expression to specify the default value for this field. It can only be set for top level fields (columns). You can use struct or array expression to specify default value for the entire struct or array. The valid SQL expressions are: - Literals for all data types, including STRUCT and ARRAY. - Following functions: - CURRENT_TIMESTAMP - CURRENT_TIME - CURRENT_DATE - CURRENT_DATETIME - GENERATE_UUID - RAND - SESSION_USER - ST_GEOGPOINT - Struct or array composed with the above allowed functions, for example, [CURRENT_DATE(), DATE '2020-01-01']
- "description": "A String", # [Optional] The field description. The maximum length is 1,024 characters.
- "fields": [ # [Optional] Describes the nested schema fields if the type property is set to RECORD.
+ "collation": "A String", # Optional. Field collation can be set only when the type of field is STRING. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.
+ "defaultValueExpression": "A String", # Optional. A SQL expression to specify the [default value] (https://cloud.google.com/bigquery/docs/default-values) for this field.
+ "description": "A String", # Optional. The field description. The maximum length is 1,024 characters.
+ "fields": [ # Optional. Describes the nested schema fields if the type property is set to RECORD.
# Object with schema name: TableFieldSchema
],
- "maxLength": "A String", # [Optional] Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
- "mode": "A String", # [Optional] The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
- "name": "A String", # [Required] The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
- "policyTags": {
- "names": [ # A list of category resource names. For example, "projects/1/location/eu/taxonomies/2/policyTags/3". At most 1 policy tag is allowed.
+ "maxLength": "A String", # Optional. Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
+ "mode": "A String", # Optional. The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
+ "name": "A String", # Required. The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
+ "policyTags": { # Optional. The policy tags attached to this field, used for field-level access control. If not set, defaults to empty policy_tags.
+ "names": [ # A list of policy tag resource names. For example, "projects/1/locations/eu/taxonomies/2/policyTags/3". At most 1 policy tag is currently allowed.
"A String",
],
},
- "precision": "A String", # [Optional] Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: - Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] - Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: - If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. - If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): - If type = "NUMERIC": 1 ≤ precision ≤ 29. - If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
- "rangeElementType": { # Optional. The subtype of the RANGE, if the type of this field is RANGE. If the type is RANGE, this field is required. Possible values for the field element type of a RANGE include: - DATE - DATETIME - TIMESTAMP
- "type": "A String", # The field element type of a RANGE
+ "precision": "A String", # Optional. Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: * Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] * Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: * If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. * If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): * If type = "NUMERIC": 1 ≤ precision ≤ 29. * If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
+ "rangeElementType": { # Represents the type of a field element.
+ "type": "A String", # Required. The type of a field element. See TableFieldSchema.type.
},
- "roundingMode": "A String", # Optional. Rounding Mode specification of the field. It only can be set on NUMERIC or BIGNUMERIC type fields.
- "scale": "A String", # [Optional] See documentation for precision.
- "type": "A String", # [Required] The field data type. Possible values include STRING, BYTES, INTEGER, INT64 (same as INTEGER), FLOAT, FLOAT64 (same as FLOAT), NUMERIC, BIGNUMERIC, BOOLEAN, BOOL (same as BOOLEAN), TIMESTAMP, DATE, TIME, DATETIME, INTERVAL, RECORD (where RECORD indicates that the field contains a nested schema) or STRUCT (same as RECORD).
+ "roundingMode": "A String", # Optional. Specifies the rounding mode to be used when storing values of NUMERIC and BIGNUMERIC type.
+ "scale": "A String", # Optional. See documentation for precision.
+ "type": "A String", # Required. The field data type. Possible values include: * STRING * BYTES * INTEGER (or INT64) * FLOAT (or FLOAT64) * BOOLEAN (or BOOL) * TIMESTAMP * DATE * TIME * DATETIME * GEOGRAPHY * NUMERIC * BIGNUMERIC * JSON * RECORD (or STRUCT) Use of RECORD/STRUCT indicates that the field contains a nested schema.
},
],
},
"schemaInline": "A String", # [Deprecated] The inline schema. For CSV schemas, specify as "Field1:Type1[,Field2:Type2]*". For example, "foo:STRING, bar:INTEGER, baz:FLOAT".
"schemaInlineFormat": "A String", # [Deprecated] The format of the schemaInline property.
- "schemaUpdateOptions": [ # Allows the schema of the destination table to be updated as a side effect of the load job if a schema is autodetected or supplied in the job configuration. Schema update options are supported in two cases: when writeDisposition is WRITE_APPEND; when writeDisposition is WRITE_TRUNCATE and the destination table is a partition of a table, specified by partition decorators. For normal tables, WRITE_TRUNCATE will always overwrite the schema. One or more of the following values are specified: ALLOW_FIELD_ADDITION: allow adding a nullable field to the schema. ALLOW_FIELD_RELAXATION: allow relaxing a required field in the original schema to nullable.
+ "schemaUpdateOptions": [ # Allows the schema of the destination table to be updated as a side effect of the load job if a schema is autodetected or supplied in the job configuration. Schema update options are supported in two cases: when writeDisposition is WRITE_APPEND; when writeDisposition is WRITE_TRUNCATE and the destination table is a partition of a table, specified by partition decorators. For normal tables, WRITE_TRUNCATE will always overwrite the schema. One or more of the following values are specified: * ALLOW_FIELD_ADDITION: allow adding a nullable field to the schema. * ALLOW_FIELD_RELAXATION: allow relaxing a required field in the original schema to nullable.
"A String",
],
- "skipLeadingRows": 42, # [Optional] The number of rows at the top of a CSV file that BigQuery will skip when loading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped.
- "sourceFormat": "A String", # [Optional] The format of the data files. For CSV files, specify "CSV". For datastore backups, specify "DATASTORE_BACKUP". For newline-delimited JSON, specify "NEWLINE_DELIMITED_JSON". For Avro, specify "AVRO". For parquet, specify "PARQUET". For orc, specify "ORC". The default value is CSV.
+ "skipLeadingRows": 42, # Optional. The number of rows at the top of a CSV file that BigQuery will skip when loading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
+ "sourceFormat": "A String", # Optional. The format of the data files. For CSV files, specify "CSV". For datastore backups, specify "DATASTORE_BACKUP". For newline-delimited JSON, specify "NEWLINE_DELIMITED_JSON". For Avro, specify "AVRO". For parquet, specify "PARQUET". For orc, specify "ORC". The default value is CSV.
"sourceUris": [ # [Required] The fully-qualified URIs that point to your data in Google Cloud. For Google Cloud Storage URIs: Each URI can contain one '*' wildcard character and it must come after the 'bucket' name. Size limits related to load jobs apply to external data sources. For Google Cloud Bigtable URIs: Exactly one URI can be specified and it has be a fully specified and valid HTTPS URL for a Google Cloud Bigtable table. For Google Cloud Datastore backups: Exactly one URI can be specified. Also, the '*' wildcard character is not allowed.
"A String",
],
"timePartitioning": { # Time-based partitioning specification for the destination table. Only one of timePartitioning and rangePartitioning should be specified.
- "expirationMs": "A String", # [Optional] Number of milliseconds for which to keep the storage for partitions in the table. The storage in a partition will have an expiration time of its partition time plus this value.
- "field": "A String", # [Beta] [Optional] If not set, the table is partitioned by pseudo column, referenced via either '_PARTITIONTIME' as TIMESTAMP type, or '_PARTITIONDATE' as DATE type. If field is specified, the table is instead partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED.
- "requirePartitionFilter": True or False,
- "type": "A String", # [Required] The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively. When the type is not specified, the default behavior is DAY.
- },
- "useAvroLogicalTypes": True or False, # [Optional] If sourceFormat is set to "AVRO", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER).
- "writeDisposition": "A String", # [Optional] Specifies the action that occurs if the destination table already exists. The following values are supported: WRITE_TRUNCATE: If the table already exists, BigQuery overwrites the table data. WRITE_APPEND: If the table already exists, BigQuery appends the data to the table. WRITE_EMPTY: If the table already exists and contains data, a 'duplicate' error is returned in the job result. The default value is WRITE_APPEND. Each action is atomic and only occurs if BigQuery is able to complete the job successfully. Creation, truncation and append actions occur as one atomic update upon job completion.
- },
- "query": { # [Pick one] Configures a query job.
- "allowLargeResults": false, # [Optional] If true and query uses legacy SQL dialect, allows the query to produce arbitrarily large result tables at a slight cost in performance. Requires destinationTable to be set. For standard SQL queries, this flag is ignored and large results are always allowed. However, you must still set destinationTable when result size exceeds the allowed maximum response size.
- "clustering": { # [Beta] Clustering specification for the destination table. Must be specified with time-based partitioning, data in the table will be first partitioned and subsequently clustered.
- "fields": [ # [Repeated] One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. When you cluster a table using multiple columns, the order of columns you specify is important. The order of the specified columns determines the sort order of the data.
+ "expirationMs": "A String", # Optional. Number of milliseconds for which to keep the storage for a partition. A wrapper is used here because 0 is an invalid value.
+ "field": "A String", # Optional. If not set, the table is partitioned by pseudo column '_PARTITIONTIME'; if set, the table is partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED. A wrapper is used here because an empty string is an invalid value.
+ "requirePartitionFilter": false, # If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. This field is deprecated; please set the field with the same name on the table itself instead. This field needs a wrapper because we want to output the default value, false, if the user explicitly set it.
+ "type": "A String", # Required. The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively.
+ },
+ "useAvroLogicalTypes": True or False, # Optional. If sourceFormat is set to "AVRO", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER).
+ "writeDisposition": "A String", # Optional. Specifies the action that occurs if the destination table already exists. The following values are supported: * WRITE_TRUNCATE: If the table already exists, BigQuery overwrites the data, removes the constraints and uses the schema from the load job. * WRITE_APPEND: If the table already exists, BigQuery appends the data to the table. * WRITE_EMPTY: If the table already exists and contains data, a 'duplicate' error is returned in the job result. The default value is WRITE_APPEND. Each action is atomic and only occurs if BigQuery is able to complete the job successfully. Creation, truncation and append actions occur as one atomic update upon job completion.
+ },
+ "query": { # JobConfigurationQuery configures a BigQuery query job. # [Pick one] Configures a query job.
+ "allowLargeResults": false, # Optional. If true and query uses legacy SQL dialect, allows the query to produce arbitrarily large result tables at a slight cost in performance. Requires destinationTable to be set. For GoogleSQL queries, this flag is ignored and large results are always allowed. However, you must still set destinationTable when result size exceeds the allowed maximum response size.
+ "clustering": { # Configures table clustering. # Clustering specification for the destination table.
+ "fields": [ # One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. The ordering of the clustering fields should be prioritized from most to least important for filtering purposes. Additional information on limitations can be found here: https://cloud.google.com/bigquery/docs/creating-clustered-tables#limitations
"A String",
],
},
- "connectionProperties": [ # Connection properties.
- {
- "key": "A String", # [Required] Name of the connection property to set.
- "value": "A String", # [Required] Value of the connection property.
+ "connectionProperties": [ # Connection properties which can modify the query behavior.
+ { # A connection-level property to customize query behavior. Under JDBC, these correspond directly to connection properties passed to the DriverManager. Under ODBC, these correspond to properties in the connection string. Currently supported connection properties: * **dataset_project_id**: represents the default project for datasets that are used in the query. Setting the system variable `@@dataset_project_id` achieves the same behavior. For more information about system variables, see: https://cloud.google.com/bigquery/docs/reference/system-variables * **time_zone**: represents the default timezone used to run the query. * **session_id**: associates the query with a given session. * **query_label**: associates the query with a given job label. If set, all subsequent queries in a script or session will have this label. For the format in which a you can specify a query label, see labels in the JobConfiguration resource type: https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#jobconfiguration Additional properties are allowed, but ignored. Specifying multiple connection properties with the same key returns an error.
+ "key": "A String", # The key of the property to set.
+ "value": "A String", # The value of the property to set.
},
],
"continuous": True or False, # [Optional] Specifies whether the query should be executed as a continuous query. The default value is false.
- "createDisposition": "A String", # [Optional] Specifies whether the job is allowed to create new tables. The following values are supported: CREATE_IF_NEEDED: If the table does not exist, BigQuery creates the table. CREATE_NEVER: The table must already exist. If it does not, a 'notFound' error is returned in the job result. The default value is CREATE_IF_NEEDED. Creation, truncation and append actions occur as one atomic update upon job completion.
- "createSession": True or False, # If true, creates a new session, where session id will be a server generated random id. If false, runs query with an existing session_id passed in ConnectionProperty, otherwise runs query in non-session mode.
- "defaultDataset": { # [Optional] Specifies the default dataset to use for unqualified table names in the query. Note that this does not alter behavior of unqualified dataset names.
- "datasetId": "A String", # [Required] A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- "projectId": "A String", # [Optional] The ID of the project containing this dataset.
+ "createDisposition": "A String", # Optional. Specifies whether the job is allowed to create new tables. The following values are supported: * CREATE_IF_NEEDED: If the table does not exist, BigQuery creates the table. * CREATE_NEVER: The table must already exist. If it does not, a 'notFound' error is returned in the job result. The default value is CREATE_IF_NEEDED. Creation, truncation and append actions occur as one atomic update upon job completion.
+ "createSession": True or False, # If this property is true, the job creates a new session using a randomly generated session_id. To continue using a created session with subsequent queries, pass the existing session identifier as a `ConnectionProperty` value. The session identifier is returned as part of the `SessionInfo` message within the query statistics. The new session's location will be set to `Job.JobReference.location` if it is present, otherwise it's set to the default location based on existing routing logic.
+ "defaultDataset": { # Optional. Specifies the default dataset to use for unqualified table names in the query. This setting does not alter behavior of unqualified dataset names. Setting the system variable `@@dataset_id` achieves the same behavior. See https://cloud.google.com/bigquery/docs/reference/system-variables for more information on system variables.
+ "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "projectId": "A String", # Optional. The ID of the project containing this dataset.
},
- "destinationEncryptionConfiguration": { # Custom encryption configuration (e.g., Cloud KMS keys).
+ "destinationEncryptionConfiguration": { # Custom encryption configuration (e.g., Cloud KMS keys)
"kmsKeyName": "A String", # Optional. Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key.
},
- "destinationTable": { # [Optional] Describes the table where the query results should be stored. If not present, a new table will be created to store the results. This property must be set for large results that exceed the maximum response size.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "destinationTable": { # Optional. Describes the table where the query results should be stored. This property must be set for large results that exceed the maximum response size. For queries that produce anonymous (cached) results, this field will be populated by BigQuery.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
- "flattenResults": true, # [Optional] If true and query uses legacy SQL dialect, flattens all nested and repeated fields in the query results. allowLargeResults must be true if this is set to false. For standard SQL queries, this flag is ignored and results are never flattened.
- "maximumBillingTier": 1, # [Optional] Limits the billing tier for this job. Queries that have resource usage beyond this tier will fail (without incurring a charge). If unspecified, this will be set to your project default.
- "maximumBytesBilled": "A String", # [Optional] Limits the bytes billed for this job. Queries that will have bytes billed beyond this limit will fail (without incurring a charge). If unspecified, this will be set to your project default.
- "parameterMode": "A String", # Standard SQL only. Set to POSITIONAL to use positional (?) query parameters or to NAMED to use named (@myparam) query parameters in this query.
+ "flattenResults": true, # Optional. If true and query uses legacy SQL dialect, flattens all nested and repeated fields in the query results. allowLargeResults must be true if this is set to false. For GoogleSQL queries, this flag is ignored and results are never flattened.
+ "maximumBillingTier": 1, # Optional. [Deprecated] Maximum billing tier allowed for this query. The billing tier controls the amount of compute resources allotted to the query, and multiplies the on-demand cost of the query accordingly. A query that runs within its allotted resources will succeed and indicate its billing tier in statistics.query.billingTier, but if the query exceeds its allotted resources, it will fail with billingTierLimitExceeded. WARNING: The billed byte amount can be multiplied by an amount up to this number! Most users should not need to alter this setting, and we recommend that you avoid introducing new uses of it.
+ "maximumBytesBilled": "A String", # Limits the bytes billed for this job. Queries that will have bytes billed beyond this limit will fail (without incurring a charge). If unspecified, this will be set to your project default.
+ "parameterMode": "A String", # GoogleSQL only. Set to POSITIONAL to use positional (?) query parameters or to NAMED to use named (@myparam) query parameters in this query.
"preserveNulls": True or False, # [Deprecated] This property is deprecated.
- "priority": "A String", # [Optional] Specifies a priority for the query. Possible values include INTERACTIVE and BATCH. The default value is INTERACTIVE.
- "query": "A String", # [Required] SQL query text to execute. The useLegacySql field can be used to indicate whether the query uses legacy SQL or standard SQL.
- "queryParameters": [ # Query parameters for standard SQL queries.
- {
- "name": "A String", # [Optional] If unset, this is a positional parameter. Otherwise, should be unique within a query.
- "parameterType": { # [Required] The type of this parameter.
- "arrayType": # Object with schema name: QueryParameterType # [Optional] The type of the array's elements, if this is an array.
- "rangeElementType": # Object with schema name: QueryParameterType # [Optional] The element type of the range, if this is a range.
- "structTypes": [ # [Optional] The types of the fields of this struct, in order, if this is a struct.
- {
- "description": "A String", # [Optional] Human-oriented description of the field.
- "name": "A String", # [Optional] The name of this field.
- "type": # Object with schema name: QueryParameterType # [Required] The type of this field.
+ "priority": "A String", # Optional. Specifies a priority for the query. Possible values include INTERACTIVE and BATCH. The default value is INTERACTIVE.
+ "query": "A String", # [Required] SQL query text to execute. The useLegacySql field can be used to indicate whether the query uses legacy SQL or GoogleSQL.
+ "queryParameters": [ # Query parameters for GoogleSQL queries.
+ { # A parameter given to a query.
+ "name": "A String", # Optional. If unset, this is a positional parameter. Otherwise, should be unique within a query.
+ "parameterType": { # The type of a query parameter. # Required. The type of this parameter.
+ "arrayType": # Object with schema name: QueryParameterType # Optional. The type of the array's elements, if this is an array.
+ "rangeElementType": # Object with schema name: QueryParameterType # Optional. The element type of the range, if this is a range.
+ "structTypes": [ # Optional. The types of the fields of this struct, in order, if this is a struct.
+ { # The type of a struct parameter.
+ "description": "A String", # Optional. Human-oriented description of the field.
+ "name": "A String", # Optional. The name of this field.
+ "type": # Object with schema name: QueryParameterType # Required. The type of this field.
},
],
- "type": "A String", # [Required] The top level type of this field.
+ "type": "A String", # Required. The top level type of this field.
},
- "parameterValue": { # [Required] The value of this parameter.
- "arrayValues": [ # [Optional] The array values, if this is an array type.
+ "parameterValue": { # The value of a query parameter. # Required. The value of this parameter.
+ "arrayValues": [ # Optional. The array values, if this is an array type.
# Object with schema name: QueryParameterValue
],
- "rangeValue": { # [Optional] The range value, if this is a range type.
- "end": # Object with schema name: QueryParameterValue
- "start": # Object with schema name: QueryParameterValue
+ "rangeValue": { # Represents the value of a range. # Optional. The range value, if this is a range type.
+ "end": # Object with schema name: QueryParameterValue # Optional. The end value of the range. A missing value represents an unbounded end.
+ "start": # Object with schema name: QueryParameterValue # Optional. The start value of the range. A missing value represents an unbounded start.
},
- "structValues": { # [Optional] The struct field values, in order of the struct type's declaration.
+ "structValues": { # The struct field values.
"a_key": # Object with schema name: QueryParameterValue
},
- "value": "A String", # [Optional] The value of this value, if a simple scalar type.
+ "value": "A String", # Optional. The value of this value, if a simple scalar type.
},
},
],
- "rangePartitioning": { # [TrustedTester] Range partitioning specification for this table. Only one of timePartitioning and rangePartitioning should be specified.
- "field": "A String", # [TrustedTester] [Required] The table is partitioned by this field. The field must be a top-level NULLABLE/REQUIRED field. The only supported type is INTEGER/INT64.
- "range": { # [TrustedTester] [Required] Defines the ranges for range partitioning.
- "end": "A String", # [TrustedTester] [Required] The end of range partitioning, exclusive.
- "interval": "A String", # [TrustedTester] [Required] The width of each interval.
- "start": "A String", # [TrustedTester] [Required] The start of range partitioning, inclusive.
+ "rangePartitioning": { # Range partitioning specification for the destination table. Only one of timePartitioning and rangePartitioning should be specified.
+ "field": "A String", # Required. [Experimental] The table is partitioned by this field. The field must be a top-level NULLABLE/REQUIRED field. The only supported type is INTEGER/INT64.
+ "range": { # [Experimental] Defines the ranges for range partitioning.
+ "end": "A String", # [Experimental] The end of range partitioning, exclusive.
+ "interval": "A String", # [Experimental] The width of each interval.
+ "start": "A String", # [Experimental] The start of range partitioning, inclusive.
},
},
- "schemaUpdateOptions": [ # Allows the schema of the destination table to be updated as a side effect of the query job. Schema update options are supported in two cases: when writeDisposition is WRITE_APPEND; when writeDisposition is WRITE_TRUNCATE and the destination table is a partition of a table, specified by partition decorators. For normal tables, WRITE_TRUNCATE will always overwrite the schema. One or more of the following values are specified: ALLOW_FIELD_ADDITION: allow adding a nullable field to the schema. ALLOW_FIELD_RELAXATION: allow relaxing a required field in the original schema to nullable.
+ "schemaUpdateOptions": [ # Allows the schema of the destination table to be updated as a side effect of the query job. Schema update options are supported in two cases: when writeDisposition is WRITE_APPEND; when writeDisposition is WRITE_TRUNCATE and the destination table is a partition of a table, specified by partition decorators. For normal tables, WRITE_TRUNCATE will always overwrite the schema. One or more of the following values are specified: * ALLOW_FIELD_ADDITION: allow adding a nullable field to the schema. * ALLOW_FIELD_RELAXATION: allow relaxing a required field in the original schema to nullable.
"A String",
],
- "tableDefinitions": { # [Optional] If querying an external data source outside of BigQuery, describes the data format, location and other properties of the data source. By defining these properties, the data source can then be queried as if it were a standard BigQuery table.
+ "scriptOptions": { # Options related to script execution. # Options controlling the execution of scripts.
+ "keyResultStatement": "A String", # Determines which statement in the script represents the "key result", used to populate the schema and query results of the script job. Default is LAST.
+ "statementByteBudget": "A String", # Limit on the number of bytes billed per statement. Exceeding this budget results in an error.
+ "statementTimeoutMs": "A String", # Timeout period for each statement in a script.
+ },
+ "systemVariables": { # System variables given to a query. # Output only. System variables for GoogleSQL queries. A system variable is output if the variable is settable and its value differs from the system default. "@@" prefix is not included in the name of the System variables.
+ "types": { # Output only. Data type for each system variable.
+ "a_key": { # The data type of a variable such as a function argument. Examples include: * INT64: `{"typeKind": "INT64"}` * ARRAY: { "typeKind": "ARRAY", "arrayElementType": {"typeKind": "STRING"} } * STRUCT>: { "typeKind": "STRUCT", "structType": { "fields": [ { "name": "x", "type": {"typeKind": "STRING"} }, { "name": "y", "type": { "typeKind": "ARRAY", "arrayElementType": {"typeKind": "DATE"} } } ] } }
+ "arrayElementType": # Object with schema name: StandardSqlDataType # The type of the array's elements, if type_kind = "ARRAY".
+ "rangeElementType": # Object with schema name: StandardSqlDataType # The type of the range's elements, if type_kind = "RANGE".
+ "structType": { # The representation of a SQL STRUCT type. # The fields of this struct, in order, if type_kind = "STRUCT".
+ "fields": [ # Fields within the struct.
+ { # A field or a column.
+ "name": "A String", # Optional. The name of this field. Can be absent for struct fields.
+ "type": # Object with schema name: StandardSqlDataType # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
+ },
+ ],
+ },
+ "typeKind": "A String", # Required. The top level type of this field. Can be any GoogleSQL data type (e.g., "INT64", "DATE", "ARRAY").
+ },
+ },
+ "values": { # Output only. Value for each system variable.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "tableDefinitions": { # Optional. You can specify external table definitions, which operate as ephemeral tables that can be queried. These definitions are configured using a JSON map, where the string key represents the table identifier, and the value is the corresponding external data configuration object.
"a_key": {
"autodetect": True or False, # Try to detect schema and format options automatically. Any option specified explicitly will be honored.
- "avroOptions": { # Additional properties to set if sourceFormat is set to Avro.
- "useAvroLogicalTypes": True or False, # [Optional] If sourceFormat is set to "AVRO", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER).
- },
- "bigtableOptions": { # [Optional] Additional options if sourceFormat is set to BIGTABLE.
- "columnFamilies": [ # [Optional] List of column families to expose in the table schema along with their types. This list restricts the column families that can be referenced in queries and specifies their value types. You can use this list to do type conversions - see the 'type' field for more details. If you leave this list empty, all column families are present in the table schema and their values are read as BYTES. During a query only the column families referenced in that query are read from Bigtable.
- {
- "columns": [ # [Optional] Lists of columns that should be exposed as individual fields as opposed to a list of (column name, value) pairs. All columns whose qualifier matches a qualifier in this list can be accessed as .. Other columns can be accessed as a list through .Column field.
- {
- "encoding": "A String", # [Optional] The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. 'encoding' can also be set at the column family level. However, the setting at this level takes precedence if 'encoding' is set at both levels.
- "fieldName": "A String", # [Optional] If the qualifier is not a valid BigQuery field identifier i.e. does not match [a-zA-Z][a-zA-Z0-9_]*, a valid identifier must be provided as the column field name and is used as field name in queries.
- "onlyReadLatest": True or False, # [Optional] If this is set, only the latest version of value in this column are exposed. 'onlyReadLatest' can also be set at the column family level. However, the setting at this level takes precedence if 'onlyReadLatest' is set at both levels.
- "qualifierEncoded": "A String", # [Required] Qualifier of the column. Columns in the parent column family that has this exact qualifier are exposed as . field. If the qualifier is valid UTF-8 string, it can be specified in the qualifier_string field. Otherwise, a base-64 encoded value must be set to qualifier_encoded. The column field name is the same as the column qualifier. However, if the qualifier is not a valid BigQuery field identifier i.e. does not match [a-zA-Z][a-zA-Z0-9_]*, a valid identifier must be provided as field_name.
- "qualifierString": "A String",
- "type": "A String", # [Optional] The type to convert the value in cells of this column. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive) - BYTES STRING INTEGER FLOAT BOOLEAN Default type is BYTES. 'type' can also be set at the column family level. However, the setting at this level takes precedence if 'type' is set at both levels.
+ "avroOptions": { # Options for external data sources. # Optional. Additional properties to set if sourceFormat is set to AVRO.
+ "useAvroLogicalTypes": True or False, # Optional. If sourceFormat is set to "AVRO", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER).
+ },
+ "bigtableOptions": { # Options specific to Google Cloud Bigtable data sources. # Optional. Additional options if sourceFormat is set to BIGTABLE.
+ "columnFamilies": [ # Optional. List of column families to expose in the table schema along with their types. This list restricts the column families that can be referenced in queries and specifies their value types. You can use this list to do type conversions - see the 'type' field for more details. If you leave this list empty, all column families are present in the table schema and their values are read as BYTES. During a query only the column families referenced in that query are read from Bigtable.
+ { # Information related to a Bigtable column family.
+ "columns": [ # Optional. Lists of columns that should be exposed as individual fields as opposed to a list of (column name, value) pairs. All columns whose qualifier matches a qualifier in this list can be accessed as .. Other columns can be accessed as a list through .Column field.
+ { # Information related to a Bigtable column.
+ "encoding": "A String", # Optional. The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. 'encoding' can also be set at the column family level. However, the setting at this level takes precedence if 'encoding' is set at both levels.
+ "fieldName": "A String", # Optional. If the qualifier is not a valid BigQuery field identifier i.e. does not match a-zA-Z*, a valid identifier must be provided as the column field name and is used as field name in queries.
+ "onlyReadLatest": True or False, # Optional. If this is set, only the latest version of value in this column are exposed. 'onlyReadLatest' can also be set at the column family level. However, the setting at this level takes precedence if 'onlyReadLatest' is set at both levels.
+ "qualifierEncoded": "A String", # [Required] Qualifier of the column. Columns in the parent column family that has this exact qualifier are exposed as . field. If the qualifier is valid UTF-8 string, it can be specified in the qualifier_string field. Otherwise, a base-64 encoded value must be set to qualifier_encoded. The column field name is the same as the column qualifier. However, if the qualifier is not a valid BigQuery field identifier i.e. does not match a-zA-Z*, a valid identifier must be provided as field_name.
+ "qualifierString": "A String", # Qualifier string.
+ "type": "A String", # Optional. The type to convert the value in cells of this column. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive): * BYTES * STRING * INTEGER * FLOAT * BOOLEAN * JSON Default type is BYTES. 'type' can also be set at the column family level. However, the setting at this level takes precedence if 'type' is set at both levels.
},
],
- "encoding": "A String", # [Optional] The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. This can be overridden for a specific column by listing that column in 'columns' and specifying an encoding for it.
+ "encoding": "A String", # Optional. The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. This can be overridden for a specific column by listing that column in 'columns' and specifying an encoding for it.
"familyId": "A String", # Identifier of the column family.
- "onlyReadLatest": True or False, # [Optional] If this is set only the latest version of value are exposed for all columns in this column family. This can be overridden for a specific column by listing that column in 'columns' and specifying a different setting for that column.
- "type": "A String", # [Optional] The type to convert the value in cells of this column family. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive) - BYTES STRING INTEGER FLOAT BOOLEAN Default type is BYTES. This can be overridden for a specific column by listing that column in 'columns' and specifying a type for it.
+ "onlyReadLatest": True or False, # Optional. If this is set only the latest version of value are exposed for all columns in this column family. This can be overridden for a specific column by listing that column in 'columns' and specifying a different setting for that column.
+ "type": "A String", # Optional. The type to convert the value in cells of this column family. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive): * BYTES * STRING * INTEGER * FLOAT * BOOLEAN * JSON Default type is BYTES. This can be overridden for a specific column by listing that column in 'columns' and specifying a type for it.
},
],
- "ignoreUnspecifiedColumnFamilies": True or False, # [Optional] If field is true, then the column families that are not specified in columnFamilies list are not exposed in the table schema. Otherwise, they are read with BYTES type values. The default value is false.
- "readRowkeyAsString": True or False, # [Optional] If field is true, then the rowkey column families will be read and converted to string. Otherwise they are read with BYTES type values and users need to manually cast them with CAST if necessary. The default value is false.
- },
- "compression": "A String", # [Optional] The compression type of the data source. Possible values include GZIP and NONE. The default value is NONE. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups and Avro formats.
- "connectionId": "A String", # [Optional, Trusted Tester] Connection for external data source.
- "csvOptions": { # Additional properties to set if sourceFormat is set to CSV.
- "allowJaggedRows": True or False, # [Optional] Indicates if BigQuery should accept rows that are missing trailing optional columns. If true, BigQuery treats missing trailing columns as null values. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false.
- "allowQuotedNewlines": True or False, # [Optional] Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false.
- "encoding": "A String", # [Optional] The character encoding of the data. The supported values are UTF-8 or ISO-8859-1. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the quote and fieldDelimiter properties.
- "fieldDelimiter": "A String", # [Optional] The separator for fields in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. BigQuery also supports the escape sequence "\t" to specify a tab separator. The default value is a comma (',').
- "nullMarker": "A String", # [Optional] An custom string that will represent a NULL value in CSV import data.
- "preserveAsciiControlCharacters": True or False, # [Optional] Preserves the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\x00' to '\x1F') when loading from CSV. Only applicable to CSV, ignored for other formats.
- "quote": """, # [Optional] The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ('"'). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true.
- "skipLeadingRows": "A String", # [Optional] The number of rows at the top of a CSV file that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
- },
- "decimalTargetTypes": [ # [Optional] Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown. Example: Suppose the value of this field is ["NUMERIC", "BIGNUMERIC"]. If (precision,scale) is: (38,9) -> NUMERIC; (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits); (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits); (76,38) -> BIGNUMERIC; (77,38) -> BIGNUMERIC (error if value exeeds supported range). This field cannot contain duplicate types. The order of the types in this field is ignored. For example, ["BIGNUMERIC", "NUMERIC"] is the same as ["NUMERIC", "BIGNUMERIC"] and NUMERIC always takes precedence over BIGNUMERIC. Defaults to ["NUMERIC", "STRING"] for ORC and ["NUMERIC"] for the other file formats.
+ "ignoreUnspecifiedColumnFamilies": True or False, # Optional. If field is true, then the column families that are not specified in columnFamilies list are not exposed in the table schema. Otherwise, they are read with BYTES type values. The default value is false.
+ "outputColumnFamiliesAsJson": True or False, # Optional. If field is true, then each column family will be read as a single JSON column. Otherwise they are read as a repeated cell structure containing timestamp/value tuples. The default value is false.
+ "readRowkeyAsString": True or False, # Optional. If field is true, then the rowkey column families will be read and converted to string. Otherwise they are read with BYTES type values and users need to manually cast them with CAST if necessary. The default value is false.
+ },
+ "compression": "A String", # Optional. The compression type of the data source. Possible values include GZIP and NONE. The default value is NONE. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups, Avro, ORC and Parquet formats. An empty string is an invalid value.
+ "connectionId": "A String", # Optional. The connection specifying the credentials to be used to read external storage, such as Azure Blob, Cloud Storage, or S3. The connection_id can have the form "<project\_id>.<location\_id>.<connection\_id>" or "projects/<project\_id>/locations/<location\_id>/connections/<connection\_id>".
+ "csvOptions": { # Information related to a CSV data source. # Optional. Additional properties to set if sourceFormat is set to CSV.
+ "allowJaggedRows": True or False, # Optional. Indicates if BigQuery should accept rows that are missing trailing optional columns. If true, BigQuery treats missing trailing columns as null values. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false.
+ "allowQuotedNewlines": True or False, # Optional. Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false.
+ "encoding": "A String", # Optional. The character encoding of the data. The supported values are UTF-8, ISO-8859-1, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the quote and fieldDelimiter properties.
+ "fieldDelimiter": "A String", # Optional. The separator character for fields in a CSV file. The separator is interpreted as a single byte. For files encoded in ISO-8859-1, any single character can be used as a separator. For files encoded in UTF-8, characters represented in decimal range 1-127 (U+0001-U+007F) can be used without any modification. UTF-8 characters encoded with multiple bytes (i.e. U+0080 and above) will have only the first byte used for separating fields. The remaining bytes will be treated as a part of the field. BigQuery also supports the escape sequence "\t" (U+0009) to specify a tab separator. The default value is comma (",", U+002C).
+ "nullMarker": "A String", # [Optional] A custom string that will represent a NULL value in CSV import data.
+ "preserveAsciiControlCharacters": True or False, # Optional. Indicates if the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\x00' to '\x1F') are preserved.
+ "quote": """, # Optional. The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ("). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true. To include the specific quote character within a quoted value, precede it with an additional matching quote character. For example, if you want to escape the default character ' " ', use ' "" '.
+ "skipLeadingRows": "A String", # Optional. The number of rows at the top of a CSV file that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
+ },
+ "decimalTargetTypes": [ # Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown. Example: Suppose the value of this field is ["NUMERIC", "BIGNUMERIC"]. If (precision,scale) is: * (38,9) -> NUMERIC; * (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits); * (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits); * (76,38) -> BIGNUMERIC; * (77,38) -> BIGNUMERIC (error if value exeeds supported range). This field cannot contain duplicate types. The order of the types in this field is ignored. For example, ["BIGNUMERIC", "NUMERIC"] is the same as ["NUMERIC", "BIGNUMERIC"] and NUMERIC always takes precedence over BIGNUMERIC. Defaults to ["NUMERIC", "STRING"] for ORC and ["NUMERIC"] for the other file formats.
"A String",
],
- "fileSetSpecType": "A String", # [Optional] Specifies how source URIs are interpreted for constructing the file set to load. By default source URIs are expanded against the underlying storage. Other options include specifying manifest files. Only applicable to object storage systems.
- "googleSheetsOptions": { # [Optional] Additional options if sourceFormat is set to GOOGLE_SHEETS.
- "range": "A String", # [Optional] Range of a sheet to query from. Only used when non-empty. Typical format: sheet_name!top_left_cell_id:bottom_right_cell_id For example: sheet1!A1:B20
- "skipLeadingRows": "A String", # [Optional] The number of rows at the top of a sheet that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows that should be skipped. When autodetect is on, behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
+ "fileSetSpecType": "A String", # Optional. Specifies how source URIs are interpreted for constructing the file set to load. By default source URIs are expanded against the underlying storage. Other options include specifying manifest files. Only applicable to object storage systems.
+ "googleSheetsOptions": { # Options specific to Google Sheets data sources. # Optional. Additional options if sourceFormat is set to GOOGLE_SHEETS.
+ "range": "A String", # Optional. Range of a sheet to query from. Only used when non-empty. Typical format: sheet_name!top_left_cell_id:bottom_right_cell_id For example: sheet1!A1:B20
+ "skipLeadingRows": "A String", # Optional. The number of rows at the top of a sheet that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
},
- "hivePartitioningOptions": { # [Optional] Options to configure hive partitioning support.
- "fields": [ # [Output-only] For permanent external tables, this field is populated with the hive partition keys in the order they were inferred. The types of the partition keys can be deduced by checking the table schema (which will include the partition keys). Not every API will populate this field in the output. For example, Tables.Get will populate it, but Tables.List will not contain this field.
+ "hivePartitioningOptions": { # Options for configuring hive partitioning detect. # Optional. When set, configures hive partitioning support. Not all storage formats support hive partitioning -- requesting hive partitioning on an unsupported format will lead to an error, as will providing an invalid specification.
+ "fields": [ # Output only. For permanent external tables, this field is populated with the hive partition keys in the order they were inferred. The types of the partition keys can be deduced by checking the table schema (which will include the partition keys). Not every API will populate this field in the output. For example, Tables.Get will populate it, but Tables.List will not contain this field.
"A String",
],
- "mode": "A String", # [Optional] When set, what mode of hive partitioning to use when reading data. The following modes are supported. (1) AUTO: automatically infer partition key name(s) and type(s). (2) STRINGS: automatically infer partition key name(s). All types are interpreted as strings. (3) CUSTOM: partition key schema is encoded in the source URI prefix. Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported types include: AVRO, CSV, JSON, ORC and Parquet.
- "requirePartitionFilter": True or False, # [Optional] If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. Note that this field should only be true when creating a permanent external table or querying a temporary external table. Hive-partitioned loads with requirePartitionFilter explicitly set to true will fail.
- "sourceUriPrefix": "A String", # [Optional] When hive partition detection is requested, a common prefix for all source uris should be supplied. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout. gs://bucket/path_to_table/dt=2019-01-01/country=BR/id=7/file.avro gs://bucket/path_to_table/dt=2018-12-31/country=CA/id=3/file.avro When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/ (trailing slash does not matter).
- },
- "ignoreUnknownValues": True or False, # [Optional] Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names Google Cloud Bigtable: This setting is ignored. Google Cloud Datastore backups: This setting is ignored. Avro: This setting is ignored.
- "jsonOptions": { # Additional properties to set if `sourceFormat` is set to `NEWLINE_DELIMITED_JSON`.
- "encoding": "A String", # [Optional] The character encoding of the data. The supported values are UTF-8, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8.
- },
- "maxBadRecords": 42, # [Optional] The maximum number of bad records that BigQuery can ignore when reading data. If the number of bad records exceeds this value, an invalid error is returned in the job result. This is only valid for CSV, JSON, and Google Sheets. The default value is 0, which requires that all records are valid. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups and Avro formats.
- "metadataCacheMode": "A String", # [Optional] Metadata Cache Mode for the table. Set this to enable caching of metadata from external data source.
- "objectMetadata": "A String", # ObjectMetadata is used to create Object Tables. Object Tables contain a listing of objects (with their metadata) found at the source_uris. If ObjectMetadata is set, source_format should be omitted. Currently SIMPLE is the only supported Object Metadata type.
- "parquetOptions": { # Additional properties to set if sourceFormat is set to Parquet.
- "enableListInference": True or False, # [Optional] Indicates whether to use schema inference specifically for Parquet LIST logical type.
- "enumAsString": True or False, # [Optional] Indicates whether to infer Parquet ENUM logical type as STRING instead of BYTES by default.
- },
- "referenceFileSchemaUri": "A String", # [Optional] Provide a referencing file with the expected table schema. Enabled for the format: AVRO, PARQUET, ORC.
- "schema": { # [Optional] The schema for the data. Schema is required for CSV and JSON formats. Schema is disallowed for Google Cloud Bigtable, Cloud Datastore backups, and Avro formats.
+ "mode": "A String", # Optional. When set, what mode of hive partitioning to use when reading data. The following modes are supported: * AUTO: automatically infer partition key name(s) and type(s). * STRINGS: automatically infer partition key name(s). All types are strings. * CUSTOM: partition key schema is encoded in the source URI prefix. Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported formats are: JSON, CSV, ORC, Avro and Parquet.
+ "requirePartitionFilter": false, # Optional. If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. Note that this field should only be true when creating a permanent external table or querying a temporary external table. Hive-partitioned loads with require_partition_filter explicitly set to true will fail.
+ "sourceUriPrefix": "A String", # Optional. When hive partition detection is requested, a common prefix for all source uris must be required. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout: gs://bucket/path_to_table/dt=2019-06-01/country=USA/id=7/file.avro gs://bucket/path_to_table/dt=2019-05-31/country=CA/id=3/file.avro When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/. CUSTOM detection requires encoding the partitioning schema immediately after the common prefix. For CUSTOM, any of * gs://bucket/path_to_table/{dt:DATE}/{country:STRING}/{id:INTEGER} * gs://bucket/path_to_table/{dt:STRING}/{country:STRING}/{id:INTEGER} * gs://bucket/path_to_table/{dt:DATE}/{country:STRING}/{id:STRING} would all be valid source URI prefixes.
+ },
+ "ignoreUnknownValues": True or False, # Optional. Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names Google Cloud Bigtable: This setting is ignored. Google Cloud Datastore backups: This setting is ignored. Avro: This setting is ignored. ORC: This setting is ignored. Parquet: This setting is ignored.
+ "jsonExtension": "A String", # Optional. Load option to be used together with source_format newline-delimited JSON to indicate that a variant of JSON is being loaded. To load newline-delimited GeoJSON, specify GEOJSON (and source_format must be set to NEWLINE_DELIMITED_JSON).
+ "jsonOptions": { # Json Options for load and make external tables. # Optional. Additional properties to set if sourceFormat is set to JSON.
+ "encoding": "A String", # Optional. The character encoding of the data. The supported values are UTF-8, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8.
+ },
+ "maxBadRecords": 42, # Optional. The maximum number of bad records that BigQuery can ignore when reading data. If the number of bad records exceeds this value, an invalid error is returned in the job result. The default value is 0, which requires that all records are valid. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups, Avro, ORC and Parquet formats.
+ "metadataCacheMode": "A String", # Optional. Metadata Cache Mode for the table. Set this to enable caching of metadata from external data source.
+ "objectMetadata": "A String", # Optional. ObjectMetadata is used to create Object Tables. Object Tables contain a listing of objects (with their metadata) found at the source_uris. If ObjectMetadata is set, source_format should be omitted. Currently SIMPLE is the only supported Object Metadata type.
+ "parquetOptions": { # Parquet Options for load and make external tables. # Optional. Additional properties to set if sourceFormat is set to PARQUET.
+ "enableListInference": True or False, # Optional. Indicates whether to use schema inference specifically for Parquet LIST logical type.
+ "enumAsString": True or False, # Optional. Indicates whether to infer Parquet ENUM logical type as STRING instead of BYTES by default.
+ },
+ "referenceFileSchemaUri": "A String", # Optional. When creating an external table, the user can provide a reference file with the table schema. This is enabled for the following formats: AVRO, PARQUET, ORC.
+ "schema": { # Schema of a table # Optional. The schema for the data. Schema is required for CSV and JSON formats if autodetect is not on. Schema is disallowed for Google Cloud Bigtable, Cloud Datastore backups, Avro, ORC and Parquet formats.
"fields": [ # Describes the fields in a table.
- {
- "categories": { # [Optional] The categories attached to this field, used for field-level access control.
- "names": [ # A list of category resource names. For example, "projects/1/taxonomies/2/categories/3". At most 5 categories are allowed.
+ { # A field in TableSchema
+ "categories": { # Deprecated.
+ "names": [ # Deprecated.
"A String",
],
},
- "collation": "A String", # Optional. Collation specification of the field. It only can be set on string type field.
- "defaultValueExpression": "A String", # Optional. A SQL expression to specify the default value for this field. It can only be set for top level fields (columns). You can use struct or array expression to specify default value for the entire struct or array. The valid SQL expressions are: - Literals for all data types, including STRUCT and ARRAY. - Following functions: - CURRENT_TIMESTAMP - CURRENT_TIME - CURRENT_DATE - CURRENT_DATETIME - GENERATE_UUID - RAND - SESSION_USER - ST_GEOGPOINT - Struct or array composed with the above allowed functions, for example, [CURRENT_DATE(), DATE '2020-01-01']
- "description": "A String", # [Optional] The field description. The maximum length is 1,024 characters.
- "fields": [ # [Optional] Describes the nested schema fields if the type property is set to RECORD.
+ "collation": "A String", # Optional. Field collation can be set only when the type of field is STRING. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.
+ "defaultValueExpression": "A String", # Optional. A SQL expression to specify the [default value] (https://cloud.google.com/bigquery/docs/default-values) for this field.
+ "description": "A String", # Optional. The field description. The maximum length is 1,024 characters.
+ "fields": [ # Optional. Describes the nested schema fields if the type property is set to RECORD.
# Object with schema name: TableFieldSchema
],
- "maxLength": "A String", # [Optional] Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
- "mode": "A String", # [Optional] The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
- "name": "A String", # [Required] The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
- "policyTags": {
- "names": [ # A list of category resource names. For example, "projects/1/location/eu/taxonomies/2/policyTags/3". At most 1 policy tag is allowed.
+ "maxLength": "A String", # Optional. Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
+ "mode": "A String", # Optional. The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
+ "name": "A String", # Required. The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
+ "policyTags": { # Optional. The policy tags attached to this field, used for field-level access control. If not set, defaults to empty policy_tags.
+ "names": [ # A list of policy tag resource names. For example, "projects/1/locations/eu/taxonomies/2/policyTags/3". At most 1 policy tag is currently allowed.
"A String",
],
},
- "precision": "A String", # [Optional] Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: - Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] - Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: - If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. - If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): - If type = "NUMERIC": 1 ≤ precision ≤ 29. - If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
- "rangeElementType": { # Optional. The subtype of the RANGE, if the type of this field is RANGE. If the type is RANGE, this field is required. Possible values for the field element type of a RANGE include: - DATE - DATETIME - TIMESTAMP
- "type": "A String", # The field element type of a RANGE
+ "precision": "A String", # Optional. Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: * Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] * Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: * If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. * If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): * If type = "NUMERIC": 1 ≤ precision ≤ 29. * If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
+ "rangeElementType": { # Represents the type of a field element.
+ "type": "A String", # Required. The type of a field element. See TableFieldSchema.type.
},
- "roundingMode": "A String", # Optional. Rounding Mode specification of the field. It only can be set on NUMERIC or BIGNUMERIC type fields.
- "scale": "A String", # [Optional] See documentation for precision.
- "type": "A String", # [Required] The field data type. Possible values include STRING, BYTES, INTEGER, INT64 (same as INTEGER), FLOAT, FLOAT64 (same as FLOAT), NUMERIC, BIGNUMERIC, BOOLEAN, BOOL (same as BOOLEAN), TIMESTAMP, DATE, TIME, DATETIME, INTERVAL, RECORD (where RECORD indicates that the field contains a nested schema) or STRUCT (same as RECORD).
+ "roundingMode": "A String", # Optional. Specifies the rounding mode to be used when storing values of NUMERIC and BIGNUMERIC type.
+ "scale": "A String", # Optional. See documentation for precision.
+ "type": "A String", # Required. The field data type. Possible values include: * STRING * BYTES * INTEGER (or INT64) * FLOAT (or FLOAT64) * BOOLEAN (or BOOL) * TIMESTAMP * DATE * TIME * DATETIME * GEOGRAPHY * NUMERIC * BIGNUMERIC * JSON * RECORD (or STRUCT) Use of RECORD/STRUCT indicates that the field contains a nested schema.
},
],
},
- "sourceFormat": "A String", # [Required] The data format. For CSV files, specify "CSV". For Google sheets, specify "GOOGLE_SHEETS". For newline-delimited JSON, specify "NEWLINE_DELIMITED_JSON". For Avro files, specify "AVRO". For Google Cloud Datastore backups, specify "DATASTORE_BACKUP". [Beta] For Google Cloud Bigtable, specify "BIGTABLE".
+ "sourceFormat": "A String", # [Required] The data format. For CSV files, specify "CSV". For Google sheets, specify "GOOGLE_SHEETS". For newline-delimited JSON, specify "NEWLINE_DELIMITED_JSON". For Avro files, specify "AVRO". For Google Cloud Datastore backups, specify "DATASTORE_BACKUP". For Apache Iceberg tables, specify "ICEBERG". For ORC files, specify "ORC". For Parquet files, specify "PARQUET". [Beta] For Google Cloud Bigtable, specify "BIGTABLE".
"sourceUris": [ # [Required] The fully-qualified URIs that point to your data in Google Cloud. For Google Cloud Storage URIs: Each URI can contain one '*' wildcard character and it must come after the 'bucket' name. Size limits related to load jobs apply to external data sources. For Google Cloud Bigtable URIs: Exactly one URI can be specified and it has be a fully specified and valid HTTPS URL for a Google Cloud Bigtable table. For Google Cloud Datastore backups, exactly one URI can be specified. Also, the '*' wildcard character is not allowed.
"A String",
],
},
},
"timePartitioning": { # Time-based partitioning specification for the destination table. Only one of timePartitioning and rangePartitioning should be specified.
- "expirationMs": "A String", # [Optional] Number of milliseconds for which to keep the storage for partitions in the table. The storage in a partition will have an expiration time of its partition time plus this value.
- "field": "A String", # [Beta] [Optional] If not set, the table is partitioned by pseudo column, referenced via either '_PARTITIONTIME' as TIMESTAMP type, or '_PARTITIONDATE' as DATE type. If field is specified, the table is instead partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED.
- "requirePartitionFilter": True or False,
- "type": "A String", # [Required] The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively. When the type is not specified, the default behavior is DAY.
+ "expirationMs": "A String", # Optional. Number of milliseconds for which to keep the storage for a partition. A wrapper is used here because 0 is an invalid value.
+ "field": "A String", # Optional. If not set, the table is partitioned by pseudo column '_PARTITIONTIME'; if set, the table is partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED. A wrapper is used here because an empty string is an invalid value.
+ "requirePartitionFilter": false, # If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. This field is deprecated; please set the field with the same name on the table itself instead. This field needs a wrapper because we want to output the default value, false, if the user explicitly set it.
+ "type": "A String", # Required. The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively.
},
- "useLegacySql": true, # Specifies whether to use BigQuery's legacy SQL dialect for this query. The default value is true. If set to false, the query will use BigQuery's standard SQL: https://cloud.google.com/bigquery/sql-reference/ When useLegacySql is set to false, the value of flattenResults is ignored; query will be run as if flattenResults is false.
- "useQueryCache": true, # [Optional] Whether to look for the result in the query cache. The query cache is a best-effort cache that will be flushed whenever tables in the query are modified. Moreover, the query cache is only available when a query does not have a destination table specified. The default value is true.
+ "useLegacySql": true, # Optional. Specifies whether to use BigQuery's legacy SQL dialect for this query. The default value is true. If set to false, the query will use BigQuery's GoogleSQL: https://cloud.google.com/bigquery/sql-reference/ When useLegacySql is set to false, the value of flattenResults is ignored; query will be run as if flattenResults is false.
+ "useQueryCache": true, # Optional. Whether to look for the result in the query cache. The query cache is a best-effort cache that will be flushed whenever tables in the query are modified. Moreover, the query cache is only available when a query does not have a destination table specified. The default value is true.
"userDefinedFunctionResources": [ # Describes user-defined function resources used in the query.
- { # This is used for defining User Defined Function (UDF) resources only when using legacy SQL. Users of Standard SQL should leverage either DDL (e.g. CREATE [TEMPORARY] FUNCTION ... ) or the Routines API to define UDF resources. For additional information on migrating, see: https://cloud.google.com/bigquery/docs/reference/standard-sql/migrating-from-legacy-sql#differences_in_user-defined_javascript_functions
+ { # This is used for defining User Defined Function (UDF) resources only when using legacy SQL. Users of GoogleSQL should leverage either DDL (e.g. CREATE [TEMPORARY] FUNCTION ... ) or the Routines API to define UDF resources. For additional information on migrating, see: https://cloud.google.com/bigquery/docs/reference/standard-sql/migrating-from-legacy-sql#differences_in_user-defined_javascript_functions
"inlineCode": "A String", # [Pick one] An inline resource that contains code for a user-defined function (UDF). Providing a inline code resource is equivalent to providing a URI for a file containing the same code.
"resourceUri": "A String", # [Pick one] A code resource to load from a Google Cloud Storage URI (gs://bucket/path).
},
],
- "writeDisposition": "A String", # [Optional] Specifies the action that occurs if the destination table already exists. The following values are supported: WRITE_TRUNCATE: If the table already exists, BigQuery overwrites the table data and uses the schema from the query result. WRITE_APPEND: If the table already exists, BigQuery appends the data to the table. WRITE_EMPTY: If the table already exists and contains data, a 'duplicate' error is returned in the job result. The default value is WRITE_EMPTY. Each action is atomic and only occurs if BigQuery is able to complete the job successfully. Creation, truncation and append actions occur as one atomic update upon job completion.
+ "writeDisposition": "A String", # Optional. Specifies the action that occurs if the destination table already exists. The following values are supported: * WRITE_TRUNCATE: If the table already exists, BigQuery overwrites the data, removes the constraints, and uses the schema from the query result. * WRITE_APPEND: If the table already exists, BigQuery appends the data to the table. * WRITE_EMPTY: If the table already exists and contains data, a 'duplicate' error is returned in the job result. The default value is WRITE_EMPTY. Each action is atomic and only occurs if BigQuery is able to complete the job successfully. Creation, truncation and append actions occur as one atomic update upon job completion.
},
},
- "etag": "A String", # [Output-only] A hash of this resource.
- "id": "A String", # [Output-only] Opaque ID field of the job
- "jobCreationReason": "", # [Output-only] If set, it provides the reason why a Job was created. If not set, it should be treated as the default: REQUESTED. This feature is not yet available. Jobs will always be created.
- "jobReference": { # [Optional] Reference describing the unique-per-user name of the job.
- "jobId": "A String", # [Required] The ID of the job. The ID must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), or dashes (-). The maximum length is 1,024 characters.
- "location": "A String", # The geographic location of the job. See details at https://cloud.google.com/bigquery/docs/locations#specifying_your_location.
- "projectId": "A String", # [Required] The ID of the project containing this job.
+ "etag": "A String", # Output only. A hash of this resource.
+ "id": "A String", # Output only. Opaque ID field of the job.
+ "jobCreationReason": { # Reason about why a Job was created from a [`jobs.query`](https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs/query) method when used with `JOB_CREATION_OPTIONAL` Job creation mode. For [`jobs.insert`](https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs/insert) method calls it will always be `REQUESTED`. This feature is not yet available. Jobs will always be created. # Output only. If set, it provides the reason why a Job was created. If not set, it should be treated as the default: REQUESTED. This feature is not yet available. Jobs will always be created.
+ "code": "A String", # Output only. Specifies the high level reason why a Job was created.
},
- "kind": "bigquery#job", # [Output-only] The type of the resource.
- "selfLink": "A String", # [Output-only] A URL that can be used to access this resource again.
- "statistics": { # [Output-only] Information about the job, including starting time and ending time of the job.
- "completionRatio": 3.14, # [TrustedTester] [Output-only] Job progress (0.0 -> 1.0) for LOAD and EXTRACT jobs.
- "copy": { # [Output-only] Statistics for a copy job.
- "copiedLogicalBytes": "A String", # [Output-only] Number of logical bytes copied to the destination table.
- "copiedRows": "A String", # [Output-only] Number of rows copied to the destination table.
- },
- "creationTime": "A String", # [Output-only] Creation time of this job, in milliseconds since the epoch. This field will be present on all jobs.
- "dataMaskingStatistics": { # [Output-only] Statistics for data masking. Present only for query and extract jobs.
- "dataMaskingApplied": false, # [Output-only] [Preview] Whether any accessed data was protected by data masking. The actual evaluation is done by accessStats.masked_field_count > 0. Since this is only used for the discovery_doc generation purpose, as long as the type (boolean) matches, client library can leverage this. The actual evaluation of the variable is done else-where.
- },
- "endTime": "A String", # [Output-only] End time of this job, in milliseconds since the epoch. This field will be present whenever a job is in the DONE state.
- "extract": { # [Output-only] Statistics for an extract job.
- "destinationUriFileCounts": [ # [Output-only] Number of files per destination URI or URI pattern specified in the extract configuration. These values will be in the same order as the URIs specified in the 'destinationUris' field.
+ "jobReference": { # A job reference is a fully qualified identifier for referring to a job. # Optional. Reference describing the unique-per-user name of the job.
+ "jobId": "A String", # Required. The ID of the job. The ID must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), or dashes (-). The maximum length is 1,024 characters.
+ "location": "A String", # Optional. The geographic location of the job. The default value is US. For more information about BigQuery locations, see: https://cloud.google.com/bigquery/docs/locations
+ "projectId": "A String", # Required. The ID of the project containing this job.
+ },
+ "kind": "bigquery#job", # Output only. The type of the resource.
+ "principal_subject": "A String", # Output only. [Full-projection-only] String representation of identity of requesting party. Populated for both first- and third-party identities. Only present for APIs that support third-party identities.
+ "selfLink": "A String", # Output only. A URL that can be used to access the resource again.
+ "statistics": { # Statistics for a single job execution. # Output only. Information about the job, including starting time and ending time of the job.
+ "completionRatio": 3.14, # Output only. [TrustedTester] Job progress (0.0 -> 1.0) for LOAD and EXTRACT jobs.
+ "copy": { # Statistics for a copy job. # Output only. Statistics for a copy job.
+ "copiedLogicalBytes": "A String", # Output only. Number of logical bytes copied to the destination table.
+ "copiedRows": "A String", # Output only. Number of rows copied to the destination table.
+ },
+ "creationTime": "A String", # Output only. Creation time of this job, in milliseconds since the epoch. This field will be present on all jobs.
+ "dataMaskingStatistics": { # Statistics for data-masking. # Output only. Statistics for data-masking. Present only for query and extract jobs.
+ "dataMaskingApplied": True or False, # Whether any accessed data was protected by the data masking.
+ },
+ "endTime": "A String", # Output only. End time of this job, in milliseconds since the epoch. This field will be present whenever a job is in the DONE state.
+ "extract": { # Statistics for an extract job. # Output only. Statistics for an extract job.
+ "destinationUriFileCounts": [ # Output only. Number of files per destination URI or URI pattern specified in the extract configuration. These values will be in the same order as the URIs specified in the 'destinationUris' field.
"A String",
],
- "inputBytes": "A String", # [Output-only] Number of user bytes extracted into the result. This is the byte count as computed by BigQuery for billing purposes.
- },
- "load": { # [Output-only] Statistics for a load job.
- "badRecords": "A String", # [Output-only] The number of bad records encountered. Note that if the job has failed because of more bad records encountered than the maximum allowed in the load job configuration, then this number can be less than the total number of bad records present in the input data.
- "inputFileBytes": "A String", # [Output-only] Number of bytes of source data in a load job.
- "inputFiles": "A String", # [Output-only] Number of source files in a load job.
- "outputBytes": "A String", # [Output-only] Size of the loaded data in bytes. Note that while a load job is in the running state, this value may change.
- "outputRows": "A String", # [Output-only] Number of rows imported in a load job. Note that while an import job is in the running state, this value may change.
- },
- "numChildJobs": "A String", # [Output-only] Number of child jobs executed.
- "parentJobId": "A String", # [Output-only] If this is a child job, the id of the parent.
- "query": { # [Output-only] Statistics for a query job.
- "biEngineStatistics": { # BI Engine specific Statistics. [Output only] BI Engine specific Statistics.
- "accelerationMode": "", # [Output-only] Specifies which mode of BI Engine acceleration was performed (if any).
- "biEngineMode": "", # [Output-only] Specifies which mode of BI Engine acceleration was performed (if any).
+ "inputBytes": "A String", # Output only. Number of user bytes extracted into the result. This is the byte count as computed by BigQuery for billing purposes and doesn't have any relationship with the number of actual result bytes extracted in the desired format.
+ "timeline": [ # Output only. Describes a timeline of job execution.
+ { # Summary of the state of query execution at a given time.
+ "activeUnits": "A String", # Total number of active workers. This does not correspond directly to slot usage. This is the largest value observed since the last sample.
+ "completedUnits": "A String", # Total parallel units of work completed by this query.
+ "elapsedMs": "A String", # Milliseconds elapsed since the start of query execution.
+ "estimatedRunnableUnits": "A String", # Units of work that can be scheduled immediately. Providing additional slots for these units of work will accelerate the query, if no other query in the reservation needs additional slots.
+ "pendingUnits": "A String", # Total units of work remaining for the query. This number can be revised (increased or decreased) while the query is running.
+ "totalSlotMs": "A String", # Cumulative slot-ms consumed by the query.
+ },
+ ],
+ },
+ "finalExecutionDurationMs": "A String", # Output only. The duration in milliseconds of the execution of the final attempt of this job, as BigQuery may internally re-attempt to execute the job.
+ "load": { # Statistics for a load job. # Output only. Statistics for a load job.
+ "badRecords": "A String", # Output only. The number of bad records encountered. Note that if the job has failed because of more bad records encountered than the maximum allowed in the load job configuration, then this number can be less than the total number of bad records present in the input data.
+ "inputFileBytes": "A String", # Output only. Number of bytes of source data in a load job.
+ "inputFiles": "A String", # Output only. Number of source files in a load job.
+ "outputBytes": "A String", # Output only. Size of the loaded data in bytes. Note that while a load job is in the running state, this value may change.
+ "outputRows": "A String", # Output only. Number of rows imported in a load job. Note that while an import job is in the running state, this value may change.
+ "timeline": [ # Output only. Describes a timeline of job execution.
+ { # Summary of the state of query execution at a given time.
+ "activeUnits": "A String", # Total number of active workers. This does not correspond directly to slot usage. This is the largest value observed since the last sample.
+ "completedUnits": "A String", # Total parallel units of work completed by this query.
+ "elapsedMs": "A String", # Milliseconds elapsed since the start of query execution.
+ "estimatedRunnableUnits": "A String", # Units of work that can be scheduled immediately. Providing additional slots for these units of work will accelerate the query, if no other query in the reservation needs additional slots.
+ "pendingUnits": "A String", # Total units of work remaining for the query. This number can be revised (increased or decreased) while the query is running.
+ "totalSlotMs": "A String", # Cumulative slot-ms consumed by the query.
+ },
+ ],
+ },
+ "numChildJobs": "A String", # Output only. Number of child jobs executed.
+ "parentJobId": "A String", # Output only. If this is a child job, specifies the job ID of the parent.
+ "query": { # Statistics for a query job. # Output only. Statistics for a query job.
+ "biEngineStatistics": { # Statistics for a BI Engine specific query. Populated as part of JobStatistics2 # Output only. BI Engine specific Statistics.
+ "accelerationMode": "A String", # Output only. Specifies which mode of BI Engine acceleration was performed (if any).
+ "biEngineMode": "A String", # Output only. Specifies which mode of BI Engine acceleration was performed (if any).
"biEngineReasons": [ # In case of DISABLED or PARTIAL bi_engine_mode, these contain the explanatory reasons as to why BI Engine could not accelerate. In case the full query was accelerated, this field is not populated.
- {
- "code": "", # [Output-only] High-level BI Engine reason for partial or disabled acceleration.
- "message": "", # [Output-only] Free form human-readable reason for partial or disabled acceleration.
+ { # Reason why BI Engine didn't accelerate the query (or sub-query).
+ "code": "A String", # Output only. High-level BI Engine reason for partial or disabled acceleration
+ "message": "A String", # Output only. Free form human-readable reason for partial or disabled acceleration.
},
],
},
- "billingTier": 42, # [Output only] Billing tier for the job.
- "cacheHit": True or False, # [Output only] Whether the query result was fetched from the query cache.
- "ddlAffectedRowAccessPolicyCount": "A String", # [Output only] [Preview] The number of row access policies affected by a DDL statement. Present only for DROP ALL ROW ACCESS POLICIES queries.
- "ddlDestinationTable": { # [Output only] The DDL destination table. Present only for ALTER TABLE RENAME TO queries. Note that ddl_target_table is used just for its type information.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "billingTier": 42, # Output only. Billing tier for the job. This is a BigQuery-specific concept which is not related to the Google Cloud notion of "free tier". The value here is a measure of the query's resource consumption relative to the amount of data scanned. For on-demand queries, the limit is 100, and all queries within this limit are billed at the standard on-demand rates. On-demand queries that exceed this limit will fail with a billingTierLimitExceeded error.
+ "cacheHit": True or False, # Output only. Whether the query result was fetched from the query cache.
+ "dclTargetDataset": { # Output only. Referenced dataset for DCL statement.
+ "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "projectId": "A String", # Optional. The ID of the project containing this dataset.
},
- "ddlOperationPerformed": "A String", # The DDL operation performed, possibly dependent on the pre-existence of the DDL target. Possible values (new values might be added in the future): "CREATE": The query created the DDL target. "SKIP": No-op. Example cases: the query is CREATE TABLE IF NOT EXISTS while the table already exists, or the query is DROP TABLE IF EXISTS while the table does not exist. "REPLACE": The query replaced the DDL target. Example case: the query is CREATE OR REPLACE TABLE, and the table already exists. "DROP": The query deleted the DDL target.
- "ddlTargetDataset": { # [Output only] The DDL target dataset. Present only for CREATE/ALTER/DROP/UNDROP SCHEMA queries.
- "datasetId": "A String", # [Required] A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- "projectId": "A String", # [Optional] The ID of the project containing this dataset.
+ "dclTargetTable": { # Output only. Referenced table for DCL statement.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
- "ddlTargetRoutine": { # The DDL target routine. Present only for CREATE/DROP FUNCTION/PROCEDURE queries.
+ "dclTargetView": { # Output only. Referenced view for DCL statement.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ "ddlAffectedRowAccessPolicyCount": "A String", # Output only. The number of row access policies affected by a DDL statement. Present only for DROP ALL ROW ACCESS POLICIES queries.
+ "ddlDestinationTable": { # Output only. The table after rename. Present only for ALTER TABLE RENAME TO query.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ "ddlOperationPerformed": "A String", # Output only. The DDL operation performed, possibly dependent on the pre-existence of the DDL target.
+ "ddlTargetDataset": { # Output only. The DDL target dataset. Present only for CREATE/ALTER/DROP SCHEMA(dataset) queries.
+ "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "projectId": "A String", # Optional. The ID of the project containing this dataset.
+ },
+ "ddlTargetRoutine": { # Id path of a routine. # Output only. [Beta] The DDL target routine. Present only for CREATE/DROP FUNCTION/PROCEDURE queries.
"datasetId": "A String", # Required. The ID of the dataset containing this routine.
"projectId": "A String", # Required. The ID of the project containing this routine.
"routineId": "A String", # Required. The ID of the routine. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 256 characters.
},
- "ddlTargetRowAccessPolicy": { # [Output only] [Preview] The DDL target row access policy. Present only for CREATE/DROP ROW ACCESS POLICY queries.
+ "ddlTargetRowAccessPolicy": { # Id path of a row access policy. # Output only. The DDL target row access policy. Present only for CREATE/DROP ROW ACCESS POLICY queries.
"datasetId": "A String", # Required. The ID of the dataset containing this row access policy.
"policyId": "A String", # Required. The ID of the row access policy. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 256 characters.
"projectId": "A String", # Required. The ID of the project containing this row access policy.
"tableId": "A String", # Required. The ID of the table containing this row access policy.
},
- "ddlTargetTable": { # [Output only] The DDL target table. Present only for CREATE/DROP TABLE/VIEW and DROP ALL ROW ACCESS POLICIES queries.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "ddlTargetTable": { # Output only. The DDL target table. Present only for CREATE/DROP TABLE/VIEW and DROP ALL ROW ACCESS POLICIES queries.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
- "dmlStats": { # [Output only] Detailed statistics for DML statements Present only for DML statements INSERT, UPDATE, DELETE or TRUNCATE.
- "deletedRowCount": "A String", # Number of deleted Rows. populated by DML DELETE, MERGE and TRUNCATE statements.
- "insertedRowCount": "A String", # Number of inserted Rows. Populated by DML INSERT and MERGE statements.
- "updatedRowCount": "A String", # Number of updated Rows. Populated by DML UPDATE and MERGE statements.
+ "dmlStats": { # Detailed statistics for DML statements # Output only. Detailed statistics for DML statements INSERT, UPDATE, DELETE, MERGE or TRUNCATE.
+ "deletedRowCount": "A String", # Output only. Number of deleted Rows. populated by DML DELETE, MERGE and TRUNCATE statements.
+ "insertedRowCount": "A String", # Output only. Number of inserted Rows. Populated by DML INSERT and MERGE statements
+ "updatedRowCount": "A String", # Output only. Number of updated Rows. Populated by DML UPDATE and MERGE statements.
},
- "estimatedBytesProcessed": "A String", # [Output only] The original estimate of bytes processed for the job.
- "mlStatistics": { # [Output only] Statistics of a BigQuery ML training job.
- "iterationResults": [ # Results for all completed iterations.
- {
+ "estimatedBytesProcessed": "A String", # Output only. The original estimate of bytes processed for the job.
+ "exportDataStatistics": { # Statistics for the EXPORT DATA statement as part of Query Job. EXTRACT JOB statistics are populated in JobStatistics4. # Output only. Stats for EXPORT DATA statement.
+ "fileCount": "A String", # Number of destination files generated in case of EXPORT DATA statement only.
+ "rowCount": "A String", # [Alpha] Number of destination rows generated in case of EXPORT DATA statement only.
+ },
+ "externalServiceCosts": [ # Output only. Job cost breakdown as bigquery internal cost and external service costs.
+ { # The external service cost is a portion of the total cost, these costs are not additive with total_bytes_billed. Moreover, this field only track external service costs that will show up as BigQuery costs (e.g. training BigQuery ML job with google cloud CAIP or Automl Tables services), not other costs which may be accrued by running the query (e.g. reading from Bigtable or Cloud Storage). The external service costs with different billing sku (e.g. CAIP job is charged based on VM usage) are converted to BigQuery billed_bytes and slot_ms with equivalent amount of US dollars. Services may not directly correlate to these metrics, but these are the equivalents for billing purposes. Output only.
+ "bytesBilled": "A String", # External service cost in terms of bigquery bytes billed.
+ "bytesProcessed": "A String", # External service cost in terms of bigquery bytes processed.
+ "externalService": "A String", # External service name.
+ "reservedSlotCount": "A String", # Non-preemptable reserved slots used for external job. For example, reserved slots for Cloua AI Platform job are the VM usages converted to BigQuery slot with equivalent mount of price.
+ "slotMs": "A String", # External service cost in terms of bigquery slot milliseconds.
+ },
+ ],
+ "loadQueryStatistics": { # Statistics for a LOAD query. # Output only. Statistics for a LOAD query.
+ "badRecords": "A String", # Output only. The number of bad records encountered while processing a LOAD query. Note that if the job has failed because of more bad records encountered than the maximum allowed in the load job configuration, then this number can be less than the total number of bad records present in the input data.
+ "bytesTransferred": "A String", # Output only. This field is deprecated. The number of bytes of source data copied over the network for a `LOAD` query. `transferred_bytes` has the canonical value for physical transferred bytes, which is used for BigQuery Omni billing.
+ "inputFileBytes": "A String", # Output only. Number of bytes of source data in a LOAD query.
+ "inputFiles": "A String", # Output only. Number of source files in a LOAD query.
+ "outputBytes": "A String", # Output only. Size of the loaded data in bytes. Note that while a LOAD query is in the running state, this value may change.
+ "outputRows": "A String", # Output only. Number of rows imported in a LOAD query. Note that while a LOAD query is in the running state, this value may change.
+ },
+ "materializedViewStatistics": { # Statistics of materialized views considered in a query job. # Output only. Statistics of materialized views of a query job.
+ "materializedView": [ # Materialized views considered for the query job. Only certain materialized views are used. For a detailed list, see the child message. If many materialized views are considered, then the list might be incomplete.
+ { # A materialized view considered for a query job.
+ "chosen": True or False, # Whether the materialized view is chosen for the query. A materialized view can be chosen to rewrite multiple parts of the same query. If a materialized view is chosen to rewrite any part of the query, then this field is true, even if the materialized view was not chosen to rewrite others parts.
+ "estimatedBytesSaved": "A String", # If present, specifies a best-effort estimation of the bytes saved by using the materialized view rather than its base tables.
+ "rejectedReason": "A String", # If present, specifies the reason why the materialized view was not chosen for the query.
+ "tableReference": { # The candidate materialized view.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ },
+ ],
+ },
+ "metadataCacheStatistics": { # Statistics for metadata caching in BigLake tables. # Output only. Statistics of metadata cache usage in a query for BigLake tables.
+ "tableMetadataCacheUsage": [ # Set for the Metadata caching eligible tables referenced in the query.
+ { # Table level detail on the usage of metadata caching. Only set for Metadata caching eligible tables referenced in the query.
+ "explanation": "A String", # Free form human-readable reason metadata caching was unused for the job.
+ "tableReference": { # Metadata caching eligible table referenced in the query.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ "tableType": "A String", # [Table type](/bigquery/docs/reference/rest/v2/tables#Table.FIELDS.type).
+ "unusedReason": "A String", # Reason for not using metadata caching for the table.
+ },
+ ],
+ },
+ "mlStatistics": { # Job statistics specific to a BigQuery ML training job. # Output only. Statistics of a BigQuery ML training job.
+ "hparamTrials": [ # Output only. Trials of a [hyperparameter tuning job](/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview) sorted by trial_id.
+ { # Training info of a trial in [hyperparameter tuning](/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview) models.
+ "endTimeMs": "A String", # Ending time of the trial.
+ "errorMessage": "A String", # Error message for FAILED and INFEASIBLE trial.
+ "evalLoss": 3.14, # Loss computed on the eval data at the end of trial.
+ "evaluationMetrics": { # Evaluation metrics of a model. These are either computed on all training data or just the eval data based on whether eval data was used during training. These are not present for imported models. # Evaluation metrics of this trial calculated on the test data. Empty in Job API.
+ "arimaForecastingMetrics": { # Model evaluation metrics for ARIMA forecasting models. # Populated for ARIMA models.
+ "arimaFittingMetrics": [ # Arima model fitting metrics.
+ { # ARIMA model fitting metrics.
+ "aic": 3.14, # AIC.
+ "logLikelihood": 3.14, # Log-likelihood.
+ "variance": 3.14, # Variance.
+ },
+ ],
+ "arimaSingleModelForecastingMetrics": [ # Repeated as there can be many metric sets (one for each model) in auto-arima and the large-scale case.
+ { # Model evaluation metrics for a single ARIMA forecasting model.
+ "arimaFittingMetrics": { # ARIMA model fitting metrics. # Arima fitting metrics.
+ "aic": 3.14, # AIC.
+ "logLikelihood": 3.14, # Log-likelihood.
+ "variance": 3.14, # Variance.
+ },
+ "hasDrift": True or False, # Is arima model fitted with drift or not. It is always false when d is not 1.
+ "hasHolidayEffect": True or False, # If true, holiday_effect is a part of time series decomposition result.
+ "hasSpikesAndDips": True or False, # If true, spikes_and_dips is a part of time series decomposition result.
+ "hasStepChanges": True or False, # If true, step_changes is a part of time series decomposition result.
+ "nonSeasonalOrder": { # Arima order, can be used for both non-seasonal and seasonal parts. # Non-seasonal order.
+ "d": "A String", # Order of the differencing part.
+ "p": "A String", # Order of the autoregressive part.
+ "q": "A String", # Order of the moving-average part.
+ },
+ "seasonalPeriods": [ # Seasonal periods. Repeated because multiple periods are supported for one time series.
+ "A String",
+ ],
+ "timeSeriesId": "A String", # The time_series_id value for this time series. It will be one of the unique values from the time_series_id_column specified during ARIMA model training. Only present when time_series_id_column training option was used.
+ "timeSeriesIds": [ # The tuple of time_series_ids identifying this time series. It will be one of the unique tuples of values present in the time_series_id_columns specified during ARIMA model training. Only present when time_series_id_columns training option was used and the order of values here are same as the order of time_series_id_columns.
+ "A String",
+ ],
+ },
+ ],
+ "hasDrift": [ # Whether Arima model fitted with drift or not. It is always false when d is not 1.
+ True or False,
+ ],
+ "nonSeasonalOrder": [ # Non-seasonal order.
+ { # Arima order, can be used for both non-seasonal and seasonal parts.
+ "d": "A String", # Order of the differencing part.
+ "p": "A String", # Order of the autoregressive part.
+ "q": "A String", # Order of the moving-average part.
+ },
+ ],
+ "seasonalPeriods": [ # Seasonal periods. Repeated because multiple periods are supported for one time series.
+ "A String",
+ ],
+ "timeSeriesId": [ # Id to differentiate different time series for the large-scale case.
+ "A String",
+ ],
+ },
+ "binaryClassificationMetrics": { # Evaluation metrics for binary classification/classifier models. # Populated for binary classification/classifier models.
+ "aggregateClassificationMetrics": { # Aggregate metrics for classification/classifier models. For multi-class models, the metrics are either macro-averaged or micro-averaged. When macro-averaged, the metrics are calculated for each label and then an unweighted average is taken of those values. When micro-averaged, the metric is calculated globally by counting the total number of correctly predicted rows. # Aggregate classification metrics.
+ "accuracy": 3.14, # Accuracy is the fraction of predictions given the correct label. For multiclass this is a micro-averaged metric.
+ "f1Score": 3.14, # The F1 score is an average of recall and precision. For multiclass this is a macro-averaged metric.
+ "logLoss": 3.14, # Logarithmic Loss. For multiclass this is a macro-averaged metric.
+ "precision": 3.14, # Precision is the fraction of actual positive predictions that had positive actual labels. For multiclass this is a macro-averaged metric treating each class as a binary classifier.
+ "recall": 3.14, # Recall is the fraction of actual positive labels that were given a positive prediction. For multiclass this is a macro-averaged metric.
+ "rocAuc": 3.14, # Area Under a ROC Curve. For multiclass this is a macro-averaged metric.
+ "threshold": 3.14, # Threshold at which the metrics are computed. For binary classification models this is the positive class threshold. For multi-class classfication models this is the confidence threshold.
+ },
+ "binaryConfusionMatrixList": [ # Binary confusion matrix at multiple thresholds.
+ { # Confusion matrix for binary classification models.
+ "accuracy": 3.14, # The fraction of predictions given the correct label.
+ "f1Score": 3.14, # The equally weighted average of recall and precision.
+ "falseNegatives": "A String", # Number of false samples predicted as false.
+ "falsePositives": "A String", # Number of false samples predicted as true.
+ "positiveClassThreshold": 3.14, # Threshold value used when computing each of the following metric.
+ "precision": 3.14, # The fraction of actual positive predictions that had positive actual labels.
+ "recall": 3.14, # The fraction of actual positive labels that were given a positive prediction.
+ "trueNegatives": "A String", # Number of true samples predicted as false.
+ "truePositives": "A String", # Number of true samples predicted as true.
+ },
+ ],
+ "negativeLabel": "A String", # Label representing the negative class.
+ "positiveLabel": "A String", # Label representing the positive class.
+ },
+ "clusteringMetrics": { # Evaluation metrics for clustering models. # Populated for clustering models.
+ "clusters": [ # Information for all clusters.
+ { # Message containing the information about one cluster.
+ "centroidId": "A String", # Centroid id.
+ "count": "A String", # Count of training data rows that were assigned to this cluster.
+ "featureValues": [ # Values of highly variant features for this cluster.
+ { # Representative value of a single feature within the cluster.
+ "categoricalValue": { # Representative value of a categorical feature. # The categorical feature value.
+ "categoryCounts": [ # Counts of all categories for the categorical feature. If there are more than ten categories, we return top ten (by count) and return one more CategoryCount with category "_OTHER_" and count as aggregate counts of remaining categories.
+ { # Represents the count of a single category within the cluster.
+ "category": "A String", # The name of category.
+ "count": "A String", # The count of training samples matching the category within the cluster.
+ },
+ ],
+ },
+ "featureColumn": "A String", # The feature column name.
+ "numericalValue": 3.14, # The numerical feature value. This is the centroid value for this feature.
+ },
+ ],
+ },
+ ],
+ "daviesBouldinIndex": 3.14, # Davies-Bouldin index.
+ "meanSquaredDistance": 3.14, # Mean of squared distances between each sample to its cluster centroid.
+ },
+ "dimensionalityReductionMetrics": { # Model evaluation metrics for dimensionality reduction models. # Evaluation metrics when the model is a dimensionality reduction model, which currently includes PCA.
+ "totalExplainedVarianceRatio": 3.14, # Total percentage of variance explained by the selected principal components.
+ },
+ "multiClassClassificationMetrics": { # Evaluation metrics for multi-class classification/classifier models. # Populated for multi-class classification/classifier models.
+ "aggregateClassificationMetrics": { # Aggregate metrics for classification/classifier models. For multi-class models, the metrics are either macro-averaged or micro-averaged. When macro-averaged, the metrics are calculated for each label and then an unweighted average is taken of those values. When micro-averaged, the metric is calculated globally by counting the total number of correctly predicted rows. # Aggregate classification metrics.
+ "accuracy": 3.14, # Accuracy is the fraction of predictions given the correct label. For multiclass this is a micro-averaged metric.
+ "f1Score": 3.14, # The F1 score is an average of recall and precision. For multiclass this is a macro-averaged metric.
+ "logLoss": 3.14, # Logarithmic Loss. For multiclass this is a macro-averaged metric.
+ "precision": 3.14, # Precision is the fraction of actual positive predictions that had positive actual labels. For multiclass this is a macro-averaged metric treating each class as a binary classifier.
+ "recall": 3.14, # Recall is the fraction of actual positive labels that were given a positive prediction. For multiclass this is a macro-averaged metric.
+ "rocAuc": 3.14, # Area Under a ROC Curve. For multiclass this is a macro-averaged metric.
+ "threshold": 3.14, # Threshold at which the metrics are computed. For binary classification models this is the positive class threshold. For multi-class classfication models this is the confidence threshold.
+ },
+ "confusionMatrixList": [ # Confusion matrix at different thresholds.
+ { # Confusion matrix for multi-class classification models.
+ "confidenceThreshold": 3.14, # Confidence threshold used when computing the entries of the confusion matrix.
+ "rows": [ # One row per actual label.
+ { # A single row in the confusion matrix.
+ "actualLabel": "A String", # The original label of this row.
+ "entries": [ # Info describing predicted label distribution.
+ { # A single entry in the confusion matrix.
+ "itemCount": "A String", # Number of items being predicted as this label.
+ "predictedLabel": "A String", # The predicted label. For confidence_threshold > 0, we will also add an entry indicating the number of items under the confidence threshold.
+ },
+ ],
+ },
+ ],
+ },
+ ],
+ },
+ "rankingMetrics": { # Evaluation metrics used by weighted-ALS models specified by feedback_type=implicit. # Populated for implicit feedback type matrix factorization models.
+ "averageRank": 3.14, # Determines the goodness of a ranking by computing the percentile rank from the predicted confidence and dividing it by the original rank.
+ "meanAveragePrecision": 3.14, # Calculates a precision per user for all the items by ranking them and then averages all the precisions across all the users.
+ "meanSquaredError": 3.14, # Similar to the mean squared error computed in regression and explicit recommendation models except instead of computing the rating directly, the output from evaluate is computed against a preference which is 1 or 0 depending on if the rating exists or not.
+ "normalizedDiscountedCumulativeGain": 3.14, # A metric to determine the goodness of a ranking calculated from the predicted confidence by comparing it to an ideal rank measured by the original ratings.
+ },
+ "regressionMetrics": { # Evaluation metrics for regression and explicit feedback type matrix factorization models. # Populated for regression models and explicit feedback type matrix factorization models.
+ "meanAbsoluteError": 3.14, # Mean absolute error.
+ "meanSquaredError": 3.14, # Mean squared error.
+ "meanSquaredLogError": 3.14, # Mean squared log error.
+ "medianAbsoluteError": 3.14, # Median absolute error.
+ "rSquared": 3.14, # R^2 score. This corresponds to r2_score in ML.EVALUATE.
+ },
+ },
+ "hparamTuningEvaluationMetrics": { # Evaluation metrics of a model. These are either computed on all training data or just the eval data based on whether eval data was used during training. These are not present for imported models. # Hyperparameter tuning evaluation metrics of this trial calculated on the eval data. Unlike evaluation_metrics, only the fields corresponding to the hparam_tuning_objectives are set.
+ "arimaForecastingMetrics": { # Model evaluation metrics for ARIMA forecasting models. # Populated for ARIMA models.
+ "arimaFittingMetrics": [ # Arima model fitting metrics.
+ { # ARIMA model fitting metrics.
+ "aic": 3.14, # AIC.
+ "logLikelihood": 3.14, # Log-likelihood.
+ "variance": 3.14, # Variance.
+ },
+ ],
+ "arimaSingleModelForecastingMetrics": [ # Repeated as there can be many metric sets (one for each model) in auto-arima and the large-scale case.
+ { # Model evaluation metrics for a single ARIMA forecasting model.
+ "arimaFittingMetrics": { # ARIMA model fitting metrics. # Arima fitting metrics.
+ "aic": 3.14, # AIC.
+ "logLikelihood": 3.14, # Log-likelihood.
+ "variance": 3.14, # Variance.
+ },
+ "hasDrift": True or False, # Is arima model fitted with drift or not. It is always false when d is not 1.
+ "hasHolidayEffect": True or False, # If true, holiday_effect is a part of time series decomposition result.
+ "hasSpikesAndDips": True or False, # If true, spikes_and_dips is a part of time series decomposition result.
+ "hasStepChanges": True or False, # If true, step_changes is a part of time series decomposition result.
+ "nonSeasonalOrder": { # Arima order, can be used for both non-seasonal and seasonal parts. # Non-seasonal order.
+ "d": "A String", # Order of the differencing part.
+ "p": "A String", # Order of the autoregressive part.
+ "q": "A String", # Order of the moving-average part.
+ },
+ "seasonalPeriods": [ # Seasonal periods. Repeated because multiple periods are supported for one time series.
+ "A String",
+ ],
+ "timeSeriesId": "A String", # The time_series_id value for this time series. It will be one of the unique values from the time_series_id_column specified during ARIMA model training. Only present when time_series_id_column training option was used.
+ "timeSeriesIds": [ # The tuple of time_series_ids identifying this time series. It will be one of the unique tuples of values present in the time_series_id_columns specified during ARIMA model training. Only present when time_series_id_columns training option was used and the order of values here are same as the order of time_series_id_columns.
+ "A String",
+ ],
+ },
+ ],
+ "hasDrift": [ # Whether Arima model fitted with drift or not. It is always false when d is not 1.
+ True or False,
+ ],
+ "nonSeasonalOrder": [ # Non-seasonal order.
+ { # Arima order, can be used for both non-seasonal and seasonal parts.
+ "d": "A String", # Order of the differencing part.
+ "p": "A String", # Order of the autoregressive part.
+ "q": "A String", # Order of the moving-average part.
+ },
+ ],
+ "seasonalPeriods": [ # Seasonal periods. Repeated because multiple periods are supported for one time series.
+ "A String",
+ ],
+ "timeSeriesId": [ # Id to differentiate different time series for the large-scale case.
+ "A String",
+ ],
+ },
+ "binaryClassificationMetrics": { # Evaluation metrics for binary classification/classifier models. # Populated for binary classification/classifier models.
+ "aggregateClassificationMetrics": { # Aggregate metrics for classification/classifier models. For multi-class models, the metrics are either macro-averaged or micro-averaged. When macro-averaged, the metrics are calculated for each label and then an unweighted average is taken of those values. When micro-averaged, the metric is calculated globally by counting the total number of correctly predicted rows. # Aggregate classification metrics.
+ "accuracy": 3.14, # Accuracy is the fraction of predictions given the correct label. For multiclass this is a micro-averaged metric.
+ "f1Score": 3.14, # The F1 score is an average of recall and precision. For multiclass this is a macro-averaged metric.
+ "logLoss": 3.14, # Logarithmic Loss. For multiclass this is a macro-averaged metric.
+ "precision": 3.14, # Precision is the fraction of actual positive predictions that had positive actual labels. For multiclass this is a macro-averaged metric treating each class as a binary classifier.
+ "recall": 3.14, # Recall is the fraction of actual positive labels that were given a positive prediction. For multiclass this is a macro-averaged metric.
+ "rocAuc": 3.14, # Area Under a ROC Curve. For multiclass this is a macro-averaged metric.
+ "threshold": 3.14, # Threshold at which the metrics are computed. For binary classification models this is the positive class threshold. For multi-class classfication models this is the confidence threshold.
+ },
+ "binaryConfusionMatrixList": [ # Binary confusion matrix at multiple thresholds.
+ { # Confusion matrix for binary classification models.
+ "accuracy": 3.14, # The fraction of predictions given the correct label.
+ "f1Score": 3.14, # The equally weighted average of recall and precision.
+ "falseNegatives": "A String", # Number of false samples predicted as false.
+ "falsePositives": "A String", # Number of false samples predicted as true.
+ "positiveClassThreshold": 3.14, # Threshold value used when computing each of the following metric.
+ "precision": 3.14, # The fraction of actual positive predictions that had positive actual labels.
+ "recall": 3.14, # The fraction of actual positive labels that were given a positive prediction.
+ "trueNegatives": "A String", # Number of true samples predicted as false.
+ "truePositives": "A String", # Number of true samples predicted as true.
+ },
+ ],
+ "negativeLabel": "A String", # Label representing the negative class.
+ "positiveLabel": "A String", # Label representing the positive class.
+ },
+ "clusteringMetrics": { # Evaluation metrics for clustering models. # Populated for clustering models.
+ "clusters": [ # Information for all clusters.
+ { # Message containing the information about one cluster.
+ "centroidId": "A String", # Centroid id.
+ "count": "A String", # Count of training data rows that were assigned to this cluster.
+ "featureValues": [ # Values of highly variant features for this cluster.
+ { # Representative value of a single feature within the cluster.
+ "categoricalValue": { # Representative value of a categorical feature. # The categorical feature value.
+ "categoryCounts": [ # Counts of all categories for the categorical feature. If there are more than ten categories, we return top ten (by count) and return one more CategoryCount with category "_OTHER_" and count as aggregate counts of remaining categories.
+ { # Represents the count of a single category within the cluster.
+ "category": "A String", # The name of category.
+ "count": "A String", # The count of training samples matching the category within the cluster.
+ },
+ ],
+ },
+ "featureColumn": "A String", # The feature column name.
+ "numericalValue": 3.14, # The numerical feature value. This is the centroid value for this feature.
+ },
+ ],
+ },
+ ],
+ "daviesBouldinIndex": 3.14, # Davies-Bouldin index.
+ "meanSquaredDistance": 3.14, # Mean of squared distances between each sample to its cluster centroid.
+ },
+ "dimensionalityReductionMetrics": { # Model evaluation metrics for dimensionality reduction models. # Evaluation metrics when the model is a dimensionality reduction model, which currently includes PCA.
+ "totalExplainedVarianceRatio": 3.14, # Total percentage of variance explained by the selected principal components.
+ },
+ "multiClassClassificationMetrics": { # Evaluation metrics for multi-class classification/classifier models. # Populated for multi-class classification/classifier models.
+ "aggregateClassificationMetrics": { # Aggregate metrics for classification/classifier models. For multi-class models, the metrics are either macro-averaged or micro-averaged. When macro-averaged, the metrics are calculated for each label and then an unweighted average is taken of those values. When micro-averaged, the metric is calculated globally by counting the total number of correctly predicted rows. # Aggregate classification metrics.
+ "accuracy": 3.14, # Accuracy is the fraction of predictions given the correct label. For multiclass this is a micro-averaged metric.
+ "f1Score": 3.14, # The F1 score is an average of recall and precision. For multiclass this is a macro-averaged metric.
+ "logLoss": 3.14, # Logarithmic Loss. For multiclass this is a macro-averaged metric.
+ "precision": 3.14, # Precision is the fraction of actual positive predictions that had positive actual labels. For multiclass this is a macro-averaged metric treating each class as a binary classifier.
+ "recall": 3.14, # Recall is the fraction of actual positive labels that were given a positive prediction. For multiclass this is a macro-averaged metric.
+ "rocAuc": 3.14, # Area Under a ROC Curve. For multiclass this is a macro-averaged metric.
+ "threshold": 3.14, # Threshold at which the metrics are computed. For binary classification models this is the positive class threshold. For multi-class classfication models this is the confidence threshold.
+ },
+ "confusionMatrixList": [ # Confusion matrix at different thresholds.
+ { # Confusion matrix for multi-class classification models.
+ "confidenceThreshold": 3.14, # Confidence threshold used when computing the entries of the confusion matrix.
+ "rows": [ # One row per actual label.
+ { # A single row in the confusion matrix.
+ "actualLabel": "A String", # The original label of this row.
+ "entries": [ # Info describing predicted label distribution.
+ { # A single entry in the confusion matrix.
+ "itemCount": "A String", # Number of items being predicted as this label.
+ "predictedLabel": "A String", # The predicted label. For confidence_threshold > 0, we will also add an entry indicating the number of items under the confidence threshold.
+ },
+ ],
+ },
+ ],
+ },
+ ],
+ },
+ "rankingMetrics": { # Evaluation metrics used by weighted-ALS models specified by feedback_type=implicit. # Populated for implicit feedback type matrix factorization models.
+ "averageRank": 3.14, # Determines the goodness of a ranking by computing the percentile rank from the predicted confidence and dividing it by the original rank.
+ "meanAveragePrecision": 3.14, # Calculates a precision per user for all the items by ranking them and then averages all the precisions across all the users.
+ "meanSquaredError": 3.14, # Similar to the mean squared error computed in regression and explicit recommendation models except instead of computing the rating directly, the output from evaluate is computed against a preference which is 1 or 0 depending on if the rating exists or not.
+ "normalizedDiscountedCumulativeGain": 3.14, # A metric to determine the goodness of a ranking calculated from the predicted confidence by comparing it to an ideal rank measured by the original ratings.
+ },
+ "regressionMetrics": { # Evaluation metrics for regression and explicit feedback type matrix factorization models. # Populated for regression models and explicit feedback type matrix factorization models.
+ "meanAbsoluteError": 3.14, # Mean absolute error.
+ "meanSquaredError": 3.14, # Mean squared error.
+ "meanSquaredLogError": 3.14, # Mean squared log error.
+ "medianAbsoluteError": 3.14, # Median absolute error.
+ "rSquared": 3.14, # R^2 score. This corresponds to r2_score in ML.EVALUATE.
+ },
+ },
+ "hparams": { # Options used in model training. # The hyperprameters selected for this trial.
+ "activationFn": "A String", # Activation function of the neural nets.
+ "adjustStepChanges": True or False, # If true, detect step changes and make data adjustment in the input time series.
+ "approxGlobalFeatureContrib": True or False, # Whether to use approximate feature contribution method in XGBoost model explanation for global explain.
+ "autoArima": True or False, # Whether to enable auto ARIMA or not.
+ "autoArimaMaxOrder": "A String", # The max value of the sum of non-seasonal p and q.
+ "autoArimaMinOrder": "A String", # The min value of the sum of non-seasonal p and q.
+ "autoClassWeights": True or False, # Whether to calculate class weights automatically based on the popularity of each label.
+ "batchSize": "A String", # Batch size for dnn models.
+ "boosterType": "A String", # Booster type for boosted tree models.
+ "budgetHours": 3.14, # Budget in hours for AutoML training.
+ "calculatePValues": True or False, # Whether or not p-value test should be computed for this model. Only available for linear and logistic regression models.
+ "categoryEncodingMethod": "A String", # Categorical feature encoding method.
+ "cleanSpikesAndDips": True or False, # If true, clean spikes and dips in the input time series.
+ "colorSpace": "A String", # Enums for color space, used for processing images in Object Table. See more details at https://www.tensorflow.org/io/tutorials/colorspace.
+ "colsampleBylevel": 3.14, # Subsample ratio of columns for each level for boosted tree models.
+ "colsampleBynode": 3.14, # Subsample ratio of columns for each node(split) for boosted tree models.
+ "colsampleBytree": 3.14, # Subsample ratio of columns when constructing each tree for boosted tree models.
+ "dartNormalizeType": "A String", # Type of normalization algorithm for boosted tree models using dart booster.
+ "dataFrequency": "A String", # The data frequency of a time series.
+ "dataSplitColumn": "A String", # The column to split data with. This column won't be used as a feature. 1. When data_split_method is CUSTOM, the corresponding column should be boolean. The rows with true value tag are eval data, and the false are training data. 2. When data_split_method is SEQ, the first DATA_SPLIT_EVAL_FRACTION rows (from smallest to largest) in the corresponding column are used as training data, and the rest are eval data. It respects the order in Orderable data types: https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types#data-type-properties
+ "dataSplitEvalFraction": 3.14, # The fraction of evaluation data over the whole input data. The rest of data will be used as training data. The format should be double. Accurate to two decimal places. Default value is 0.2.
+ "dataSplitMethod": "A String", # The data split type for training and evaluation, e.g. RANDOM.
+ "decomposeTimeSeries": True or False, # If true, perform decompose time series and save the results.
+ "distanceType": "A String", # Distance type for clustering models.
+ "dropout": 3.14, # Dropout probability for dnn models.
+ "earlyStop": True or False, # Whether to stop early when the loss doesn't improve significantly any more (compared to min_relative_progress). Used only for iterative training algorithms.
+ "enableGlobalExplain": True or False, # If true, enable global explanation during training.
+ "feedbackType": "A String", # Feedback type that specifies which algorithm to run for matrix factorization.
+ "fitIntercept": True or False, # Whether the model should include intercept during model training.
+ "hiddenUnits": [ # Hidden units for dnn models.
+ "A String",
+ ],
+ "holidayRegion": "A String", # The geographical region based on which the holidays are considered in time series modeling. If a valid value is specified, then holiday effects modeling is enabled.
+ "holidayRegions": [ # A list of geographical regions that are used for time series modeling.
+ "A String",
+ ],
+ "horizon": "A String", # The number of periods ahead that need to be forecasted.
+ "hparamTuningObjectives": [ # The target evaluation metrics to optimize the hyperparameters for.
+ "A String",
+ ],
+ "includeDrift": True or False, # Include drift when fitting an ARIMA model.
+ "initialLearnRate": 3.14, # Specifies the initial learning rate for the line search learn rate strategy.
+ "inputLabelColumns": [ # Name of input label columns in training data.
+ "A String",
+ ],
+ "instanceWeightColumn": "A String", # Name of the instance weight column for training data. This column isn't be used as a feature.
+ "integratedGradientsNumSteps": "A String", # Number of integral steps for the integrated gradients explain method.
+ "itemColumn": "A String", # Item column specified for matrix factorization models.
+ "kmeansInitializationColumn": "A String", # The column used to provide the initial centroids for kmeans algorithm when kmeans_initialization_method is CUSTOM.
+ "kmeansInitializationMethod": "A String", # The method used to initialize the centroids for kmeans algorithm.
+ "l1RegActivation": 3.14, # L1 regularization coefficient to activations.
+ "l1Regularization": 3.14, # L1 regularization coefficient.
+ "l2Regularization": 3.14, # L2 regularization coefficient.
+ "labelClassWeights": { # Weights associated with each label class, for rebalancing the training data. Only applicable for classification models.
+ "a_key": 3.14,
+ },
+ "learnRate": 3.14, # Learning rate in training. Used only for iterative training algorithms.
+ "learnRateStrategy": "A String", # The strategy to determine learn rate for the current iteration.
+ "lossType": "A String", # Type of loss function used during training run.
+ "maxIterations": "A String", # The maximum number of iterations in training. Used only for iterative training algorithms.
+ "maxParallelTrials": "A String", # Maximum number of trials to run in parallel.
+ "maxTimeSeriesLength": "A String", # The maximum number of time points in a time series that can be used in modeling the trend component of the time series. Don't use this option with the `timeSeriesLengthFraction` or `minTimeSeriesLength` options.
+ "maxTreeDepth": "A String", # Maximum depth of a tree for boosted tree models.
+ "minRelativeProgress": 3.14, # When early_stop is true, stops training when accuracy improvement is less than 'min_relative_progress'. Used only for iterative training algorithms.
+ "minSplitLoss": 3.14, # Minimum split loss for boosted tree models.
+ "minTimeSeriesLength": "A String", # The minimum number of time points in a time series that are used in modeling the trend component of the time series. If you use this option you must also set the `timeSeriesLengthFraction` option. This training option ensures that enough time points are available when you use `timeSeriesLengthFraction` in trend modeling. This is particularly important when forecasting multiple time series in a single query using `timeSeriesIdColumn`. If the total number of time points is less than the `minTimeSeriesLength` value, then the query uses all available time points.
+ "minTreeChildWeight": "A String", # Minimum sum of instance weight needed in a child for boosted tree models.
+ "modelRegistry": "A String", # The model registry.
+ "modelUri": "A String", # Google Cloud Storage URI from which the model was imported. Only applicable for imported models.
+ "nonSeasonalOrder": { # Arima order, can be used for both non-seasonal and seasonal parts. # A specification of the non-seasonal part of the ARIMA model: the three components (p, d, q) are the AR order, the degree of differencing, and the MA order.
+ "d": "A String", # Order of the differencing part.
+ "p": "A String", # Order of the autoregressive part.
+ "q": "A String", # Order of the moving-average part.
+ },
+ "numClusters": "A String", # Number of clusters for clustering models.
+ "numFactors": "A String", # Num factors specified for matrix factorization models.
+ "numParallelTree": "A String", # Number of parallel trees constructed during each iteration for boosted tree models.
+ "numPrincipalComponents": "A String", # Number of principal components to keep in the PCA model. Must be <= the number of features.
+ "numTrials": "A String", # Number of trials to run this hyperparameter tuning job.
+ "optimizationStrategy": "A String", # Optimization strategy for training linear regression models.
+ "optimizer": "A String", # Optimizer used for training the neural nets.
+ "pcaExplainedVarianceRatio": 3.14, # The minimum ratio of cumulative explained variance that needs to be given by the PCA model.
+ "pcaSolver": "A String", # The solver for PCA.
+ "sampledShapleyNumPaths": "A String", # Number of paths for the sampled Shapley explain method.
+ "scaleFeatures": True or False, # If true, scale the feature values by dividing the feature standard deviation. Currently only apply to PCA.
+ "standardizeFeatures": True or False, # Whether to standardize numerical features. Default to true.
+ "subsample": 3.14, # Subsample fraction of the training data to grow tree to prevent overfitting for boosted tree models.
+ "tfVersion": "A String", # Based on the selected TF version, the corresponding docker image is used to train external models.
+ "timeSeriesDataColumn": "A String", # Column to be designated as time series data for ARIMA model.
+ "timeSeriesIdColumn": "A String", # The time series id column that was used during ARIMA model training.
+ "timeSeriesIdColumns": [ # The time series id columns that were used during ARIMA model training.
+ "A String",
+ ],
+ "timeSeriesLengthFraction": 3.14, # The fraction of the interpolated length of the time series that's used to model the time series trend component. All of the time points of the time series are used to model the non-trend component. This training option accelerates modeling training without sacrificing much forecasting accuracy. You can use this option with `minTimeSeriesLength` but not with `maxTimeSeriesLength`.
+ "timeSeriesTimestampColumn": "A String", # Column to be designated as time series timestamp for ARIMA model.
+ "treeMethod": "A String", # Tree construction algorithm for boosted tree models.
+ "trendSmoothingWindowSize": "A String", # Smoothing window size for the trend component. When a positive value is specified, a center moving average smoothing is applied on the history trend. When the smoothing window is out of the boundary at the beginning or the end of the trend, the first element or the last element is padded to fill the smoothing window before the average is applied.
+ "userColumn": "A String", # User column specified for matrix factorization models.
+ "vertexAiModelVersionAliases": [ # The version aliases to apply in Vertex AI model registry. Always overwrite if the version aliases exists in a existing model.
+ "A String",
+ ],
+ "walsAlpha": 3.14, # Hyperparameter for matrix factoration when implicit feedback type is specified.
+ "warmStart": True or False, # Whether to train a model from the last checkpoint.
+ "xgboostVersion": "A String", # User-selected XGBoost versions for training of XGBoost models.
+ },
+ "startTimeMs": "A String", # Starting time of the trial.
+ "status": "A String", # The status of the trial.
+ "trainingLoss": 3.14, # Loss computed on the training data at the end of trial.
+ "trialId": "A String", # 1-based index of the trial.
+ },
+ ],
+ "iterationResults": [ # Results for all completed iterations. Empty for [hyperparameter tuning jobs](/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview).
+ { # Information about a single iteration of the training run.
+ "arimaResult": { # (Auto-)arima fitting result. Wrap everything in ArimaResult for easier refactoring if we want to use model-specific iteration results. # Arima result.
+ "arimaModelInfo": [ # This message is repeated because there are multiple arima models fitted in auto-arima. For non-auto-arima model, its size is one.
+ { # Arima model information.
+ "arimaCoefficients": { # Arima coefficients. # Arima coefficients.
+ "autoRegressiveCoefficients": [ # Auto-regressive coefficients, an array of double.
+ 3.14,
+ ],
+ "interceptCoefficient": 3.14, # Intercept coefficient, just a double not an array.
+ "movingAverageCoefficients": [ # Moving-average coefficients, an array of double.
+ 3.14,
+ ],
+ },
+ "arimaFittingMetrics": { # ARIMA model fitting metrics. # Arima fitting metrics.
+ "aic": 3.14, # AIC.
+ "logLikelihood": 3.14, # Log-likelihood.
+ "variance": 3.14, # Variance.
+ },
+ "hasDrift": True or False, # Whether Arima model fitted with drift or not. It is always false when d is not 1.
+ "hasHolidayEffect": True or False, # If true, holiday_effect is a part of time series decomposition result.
+ "hasSpikesAndDips": True or False, # If true, spikes_and_dips is a part of time series decomposition result.
+ "hasStepChanges": True or False, # If true, step_changes is a part of time series decomposition result.
+ "nonSeasonalOrder": { # Arima order, can be used for both non-seasonal and seasonal parts. # Non-seasonal order.
+ "d": "A String", # Order of the differencing part.
+ "p": "A String", # Order of the autoregressive part.
+ "q": "A String", # Order of the moving-average part.
+ },
+ "seasonalPeriods": [ # Seasonal periods. Repeated because multiple periods are supported for one time series.
+ "A String",
+ ],
+ "timeSeriesId": "A String", # The time_series_id value for this time series. It will be one of the unique values from the time_series_id_column specified during ARIMA model training. Only present when time_series_id_column training option was used.
+ "timeSeriesIds": [ # The tuple of time_series_ids identifying this time series. It will be one of the unique tuples of values present in the time_series_id_columns specified during ARIMA model training. Only present when time_series_id_columns training option was used and the order of values here are same as the order of time_series_id_columns.
+ "A String",
+ ],
+ },
+ ],
+ "seasonalPeriods": [ # Seasonal periods. Repeated because multiple periods are supported for one time series.
+ "A String",
+ ],
+ },
+ "clusterInfos": [ # Information about top clusters for clustering models.
+ { # Information about a single cluster for clustering model.
+ "centroidId": "A String", # Centroid id.
+ "clusterRadius": 3.14, # Cluster radius, the average distance from centroid to each point assigned to the cluster.
+ "clusterSize": "A String", # Cluster size, the total number of points assigned to the cluster.
+ },
+ ],
"durationMs": "A String", # Time taken to run the iteration in milliseconds.
"evalLoss": 3.14, # Loss computed on the eval data at the end of iteration.
"index": 42, # Index of the iteration, 0 based.
"learnRate": 3.14, # Learn rate used for this iteration.
+ "principalComponentInfos": [ # The information of the principal components.
+ { # Principal component infos, used only for eigen decomposition based models, e.g., PCA. Ordered by explained_variance in the descending order.
+ "cumulativeExplainedVarianceRatio": 3.14, # The explained_variance is pre-ordered in the descending order to compute the cumulative explained variance ratio.
+ "explainedVariance": 3.14, # Explained variance by this principal component, which is simply the eigenvalue.
+ "explainedVarianceRatio": 3.14, # Explained_variance over the total explained variance.
+ "principalComponentId": "A String", # Id of the principal component.
+ },
+ ],
"trainingLoss": 3.14, # Loss computed on the training data at the end of iteration.
},
],
- "maxIterations": "A String", # Maximum number of iterations specified as max_iterations in the 'CREATE MODEL' query. The actual number of iterations may be less than this number due to early stop.
+ "maxIterations": "A String", # Output only. Maximum number of iterations specified as max_iterations in the 'CREATE MODEL' query. The actual number of iterations may be less than this number due to early stop.
+ "modelType": "A String", # Output only. The type of the model that is being trained.
+ "trainingType": "A String", # Output only. Training type of the job.
},
- "modelTraining": { # [Output only, Beta] Information about create model query job progress.
- "currentIteration": 42, # [Output-only, Beta] Index of current ML training iteration. Updated during create model query job to show job progress.
- "expectedTotalIterations": "A String", # [Output-only, Beta] Expected number of iterations for the create model query job specified as num_iterations in the input query. The actual total number of iterations may be less than this number due to early stop.
+ "modelTraining": { # Deprecated.
+ "currentIteration": 42, # Deprecated.
+ "expectedTotalIterations": "A String", # Deprecated.
},
- "modelTrainingCurrentIteration": 42, # [Output only, Beta] Deprecated; do not use.
- "modelTrainingExpectedTotalIteration": "A String", # [Output only, Beta] Deprecated; do not use.
- "numDmlAffectedRows": "A String", # [Output only] The number of rows affected by a DML statement. Present only for DML statements INSERT, UPDATE or DELETE.
- "queryPlan": [ # [Output only] Describes execution plan for the query.
- {
+ "modelTrainingCurrentIteration": 42, # Deprecated.
+ "modelTrainingExpectedTotalIteration": "A String", # Deprecated.
+ "numDmlAffectedRows": "A String", # Output only. The number of rows affected by a DML statement. Present only for DML statements INSERT, UPDATE or DELETE.
+ "performanceInsights": { # Performance insights for the job. # Output only. Performance insights.
+ "avgPreviousExecutionMs": "A String", # Output only. Average execution ms of previous runs. Indicates the job ran slow compared to previous executions. To find previous executions, use INFORMATION_SCHEMA tables and filter jobs with same query hash.
+ "stagePerformanceChangeInsights": [ # Output only. Query stage performance insights compared to previous runs, for diagnosing performance regression.
+ { # Performance insights compared to the previous executions for a specific stage.
+ "inputDataChange": { # Details about the input data change insight. # Output only. Input data change insight of the query stage.
+ "recordsReadDiffPercentage": 3.14, # Output only. Records read difference percentage compared to a previous run.
+ },
+ "stageId": "A String", # Output only. The stage id that the insight mapped to.
+ },
+ ],
+ "stagePerformanceStandaloneInsights": [ # Output only. Standalone query stage performance insights, for exploring potential improvements.
+ { # Standalone performance insights for a specific stage.
+ "biEngineReasons": [ # Output only. If present, the stage had the following reasons for being disqualified from BI Engine execution.
+ { # Reason why BI Engine didn't accelerate the query (or sub-query).
+ "code": "A String", # Output only. High-level BI Engine reason for partial or disabled acceleration
+ "message": "A String", # Output only. Free form human-readable reason for partial or disabled acceleration.
+ },
+ ],
+ "highCardinalityJoins": [ # Output only. High cardinality joins in the stage.
+ { # High cardinality join detailed information.
+ "leftRows": "A String", # Output only. Count of left input rows.
+ "outputRows": "A String", # Output only. Count of the output rows.
+ "rightRows": "A String", # Output only. Count of right input rows.
+ "stepIndex": 42, # Output only. The index of the join operator in the ExplainQueryStep lists.
+ },
+ ],
+ "insufficientShuffleQuota": True or False, # Output only. True if the stage has insufficient shuffle quota.
+ "slotContention": True or False, # Output only. True if the stage has a slot contention issue.
+ "stageId": "A String", # Output only. The stage id that the insight mapped to.
+ },
+ ],
+ },
+ "queryInfo": { # Query optimization information for a QUERY job. # Output only. Query optimization information for a QUERY job.
+ "optimizationDetails": { # Output only. Information about query optimizations.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "queryPlan": [ # Output only. Describes execution plan for the query.
+ { # A single stage of query execution.
"completedParallelInputs": "A String", # Number of parallel input segments completed.
+ "computeMode": "A String", # Output only. Compute mode for this stage.
"computeMsAvg": "A String", # Milliseconds the average shard spent on CPU-bound tasks.
"computeMsMax": "A String", # Milliseconds the slowest shard spent on CPU-bound tasks.
"computeRatioAvg": 3.14, # Relative amount of time the average shard spent on CPU-bound tasks.
"computeRatioMax": 3.14, # Relative amount of time the slowest shard spent on CPU-bound tasks.
- "endMs": "A String", # Stage end time represented as milliseconds since epoch.
- "id": "A String", # Unique ID for stage within plan.
+ "endMs": "A String", # Stage end time represented as milliseconds since the epoch.
+ "id": "A String", # Unique ID for the stage within the plan.
"inputStages": [ # IDs for stages that are inputs to this stage.
"A String",
],
- "name": "A String", # Human-readable name for stage.
- "parallelInputs": "A String", # Number of parallel input segments to be processed.
+ "name": "A String", # Human-readable name for the stage.
+ "parallelInputs": "A String", # Number of parallel input segments to be processed
"readMsAvg": "A String", # Milliseconds the average shard spent reading input.
"readMsMax": "A String", # Milliseconds the slowest shard spent reading input.
"readRatioAvg": 3.14, # Relative amount of time the average shard spent reading input.
@@ -616,12 +1238,12 @@ Method Details
"shuffleOutputBytes": "A String", # Total number of bytes written to shuffle.
"shuffleOutputBytesSpilled": "A String", # Total number of bytes written to shuffle and spilled to disk.
"slotMs": "A String", # Slot-milliseconds used by the stage.
- "startMs": "A String", # Stage start time represented as milliseconds since epoch.
- "status": "A String", # Current status for the stage.
+ "startMs": "A String", # Stage start time represented as milliseconds since the epoch.
+ "status": "A String", # Current status for this stage.
"steps": [ # List of operations within the stage in dependency order (approximately chronological).
- {
+ { # An operation within a stage.
"kind": "A String", # Machine-readable operation type.
- "substeps": [ # Human-readable stage descriptions.
+ "substeps": [ # Human-readable description of the step(s).
"A String",
],
},
@@ -636,186 +1258,203 @@ Method Details
"writeRatioMax": 3.14, # Relative amount of time the slowest shard spent on writing output.
},
],
- "referencedRoutines": [ # [Output only] Referenced routines (persistent user-defined functions and stored procedures) for the job.
- {
+ "referencedRoutines": [ # Output only. Referenced routines for the job.
+ { # Id path of a routine.
"datasetId": "A String", # Required. The ID of the dataset containing this routine.
"projectId": "A String", # Required. The ID of the project containing this routine.
"routineId": "A String", # Required. The ID of the routine. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 256 characters.
},
],
- "referencedTables": [ # [Output only] Referenced tables for the job. Queries that reference more than 50 tables will not have a complete list.
+ "referencedTables": [ # Output only. Referenced tables for the job. Queries that reference more than 50 tables will not have a complete list.
{
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
],
- "reservationUsage": [ # [Output only] Job resource usage breakdown by reservation.
- {
- "name": "A String", # [Output only] Reservation name or "unreserved" for on-demand resources usage.
- "slotMs": "A String", # [Output only] Slot-milliseconds the job spent in the given reservation.
+ "reservationUsage": [ # Output only. Job resource usage breakdown by reservation. This field reported misleading information and will no longer be populated.
+ { # Job resource usage breakdown by reservation.
+ "name": "A String", # Reservation name or "unreserved" for on-demand resources usage.
+ "slotMs": "A String", # Total slot milliseconds used by the reservation for a particular job.
},
],
- "schema": { # [Output only] The schema of the results. Present only for successful dry run of non-legacy SQL queries.
+ "schema": { # Schema of a table # Output only. The schema of the results. Present only for successful dry run of non-legacy SQL queries.
"fields": [ # Describes the fields in a table.
- {
- "categories": { # [Optional] The categories attached to this field, used for field-level access control.
- "names": [ # A list of category resource names. For example, "projects/1/taxonomies/2/categories/3". At most 5 categories are allowed.
+ { # A field in TableSchema
+ "categories": { # Deprecated.
+ "names": [ # Deprecated.
"A String",
],
},
- "collation": "A String", # Optional. Collation specification of the field. It only can be set on string type field.
- "defaultValueExpression": "A String", # Optional. A SQL expression to specify the default value for this field. It can only be set for top level fields (columns). You can use struct or array expression to specify default value for the entire struct or array. The valid SQL expressions are: - Literals for all data types, including STRUCT and ARRAY. - Following functions: - CURRENT_TIMESTAMP - CURRENT_TIME - CURRENT_DATE - CURRENT_DATETIME - GENERATE_UUID - RAND - SESSION_USER - ST_GEOGPOINT - Struct or array composed with the above allowed functions, for example, [CURRENT_DATE(), DATE '2020-01-01']
- "description": "A String", # [Optional] The field description. The maximum length is 1,024 characters.
- "fields": [ # [Optional] Describes the nested schema fields if the type property is set to RECORD.
+ "collation": "A String", # Optional. Field collation can be set only when the type of field is STRING. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.
+ "defaultValueExpression": "A String", # Optional. A SQL expression to specify the [default value] (https://cloud.google.com/bigquery/docs/default-values) for this field.
+ "description": "A String", # Optional. The field description. The maximum length is 1,024 characters.
+ "fields": [ # Optional. Describes the nested schema fields if the type property is set to RECORD.
# Object with schema name: TableFieldSchema
],
- "maxLength": "A String", # [Optional] Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
- "mode": "A String", # [Optional] The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
- "name": "A String", # [Required] The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
- "policyTags": {
- "names": [ # A list of category resource names. For example, "projects/1/location/eu/taxonomies/2/policyTags/3". At most 1 policy tag is allowed.
+ "maxLength": "A String", # Optional. Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
+ "mode": "A String", # Optional. The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
+ "name": "A String", # Required. The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
+ "policyTags": { # Optional. The policy tags attached to this field, used for field-level access control. If not set, defaults to empty policy_tags.
+ "names": [ # A list of policy tag resource names. For example, "projects/1/locations/eu/taxonomies/2/policyTags/3". At most 1 policy tag is currently allowed.
"A String",
],
},
- "precision": "A String", # [Optional] Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: - Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] - Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: - If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. - If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): - If type = "NUMERIC": 1 ≤ precision ≤ 29. - If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
- "rangeElementType": { # Optional. The subtype of the RANGE, if the type of this field is RANGE. If the type is RANGE, this field is required. Possible values for the field element type of a RANGE include: - DATE - DATETIME - TIMESTAMP
- "type": "A String", # The field element type of a RANGE
+ "precision": "A String", # Optional. Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: * Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] * Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: * If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. * If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): * If type = "NUMERIC": 1 ≤ precision ≤ 29. * If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
+ "rangeElementType": { # Represents the type of a field element.
+ "type": "A String", # Required. The type of a field element. See TableFieldSchema.type.
},
- "roundingMode": "A String", # Optional. Rounding Mode specification of the field. It only can be set on NUMERIC or BIGNUMERIC type fields.
- "scale": "A String", # [Optional] See documentation for precision.
- "type": "A String", # [Required] The field data type. Possible values include STRING, BYTES, INTEGER, INT64 (same as INTEGER), FLOAT, FLOAT64 (same as FLOAT), NUMERIC, BIGNUMERIC, BOOLEAN, BOOL (same as BOOLEAN), TIMESTAMP, DATE, TIME, DATETIME, INTERVAL, RECORD (where RECORD indicates that the field contains a nested schema) or STRUCT (same as RECORD).
+ "roundingMode": "A String", # Optional. Specifies the rounding mode to be used when storing values of NUMERIC and BIGNUMERIC type.
+ "scale": "A String", # Optional. See documentation for precision.
+ "type": "A String", # Required. The field data type. Possible values include: * STRING * BYTES * INTEGER (or INT64) * FLOAT (or FLOAT64) * BOOLEAN (or BOOL) * TIMESTAMP * DATE * TIME * DATETIME * GEOGRAPHY * NUMERIC * BIGNUMERIC * JSON * RECORD (or STRUCT) Use of RECORD/STRUCT indicates that the field contains a nested schema.
},
],
},
- "searchStatistics": { # [Output only] Search query specific statistics.
- "indexUnusedReasons": [ # When index_usage_mode is UNUSED or PARTIALLY_USED, this field explains why index was not used in all or part of the search query. If index_usage_mode is FULLLY_USED, this field is not populated.
- {
- "baseTable": { # [Output-only] Specifies the base table involved in the reason that no search index was used.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "searchStatistics": { # Statistics for a search query. Populated as part of JobStatistics2. # Output only. Search query specific statistics.
+ "indexUnusedReasons": [ # When `indexUsageMode` is `UNUSED` or `PARTIALLY_USED`, this field explains why indexes were not used in all or part of the search query. If `indexUsageMode` is `FULLY_USED`, this field is not populated.
+ { # Reason about why no search index was used in the search query (or sub-query).
+ "baseTable": { # Specifies the base table involved in the reason that no search index was used.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
- "code": "$(reason.code)", # [Output-only] Specifies the high-level reason for the scenario when no search index was used.
- "indexName": "$(reason.index_name)", # [Output-only] Specifies the name of the unused search index, if available.
- "message": "$(reason.message)", # [Output-only] Free form human-readable reason for the scenario when no search index was used.
+ "code": "A String", # Specifies the high-level reason for the scenario when no search index was used.
+ "indexName": "A String", # Specifies the name of the unused search index, if available.
+ "message": "A String", # Free form human-readable reason for the scenario when no search index was used.
},
],
- "indexUsageMode": "A String", # Specifies index usage mode for the query.
+ "indexUsageMode": "A String", # Specifies the index usage mode for the query.
},
- "sparkStatistics": { # [Output only] Statistics of a Spark procedure job.
- "endpoints": { # [Output-only] Endpoints generated for the Spark job.
+ "sparkStatistics": { # Statistics for a BigSpark query. Populated as part of JobStatistics2 # Output only. Statistics of a Spark procedure job.
+ "endpoints": { # Output only. Endpoints returned from Dataproc. Key list: - history_server_endpoint: A link to Spark job UI.
"a_key": "A String",
},
- "loggingInfo": { # [Output-only] Logging info is used to generate a link to Cloud Logging.
- "projectId": "A String", # [Output-only] Project ID used for logging
- "resourceType": "A String", # [Output-only] Resource type used for logging
+ "gcsStagingBucket": "A String", # Output only. The Google Cloud Storage bucket that is used as the default filesystem by the Spark application. This fields is only filled when the Spark procedure uses the INVOKER security mode. It is inferred from the system variable @@spark_proc_properties.staging_bucket if it is provided. Otherwise, BigQuery creates a default staging bucket for the job and returns the bucket name in this field. Example: * `gs://[bucket_name]`
+ "kmsKeyName": "A String", # Output only. The Cloud KMS encryption key that is used to protect the resources created by the Spark job. If the Spark procedure uses DEFINER security mode, the Cloud KMS key is inferred from the Spark connection associated with the procedure if it is provided. Otherwise the key is inferred from the default key of the Spark connection's project if the CMEK organization policy is enforced. If the Spark procedure uses INVOKER security mode, the Cloud KMS encryption key is inferred from the system variable @@spark_proc_properties.kms_key_name if it is provided. Otherwise, the key is inferred fromt he default key of the BigQuery job's project if the CMEK organization policy is enforced. Example: * `projects/[kms_project_id]/locations/[region]/keyRings/[key_region]/cryptoKeys/[key]`
+ "loggingInfo": { # Spark job logs can be filtered by these fields in Cloud Logging. # Output only. Logging info is used to generate a link to Cloud Logging.
+ "projectId": "A String", # Output only. Project ID where the Spark logs were written.
+ "resourceType": "A String", # Output only. Resource type used for logging.
},
- "sparkJobId": "A String", # [Output-only] Spark job id if a Spark job is created successfully.
- "sparkJobLocation": "A String", # [Output-only] Location where the Spark job is executed.
+ "sparkJobId": "A String", # Output only. Spark job ID if a Spark job is created successfully.
+ "sparkJobLocation": "A String", # Output only. Location where the Spark job is executed. A location is selected by BigQueury for jobs configured to run in a multi-region.
},
- "statementType": "A String", # The type of query statement, if valid. Possible values (new values might be added in the future): "SELECT": SELECT query. "INSERT": INSERT query; see https://cloud.google.com/bigquery/docs/reference/standard-sql/data-manipulation-language. "UPDATE": UPDATE query; see https://cloud.google.com/bigquery/docs/reference/standard-sql/data-manipulation-language. "DELETE": DELETE query; see https://cloud.google.com/bigquery/docs/reference/standard-sql/data-manipulation-language. "MERGE": MERGE query; see https://cloud.google.com/bigquery/docs/reference/standard-sql/data-manipulation-language. "ALTER_TABLE": ALTER TABLE query. "ALTER_VIEW": ALTER VIEW query. "ASSERT": ASSERT condition AS 'description'. "CREATE_FUNCTION": CREATE FUNCTION query. "CREATE_MODEL": CREATE [OR REPLACE] MODEL ... AS SELECT ... . "CREATE_PROCEDURE": CREATE PROCEDURE query. "CREATE_TABLE": CREATE [OR REPLACE] TABLE without AS SELECT. "CREATE_TABLE_AS_SELECT": CREATE [OR REPLACE] TABLE ... AS SELECT ... . "CREATE_VIEW": CREATE [OR REPLACE] VIEW ... AS SELECT ... . "DROP_FUNCTION" : DROP FUNCTION query. "DROP_PROCEDURE": DROP PROCEDURE query. "DROP_TABLE": DROP TABLE query. "DROP_VIEW": DROP VIEW query.
- "timeline": [ # [Output only] [Beta] Describes a timeline of job execution.
- {
- "activeUnits": "A String", # Total number of units currently being processed by workers. This does not correspond directly to slot usage. This is the largest value observed since the last sample.
+ "statementType": "A String", # Output only. The type of query statement, if valid. Possible values: * `SELECT`: [`SELECT`](/bigquery/docs/reference/standard-sql/query-syntax#select_list) statement. * `ASSERT`: [`ASSERT`](/bigquery/docs/reference/standard-sql/debugging-statements#assert) statement. * `INSERT`: [`INSERT`](/bigquery/docs/reference/standard-sql/dml-syntax#insert_statement) statement. * `UPDATE`: [`UPDATE`](/bigquery/docs/reference/standard-sql/query-syntax#update_statement) statement. * `DELETE`: [`DELETE`](/bigquery/docs/reference/standard-sql/data-manipulation-language) statement. * `MERGE`: [`MERGE`](/bigquery/docs/reference/standard-sql/data-manipulation-language) statement. * `CREATE_TABLE`: [`CREATE TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#create_table_statement) statement, without `AS SELECT`. * `CREATE_TABLE_AS_SELECT`: [`CREATE TABLE AS SELECT`](/bigquery/docs/reference/standard-sql/data-definition-language#query_statement) statement. * `CREATE_VIEW`: [`CREATE VIEW`](/bigquery/docs/reference/standard-sql/data-definition-language#create_view_statement) statement. * `CREATE_MODEL`: [`CREATE MODEL`](/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-create#create_model_statement) statement. * `CREATE_MATERIALIZED_VIEW`: [`CREATE MATERIALIZED VIEW`](/bigquery/docs/reference/standard-sql/data-definition-language#create_materialized_view_statement) statement. * `CREATE_FUNCTION`: [`CREATE FUNCTION`](/bigquery/docs/reference/standard-sql/data-definition-language#create_function_statement) statement. * `CREATE_TABLE_FUNCTION`: [`CREATE TABLE FUNCTION`](/bigquery/docs/reference/standard-sql/data-definition-language#create_table_function_statement) statement. * `CREATE_PROCEDURE`: [`CREATE PROCEDURE`](/bigquery/docs/reference/standard-sql/data-definition-language#create_procedure) statement. * `CREATE_ROW_ACCESS_POLICY`: [`CREATE ROW ACCESS POLICY`](/bigquery/docs/reference/standard-sql/data-definition-language#create_row_access_policy_statement) statement. * `CREATE_SCHEMA`: [`CREATE SCHEMA`](/bigquery/docs/reference/standard-sql/data-definition-language#create_schema_statement) statement. * `CREATE_SNAPSHOT_TABLE`: [`CREATE SNAPSHOT TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#create_snapshot_table_statement) statement. * `CREATE_SEARCH_INDEX`: [`CREATE SEARCH INDEX`](/bigquery/docs/reference/standard-sql/data-definition-language#create_search_index_statement) statement. * `DROP_TABLE`: [`DROP TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_table_statement) statement. * `DROP_EXTERNAL_TABLE`: [`DROP EXTERNAL TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_external_table_statement) statement. * `DROP_VIEW`: [`DROP VIEW`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_view_statement) statement. * `DROP_MODEL`: [`DROP MODEL`](/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-drop-model) statement. * `DROP_MATERIALIZED_VIEW`: [`DROP MATERIALIZED VIEW`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_materialized_view_statement) statement. * `DROP_FUNCTION` : [`DROP FUNCTION`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_function_statement) statement. * `DROP_TABLE_FUNCTION` : [`DROP TABLE FUNCTION`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_table_function) statement. * `DROP_PROCEDURE`: [`DROP PROCEDURE`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_procedure_statement) statement. * `DROP_SEARCH_INDEX`: [`DROP SEARCH INDEX`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_search_index) statement. * `DROP_SCHEMA`: [`DROP SCHEMA`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_schema_statement) statement. * `DROP_SNAPSHOT_TABLE`: [`DROP SNAPSHOT TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_snapshot_table_statement) statement. * `DROP_ROW_ACCESS_POLICY`: [`DROP [ALL] ROW ACCESS POLICY|POLICIES`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_row_access_policy_statement) statement. * `ALTER_TABLE`: [`ALTER TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#alter_table_set_options_statement) statement. * `ALTER_VIEW`: [`ALTER VIEW`](/bigquery/docs/reference/standard-sql/data-definition-language#alter_view_set_options_statement) statement. * `ALTER_MATERIALIZED_VIEW`: [`ALTER MATERIALIZED VIEW`](/bigquery/docs/reference/standard-sql/data-definition-language#alter_materialized_view_set_options_statement) statement. * `ALTER_SCHEMA`: [`ALTER SCHEMA`](/bigquery/docs/reference/standard-sql/data-definition-language#aalter_schema_set_options_statement) statement. * `SCRIPT`: [`SCRIPT`](/bigquery/docs/reference/standard-sql/procedural-language). * `TRUNCATE_TABLE`: [`TRUNCATE TABLE`](/bigquery/docs/reference/standard-sql/dml-syntax#truncate_table_statement) statement. * `CREATE_EXTERNAL_TABLE`: [`CREATE EXTERNAL TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#create_external_table_statement) statement. * `EXPORT_DATA`: [`EXPORT DATA`](/bigquery/docs/reference/standard-sql/other-statements#export_data_statement) statement. * `EXPORT_MODEL`: [`EXPORT MODEL`](/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-export-model) statement. * `LOAD_DATA`: [`LOAD DATA`](/bigquery/docs/reference/standard-sql/other-statements#load_data_statement) statement. * `CALL`: [`CALL`](/bigquery/docs/reference/standard-sql/procedural-language#call) statement.
+ "timeline": [ # Output only. Describes a timeline of job execution.
+ { # Summary of the state of query execution at a given time.
+ "activeUnits": "A String", # Total number of active workers. This does not correspond directly to slot usage. This is the largest value observed since the last sample.
"completedUnits": "A String", # Total parallel units of work completed by this query.
"elapsedMs": "A String", # Milliseconds elapsed since the start of query execution.
- "estimatedRunnableUnits": "A String", # Units of work that can be scheduled immediately. Providing additional slots for these units of work will speed up the query, provided no other query in the reservation needs additional slots.
+ "estimatedRunnableUnits": "A String", # Units of work that can be scheduled immediately. Providing additional slots for these units of work will accelerate the query, if no other query in the reservation needs additional slots.
"pendingUnits": "A String", # Total units of work remaining for the query. This number can be revised (increased or decreased) while the query is running.
"totalSlotMs": "A String", # Cumulative slot-ms consumed by the query.
},
],
- "totalBytesBilled": "A String", # [Output only] Total bytes billed for the job.
- "totalBytesProcessed": "A String", # [Output only] Total bytes processed for the job.
- "totalBytesProcessedAccuracy": "A String", # [Output only] For dry-run jobs, totalBytesProcessed is an estimate and this field specifies the accuracy of the estimate. Possible values can be: UNKNOWN: accuracy of the estimate is unknown. PRECISE: estimate is precise. LOWER_BOUND: estimate is lower bound of what the query would cost. UPPER_BOUND: estimate is upper bound of what the query would cost.
- "totalPartitionsProcessed": "A String", # [Output only] Total number of partitions processed from all partitioned tables referenced in the job.
- "totalSlotMs": "A String", # [Output only] Slot-milliseconds for the job.
- "transferredBytes": "A String", # [Output-only] Total bytes transferred for cross-cloud queries such as Cross Cloud Transfer and CREATE TABLE AS SELECT (CTAS).
- "undeclaredQueryParameters": [ # Standard SQL only: list of undeclared query parameters detected during a dry run validation.
- {
- "name": "A String", # [Optional] If unset, this is a positional parameter. Otherwise, should be unique within a query.
- "parameterType": { # [Required] The type of this parameter.
- "arrayType": # Object with schema name: QueryParameterType # [Optional] The type of the array's elements, if this is an array.
- "rangeElementType": # Object with schema name: QueryParameterType # [Optional] The element type of the range, if this is a range.
- "structTypes": [ # [Optional] The types of the fields of this struct, in order, if this is a struct.
- {
- "description": "A String", # [Optional] Human-oriented description of the field.
- "name": "A String", # [Optional] The name of this field.
- "type": # Object with schema name: QueryParameterType # [Required] The type of this field.
+ "totalBytesBilled": "A String", # Output only. If the project is configured to use on-demand pricing, then this field contains the total bytes billed for the job. If the project is configured to use flat-rate pricing, then you are not billed for bytes and this field is informational only.
+ "totalBytesProcessed": "A String", # Output only. Total bytes processed for the job.
+ "totalBytesProcessedAccuracy": "A String", # Output only. For dry-run jobs, totalBytesProcessed is an estimate and this field specifies the accuracy of the estimate. Possible values can be: UNKNOWN: accuracy of the estimate is unknown. PRECISE: estimate is precise. LOWER_BOUND: estimate is lower bound of what the query would cost. UPPER_BOUND: estimate is upper bound of what the query would cost.
+ "totalPartitionsProcessed": "A String", # Output only. Total number of partitions processed from all partitioned tables referenced in the job.
+ "totalSlotMs": "A String", # Output only. Slot-milliseconds for the job.
+ "transferredBytes": "A String", # Output only. Total bytes transferred for cross-cloud queries such as Cross Cloud Transfer and CREATE TABLE AS SELECT (CTAS).
+ "undeclaredQueryParameters": [ # Output only. GoogleSQL only: list of undeclared query parameters detected during a dry run validation.
+ { # A parameter given to a query.
+ "name": "A String", # Optional. If unset, this is a positional parameter. Otherwise, should be unique within a query.
+ "parameterType": { # The type of a query parameter. # Required. The type of this parameter.
+ "arrayType": # Object with schema name: QueryParameterType # Optional. The type of the array's elements, if this is an array.
+ "rangeElementType": # Object with schema name: QueryParameterType # Optional. The element type of the range, if this is a range.
+ "structTypes": [ # Optional. The types of the fields of this struct, in order, if this is a struct.
+ { # The type of a struct parameter.
+ "description": "A String", # Optional. Human-oriented description of the field.
+ "name": "A String", # Optional. The name of this field.
+ "type": # Object with schema name: QueryParameterType # Required. The type of this field.
},
],
- "type": "A String", # [Required] The top level type of this field.
+ "type": "A String", # Required. The top level type of this field.
},
- "parameterValue": { # [Required] The value of this parameter.
- "arrayValues": [ # [Optional] The array values, if this is an array type.
+ "parameterValue": { # The value of a query parameter. # Required. The value of this parameter.
+ "arrayValues": [ # Optional. The array values, if this is an array type.
# Object with schema name: QueryParameterValue
],
- "rangeValue": { # [Optional] The range value, if this is a range type.
- "end": # Object with schema name: QueryParameterValue
- "start": # Object with schema name: QueryParameterValue
+ "rangeValue": { # Represents the value of a range. # Optional. The range value, if this is a range type.
+ "end": # Object with schema name: QueryParameterValue # Optional. The end value of the range. A missing value represents an unbounded end.
+ "start": # Object with schema name: QueryParameterValue # Optional. The start value of the range. A missing value represents an unbounded start.
},
- "structValues": { # [Optional] The struct field values, in order of the struct type's declaration.
+ "structValues": { # The struct field values.
"a_key": # Object with schema name: QueryParameterValue
},
- "value": "A String", # [Optional] The value of this value, if a simple scalar type.
+ "value": "A String", # Optional. The value of this value, if a simple scalar type.
},
},
],
+ "vectorSearchStatistics": { # Statistics for a vector search query. Populated as part of JobStatistics2. # Output only. Search query specific statistics.
+ "indexUnusedReasons": [ # When `indexUsageMode` is `UNUSED` or `PARTIALLY_USED`, this field explains why indexes were not used in all or part of the vector search query. If `indexUsageMode` is `FULLY_USED`, this field is not populated.
+ { # Reason about why no search index was used in the search query (or sub-query).
+ "baseTable": { # Specifies the base table involved in the reason that no search index was used.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ "code": "A String", # Specifies the high-level reason for the scenario when no search index was used.
+ "indexName": "A String", # Specifies the name of the unused search index, if available.
+ "message": "A String", # Free form human-readable reason for the scenario when no search index was used.
+ },
+ ],
+ "indexUsageMode": "A String", # Specifies the index usage mode for the query.
+ },
},
- "quotaDeferments": [ # [Output-only] Quotas which delayed this job's start time.
+ "quotaDeferments": [ # Output only. Quotas which delayed this job's start time.
"A String",
],
- "reservationUsage": [ # [Output-only] Job resource usage breakdown by reservation.
- {
- "name": "A String", # [Output-only] Reservation name or "unreserved" for on-demand resources usage.
- "slotMs": "A String", # [Output-only] Slot-milliseconds the job spent in the given reservation.
+ "reservationUsage": [ # Output only. Job resource usage breakdown by reservation. This field reported misleading information and will no longer be populated.
+ { # Job resource usage breakdown by reservation.
+ "name": "A String", # Reservation name or "unreserved" for on-demand resources usage.
+ "slotMs": "A String", # Total slot milliseconds used by the reservation for a particular job.
},
],
- "reservation_id": "A String", # [Output-only] Name of the primary reservation assigned to this job. Note that this could be different than reservations reported in the reservation usage field if parent reservations were used to execute this job.
- "rowLevelSecurityStatistics": { # [Output-only] [Preview] Statistics for row-level security. Present only for query and extract jobs.
- "rowLevelSecurityApplied": True or False, # [Output-only] [Preview] Whether any accessed data was protected by row access policies.
+ "reservation_id": "A String", # Output only. Name of the primary reservation assigned to this job. Note that this could be different than reservations reported in the reservation usage field if parent reservations were used to execute this job.
+ "rowLevelSecurityStatistics": { # Statistics for row-level security. # Output only. Statistics for row-level security. Present only for query and extract jobs.
+ "rowLevelSecurityApplied": True or False, # Whether any accessed data was protected by row access policies.
},
- "scriptStatistics": { # [Output-only] Statistics for a child job of a script.
- "evaluationKind": "A String", # [Output-only] Whether this child job was a statement or expression.
+ "scriptStatistics": { # Job statistics specific to the child job of a script. # Output only. If this a child job of a script, specifies information about the context of this job within the script.
+ "evaluationKind": "A String", # Whether this child job was a statement or expression.
"stackFrames": [ # Stack trace showing the line/column/procedure name of each frame on the stack at the point where the current evaluation happened. The leaf frame is first, the primary script is last. Never empty.
- {
- "endColumn": 42, # [Output-only] One-based end column.
- "endLine": 42, # [Output-only] One-based end line.
- "procedureId": "A String", # [Output-only] Name of the active procedure, empty if in a top-level script.
- "startColumn": 42, # [Output-only] One-based start column.
- "startLine": 42, # [Output-only] One-based start line.
- "text": "A String", # [Output-only] Text of the current statement/expression.
+ { # Represents the location of the statement/expression being evaluated. Line and column numbers are defined as follows: - Line and column numbers start with one. That is, line 1 column 1 denotes the start of the script. - When inside a stored procedure, all line/column numbers are relative to the procedure body, not the script in which the procedure was defined. - Start/end positions exclude leading/trailing comments and whitespace. The end position always ends with a ";", when present. - Multi-byte Unicode characters are treated as just one column. - If the original script (or procedure definition) contains TAB characters, a tab "snaps" the indentation forward to the nearest multiple of 8 characters, plus 1. For example, a TAB on column 1, 2, 3, 4, 5, 6 , or 8 will advance the next character to column 9. A TAB on column 9, 10, 11, 12, 13, 14, 15, or 16 will advance the next character to column 17.
+ "endColumn": 42, # Output only. One-based end column.
+ "endLine": 42, # Output only. One-based end line.
+ "procedureId": "A String", # Output only. Name of the active procedure, empty if in a top-level script.
+ "startColumn": 42, # Output only. One-based start column.
+ "startLine": 42, # Output only. One-based start line.
+ "text": "A String", # Output only. Text of the current statement/expression.
},
],
},
- "sessionInfo": { # [Output-only] [Preview] Information of the session if this job is part of one.
- "sessionId": "A String", # [Output-only] // [Preview] Id of the session.
+ "sessionInfo": { # [Preview] Information related to sessions. # Output only. Information of the session if this job is part of one.
+ "sessionId": "A String", # Output only. The id of the session.
},
- "startTime": "A String", # [Output-only] Start time of this job, in milliseconds since the epoch. This field will be present when the job transitions from the PENDING state to either RUNNING or DONE.
- "totalBytesProcessed": "A String", # [Output-only] [Deprecated] Use the bytes processed in the query statistics instead.
- "totalSlotMs": "A String", # [Output-only] Slot-milliseconds for the job.
- "transactionInfo": { # [Output-only] [Alpha] Information of the multi-statement transaction if this job is part of one.
- "transactionId": "A String", # [Output-only] // [Alpha] Id of the transaction.
+ "startTime": "A String", # Output only. Start time of this job, in milliseconds since the epoch. This field will be present when the job transitions from the PENDING state to either RUNNING or DONE.
+ "totalBytesProcessed": "A String", # Output only. Total bytes processed for the job.
+ "totalSlotMs": "A String", # Output only. Slot-milliseconds for the job.
+ "transactionInfo": { # [Alpha] Information of a multi-statement transaction. # Output only. [Alpha] Information of the multi-statement transaction if this job is part of one. This property is only expected on a child job or a job that is in a session. A script parent job is not part of the transaction started in the script.
+ "transactionId": "A String", # Output only. [Alpha] Id of the transaction.
},
},
- "status": { # [Output-only] The status of this job. Examine this value when polling an asynchronous job to see if the job is complete.
- "errorResult": { # [Output-only] Final error result of the job. If present, indicates that the job has completed and was unsuccessful.
+ "status": { # Output only. The status of this job. Examine this value when polling an asynchronous job to see if the job is complete.
+ "errorResult": { # Error details. # Output only. Final error result of the job. If present, indicates that the job has completed and was unsuccessful.
"debugInfo": "A String", # Debugging information. This property is internal to Google and should not be used.
"location": "A String", # Specifies where the error occurred, if present.
"message": "A String", # A human-readable description of the error.
"reason": "A String", # A short error code that summarizes the error.
},
- "errors": [ # [Output-only] The first errors encountered during the running of the job. The final message includes the number of errors that caused the process to stop. Errors here do not necessarily mean that the job has completed or was unsuccessful.
- {
+ "errors": [ # Output only. The first errors encountered during the running of the job. The final message includes the number of errors that caused the process to stop. Errors here do not necessarily mean that the job has not completed or was unsuccessful.
+ { # Error details.
"debugInfo": "A String", # Debugging information. This property is internal to Google and should not be used.
"location": "A String", # Specifies where the error occurred, if present.
"message": "A String", # A human-readable description of the error.
"reason": "A String", # A short error code that summarizes the error.
},
],
- "state": "A String", # [Output-only] Running state of the job.
+ "state": "A String", # Output only. Running state of the job. Valid states include 'PENDING', 'RUNNING', and 'DONE'.
},
- "user_email": "A String", # [Output-only] Email address of the user who ran the job.
+ "user_email": "A String", # Output only. Email address of the user who ran the job.
},
"kind": "bigquery#jobCancelResponse", # The resource type of the response.
}
@@ -827,517 +1466,1143 @@ delete(projectId, jobId, location=None)
+ delete(projectId, jobId, location=None, x__xgafv=None)
Requests the deletion of the metadata of a job. This call returns when the job's metadata is deleted. Args: projectId: string, Required. Project ID of the job for which metadata is to be deleted. (required) jobId: string, Required. Job ID of the job for which metadata is to be deleted. If this is a parent job which has child jobs, the metadata from all child jobs will be deleted as well. Direct deletion of the metadata of child jobs is not allowed. (required) location: string, The geographic location of the job. Required. See details at: https://cloud.google.com/bigquery/docs/locations#specifying_your_location. + x__xgafv: string, V1 error format. + Allowed values + 1 - v1 error format + 2 - v2 error format
get(projectId, jobId, location=None)
+ get(projectId, jobId, location=None, x__xgafv=None)
Returns information about a specific job. Job information is available for a six month period after creation. Requires that you're the person who ran the job, or have the Is Owner project role.
Args:
- projectId: string, [Required] Project ID of the requested job (required)
- jobId: string, [Required] Job ID of the requested job (required)
- location: string, The geographic location of the job. Required except for US and EU. See details at https://cloud.google.com/bigquery/docs/locations#specifying_your_location.
+ projectId: string, Required. Project ID of the requested job. (required)
+ jobId: string, Required. Job ID of the requested job. (required)
+ location: string, The geographic location of the job. You must specify the location to run the job for the following scenarios: - If the location to run a job is not in the `us` or the `eu` multi-regional location - If the job's location is in a single region (for example, `us-central1`) For more information, see https://cloud.google.com/bigquery/docs/locations#specifying_your_location.
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
Returns:
An object of the form:
{
- "configuration": { # [Required] Describes the job configuration.
- "copy": { # [Pick one] Copies a table.
- "createDisposition": "A String", # [Optional] Specifies whether the job is allowed to create new tables. The following values are supported: CREATE_IF_NEEDED: If the table does not exist, BigQuery creates the table. CREATE_NEVER: The table must already exist. If it does not, a 'notFound' error is returned in the job result. The default value is CREATE_IF_NEEDED. Creation, truncation and append actions occur as one atomic update upon job completion.
+ "configuration": { # Required. Describes the job configuration.
+ "copy": { # JobConfigurationTableCopy configures a job that copies data from one table to another. For more information on copying tables, see [Copy a table](https://cloud.google.com/bigquery/docs/managing-tables#copy-table). # [Pick one] Copies a table.
+ "createDisposition": "A String", # Optional. Specifies whether the job is allowed to create new tables. The following values are supported: * CREATE_IF_NEEDED: If the table does not exist, BigQuery creates the table. * CREATE_NEVER: The table must already exist. If it does not, a 'notFound' error is returned in the job result. The default value is CREATE_IF_NEEDED. Creation, truncation and append actions occur as one atomic update upon job completion.
"destinationEncryptionConfiguration": { # Custom encryption configuration (e.g., Cloud KMS keys).
"kmsKeyName": "A String", # Optional. Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key.
},
- "destinationExpirationTime": "", # [Optional] The time when the destination table expires. Expired tables will be deleted and their storage reclaimed.
- "destinationTable": { # [Required] The destination table
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "destinationExpirationTime": "A String", # Optional. The time when the destination table expires. Expired tables will be deleted and their storage reclaimed.
+ "destinationTable": { # [Required] The destination table.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
- "operationType": "A String", # [Optional] Supported operation types in table copy job.
+ "operationType": "A String", # Optional. Supported operation types in table copy job.
"sourceTable": { # [Pick one] Source table to copy.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
"sourceTables": [ # [Pick one] Source tables to copy.
{
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
],
- "writeDisposition": "A String", # [Optional] Specifies the action that occurs if the destination table already exists. The following values are supported: WRITE_TRUNCATE: If the table already exists, BigQuery overwrites the table data. WRITE_APPEND: If the table already exists, BigQuery appends the data to the table. WRITE_EMPTY: If the table already exists and contains data, a 'duplicate' error is returned in the job result. The default value is WRITE_EMPTY. Each action is atomic and only occurs if BigQuery is able to complete the job successfully. Creation, truncation and append actions occur as one atomic update upon job completion.
+ "writeDisposition": "A String", # Optional. Specifies the action that occurs if the destination table already exists. The following values are supported: * WRITE_TRUNCATE: If the table already exists, BigQuery overwrites the table data and uses the schema and table constraints from the source table. * WRITE_APPEND: If the table already exists, BigQuery appends the data to the table. * WRITE_EMPTY: If the table already exists and contains data, a 'duplicate' error is returned in the job result. The default value is WRITE_EMPTY. Each action is atomic and only occurs if BigQuery is able to complete the job successfully. Creation, truncation and append actions occur as one atomic update upon job completion.
},
- "dryRun": True or False, # [Optional] If set, don't actually run this job. A valid query will return a mostly empty response with some processing statistics, while an invalid query will return the same error it would if it wasn't a dry run. Behavior of non-query jobs is undefined.
- "extract": { # [Pick one] Configures an extract job.
- "compression": "A String", # [Optional] The compression type to use for exported files. Possible values include GZIP, DEFLATE, SNAPPY, and NONE. The default value is NONE. DEFLATE and SNAPPY are only supported for Avro. Not applicable when extracting models.
- "destinationFormat": "A String", # [Optional] The exported file format. Possible values include CSV, NEWLINE_DELIMITED_JSON, PARQUET or AVRO for tables and ML_TF_SAVED_MODEL or ML_XGBOOST_BOOSTER for models. The default value for tables is CSV. Tables with nested or repeated fields cannot be exported as CSV. The default value for models is ML_TF_SAVED_MODEL.
+ "dryRun": True or False, # Optional. If set, don't actually run this job. A valid query will return a mostly empty response with some processing statistics, while an invalid query will return the same error it would if it wasn't a dry run. Behavior of non-query jobs is undefined.
+ "extract": { # JobConfigurationExtract configures a job that exports data from a BigQuery table into Google Cloud Storage. # [Pick one] Configures an extract job.
+ "compression": "A String", # Optional. The compression type to use for exported files. Possible values include DEFLATE, GZIP, NONE, SNAPPY, and ZSTD. The default value is NONE. Not all compression formats are support for all file formats. DEFLATE is only supported for Avro. ZSTD is only supported for Parquet. Not applicable when extracting models.
+ "destinationFormat": "A String", # Optional. The exported file format. Possible values include CSV, NEWLINE_DELIMITED_JSON, PARQUET, or AVRO for tables and ML_TF_SAVED_MODEL or ML_XGBOOST_BOOSTER for models. The default value for tables is CSV. Tables with nested or repeated fields cannot be exported as CSV. The default value for models is ML_TF_SAVED_MODEL.
"destinationUri": "A String", # [Pick one] DEPRECATED: Use destinationUris instead, passing only one URI as necessary. The fully-qualified Google Cloud Storage URI where the extracted table should be written.
"destinationUris": [ # [Pick one] A list of fully-qualified Google Cloud Storage URIs where the extracted table should be written.
"A String",
],
- "fieldDelimiter": "A String", # [Optional] Delimiter to use between fields in the exported data. Default is ','. Not applicable when extracting models.
- "printHeader": true, # [Optional] Whether to print out a header row in the results. Default is true. Not applicable when extracting models.
- "sourceModel": { # A reference to the model being exported.
+ "fieldDelimiter": "A String", # Optional. When extracting data in CSV format, this defines the delimiter to use between fields in the exported data. Default is ','. Not applicable when extracting models.
+ "modelExtractOptions": { # Options related to model extraction. # Optional. Model extract options only applicable when extracting models.
+ "trialId": "A String", # The 1-based ID of the trial to be exported from a hyperparameter tuning model. If not specified, the trial with id = [Model](/bigquery/docs/reference/rest/v2/models#resource:-model).defaultTrialId is exported. This field is ignored for models not trained with hyperparameter tuning.
+ },
+ "printHeader": true, # Optional. Whether to print out a header row in the results. Default is true. Not applicable when extracting models.
+ "sourceModel": { # Id path of a model. # A reference to the model being exported.
"datasetId": "A String", # Required. The ID of the dataset containing this model.
"modelId": "A String", # Required. The ID of the model. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
"projectId": "A String", # Required. The ID of the project containing this model.
},
"sourceTable": { # A reference to the table being exported.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
- "useAvroLogicalTypes": True or False, # [Optional] If destinationFormat is set to "AVRO", this flag indicates whether to enable extracting applicable column types (such as TIMESTAMP) to their corresponding AVRO logical types (timestamp-micros), instead of only using their raw types (avro-long). Not applicable when extracting models.
+ "useAvroLogicalTypes": True or False, # Whether to use logical types when extracting to AVRO format. Not applicable when extracting models.
},
- "jobTimeoutMs": "A String", # [Optional] Job timeout in milliseconds. If this time limit is exceeded, BigQuery may attempt to terminate the job.
- "jobType": "A String", # [Output-only] The type of the job. Can be QUERY, LOAD, EXTRACT, COPY or UNKNOWN.
+ "jobTimeoutMs": "A String", # Optional. Job timeout in milliseconds. If this time limit is exceeded, BigQuery might attempt to stop the job.
+ "jobType": "A String", # Output only. The type of the job. Can be QUERY, LOAD, EXTRACT, COPY or UNKNOWN.
"labels": { # The labels associated with this job. You can use these to organize and group your jobs. Label keys and values can be no longer than 63 characters, can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. Label values are optional. Label keys must start with a letter and each label in the list must have a different key.
"a_key": "A String",
},
- "load": { # [Pick one] Configures a load job.
- "allowJaggedRows": True or False, # [Optional] Accept rows that are missing trailing optional columns. The missing values are treated as nulls. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. Only applicable to CSV, ignored for other formats.
+ "load": { # JobConfigurationLoad contains the configuration properties for loading data into a destination table. # [Pick one] Configures a load job.
+ "allowJaggedRows": True or False, # Optional. Accept rows that are missing trailing optional columns. The missing values are treated as nulls. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. Only applicable to CSV, ignored for other formats.
"allowQuotedNewlines": True or False, # Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false.
- "autodetect": True or False, # [Optional] Indicates if we should automatically infer the options and schema for CSV and JSON sources.
- "clustering": { # [Beta] Clustering specification for the destination table. Must be specified with time-based partitioning, data in the table will be first partitioned and subsequently clustered.
- "fields": [ # [Repeated] One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. When you cluster a table using multiple columns, the order of columns you specify is important. The order of the specified columns determines the sort order of the data.
+ "autodetect": True or False, # Optional. Indicates if we should automatically infer the options and schema for CSV and JSON sources.
+ "clustering": { # Configures table clustering. # Clustering specification for the destination table.
+ "fields": [ # One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. The ordering of the clustering fields should be prioritized from most to least important for filtering purposes. Additional information on limitations can be found here: https://cloud.google.com/bigquery/docs/creating-clustered-tables#limitations
"A String",
],
},
- "connectionProperties": [ # Connection properties.
- {
- "key": "A String", # [Required] Name of the connection property to set.
- "value": "A String", # [Required] Value of the connection property.
+ "connectionProperties": [ # Optional. Connection properties which can modify the load job behavior. Currently, only the 'session_id' connection property is supported, and is used to resolve _SESSION appearing as the dataset id.
+ { # A connection-level property to customize query behavior. Under JDBC, these correspond directly to connection properties passed to the DriverManager. Under ODBC, these correspond to properties in the connection string. Currently supported connection properties: * **dataset_project_id**: represents the default project for datasets that are used in the query. Setting the system variable `@@dataset_project_id` achieves the same behavior. For more information about system variables, see: https://cloud.google.com/bigquery/docs/reference/system-variables * **time_zone**: represents the default timezone used to run the query. * **session_id**: associates the query with a given session. * **query_label**: associates the query with a given job label. If set, all subsequent queries in a script or session will have this label. For the format in which a you can specify a query label, see labels in the JobConfiguration resource type: https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#jobconfiguration Additional properties are allowed, but ignored. Specifying multiple connection properties with the same key returns an error.
+ "key": "A String", # The key of the property to set.
+ "value": "A String", # The value of the property to set.
},
],
- "createDisposition": "A String", # [Optional] Specifies whether the job is allowed to create new tables. The following values are supported: CREATE_IF_NEEDED: If the table does not exist, BigQuery creates the table. CREATE_NEVER: The table must already exist. If it does not, a 'notFound' error is returned in the job result. The default value is CREATE_IF_NEEDED. Creation, truncation and append actions occur as one atomic update upon job completion.
- "createSession": True or False, # If true, creates a new session, where session id will be a server generated random id. If false, runs query with an existing session_id passed in ConnectionProperty, otherwise runs the load job in non-session mode.
- "decimalTargetTypes": [ # [Optional] Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown. Example: Suppose the value of this field is ["NUMERIC", "BIGNUMERIC"]. If (precision,scale) is: (38,9) -> NUMERIC; (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits); (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits); (76,38) -> BIGNUMERIC; (77,38) -> BIGNUMERIC (error if value exeeds supported range). This field cannot contain duplicate types. The order of the types in this field is ignored. For example, ["BIGNUMERIC", "NUMERIC"] is the same as ["NUMERIC", "BIGNUMERIC"] and NUMERIC always takes precedence over BIGNUMERIC. Defaults to ["NUMERIC", "STRING"] for ORC and ["NUMERIC"] for the other file formats.
+ "createDisposition": "A String", # Optional. Specifies whether the job is allowed to create new tables. The following values are supported: * CREATE_IF_NEEDED: If the table does not exist, BigQuery creates the table. * CREATE_NEVER: The table must already exist. If it does not, a 'notFound' error is returned in the job result. The default value is CREATE_IF_NEEDED. Creation, truncation and append actions occur as one atomic update upon job completion.
+ "createSession": True or False, # Optional. If this property is true, the job creates a new session using a randomly generated session_id. To continue using a created session with subsequent queries, pass the existing session identifier as a `ConnectionProperty` value. The session identifier is returned as part of the `SessionInfo` message within the query statistics. The new session's location will be set to `Job.JobReference.location` if it is present, otherwise it's set to the default location based on existing routing logic.
+ "decimalTargetTypes": [ # Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown. Example: Suppose the value of this field is ["NUMERIC", "BIGNUMERIC"]. If (precision,scale) is: * (38,9) -> NUMERIC; * (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits); * (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits); * (76,38) -> BIGNUMERIC; * (77,38) -> BIGNUMERIC (error if value exeeds supported range). This field cannot contain duplicate types. The order of the types in this field is ignored. For example, ["BIGNUMERIC", "NUMERIC"] is the same as ["NUMERIC", "BIGNUMERIC"] and NUMERIC always takes precedence over BIGNUMERIC. Defaults to ["NUMERIC", "STRING"] for ORC and ["NUMERIC"] for the other file formats.
"A String",
],
- "destinationEncryptionConfiguration": { # Custom encryption configuration (e.g., Cloud KMS keys).
+ "destinationEncryptionConfiguration": { # Custom encryption configuration (e.g., Cloud KMS keys)
"kmsKeyName": "A String", # Optional. Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key.
},
"destinationTable": { # [Required] The destination table to load the data into.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- },
- "destinationTableProperties": { # [Beta] [Optional] Properties with which to create the destination table if it is new.
- "description": "A String", # [Optional] The description for the destination table. This will only be used if the destination table is newly created. If the table already exists and a value different than the current description is provided, the job will fail.
- "expirationTime": "A String", # [Internal] This field is for Google internal use only.
- "friendlyName": "A String", # [Optional] The friendly name for the destination table. This will only be used if the destination table is newly created. If the table already exists and a value different than the current friendly name is provided, the job will fail.
- "labels": { # [Optional] The labels associated with this table. You can use these to organize and group your tables. This will only be used if the destination table is newly created. If the table already exists and labels are different than the current labels are provided, the job will fail.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ "destinationTableProperties": { # Properties for the destination table. # Optional. [Experimental] Properties with which to create the destination table if it is new.
+ "description": "A String", # Optional. The description for the destination table. This will only be used if the destination table is newly created. If the table already exists and a value different than the current description is provided, the job will fail.
+ "expirationTime": "A String", # Internal use only.
+ "friendlyName": "A String", # Optional. Friendly name for the destination table. If the table already exists, it should be same as the existing friendly name.
+ "labels": { # Optional. The labels associated with this table. You can use these to organize and group your tables. This will only be used if the destination table is newly created. If the table already exists and labels are different than the current labels are provided, the job will fail.
"a_key": "A String",
},
},
- "encoding": "A String", # [Optional] The character encoding of the data. The supported values are UTF-8 or ISO-8859-1. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the quote and fieldDelimiter properties.
- "fieldDelimiter": "A String", # [Optional] The separator for fields in a CSV file. The separator can be any ISO-8859-1 single-byte character. To use a character in the range 128-255, you must encode the character as UTF8. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. BigQuery also supports the escape sequence "\t" to specify a tab separator. The default value is a comma (',').
- "fileSetSpecType": "A String", # [Optional] Specifies how source URIs are interpreted for constructing the file set to load. By default source URIs are expanded against the underlying storage. Other options include specifying manifest files. Only applicable to object storage systems.
- "hivePartitioningOptions": { # [Optional] Options to configure hive partitioning support.
- "fields": [ # [Output-only] For permanent external tables, this field is populated with the hive partition keys in the order they were inferred. The types of the partition keys can be deduced by checking the table schema (which will include the partition keys). Not every API will populate this field in the output. For example, Tables.Get will populate it, but Tables.List will not contain this field.
+ "encoding": "A String", # Optional. The character encoding of the data. The supported values are UTF-8, ISO-8859-1, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the `quote` and `fieldDelimiter` properties. If you don't specify an encoding, or if you specify a UTF-8 encoding when the CSV file is not UTF-8 encoded, BigQuery attempts to convert the data to UTF-8. Generally, your data loads successfully, but it may not match byte-for-byte what you expect. To avoid this, specify the correct encoding by using the `--encoding` flag. If BigQuery can't convert a character other than the ASCII `0` character, BigQuery converts the character to the standard Unicode replacement character: �.
+ "fieldDelimiter": "A String", # Optional. The separator character for fields in a CSV file. The separator is interpreted as a single byte. For files encoded in ISO-8859-1, any single character can be used as a separator. For files encoded in UTF-8, characters represented in decimal range 1-127 (U+0001-U+007F) can be used without any modification. UTF-8 characters encoded with multiple bytes (i.e. U+0080 and above) will have only the first byte used for separating fields. The remaining bytes will be treated as a part of the field. BigQuery also supports the escape sequence "\t" (U+0009) to specify a tab separator. The default value is comma (",", U+002C).
+ "fileSetSpecType": "A String", # Optional. Specifies how source URIs are interpreted for constructing the file set to load. By default, source URIs are expanded against the underlying storage. You can also specify manifest files to control how the file set is constructed. This option is only applicable to object storage systems.
+ "hivePartitioningOptions": { # Options for configuring hive partitioning detect. # Optional. When set, configures hive partitioning support. Not all storage formats support hive partitioning -- requesting hive partitioning on an unsupported format will lead to an error, as will providing an invalid specification.
+ "fields": [ # Output only. For permanent external tables, this field is populated with the hive partition keys in the order they were inferred. The types of the partition keys can be deduced by checking the table schema (which will include the partition keys). Not every API will populate this field in the output. For example, Tables.Get will populate it, but Tables.List will not contain this field.
"A String",
],
- "mode": "A String", # [Optional] When set, what mode of hive partitioning to use when reading data. The following modes are supported. (1) AUTO: automatically infer partition key name(s) and type(s). (2) STRINGS: automatically infer partition key name(s). All types are interpreted as strings. (3) CUSTOM: partition key schema is encoded in the source URI prefix. Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported types include: AVRO, CSV, JSON, ORC and Parquet.
- "requirePartitionFilter": True or False, # [Optional] If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. Note that this field should only be true when creating a permanent external table or querying a temporary external table. Hive-partitioned loads with requirePartitionFilter explicitly set to true will fail.
- "sourceUriPrefix": "A String", # [Optional] When hive partition detection is requested, a common prefix for all source uris should be supplied. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout. gs://bucket/path_to_table/dt=2019-01-01/country=BR/id=7/file.avro gs://bucket/path_to_table/dt=2018-12-31/country=CA/id=3/file.avro When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/ (trailing slash does not matter).
- },
- "ignoreUnknownValues": True or False, # [Optional] Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names
- "jsonExtension": "A String", # [Optional] If sourceFormat is set to newline-delimited JSON, indicates whether it should be processed as a JSON variant such as GeoJSON. For a sourceFormat other than JSON, omit this field. If the sourceFormat is newline-delimited JSON: - for newline-delimited GeoJSON: set to GEOJSON.
- "maxBadRecords": 42, # [Optional] The maximum number of bad records that BigQuery can ignore when running the job. If the number of bad records exceeds this value, an invalid error is returned in the job result. This is only valid for CSV and JSON. The default value is 0, which requires that all records are valid.
- "nullMarker": "A String", # [Optional] Specifies a string that represents a null value in a CSV file. For example, if you specify "\N", BigQuery interprets "\N" as a null value when loading a CSV file. The default value is the empty string. If you set this property to a custom value, BigQuery throws an error if an empty string is present for all data types except for STRING and BYTE. For STRING and BYTE columns, BigQuery interprets the empty string as an empty value.
- "parquetOptions": { # [Optional] Options to configure parquet support.
- "enableListInference": True or False, # [Optional] Indicates whether to use schema inference specifically for Parquet LIST logical type.
- "enumAsString": True or False, # [Optional] Indicates whether to infer Parquet ENUM logical type as STRING instead of BYTES by default.
- },
- "preserveAsciiControlCharacters": True or False, # [Optional] Preserves the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\x00' to '\x1F') when loading from CSV. Only applicable to CSV, ignored for other formats.
+ "mode": "A String", # Optional. When set, what mode of hive partitioning to use when reading data. The following modes are supported: * AUTO: automatically infer partition key name(s) and type(s). * STRINGS: automatically infer partition key name(s). All types are strings. * CUSTOM: partition key schema is encoded in the source URI prefix. Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported formats are: JSON, CSV, ORC, Avro and Parquet.
+ "requirePartitionFilter": false, # Optional. If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. Note that this field should only be true when creating a permanent external table or querying a temporary external table. Hive-partitioned loads with require_partition_filter explicitly set to true will fail.
+ "sourceUriPrefix": "A String", # Optional. When hive partition detection is requested, a common prefix for all source uris must be required. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout: gs://bucket/path_to_table/dt=2019-06-01/country=USA/id=7/file.avro gs://bucket/path_to_table/dt=2019-05-31/country=CA/id=3/file.avro When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/. CUSTOM detection requires encoding the partitioning schema immediately after the common prefix. For CUSTOM, any of * gs://bucket/path_to_table/{dt:DATE}/{country:STRING}/{id:INTEGER} * gs://bucket/path_to_table/{dt:STRING}/{country:STRING}/{id:INTEGER} * gs://bucket/path_to_table/{dt:DATE}/{country:STRING}/{id:STRING} would all be valid source URI prefixes.
+ },
+ "ignoreUnknownValues": True or False, # Optional. Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names in the table schema Avro, Parquet, ORC: Fields in the file schema that don't exist in the table schema.
+ "jsonExtension": "A String", # Optional. Load option to be used together with source_format newline-delimited JSON to indicate that a variant of JSON is being loaded. To load newline-delimited GeoJSON, specify GEOJSON (and source_format must be set to NEWLINE_DELIMITED_JSON).
+ "maxBadRecords": 42, # Optional. The maximum number of bad records that BigQuery can ignore when running the job. If the number of bad records exceeds this value, an invalid error is returned in the job result. The default value is 0, which requires that all records are valid. This is only supported for CSV and NEWLINE_DELIMITED_JSON file formats.
+ "nullMarker": "A String", # Optional. Specifies a string that represents a null value in a CSV file. For example, if you specify "\N", BigQuery interprets "\N" as a null value when loading a CSV file. The default value is the empty string. If you set this property to a custom value, BigQuery throws an error if an empty string is present for all data types except for STRING and BYTE. For STRING and BYTE columns, BigQuery interprets the empty string as an empty value.
+ "parquetOptions": { # Parquet Options for load and make external tables. # Optional. Additional properties to set if sourceFormat is set to PARQUET.
+ "enableListInference": True or False, # Optional. Indicates whether to use schema inference specifically for Parquet LIST logical type.
+ "enumAsString": True or False, # Optional. Indicates whether to infer Parquet ENUM logical type as STRING instead of BYTES by default.
+ },
+ "preserveAsciiControlCharacters": True or False, # Optional. When sourceFormat is set to "CSV", this indicates whether the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\x00' to '\x1F') are preserved.
"projectionFields": [ # If sourceFormat is set to "DATASTORE_BACKUP", indicates which entity properties to load into BigQuery from a Cloud Datastore backup. Property names are case sensitive and must be top-level properties. If no properties are specified, BigQuery loads all properties. If any named property isn't found in the Cloud Datastore backup, an invalid error is returned in the job result.
"A String",
],
- "quote": """, # [Optional] The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ('"'). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true.
- "rangePartitioning": { # [TrustedTester] Range partitioning specification for this table. Only one of timePartitioning and rangePartitioning should be specified.
- "field": "A String", # [TrustedTester] [Required] The table is partitioned by this field. The field must be a top-level NULLABLE/REQUIRED field. The only supported type is INTEGER/INT64.
- "range": { # [TrustedTester] [Required] Defines the ranges for range partitioning.
- "end": "A String", # [TrustedTester] [Required] The end of range partitioning, exclusive.
- "interval": "A String", # [TrustedTester] [Required] The width of each interval.
- "start": "A String", # [TrustedTester] [Required] The start of range partitioning, inclusive.
+ "quote": """, # Optional. The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ('"'). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true. To include the specific quote character within a quoted value, precede it with an additional matching quote character. For example, if you want to escape the default character ' " ', use ' "" '. @default "
+ "rangePartitioning": { # Range partitioning specification for the destination table. Only one of timePartitioning and rangePartitioning should be specified.
+ "field": "A String", # Required. [Experimental] The table is partitioned by this field. The field must be a top-level NULLABLE/REQUIRED field. The only supported type is INTEGER/INT64.
+ "range": { # [Experimental] Defines the ranges for range partitioning.
+ "end": "A String", # [Experimental] The end of range partitioning, exclusive.
+ "interval": "A String", # [Experimental] The width of each interval.
+ "start": "A String", # [Experimental] The start of range partitioning, inclusive.
},
},
- "referenceFileSchemaUri": "A String", # User provided referencing file with the expected reader schema, Available for the format: AVRO, PARQUET, ORC.
- "schema": { # [Optional] The schema for the destination table. The schema can be omitted if the destination table already exists, or if you're loading data from Google Cloud Datastore.
+ "referenceFileSchemaUri": "A String", # Optional. The user can provide a reference file with the reader schema. This file is only loaded if it is part of source URIs, but is not loaded otherwise. It is enabled for the following formats: AVRO, PARQUET, ORC.
+ "schema": { # Schema of a table # Optional. The schema for the destination table. The schema can be omitted if the destination table already exists, or if you're loading data from Google Cloud Datastore.
"fields": [ # Describes the fields in a table.
- {
- "categories": { # [Optional] The categories attached to this field, used for field-level access control.
- "names": [ # A list of category resource names. For example, "projects/1/taxonomies/2/categories/3". At most 5 categories are allowed.
+ { # A field in TableSchema
+ "categories": { # Deprecated.
+ "names": [ # Deprecated.
"A String",
],
},
- "collation": "A String", # Optional. Collation specification of the field. It only can be set on string type field.
- "defaultValueExpression": "A String", # Optional. A SQL expression to specify the default value for this field. It can only be set for top level fields (columns). You can use struct or array expression to specify default value for the entire struct or array. The valid SQL expressions are: - Literals for all data types, including STRUCT and ARRAY. - Following functions: - CURRENT_TIMESTAMP - CURRENT_TIME - CURRENT_DATE - CURRENT_DATETIME - GENERATE_UUID - RAND - SESSION_USER - ST_GEOGPOINT - Struct or array composed with the above allowed functions, for example, [CURRENT_DATE(), DATE '2020-01-01']
- "description": "A String", # [Optional] The field description. The maximum length is 1,024 characters.
- "fields": [ # [Optional] Describes the nested schema fields if the type property is set to RECORD.
+ "collation": "A String", # Optional. Field collation can be set only when the type of field is STRING. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.
+ "defaultValueExpression": "A String", # Optional. A SQL expression to specify the [default value] (https://cloud.google.com/bigquery/docs/default-values) for this field.
+ "description": "A String", # Optional. The field description. The maximum length is 1,024 characters.
+ "fields": [ # Optional. Describes the nested schema fields if the type property is set to RECORD.
# Object with schema name: TableFieldSchema
],
- "maxLength": "A String", # [Optional] Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
- "mode": "A String", # [Optional] The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
- "name": "A String", # [Required] The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
- "policyTags": {
- "names": [ # A list of category resource names. For example, "projects/1/location/eu/taxonomies/2/policyTags/3". At most 1 policy tag is allowed.
+ "maxLength": "A String", # Optional. Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
+ "mode": "A String", # Optional. The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
+ "name": "A String", # Required. The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
+ "policyTags": { # Optional. The policy tags attached to this field, used for field-level access control. If not set, defaults to empty policy_tags.
+ "names": [ # A list of policy tag resource names. For example, "projects/1/locations/eu/taxonomies/2/policyTags/3". At most 1 policy tag is currently allowed.
"A String",
],
},
- "precision": "A String", # [Optional] Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: - Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] - Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: - If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. - If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): - If type = "NUMERIC": 1 ≤ precision ≤ 29. - If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
- "rangeElementType": { # Optional. The subtype of the RANGE, if the type of this field is RANGE. If the type is RANGE, this field is required. Possible values for the field element type of a RANGE include: - DATE - DATETIME - TIMESTAMP
- "type": "A String", # The field element type of a RANGE
+ "precision": "A String", # Optional. Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: * Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] * Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: * If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. * If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): * If type = "NUMERIC": 1 ≤ precision ≤ 29. * If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
+ "rangeElementType": { # Represents the type of a field element.
+ "type": "A String", # Required. The type of a field element. See TableFieldSchema.type.
},
- "roundingMode": "A String", # Optional. Rounding Mode specification of the field. It only can be set on NUMERIC or BIGNUMERIC type fields.
- "scale": "A String", # [Optional] See documentation for precision.
- "type": "A String", # [Required] The field data type. Possible values include STRING, BYTES, INTEGER, INT64 (same as INTEGER), FLOAT, FLOAT64 (same as FLOAT), NUMERIC, BIGNUMERIC, BOOLEAN, BOOL (same as BOOLEAN), TIMESTAMP, DATE, TIME, DATETIME, INTERVAL, RECORD (where RECORD indicates that the field contains a nested schema) or STRUCT (same as RECORD).
+ "roundingMode": "A String", # Optional. Specifies the rounding mode to be used when storing values of NUMERIC and BIGNUMERIC type.
+ "scale": "A String", # Optional. See documentation for precision.
+ "type": "A String", # Required. The field data type. Possible values include: * STRING * BYTES * INTEGER (or INT64) * FLOAT (or FLOAT64) * BOOLEAN (or BOOL) * TIMESTAMP * DATE * TIME * DATETIME * GEOGRAPHY * NUMERIC * BIGNUMERIC * JSON * RECORD (or STRUCT) Use of RECORD/STRUCT indicates that the field contains a nested schema.
},
],
},
"schemaInline": "A String", # [Deprecated] The inline schema. For CSV schemas, specify as "Field1:Type1[,Field2:Type2]*". For example, "foo:STRING, bar:INTEGER, baz:FLOAT".
"schemaInlineFormat": "A String", # [Deprecated] The format of the schemaInline property.
- "schemaUpdateOptions": [ # Allows the schema of the destination table to be updated as a side effect of the load job if a schema is autodetected or supplied in the job configuration. Schema update options are supported in two cases: when writeDisposition is WRITE_APPEND; when writeDisposition is WRITE_TRUNCATE and the destination table is a partition of a table, specified by partition decorators. For normal tables, WRITE_TRUNCATE will always overwrite the schema. One or more of the following values are specified: ALLOW_FIELD_ADDITION: allow adding a nullable field to the schema. ALLOW_FIELD_RELAXATION: allow relaxing a required field in the original schema to nullable.
+ "schemaUpdateOptions": [ # Allows the schema of the destination table to be updated as a side effect of the load job if a schema is autodetected or supplied in the job configuration. Schema update options are supported in two cases: when writeDisposition is WRITE_APPEND; when writeDisposition is WRITE_TRUNCATE and the destination table is a partition of a table, specified by partition decorators. For normal tables, WRITE_TRUNCATE will always overwrite the schema. One or more of the following values are specified: * ALLOW_FIELD_ADDITION: allow adding a nullable field to the schema. * ALLOW_FIELD_RELAXATION: allow relaxing a required field in the original schema to nullable.
"A String",
],
- "skipLeadingRows": 42, # [Optional] The number of rows at the top of a CSV file that BigQuery will skip when loading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped.
- "sourceFormat": "A String", # [Optional] The format of the data files. For CSV files, specify "CSV". For datastore backups, specify "DATASTORE_BACKUP". For newline-delimited JSON, specify "NEWLINE_DELIMITED_JSON". For Avro, specify "AVRO". For parquet, specify "PARQUET". For orc, specify "ORC". The default value is CSV.
+ "skipLeadingRows": 42, # Optional. The number of rows at the top of a CSV file that BigQuery will skip when loading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
+ "sourceFormat": "A String", # Optional. The format of the data files. For CSV files, specify "CSV". For datastore backups, specify "DATASTORE_BACKUP". For newline-delimited JSON, specify "NEWLINE_DELIMITED_JSON". For Avro, specify "AVRO". For parquet, specify "PARQUET". For orc, specify "ORC". The default value is CSV.
"sourceUris": [ # [Required] The fully-qualified URIs that point to your data in Google Cloud. For Google Cloud Storage URIs: Each URI can contain one '*' wildcard character and it must come after the 'bucket' name. Size limits related to load jobs apply to external data sources. For Google Cloud Bigtable URIs: Exactly one URI can be specified and it has be a fully specified and valid HTTPS URL for a Google Cloud Bigtable table. For Google Cloud Datastore backups: Exactly one URI can be specified. Also, the '*' wildcard character is not allowed.
"A String",
],
"timePartitioning": { # Time-based partitioning specification for the destination table. Only one of timePartitioning and rangePartitioning should be specified.
- "expirationMs": "A String", # [Optional] Number of milliseconds for which to keep the storage for partitions in the table. The storage in a partition will have an expiration time of its partition time plus this value.
- "field": "A String", # [Beta] [Optional] If not set, the table is partitioned by pseudo column, referenced via either '_PARTITIONTIME' as TIMESTAMP type, or '_PARTITIONDATE' as DATE type. If field is specified, the table is instead partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED.
- "requirePartitionFilter": True or False,
- "type": "A String", # [Required] The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively. When the type is not specified, the default behavior is DAY.
+ "expirationMs": "A String", # Optional. Number of milliseconds for which to keep the storage for a partition. A wrapper is used here because 0 is an invalid value.
+ "field": "A String", # Optional. If not set, the table is partitioned by pseudo column '_PARTITIONTIME'; if set, the table is partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED. A wrapper is used here because an empty string is an invalid value.
+ "requirePartitionFilter": false, # If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. This field is deprecated; please set the field with the same name on the table itself instead. This field needs a wrapper because we want to output the default value, false, if the user explicitly set it.
+ "type": "A String", # Required. The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively.
},
- "useAvroLogicalTypes": True or False, # [Optional] If sourceFormat is set to "AVRO", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER).
- "writeDisposition": "A String", # [Optional] Specifies the action that occurs if the destination table already exists. The following values are supported: WRITE_TRUNCATE: If the table already exists, BigQuery overwrites the table data. WRITE_APPEND: If the table already exists, BigQuery appends the data to the table. WRITE_EMPTY: If the table already exists and contains data, a 'duplicate' error is returned in the job result. The default value is WRITE_APPEND. Each action is atomic and only occurs if BigQuery is able to complete the job successfully. Creation, truncation and append actions occur as one atomic update upon job completion.
+ "useAvroLogicalTypes": True or False, # Optional. If sourceFormat is set to "AVRO", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER).
+ "writeDisposition": "A String", # Optional. Specifies the action that occurs if the destination table already exists. The following values are supported: * WRITE_TRUNCATE: If the table already exists, BigQuery overwrites the data, removes the constraints and uses the schema from the load job. * WRITE_APPEND: If the table already exists, BigQuery appends the data to the table. * WRITE_EMPTY: If the table already exists and contains data, a 'duplicate' error is returned in the job result. The default value is WRITE_APPEND. Each action is atomic and only occurs if BigQuery is able to complete the job successfully. Creation, truncation and append actions occur as one atomic update upon job completion.
},
- "query": { # [Pick one] Configures a query job.
- "allowLargeResults": false, # [Optional] If true and query uses legacy SQL dialect, allows the query to produce arbitrarily large result tables at a slight cost in performance. Requires destinationTable to be set. For standard SQL queries, this flag is ignored and large results are always allowed. However, you must still set destinationTable when result size exceeds the allowed maximum response size.
- "clustering": { # [Beta] Clustering specification for the destination table. Must be specified with time-based partitioning, data in the table will be first partitioned and subsequently clustered.
- "fields": [ # [Repeated] One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. When you cluster a table using multiple columns, the order of columns you specify is important. The order of the specified columns determines the sort order of the data.
+ "query": { # JobConfigurationQuery configures a BigQuery query job. # [Pick one] Configures a query job.
+ "allowLargeResults": false, # Optional. If true and query uses legacy SQL dialect, allows the query to produce arbitrarily large result tables at a slight cost in performance. Requires destinationTable to be set. For GoogleSQL queries, this flag is ignored and large results are always allowed. However, you must still set destinationTable when result size exceeds the allowed maximum response size.
+ "clustering": { # Configures table clustering. # Clustering specification for the destination table.
+ "fields": [ # One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. The ordering of the clustering fields should be prioritized from most to least important for filtering purposes. Additional information on limitations can be found here: https://cloud.google.com/bigquery/docs/creating-clustered-tables#limitations
"A String",
],
},
- "connectionProperties": [ # Connection properties.
- {
- "key": "A String", # [Required] Name of the connection property to set.
- "value": "A String", # [Required] Value of the connection property.
+ "connectionProperties": [ # Connection properties which can modify the query behavior.
+ { # A connection-level property to customize query behavior. Under JDBC, these correspond directly to connection properties passed to the DriverManager. Under ODBC, these correspond to properties in the connection string. Currently supported connection properties: * **dataset_project_id**: represents the default project for datasets that are used in the query. Setting the system variable `@@dataset_project_id` achieves the same behavior. For more information about system variables, see: https://cloud.google.com/bigquery/docs/reference/system-variables * **time_zone**: represents the default timezone used to run the query. * **session_id**: associates the query with a given session. * **query_label**: associates the query with a given job label. If set, all subsequent queries in a script or session will have this label. For the format in which a you can specify a query label, see labels in the JobConfiguration resource type: https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#jobconfiguration Additional properties are allowed, but ignored. Specifying multiple connection properties with the same key returns an error.
+ "key": "A String", # The key of the property to set.
+ "value": "A String", # The value of the property to set.
},
],
"continuous": True or False, # [Optional] Specifies whether the query should be executed as a continuous query. The default value is false.
- "createDisposition": "A String", # [Optional] Specifies whether the job is allowed to create new tables. The following values are supported: CREATE_IF_NEEDED: If the table does not exist, BigQuery creates the table. CREATE_NEVER: The table must already exist. If it does not, a 'notFound' error is returned in the job result. The default value is CREATE_IF_NEEDED. Creation, truncation and append actions occur as one atomic update upon job completion.
- "createSession": True or False, # If true, creates a new session, where session id will be a server generated random id. If false, runs query with an existing session_id passed in ConnectionProperty, otherwise runs query in non-session mode.
- "defaultDataset": { # [Optional] Specifies the default dataset to use for unqualified table names in the query. Note that this does not alter behavior of unqualified dataset names.
- "datasetId": "A String", # [Required] A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- "projectId": "A String", # [Optional] The ID of the project containing this dataset.
+ "createDisposition": "A String", # Optional. Specifies whether the job is allowed to create new tables. The following values are supported: * CREATE_IF_NEEDED: If the table does not exist, BigQuery creates the table. * CREATE_NEVER: The table must already exist. If it does not, a 'notFound' error is returned in the job result. The default value is CREATE_IF_NEEDED. Creation, truncation and append actions occur as one atomic update upon job completion.
+ "createSession": True or False, # If this property is true, the job creates a new session using a randomly generated session_id. To continue using a created session with subsequent queries, pass the existing session identifier as a `ConnectionProperty` value. The session identifier is returned as part of the `SessionInfo` message within the query statistics. The new session's location will be set to `Job.JobReference.location` if it is present, otherwise it's set to the default location based on existing routing logic.
+ "defaultDataset": { # Optional. Specifies the default dataset to use for unqualified table names in the query. This setting does not alter behavior of unqualified dataset names. Setting the system variable `@@dataset_id` achieves the same behavior. See https://cloud.google.com/bigquery/docs/reference/system-variables for more information on system variables.
+ "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "projectId": "A String", # Optional. The ID of the project containing this dataset.
},
- "destinationEncryptionConfiguration": { # Custom encryption configuration (e.g., Cloud KMS keys).
+ "destinationEncryptionConfiguration": { # Custom encryption configuration (e.g., Cloud KMS keys)
"kmsKeyName": "A String", # Optional. Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key.
},
- "destinationTable": { # [Optional] Describes the table where the query results should be stored. If not present, a new table will be created to store the results. This property must be set for large results that exceed the maximum response size.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "destinationTable": { # Optional. Describes the table where the query results should be stored. This property must be set for large results that exceed the maximum response size. For queries that produce anonymous (cached) results, this field will be populated by BigQuery.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
- "flattenResults": true, # [Optional] If true and query uses legacy SQL dialect, flattens all nested and repeated fields in the query results. allowLargeResults must be true if this is set to false. For standard SQL queries, this flag is ignored and results are never flattened.
- "maximumBillingTier": 1, # [Optional] Limits the billing tier for this job. Queries that have resource usage beyond this tier will fail (without incurring a charge). If unspecified, this will be set to your project default.
- "maximumBytesBilled": "A String", # [Optional] Limits the bytes billed for this job. Queries that will have bytes billed beyond this limit will fail (without incurring a charge). If unspecified, this will be set to your project default.
- "parameterMode": "A String", # Standard SQL only. Set to POSITIONAL to use positional (?) query parameters or to NAMED to use named (@myparam) query parameters in this query.
+ "flattenResults": true, # Optional. If true and query uses legacy SQL dialect, flattens all nested and repeated fields in the query results. allowLargeResults must be true if this is set to false. For GoogleSQL queries, this flag is ignored and results are never flattened.
+ "maximumBillingTier": 1, # Optional. [Deprecated] Maximum billing tier allowed for this query. The billing tier controls the amount of compute resources allotted to the query, and multiplies the on-demand cost of the query accordingly. A query that runs within its allotted resources will succeed and indicate its billing tier in statistics.query.billingTier, but if the query exceeds its allotted resources, it will fail with billingTierLimitExceeded. WARNING: The billed byte amount can be multiplied by an amount up to this number! Most users should not need to alter this setting, and we recommend that you avoid introducing new uses of it.
+ "maximumBytesBilled": "A String", # Limits the bytes billed for this job. Queries that will have bytes billed beyond this limit will fail (without incurring a charge). If unspecified, this will be set to your project default.
+ "parameterMode": "A String", # GoogleSQL only. Set to POSITIONAL to use positional (?) query parameters or to NAMED to use named (@myparam) query parameters in this query.
"preserveNulls": True or False, # [Deprecated] This property is deprecated.
- "priority": "A String", # [Optional] Specifies a priority for the query. Possible values include INTERACTIVE and BATCH. The default value is INTERACTIVE.
- "query": "A String", # [Required] SQL query text to execute. The useLegacySql field can be used to indicate whether the query uses legacy SQL or standard SQL.
- "queryParameters": [ # Query parameters for standard SQL queries.
- {
- "name": "A String", # [Optional] If unset, this is a positional parameter. Otherwise, should be unique within a query.
- "parameterType": { # [Required] The type of this parameter.
- "arrayType": # Object with schema name: QueryParameterType # [Optional] The type of the array's elements, if this is an array.
- "rangeElementType": # Object with schema name: QueryParameterType # [Optional] The element type of the range, if this is a range.
- "structTypes": [ # [Optional] The types of the fields of this struct, in order, if this is a struct.
- {
- "description": "A String", # [Optional] Human-oriented description of the field.
- "name": "A String", # [Optional] The name of this field.
- "type": # Object with schema name: QueryParameterType # [Required] The type of this field.
+ "priority": "A String", # Optional. Specifies a priority for the query. Possible values include INTERACTIVE and BATCH. The default value is INTERACTIVE.
+ "query": "A String", # [Required] SQL query text to execute. The useLegacySql field can be used to indicate whether the query uses legacy SQL or GoogleSQL.
+ "queryParameters": [ # Query parameters for GoogleSQL queries.
+ { # A parameter given to a query.
+ "name": "A String", # Optional. If unset, this is a positional parameter. Otherwise, should be unique within a query.
+ "parameterType": { # The type of a query parameter. # Required. The type of this parameter.
+ "arrayType": # Object with schema name: QueryParameterType # Optional. The type of the array's elements, if this is an array.
+ "rangeElementType": # Object with schema name: QueryParameterType # Optional. The element type of the range, if this is a range.
+ "structTypes": [ # Optional. The types of the fields of this struct, in order, if this is a struct.
+ { # The type of a struct parameter.
+ "description": "A String", # Optional. Human-oriented description of the field.
+ "name": "A String", # Optional. The name of this field.
+ "type": # Object with schema name: QueryParameterType # Required. The type of this field.
},
],
- "type": "A String", # [Required] The top level type of this field.
+ "type": "A String", # Required. The top level type of this field.
},
- "parameterValue": { # [Required] The value of this parameter.
- "arrayValues": [ # [Optional] The array values, if this is an array type.
+ "parameterValue": { # The value of a query parameter. # Required. The value of this parameter.
+ "arrayValues": [ # Optional. The array values, if this is an array type.
# Object with schema name: QueryParameterValue
],
- "rangeValue": { # [Optional] The range value, if this is a range type.
- "end": # Object with schema name: QueryParameterValue
- "start": # Object with schema name: QueryParameterValue
+ "rangeValue": { # Represents the value of a range. # Optional. The range value, if this is a range type.
+ "end": # Object with schema name: QueryParameterValue # Optional. The end value of the range. A missing value represents an unbounded end.
+ "start": # Object with schema name: QueryParameterValue # Optional. The start value of the range. A missing value represents an unbounded start.
},
- "structValues": { # [Optional] The struct field values, in order of the struct type's declaration.
+ "structValues": { # The struct field values.
"a_key": # Object with schema name: QueryParameterValue
},
- "value": "A String", # [Optional] The value of this value, if a simple scalar type.
+ "value": "A String", # Optional. The value of this value, if a simple scalar type.
},
},
],
- "rangePartitioning": { # [TrustedTester] Range partitioning specification for this table. Only one of timePartitioning and rangePartitioning should be specified.
- "field": "A String", # [TrustedTester] [Required] The table is partitioned by this field. The field must be a top-level NULLABLE/REQUIRED field. The only supported type is INTEGER/INT64.
- "range": { # [TrustedTester] [Required] Defines the ranges for range partitioning.
- "end": "A String", # [TrustedTester] [Required] The end of range partitioning, exclusive.
- "interval": "A String", # [TrustedTester] [Required] The width of each interval.
- "start": "A String", # [TrustedTester] [Required] The start of range partitioning, inclusive.
+ "rangePartitioning": { # Range partitioning specification for the destination table. Only one of timePartitioning and rangePartitioning should be specified.
+ "field": "A String", # Required. [Experimental] The table is partitioned by this field. The field must be a top-level NULLABLE/REQUIRED field. The only supported type is INTEGER/INT64.
+ "range": { # [Experimental] Defines the ranges for range partitioning.
+ "end": "A String", # [Experimental] The end of range partitioning, exclusive.
+ "interval": "A String", # [Experimental] The width of each interval.
+ "start": "A String", # [Experimental] The start of range partitioning, inclusive.
},
},
- "schemaUpdateOptions": [ # Allows the schema of the destination table to be updated as a side effect of the query job. Schema update options are supported in two cases: when writeDisposition is WRITE_APPEND; when writeDisposition is WRITE_TRUNCATE and the destination table is a partition of a table, specified by partition decorators. For normal tables, WRITE_TRUNCATE will always overwrite the schema. One or more of the following values are specified: ALLOW_FIELD_ADDITION: allow adding a nullable field to the schema. ALLOW_FIELD_RELAXATION: allow relaxing a required field in the original schema to nullable.
+ "schemaUpdateOptions": [ # Allows the schema of the destination table to be updated as a side effect of the query job. Schema update options are supported in two cases: when writeDisposition is WRITE_APPEND; when writeDisposition is WRITE_TRUNCATE and the destination table is a partition of a table, specified by partition decorators. For normal tables, WRITE_TRUNCATE will always overwrite the schema. One or more of the following values are specified: * ALLOW_FIELD_ADDITION: allow adding a nullable field to the schema. * ALLOW_FIELD_RELAXATION: allow relaxing a required field in the original schema to nullable.
"A String",
],
- "tableDefinitions": { # [Optional] If querying an external data source outside of BigQuery, describes the data format, location and other properties of the data source. By defining these properties, the data source can then be queried as if it were a standard BigQuery table.
+ "scriptOptions": { # Options related to script execution. # Options controlling the execution of scripts.
+ "keyResultStatement": "A String", # Determines which statement in the script represents the "key result", used to populate the schema and query results of the script job. Default is LAST.
+ "statementByteBudget": "A String", # Limit on the number of bytes billed per statement. Exceeding this budget results in an error.
+ "statementTimeoutMs": "A String", # Timeout period for each statement in a script.
+ },
+ "systemVariables": { # System variables given to a query. # Output only. System variables for GoogleSQL queries. A system variable is output if the variable is settable and its value differs from the system default. "@@" prefix is not included in the name of the System variables.
+ "types": { # Output only. Data type for each system variable.
+ "a_key": { # The data type of a variable such as a function argument. Examples include: * INT64: `{"typeKind": "INT64"}` * ARRAY: { "typeKind": "ARRAY", "arrayElementType": {"typeKind": "STRING"} } * STRUCT>: { "typeKind": "STRUCT", "structType": { "fields": [ { "name": "x", "type": {"typeKind": "STRING"} }, { "name": "y", "type": { "typeKind": "ARRAY", "arrayElementType": {"typeKind": "DATE"} } } ] } }
+ "arrayElementType": # Object with schema name: StandardSqlDataType # The type of the array's elements, if type_kind = "ARRAY".
+ "rangeElementType": # Object with schema name: StandardSqlDataType # The type of the range's elements, if type_kind = "RANGE".
+ "structType": { # The representation of a SQL STRUCT type. # The fields of this struct, in order, if type_kind = "STRUCT".
+ "fields": [ # Fields within the struct.
+ { # A field or a column.
+ "name": "A String", # Optional. The name of this field. Can be absent for struct fields.
+ "type": # Object with schema name: StandardSqlDataType # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
+ },
+ ],
+ },
+ "typeKind": "A String", # Required. The top level type of this field. Can be any GoogleSQL data type (e.g., "INT64", "DATE", "ARRAY").
+ },
+ },
+ "values": { # Output only. Value for each system variable.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "tableDefinitions": { # Optional. You can specify external table definitions, which operate as ephemeral tables that can be queried. These definitions are configured using a JSON map, where the string key represents the table identifier, and the value is the corresponding external data configuration object.
"a_key": {
"autodetect": True or False, # Try to detect schema and format options automatically. Any option specified explicitly will be honored.
- "avroOptions": { # Additional properties to set if sourceFormat is set to Avro.
- "useAvroLogicalTypes": True or False, # [Optional] If sourceFormat is set to "AVRO", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER).
- },
- "bigtableOptions": { # [Optional] Additional options if sourceFormat is set to BIGTABLE.
- "columnFamilies": [ # [Optional] List of column families to expose in the table schema along with their types. This list restricts the column families that can be referenced in queries and specifies their value types. You can use this list to do type conversions - see the 'type' field for more details. If you leave this list empty, all column families are present in the table schema and their values are read as BYTES. During a query only the column families referenced in that query are read from Bigtable.
- {
- "columns": [ # [Optional] Lists of columns that should be exposed as individual fields as opposed to a list of (column name, value) pairs. All columns whose qualifier matches a qualifier in this list can be accessed as .. Other columns can be accessed as a list through .Column field.
- {
- "encoding": "A String", # [Optional] The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. 'encoding' can also be set at the column family level. However, the setting at this level takes precedence if 'encoding' is set at both levels.
- "fieldName": "A String", # [Optional] If the qualifier is not a valid BigQuery field identifier i.e. does not match [a-zA-Z][a-zA-Z0-9_]*, a valid identifier must be provided as the column field name and is used as field name in queries.
- "onlyReadLatest": True or False, # [Optional] If this is set, only the latest version of value in this column are exposed. 'onlyReadLatest' can also be set at the column family level. However, the setting at this level takes precedence if 'onlyReadLatest' is set at both levels.
- "qualifierEncoded": "A String", # [Required] Qualifier of the column. Columns in the parent column family that has this exact qualifier are exposed as . field. If the qualifier is valid UTF-8 string, it can be specified in the qualifier_string field. Otherwise, a base-64 encoded value must be set to qualifier_encoded. The column field name is the same as the column qualifier. However, if the qualifier is not a valid BigQuery field identifier i.e. does not match [a-zA-Z][a-zA-Z0-9_]*, a valid identifier must be provided as field_name.
- "qualifierString": "A String",
- "type": "A String", # [Optional] The type to convert the value in cells of this column. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive) - BYTES STRING INTEGER FLOAT BOOLEAN Default type is BYTES. 'type' can also be set at the column family level. However, the setting at this level takes precedence if 'type' is set at both levels.
- },
- ],
- "encoding": "A String", # [Optional] The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. This can be overridden for a specific column by listing that column in 'columns' and specifying an encoding for it.
+ "avroOptions": { # Options for external data sources. # Optional. Additional properties to set if sourceFormat is set to AVRO.
+ "useAvroLogicalTypes": True or False, # Optional. If sourceFormat is set to "AVRO", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER).
+ },
+ "bigtableOptions": { # Options specific to Google Cloud Bigtable data sources. # Optional. Additional options if sourceFormat is set to BIGTABLE.
+ "columnFamilies": [ # Optional. List of column families to expose in the table schema along with their types. This list restricts the column families that can be referenced in queries and specifies their value types. You can use this list to do type conversions - see the 'type' field for more details. If you leave this list empty, all column families are present in the table schema and their values are read as BYTES. During a query only the column families referenced in that query are read from Bigtable.
+ { # Information related to a Bigtable column family.
+ "columns": [ # Optional. Lists of columns that should be exposed as individual fields as opposed to a list of (column name, value) pairs. All columns whose qualifier matches a qualifier in this list can be accessed as .. Other columns can be accessed as a list through .Column field.
+ { # Information related to a Bigtable column.
+ "encoding": "A String", # Optional. The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. 'encoding' can also be set at the column family level. However, the setting at this level takes precedence if 'encoding' is set at both levels.
+ "fieldName": "A String", # Optional. If the qualifier is not a valid BigQuery field identifier i.e. does not match a-zA-Z*, a valid identifier must be provided as the column field name and is used as field name in queries.
+ "onlyReadLatest": True or False, # Optional. If this is set, only the latest version of value in this column are exposed. 'onlyReadLatest' can also be set at the column family level. However, the setting at this level takes precedence if 'onlyReadLatest' is set at both levels.
+ "qualifierEncoded": "A String", # [Required] Qualifier of the column. Columns in the parent column family that has this exact qualifier are exposed as . field. If the qualifier is valid UTF-8 string, it can be specified in the qualifier_string field. Otherwise, a base-64 encoded value must be set to qualifier_encoded. The column field name is the same as the column qualifier. However, if the qualifier is not a valid BigQuery field identifier i.e. does not match a-zA-Z*, a valid identifier must be provided as field_name.
+ "qualifierString": "A String", # Qualifier string.
+ "type": "A String", # Optional. The type to convert the value in cells of this column. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive): * BYTES * STRING * INTEGER * FLOAT * BOOLEAN * JSON Default type is BYTES. 'type' can also be set at the column family level. However, the setting at this level takes precedence if 'type' is set at both levels.
+ },
+ ],
+ "encoding": "A String", # Optional. The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. This can be overridden for a specific column by listing that column in 'columns' and specifying an encoding for it.
"familyId": "A String", # Identifier of the column family.
- "onlyReadLatest": True or False, # [Optional] If this is set only the latest version of value are exposed for all columns in this column family. This can be overridden for a specific column by listing that column in 'columns' and specifying a different setting for that column.
- "type": "A String", # [Optional] The type to convert the value in cells of this column family. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive) - BYTES STRING INTEGER FLOAT BOOLEAN Default type is BYTES. This can be overridden for a specific column by listing that column in 'columns' and specifying a type for it.
+ "onlyReadLatest": True or False, # Optional. If this is set only the latest version of value are exposed for all columns in this column family. This can be overridden for a specific column by listing that column in 'columns' and specifying a different setting for that column.
+ "type": "A String", # Optional. The type to convert the value in cells of this column family. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive): * BYTES * STRING * INTEGER * FLOAT * BOOLEAN * JSON Default type is BYTES. This can be overridden for a specific column by listing that column in 'columns' and specifying a type for it.
},
],
- "ignoreUnspecifiedColumnFamilies": True or False, # [Optional] If field is true, then the column families that are not specified in columnFamilies list are not exposed in the table schema. Otherwise, they are read with BYTES type values. The default value is false.
- "readRowkeyAsString": True or False, # [Optional] If field is true, then the rowkey column families will be read and converted to string. Otherwise they are read with BYTES type values and users need to manually cast them with CAST if necessary. The default value is false.
- },
- "compression": "A String", # [Optional] The compression type of the data source. Possible values include GZIP and NONE. The default value is NONE. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups and Avro formats.
- "connectionId": "A String", # [Optional, Trusted Tester] Connection for external data source.
- "csvOptions": { # Additional properties to set if sourceFormat is set to CSV.
- "allowJaggedRows": True or False, # [Optional] Indicates if BigQuery should accept rows that are missing trailing optional columns. If true, BigQuery treats missing trailing columns as null values. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false.
- "allowQuotedNewlines": True or False, # [Optional] Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false.
- "encoding": "A String", # [Optional] The character encoding of the data. The supported values are UTF-8 or ISO-8859-1. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the quote and fieldDelimiter properties.
- "fieldDelimiter": "A String", # [Optional] The separator for fields in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. BigQuery also supports the escape sequence "\t" to specify a tab separator. The default value is a comma (',').
- "nullMarker": "A String", # [Optional] An custom string that will represent a NULL value in CSV import data.
- "preserveAsciiControlCharacters": True or False, # [Optional] Preserves the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\x00' to '\x1F') when loading from CSV. Only applicable to CSV, ignored for other formats.
- "quote": """, # [Optional] The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ('"'). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true.
- "skipLeadingRows": "A String", # [Optional] The number of rows at the top of a CSV file that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
- },
- "decimalTargetTypes": [ # [Optional] Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown. Example: Suppose the value of this field is ["NUMERIC", "BIGNUMERIC"]. If (precision,scale) is: (38,9) -> NUMERIC; (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits); (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits); (76,38) -> BIGNUMERIC; (77,38) -> BIGNUMERIC (error if value exeeds supported range). This field cannot contain duplicate types. The order of the types in this field is ignored. For example, ["BIGNUMERIC", "NUMERIC"] is the same as ["NUMERIC", "BIGNUMERIC"] and NUMERIC always takes precedence over BIGNUMERIC. Defaults to ["NUMERIC", "STRING"] for ORC and ["NUMERIC"] for the other file formats.
+ "ignoreUnspecifiedColumnFamilies": True or False, # Optional. If field is true, then the column families that are not specified in columnFamilies list are not exposed in the table schema. Otherwise, they are read with BYTES type values. The default value is false.
+ "outputColumnFamiliesAsJson": True or False, # Optional. If field is true, then each column family will be read as a single JSON column. Otherwise they are read as a repeated cell structure containing timestamp/value tuples. The default value is false.
+ "readRowkeyAsString": True or False, # Optional. If field is true, then the rowkey column families will be read and converted to string. Otherwise they are read with BYTES type values and users need to manually cast them with CAST if necessary. The default value is false.
+ },
+ "compression": "A String", # Optional. The compression type of the data source. Possible values include GZIP and NONE. The default value is NONE. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups, Avro, ORC and Parquet formats. An empty string is an invalid value.
+ "connectionId": "A String", # Optional. The connection specifying the credentials to be used to read external storage, such as Azure Blob, Cloud Storage, or S3. The connection_id can have the form "<project\_id>.<location\_id>.<connection\_id>" or "projects/<project\_id>/locations/<location\_id>/connections/<connection\_id>".
+ "csvOptions": { # Information related to a CSV data source. # Optional. Additional properties to set if sourceFormat is set to CSV.
+ "allowJaggedRows": True or False, # Optional. Indicates if BigQuery should accept rows that are missing trailing optional columns. If true, BigQuery treats missing trailing columns as null values. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false.
+ "allowQuotedNewlines": True or False, # Optional. Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false.
+ "encoding": "A String", # Optional. The character encoding of the data. The supported values are UTF-8, ISO-8859-1, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the quote and fieldDelimiter properties.
+ "fieldDelimiter": "A String", # Optional. The separator character for fields in a CSV file. The separator is interpreted as a single byte. For files encoded in ISO-8859-1, any single character can be used as a separator. For files encoded in UTF-8, characters represented in decimal range 1-127 (U+0001-U+007F) can be used without any modification. UTF-8 characters encoded with multiple bytes (i.e. U+0080 and above) will have only the first byte used for separating fields. The remaining bytes will be treated as a part of the field. BigQuery also supports the escape sequence "\t" (U+0009) to specify a tab separator. The default value is comma (",", U+002C).
+ "nullMarker": "A String", # [Optional] A custom string that will represent a NULL value in CSV import data.
+ "preserveAsciiControlCharacters": True or False, # Optional. Indicates if the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\x00' to '\x1F') are preserved.
+ "quote": """, # Optional. The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ("). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true. To include the specific quote character within a quoted value, precede it with an additional matching quote character. For example, if you want to escape the default character ' " ', use ' "" '.
+ "skipLeadingRows": "A String", # Optional. The number of rows at the top of a CSV file that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
+ },
+ "decimalTargetTypes": [ # Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown. Example: Suppose the value of this field is ["NUMERIC", "BIGNUMERIC"]. If (precision,scale) is: * (38,9) -> NUMERIC; * (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits); * (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits); * (76,38) -> BIGNUMERIC; * (77,38) -> BIGNUMERIC (error if value exeeds supported range). This field cannot contain duplicate types. The order of the types in this field is ignored. For example, ["BIGNUMERIC", "NUMERIC"] is the same as ["NUMERIC", "BIGNUMERIC"] and NUMERIC always takes precedence over BIGNUMERIC. Defaults to ["NUMERIC", "STRING"] for ORC and ["NUMERIC"] for the other file formats.
"A String",
],
- "fileSetSpecType": "A String", # [Optional] Specifies how source URIs are interpreted for constructing the file set to load. By default source URIs are expanded against the underlying storage. Other options include specifying manifest files. Only applicable to object storage systems.
- "googleSheetsOptions": { # [Optional] Additional options if sourceFormat is set to GOOGLE_SHEETS.
- "range": "A String", # [Optional] Range of a sheet to query from. Only used when non-empty. Typical format: sheet_name!top_left_cell_id:bottom_right_cell_id For example: sheet1!A1:B20
- "skipLeadingRows": "A String", # [Optional] The number of rows at the top of a sheet that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows that should be skipped. When autodetect is on, behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
+ "fileSetSpecType": "A String", # Optional. Specifies how source URIs are interpreted for constructing the file set to load. By default source URIs are expanded against the underlying storage. Other options include specifying manifest files. Only applicable to object storage systems.
+ "googleSheetsOptions": { # Options specific to Google Sheets data sources. # Optional. Additional options if sourceFormat is set to GOOGLE_SHEETS.
+ "range": "A String", # Optional. Range of a sheet to query from. Only used when non-empty. Typical format: sheet_name!top_left_cell_id:bottom_right_cell_id For example: sheet1!A1:B20
+ "skipLeadingRows": "A String", # Optional. The number of rows at the top of a sheet that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
},
- "hivePartitioningOptions": { # [Optional] Options to configure hive partitioning support.
- "fields": [ # [Output-only] For permanent external tables, this field is populated with the hive partition keys in the order they were inferred. The types of the partition keys can be deduced by checking the table schema (which will include the partition keys). Not every API will populate this field in the output. For example, Tables.Get will populate it, but Tables.List will not contain this field.
+ "hivePartitioningOptions": { # Options for configuring hive partitioning detect. # Optional. When set, configures hive partitioning support. Not all storage formats support hive partitioning -- requesting hive partitioning on an unsupported format will lead to an error, as will providing an invalid specification.
+ "fields": [ # Output only. For permanent external tables, this field is populated with the hive partition keys in the order they were inferred. The types of the partition keys can be deduced by checking the table schema (which will include the partition keys). Not every API will populate this field in the output. For example, Tables.Get will populate it, but Tables.List will not contain this field.
"A String",
],
- "mode": "A String", # [Optional] When set, what mode of hive partitioning to use when reading data. The following modes are supported. (1) AUTO: automatically infer partition key name(s) and type(s). (2) STRINGS: automatically infer partition key name(s). All types are interpreted as strings. (3) CUSTOM: partition key schema is encoded in the source URI prefix. Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported types include: AVRO, CSV, JSON, ORC and Parquet.
- "requirePartitionFilter": True or False, # [Optional] If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. Note that this field should only be true when creating a permanent external table or querying a temporary external table. Hive-partitioned loads with requirePartitionFilter explicitly set to true will fail.
- "sourceUriPrefix": "A String", # [Optional] When hive partition detection is requested, a common prefix for all source uris should be supplied. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout. gs://bucket/path_to_table/dt=2019-01-01/country=BR/id=7/file.avro gs://bucket/path_to_table/dt=2018-12-31/country=CA/id=3/file.avro When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/ (trailing slash does not matter).
- },
- "ignoreUnknownValues": True or False, # [Optional] Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names Google Cloud Bigtable: This setting is ignored. Google Cloud Datastore backups: This setting is ignored. Avro: This setting is ignored.
- "jsonOptions": { # Additional properties to set if `sourceFormat` is set to `NEWLINE_DELIMITED_JSON`.
- "encoding": "A String", # [Optional] The character encoding of the data. The supported values are UTF-8, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8.
- },
- "maxBadRecords": 42, # [Optional] The maximum number of bad records that BigQuery can ignore when reading data. If the number of bad records exceeds this value, an invalid error is returned in the job result. This is only valid for CSV, JSON, and Google Sheets. The default value is 0, which requires that all records are valid. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups and Avro formats.
- "metadataCacheMode": "A String", # [Optional] Metadata Cache Mode for the table. Set this to enable caching of metadata from external data source.
- "objectMetadata": "A String", # ObjectMetadata is used to create Object Tables. Object Tables contain a listing of objects (with their metadata) found at the source_uris. If ObjectMetadata is set, source_format should be omitted. Currently SIMPLE is the only supported Object Metadata type.
- "parquetOptions": { # Additional properties to set if sourceFormat is set to Parquet.
- "enableListInference": True or False, # [Optional] Indicates whether to use schema inference specifically for Parquet LIST logical type.
- "enumAsString": True or False, # [Optional] Indicates whether to infer Parquet ENUM logical type as STRING instead of BYTES by default.
- },
- "referenceFileSchemaUri": "A String", # [Optional] Provide a referencing file with the expected table schema. Enabled for the format: AVRO, PARQUET, ORC.
- "schema": { # [Optional] The schema for the data. Schema is required for CSV and JSON formats. Schema is disallowed for Google Cloud Bigtable, Cloud Datastore backups, and Avro formats.
+ "mode": "A String", # Optional. When set, what mode of hive partitioning to use when reading data. The following modes are supported: * AUTO: automatically infer partition key name(s) and type(s). * STRINGS: automatically infer partition key name(s). All types are strings. * CUSTOM: partition key schema is encoded in the source URI prefix. Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported formats are: JSON, CSV, ORC, Avro and Parquet.
+ "requirePartitionFilter": false, # Optional. If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. Note that this field should only be true when creating a permanent external table or querying a temporary external table. Hive-partitioned loads with require_partition_filter explicitly set to true will fail.
+ "sourceUriPrefix": "A String", # Optional. When hive partition detection is requested, a common prefix for all source uris must be required. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout: gs://bucket/path_to_table/dt=2019-06-01/country=USA/id=7/file.avro gs://bucket/path_to_table/dt=2019-05-31/country=CA/id=3/file.avro When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/. CUSTOM detection requires encoding the partitioning schema immediately after the common prefix. For CUSTOM, any of * gs://bucket/path_to_table/{dt:DATE}/{country:STRING}/{id:INTEGER} * gs://bucket/path_to_table/{dt:STRING}/{country:STRING}/{id:INTEGER} * gs://bucket/path_to_table/{dt:DATE}/{country:STRING}/{id:STRING} would all be valid source URI prefixes.
+ },
+ "ignoreUnknownValues": True or False, # Optional. Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names Google Cloud Bigtable: This setting is ignored. Google Cloud Datastore backups: This setting is ignored. Avro: This setting is ignored. ORC: This setting is ignored. Parquet: This setting is ignored.
+ "jsonExtension": "A String", # Optional. Load option to be used together with source_format newline-delimited JSON to indicate that a variant of JSON is being loaded. To load newline-delimited GeoJSON, specify GEOJSON (and source_format must be set to NEWLINE_DELIMITED_JSON).
+ "jsonOptions": { # Json Options for load and make external tables. # Optional. Additional properties to set if sourceFormat is set to JSON.
+ "encoding": "A String", # Optional. The character encoding of the data. The supported values are UTF-8, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8.
+ },
+ "maxBadRecords": 42, # Optional. The maximum number of bad records that BigQuery can ignore when reading data. If the number of bad records exceeds this value, an invalid error is returned in the job result. The default value is 0, which requires that all records are valid. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups, Avro, ORC and Parquet formats.
+ "metadataCacheMode": "A String", # Optional. Metadata Cache Mode for the table. Set this to enable caching of metadata from external data source.
+ "objectMetadata": "A String", # Optional. ObjectMetadata is used to create Object Tables. Object Tables contain a listing of objects (with their metadata) found at the source_uris. If ObjectMetadata is set, source_format should be omitted. Currently SIMPLE is the only supported Object Metadata type.
+ "parquetOptions": { # Parquet Options for load and make external tables. # Optional. Additional properties to set if sourceFormat is set to PARQUET.
+ "enableListInference": True or False, # Optional. Indicates whether to use schema inference specifically for Parquet LIST logical type.
+ "enumAsString": True or False, # Optional. Indicates whether to infer Parquet ENUM logical type as STRING instead of BYTES by default.
+ },
+ "referenceFileSchemaUri": "A String", # Optional. When creating an external table, the user can provide a reference file with the table schema. This is enabled for the following formats: AVRO, PARQUET, ORC.
+ "schema": { # Schema of a table # Optional. The schema for the data. Schema is required for CSV and JSON formats if autodetect is not on. Schema is disallowed for Google Cloud Bigtable, Cloud Datastore backups, Avro, ORC and Parquet formats.
"fields": [ # Describes the fields in a table.
- {
- "categories": { # [Optional] The categories attached to this field, used for field-level access control.
- "names": [ # A list of category resource names. For example, "projects/1/taxonomies/2/categories/3". At most 5 categories are allowed.
+ { # A field in TableSchema
+ "categories": { # Deprecated.
+ "names": [ # Deprecated.
"A String",
],
},
- "collation": "A String", # Optional. Collation specification of the field. It only can be set on string type field.
- "defaultValueExpression": "A String", # Optional. A SQL expression to specify the default value for this field. It can only be set for top level fields (columns). You can use struct or array expression to specify default value for the entire struct or array. The valid SQL expressions are: - Literals for all data types, including STRUCT and ARRAY. - Following functions: - CURRENT_TIMESTAMP - CURRENT_TIME - CURRENT_DATE - CURRENT_DATETIME - GENERATE_UUID - RAND - SESSION_USER - ST_GEOGPOINT - Struct or array composed with the above allowed functions, for example, [CURRENT_DATE(), DATE '2020-01-01']
- "description": "A String", # [Optional] The field description. The maximum length is 1,024 characters.
- "fields": [ # [Optional] Describes the nested schema fields if the type property is set to RECORD.
+ "collation": "A String", # Optional. Field collation can be set only when the type of field is STRING. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.
+ "defaultValueExpression": "A String", # Optional. A SQL expression to specify the [default value] (https://cloud.google.com/bigquery/docs/default-values) for this field.
+ "description": "A String", # Optional. The field description. The maximum length is 1,024 characters.
+ "fields": [ # Optional. Describes the nested schema fields if the type property is set to RECORD.
# Object with schema name: TableFieldSchema
],
- "maxLength": "A String", # [Optional] Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
- "mode": "A String", # [Optional] The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
- "name": "A String", # [Required] The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
- "policyTags": {
- "names": [ # A list of category resource names. For example, "projects/1/location/eu/taxonomies/2/policyTags/3". At most 1 policy tag is allowed.
+ "maxLength": "A String", # Optional. Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
+ "mode": "A String", # Optional. The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
+ "name": "A String", # Required. The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
+ "policyTags": { # Optional. The policy tags attached to this field, used for field-level access control. If not set, defaults to empty policy_tags.
+ "names": [ # A list of policy tag resource names. For example, "projects/1/locations/eu/taxonomies/2/policyTags/3". At most 1 policy tag is currently allowed.
"A String",
],
},
- "precision": "A String", # [Optional] Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: - Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] - Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: - If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. - If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): - If type = "NUMERIC": 1 ≤ precision ≤ 29. - If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
- "rangeElementType": { # Optional. The subtype of the RANGE, if the type of this field is RANGE. If the type is RANGE, this field is required. Possible values for the field element type of a RANGE include: - DATE - DATETIME - TIMESTAMP
- "type": "A String", # The field element type of a RANGE
+ "precision": "A String", # Optional. Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: * Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] * Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: * If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. * If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): * If type = "NUMERIC": 1 ≤ precision ≤ 29. * If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
+ "rangeElementType": { # Represents the type of a field element.
+ "type": "A String", # Required. The type of a field element. See TableFieldSchema.type.
},
- "roundingMode": "A String", # Optional. Rounding Mode specification of the field. It only can be set on NUMERIC or BIGNUMERIC type fields.
- "scale": "A String", # [Optional] See documentation for precision.
- "type": "A String", # [Required] The field data type. Possible values include STRING, BYTES, INTEGER, INT64 (same as INTEGER), FLOAT, FLOAT64 (same as FLOAT), NUMERIC, BIGNUMERIC, BOOLEAN, BOOL (same as BOOLEAN), TIMESTAMP, DATE, TIME, DATETIME, INTERVAL, RECORD (where RECORD indicates that the field contains a nested schema) or STRUCT (same as RECORD).
+ "roundingMode": "A String", # Optional. Specifies the rounding mode to be used when storing values of NUMERIC and BIGNUMERIC type.
+ "scale": "A String", # Optional. See documentation for precision.
+ "type": "A String", # Required. The field data type. Possible values include: * STRING * BYTES * INTEGER (or INT64) * FLOAT (or FLOAT64) * BOOLEAN (or BOOL) * TIMESTAMP * DATE * TIME * DATETIME * GEOGRAPHY * NUMERIC * BIGNUMERIC * JSON * RECORD (or STRUCT) Use of RECORD/STRUCT indicates that the field contains a nested schema.
},
],
},
- "sourceFormat": "A String", # [Required] The data format. For CSV files, specify "CSV". For Google sheets, specify "GOOGLE_SHEETS". For newline-delimited JSON, specify "NEWLINE_DELIMITED_JSON". For Avro files, specify "AVRO". For Google Cloud Datastore backups, specify "DATASTORE_BACKUP". [Beta] For Google Cloud Bigtable, specify "BIGTABLE".
+ "sourceFormat": "A String", # [Required] The data format. For CSV files, specify "CSV". For Google sheets, specify "GOOGLE_SHEETS". For newline-delimited JSON, specify "NEWLINE_DELIMITED_JSON". For Avro files, specify "AVRO". For Google Cloud Datastore backups, specify "DATASTORE_BACKUP". For Apache Iceberg tables, specify "ICEBERG". For ORC files, specify "ORC". For Parquet files, specify "PARQUET". [Beta] For Google Cloud Bigtable, specify "BIGTABLE".
"sourceUris": [ # [Required] The fully-qualified URIs that point to your data in Google Cloud. For Google Cloud Storage URIs: Each URI can contain one '*' wildcard character and it must come after the 'bucket' name. Size limits related to load jobs apply to external data sources. For Google Cloud Bigtable URIs: Exactly one URI can be specified and it has be a fully specified and valid HTTPS URL for a Google Cloud Bigtable table. For Google Cloud Datastore backups, exactly one URI can be specified. Also, the '*' wildcard character is not allowed.
"A String",
],
},
},
"timePartitioning": { # Time-based partitioning specification for the destination table. Only one of timePartitioning and rangePartitioning should be specified.
- "expirationMs": "A String", # [Optional] Number of milliseconds for which to keep the storage for partitions in the table. The storage in a partition will have an expiration time of its partition time plus this value.
- "field": "A String", # [Beta] [Optional] If not set, the table is partitioned by pseudo column, referenced via either '_PARTITIONTIME' as TIMESTAMP type, or '_PARTITIONDATE' as DATE type. If field is specified, the table is instead partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED.
- "requirePartitionFilter": True or False,
- "type": "A String", # [Required] The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively. When the type is not specified, the default behavior is DAY.
+ "expirationMs": "A String", # Optional. Number of milliseconds for which to keep the storage for a partition. A wrapper is used here because 0 is an invalid value.
+ "field": "A String", # Optional. If not set, the table is partitioned by pseudo column '_PARTITIONTIME'; if set, the table is partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED. A wrapper is used here because an empty string is an invalid value.
+ "requirePartitionFilter": false, # If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. This field is deprecated; please set the field with the same name on the table itself instead. This field needs a wrapper because we want to output the default value, false, if the user explicitly set it.
+ "type": "A String", # Required. The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively.
},
- "useLegacySql": true, # Specifies whether to use BigQuery's legacy SQL dialect for this query. The default value is true. If set to false, the query will use BigQuery's standard SQL: https://cloud.google.com/bigquery/sql-reference/ When useLegacySql is set to false, the value of flattenResults is ignored; query will be run as if flattenResults is false.
- "useQueryCache": true, # [Optional] Whether to look for the result in the query cache. The query cache is a best-effort cache that will be flushed whenever tables in the query are modified. Moreover, the query cache is only available when a query does not have a destination table specified. The default value is true.
+ "useLegacySql": true, # Optional. Specifies whether to use BigQuery's legacy SQL dialect for this query. The default value is true. If set to false, the query will use BigQuery's GoogleSQL: https://cloud.google.com/bigquery/sql-reference/ When useLegacySql is set to false, the value of flattenResults is ignored; query will be run as if flattenResults is false.
+ "useQueryCache": true, # Optional. Whether to look for the result in the query cache. The query cache is a best-effort cache that will be flushed whenever tables in the query are modified. Moreover, the query cache is only available when a query does not have a destination table specified. The default value is true.
"userDefinedFunctionResources": [ # Describes user-defined function resources used in the query.
- { # This is used for defining User Defined Function (UDF) resources only when using legacy SQL. Users of Standard SQL should leverage either DDL (e.g. CREATE [TEMPORARY] FUNCTION ... ) or the Routines API to define UDF resources. For additional information on migrating, see: https://cloud.google.com/bigquery/docs/reference/standard-sql/migrating-from-legacy-sql#differences_in_user-defined_javascript_functions
+ { # This is used for defining User Defined Function (UDF) resources only when using legacy SQL. Users of GoogleSQL should leverage either DDL (e.g. CREATE [TEMPORARY] FUNCTION ... ) or the Routines API to define UDF resources. For additional information on migrating, see: https://cloud.google.com/bigquery/docs/reference/standard-sql/migrating-from-legacy-sql#differences_in_user-defined_javascript_functions
"inlineCode": "A String", # [Pick one] An inline resource that contains code for a user-defined function (UDF). Providing a inline code resource is equivalent to providing a URI for a file containing the same code.
"resourceUri": "A String", # [Pick one] A code resource to load from a Google Cloud Storage URI (gs://bucket/path).
},
],
- "writeDisposition": "A String", # [Optional] Specifies the action that occurs if the destination table already exists. The following values are supported: WRITE_TRUNCATE: If the table already exists, BigQuery overwrites the table data and uses the schema from the query result. WRITE_APPEND: If the table already exists, BigQuery appends the data to the table. WRITE_EMPTY: If the table already exists and contains data, a 'duplicate' error is returned in the job result. The default value is WRITE_EMPTY. Each action is atomic and only occurs if BigQuery is able to complete the job successfully. Creation, truncation and append actions occur as one atomic update upon job completion.
+ "writeDisposition": "A String", # Optional. Specifies the action that occurs if the destination table already exists. The following values are supported: * WRITE_TRUNCATE: If the table already exists, BigQuery overwrites the data, removes the constraints, and uses the schema from the query result. * WRITE_APPEND: If the table already exists, BigQuery appends the data to the table. * WRITE_EMPTY: If the table already exists and contains data, a 'duplicate' error is returned in the job result. The default value is WRITE_EMPTY. Each action is atomic and only occurs if BigQuery is able to complete the job successfully. Creation, truncation and append actions occur as one atomic update upon job completion.
},
},
- "etag": "A String", # [Output-only] A hash of this resource.
- "id": "A String", # [Output-only] Opaque ID field of the job
- "jobCreationReason": "", # [Output-only] If set, it provides the reason why a Job was created. If not set, it should be treated as the default: REQUESTED. This feature is not yet available. Jobs will always be created.
- "jobReference": { # [Optional] Reference describing the unique-per-user name of the job.
- "jobId": "A String", # [Required] The ID of the job. The ID must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), or dashes (-). The maximum length is 1,024 characters.
- "location": "A String", # The geographic location of the job. See details at https://cloud.google.com/bigquery/docs/locations#specifying_your_location.
- "projectId": "A String", # [Required] The ID of the project containing this job.
+ "etag": "A String", # Output only. A hash of this resource.
+ "id": "A String", # Output only. Opaque ID field of the job.
+ "jobCreationReason": { # Reason about why a Job was created from a [`jobs.query`](https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs/query) method when used with `JOB_CREATION_OPTIONAL` Job creation mode. For [`jobs.insert`](https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs/insert) method calls it will always be `REQUESTED`. This feature is not yet available. Jobs will always be created. # Output only. If set, it provides the reason why a Job was created. If not set, it should be treated as the default: REQUESTED. This feature is not yet available. Jobs will always be created.
+ "code": "A String", # Output only. Specifies the high level reason why a Job was created.
+ },
+ "jobReference": { # A job reference is a fully qualified identifier for referring to a job. # Optional. Reference describing the unique-per-user name of the job.
+ "jobId": "A String", # Required. The ID of the job. The ID must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), or dashes (-). The maximum length is 1,024 characters.
+ "location": "A String", # Optional. The geographic location of the job. The default value is US. For more information about BigQuery locations, see: https://cloud.google.com/bigquery/docs/locations
+ "projectId": "A String", # Required. The ID of the project containing this job.
},
- "kind": "bigquery#job", # [Output-only] The type of the resource.
- "selfLink": "A String", # [Output-only] A URL that can be used to access this resource again.
- "statistics": { # [Output-only] Information about the job, including starting time and ending time of the job.
- "completionRatio": 3.14, # [TrustedTester] [Output-only] Job progress (0.0 -> 1.0) for LOAD and EXTRACT jobs.
- "copy": { # [Output-only] Statistics for a copy job.
- "copiedLogicalBytes": "A String", # [Output-only] Number of logical bytes copied to the destination table.
- "copiedRows": "A String", # [Output-only] Number of rows copied to the destination table.
+ "kind": "bigquery#job", # Output only. The type of the resource.
+ "principal_subject": "A String", # Output only. [Full-projection-only] String representation of identity of requesting party. Populated for both first- and third-party identities. Only present for APIs that support third-party identities.
+ "selfLink": "A String", # Output only. A URL that can be used to access the resource again.
+ "statistics": { # Statistics for a single job execution. # Output only. Information about the job, including starting time and ending time of the job.
+ "completionRatio": 3.14, # Output only. [TrustedTester] Job progress (0.0 -> 1.0) for LOAD and EXTRACT jobs.
+ "copy": { # Statistics for a copy job. # Output only. Statistics for a copy job.
+ "copiedLogicalBytes": "A String", # Output only. Number of logical bytes copied to the destination table.
+ "copiedRows": "A String", # Output only. Number of rows copied to the destination table.
},
- "creationTime": "A String", # [Output-only] Creation time of this job, in milliseconds since the epoch. This field will be present on all jobs.
- "dataMaskingStatistics": { # [Output-only] Statistics for data masking. Present only for query and extract jobs.
- "dataMaskingApplied": false, # [Output-only] [Preview] Whether any accessed data was protected by data masking. The actual evaluation is done by accessStats.masked_field_count > 0. Since this is only used for the discovery_doc generation purpose, as long as the type (boolean) matches, client library can leverage this. The actual evaluation of the variable is done else-where.
+ "creationTime": "A String", # Output only. Creation time of this job, in milliseconds since the epoch. This field will be present on all jobs.
+ "dataMaskingStatistics": { # Statistics for data-masking. # Output only. Statistics for data-masking. Present only for query and extract jobs.
+ "dataMaskingApplied": True or False, # Whether any accessed data was protected by the data masking.
},
- "endTime": "A String", # [Output-only] End time of this job, in milliseconds since the epoch. This field will be present whenever a job is in the DONE state.
- "extract": { # [Output-only] Statistics for an extract job.
- "destinationUriFileCounts": [ # [Output-only] Number of files per destination URI or URI pattern specified in the extract configuration. These values will be in the same order as the URIs specified in the 'destinationUris' field.
+ "endTime": "A String", # Output only. End time of this job, in milliseconds since the epoch. This field will be present whenever a job is in the DONE state.
+ "extract": { # Statistics for an extract job. # Output only. Statistics for an extract job.
+ "destinationUriFileCounts": [ # Output only. Number of files per destination URI or URI pattern specified in the extract configuration. These values will be in the same order as the URIs specified in the 'destinationUris' field.
"A String",
],
- "inputBytes": "A String", # [Output-only] Number of user bytes extracted into the result. This is the byte count as computed by BigQuery for billing purposes.
+ "inputBytes": "A String", # Output only. Number of user bytes extracted into the result. This is the byte count as computed by BigQuery for billing purposes and doesn't have any relationship with the number of actual result bytes extracted in the desired format.
+ "timeline": [ # Output only. Describes a timeline of job execution.
+ { # Summary of the state of query execution at a given time.
+ "activeUnits": "A String", # Total number of active workers. This does not correspond directly to slot usage. This is the largest value observed since the last sample.
+ "completedUnits": "A String", # Total parallel units of work completed by this query.
+ "elapsedMs": "A String", # Milliseconds elapsed since the start of query execution.
+ "estimatedRunnableUnits": "A String", # Units of work that can be scheduled immediately. Providing additional slots for these units of work will accelerate the query, if no other query in the reservation needs additional slots.
+ "pendingUnits": "A String", # Total units of work remaining for the query. This number can be revised (increased or decreased) while the query is running.
+ "totalSlotMs": "A String", # Cumulative slot-ms consumed by the query.
+ },
+ ],
},
- "load": { # [Output-only] Statistics for a load job.
- "badRecords": "A String", # [Output-only] The number of bad records encountered. Note that if the job has failed because of more bad records encountered than the maximum allowed in the load job configuration, then this number can be less than the total number of bad records present in the input data.
- "inputFileBytes": "A String", # [Output-only] Number of bytes of source data in a load job.
- "inputFiles": "A String", # [Output-only] Number of source files in a load job.
- "outputBytes": "A String", # [Output-only] Size of the loaded data in bytes. Note that while a load job is in the running state, this value may change.
- "outputRows": "A String", # [Output-only] Number of rows imported in a load job. Note that while an import job is in the running state, this value may change.
+ "finalExecutionDurationMs": "A String", # Output only. The duration in milliseconds of the execution of the final attempt of this job, as BigQuery may internally re-attempt to execute the job.
+ "load": { # Statistics for a load job. # Output only. Statistics for a load job.
+ "badRecords": "A String", # Output only. The number of bad records encountered. Note that if the job has failed because of more bad records encountered than the maximum allowed in the load job configuration, then this number can be less than the total number of bad records present in the input data.
+ "inputFileBytes": "A String", # Output only. Number of bytes of source data in a load job.
+ "inputFiles": "A String", # Output only. Number of source files in a load job.
+ "outputBytes": "A String", # Output only. Size of the loaded data in bytes. Note that while a load job is in the running state, this value may change.
+ "outputRows": "A String", # Output only. Number of rows imported in a load job. Note that while an import job is in the running state, this value may change.
+ "timeline": [ # Output only. Describes a timeline of job execution.
+ { # Summary of the state of query execution at a given time.
+ "activeUnits": "A String", # Total number of active workers. This does not correspond directly to slot usage. This is the largest value observed since the last sample.
+ "completedUnits": "A String", # Total parallel units of work completed by this query.
+ "elapsedMs": "A String", # Milliseconds elapsed since the start of query execution.
+ "estimatedRunnableUnits": "A String", # Units of work that can be scheduled immediately. Providing additional slots for these units of work will accelerate the query, if no other query in the reservation needs additional slots.
+ "pendingUnits": "A String", # Total units of work remaining for the query. This number can be revised (increased or decreased) while the query is running.
+ "totalSlotMs": "A String", # Cumulative slot-ms consumed by the query.
+ },
+ ],
},
- "numChildJobs": "A String", # [Output-only] Number of child jobs executed.
- "parentJobId": "A String", # [Output-only] If this is a child job, the id of the parent.
- "query": { # [Output-only] Statistics for a query job.
- "biEngineStatistics": { # BI Engine specific Statistics. [Output only] BI Engine specific Statistics.
- "accelerationMode": "", # [Output-only] Specifies which mode of BI Engine acceleration was performed (if any).
- "biEngineMode": "", # [Output-only] Specifies which mode of BI Engine acceleration was performed (if any).
+ "numChildJobs": "A String", # Output only. Number of child jobs executed.
+ "parentJobId": "A String", # Output only. If this is a child job, specifies the job ID of the parent.
+ "query": { # Statistics for a query job. # Output only. Statistics for a query job.
+ "biEngineStatistics": { # Statistics for a BI Engine specific query. Populated as part of JobStatistics2 # Output only. BI Engine specific Statistics.
+ "accelerationMode": "A String", # Output only. Specifies which mode of BI Engine acceleration was performed (if any).
+ "biEngineMode": "A String", # Output only. Specifies which mode of BI Engine acceleration was performed (if any).
"biEngineReasons": [ # In case of DISABLED or PARTIAL bi_engine_mode, these contain the explanatory reasons as to why BI Engine could not accelerate. In case the full query was accelerated, this field is not populated.
- {
- "code": "", # [Output-only] High-level BI Engine reason for partial or disabled acceleration.
- "message": "", # [Output-only] Free form human-readable reason for partial or disabled acceleration.
+ { # Reason why BI Engine didn't accelerate the query (or sub-query).
+ "code": "A String", # Output only. High-level BI Engine reason for partial or disabled acceleration
+ "message": "A String", # Output only. Free form human-readable reason for partial or disabled acceleration.
},
],
},
- "billingTier": 42, # [Output only] Billing tier for the job.
- "cacheHit": True or False, # [Output only] Whether the query result was fetched from the query cache.
- "ddlAffectedRowAccessPolicyCount": "A String", # [Output only] [Preview] The number of row access policies affected by a DDL statement. Present only for DROP ALL ROW ACCESS POLICIES queries.
- "ddlDestinationTable": { # [Output only] The DDL destination table. Present only for ALTER TABLE RENAME TO queries. Note that ddl_target_table is used just for its type information.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- },
- "ddlOperationPerformed": "A String", # The DDL operation performed, possibly dependent on the pre-existence of the DDL target. Possible values (new values might be added in the future): "CREATE": The query created the DDL target. "SKIP": No-op. Example cases: the query is CREATE TABLE IF NOT EXISTS while the table already exists, or the query is DROP TABLE IF EXISTS while the table does not exist. "REPLACE": The query replaced the DDL target. Example case: the query is CREATE OR REPLACE TABLE, and the table already exists. "DROP": The query deleted the DDL target.
- "ddlTargetDataset": { # [Output only] The DDL target dataset. Present only for CREATE/ALTER/DROP/UNDROP SCHEMA queries.
- "datasetId": "A String", # [Required] A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- "projectId": "A String", # [Optional] The ID of the project containing this dataset.
- },
- "ddlTargetRoutine": { # The DDL target routine. Present only for CREATE/DROP FUNCTION/PROCEDURE queries.
+ "billingTier": 42, # Output only. Billing tier for the job. This is a BigQuery-specific concept which is not related to the Google Cloud notion of "free tier". The value here is a measure of the query's resource consumption relative to the amount of data scanned. For on-demand queries, the limit is 100, and all queries within this limit are billed at the standard on-demand rates. On-demand queries that exceed this limit will fail with a billingTierLimitExceeded error.
+ "cacheHit": True or False, # Output only. Whether the query result was fetched from the query cache.
+ "dclTargetDataset": { # Output only. Referenced dataset for DCL statement.
+ "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "projectId": "A String", # Optional. The ID of the project containing this dataset.
+ },
+ "dclTargetTable": { # Output only. Referenced table for DCL statement.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ "dclTargetView": { # Output only. Referenced view for DCL statement.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ "ddlAffectedRowAccessPolicyCount": "A String", # Output only. The number of row access policies affected by a DDL statement. Present only for DROP ALL ROW ACCESS POLICIES queries.
+ "ddlDestinationTable": { # Output only. The table after rename. Present only for ALTER TABLE RENAME TO query.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ "ddlOperationPerformed": "A String", # Output only. The DDL operation performed, possibly dependent on the pre-existence of the DDL target.
+ "ddlTargetDataset": { # Output only. The DDL target dataset. Present only for CREATE/ALTER/DROP SCHEMA(dataset) queries.
+ "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "projectId": "A String", # Optional. The ID of the project containing this dataset.
+ },
+ "ddlTargetRoutine": { # Id path of a routine. # Output only. [Beta] The DDL target routine. Present only for CREATE/DROP FUNCTION/PROCEDURE queries.
"datasetId": "A String", # Required. The ID of the dataset containing this routine.
"projectId": "A String", # Required. The ID of the project containing this routine.
"routineId": "A String", # Required. The ID of the routine. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 256 characters.
},
- "ddlTargetRowAccessPolicy": { # [Output only] [Preview] The DDL target row access policy. Present only for CREATE/DROP ROW ACCESS POLICY queries.
+ "ddlTargetRowAccessPolicy": { # Id path of a row access policy. # Output only. The DDL target row access policy. Present only for CREATE/DROP ROW ACCESS POLICY queries.
"datasetId": "A String", # Required. The ID of the dataset containing this row access policy.
"policyId": "A String", # Required. The ID of the row access policy. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 256 characters.
"projectId": "A String", # Required. The ID of the project containing this row access policy.
"tableId": "A String", # Required. The ID of the table containing this row access policy.
},
- "ddlTargetTable": { # [Output only] The DDL target table. Present only for CREATE/DROP TABLE/VIEW and DROP ALL ROW ACCESS POLICIES queries.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- },
- "dmlStats": { # [Output only] Detailed statistics for DML statements Present only for DML statements INSERT, UPDATE, DELETE or TRUNCATE.
- "deletedRowCount": "A String", # Number of deleted Rows. populated by DML DELETE, MERGE and TRUNCATE statements.
- "insertedRowCount": "A String", # Number of inserted Rows. Populated by DML INSERT and MERGE statements.
- "updatedRowCount": "A String", # Number of updated Rows. Populated by DML UPDATE and MERGE statements.
- },
- "estimatedBytesProcessed": "A String", # [Output only] The original estimate of bytes processed for the job.
- "mlStatistics": { # [Output only] Statistics of a BigQuery ML training job.
- "iterationResults": [ # Results for all completed iterations.
- {
- "durationMs": "A String", # Time taken to run the iteration in milliseconds.
- "evalLoss": 3.14, # Loss computed on the eval data at the end of iteration.
- "index": 42, # Index of the iteration, 0 based.
- "learnRate": 3.14, # Learn rate used for this iteration.
- "trainingLoss": 3.14, # Loss computed on the training data at the end of iteration.
+ "ddlTargetTable": { # Output only. The DDL target table. Present only for CREATE/DROP TABLE/VIEW and DROP ALL ROW ACCESS POLICIES queries.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ "dmlStats": { # Detailed statistics for DML statements # Output only. Detailed statistics for DML statements INSERT, UPDATE, DELETE, MERGE or TRUNCATE.
+ "deletedRowCount": "A String", # Output only. Number of deleted Rows. populated by DML DELETE, MERGE and TRUNCATE statements.
+ "insertedRowCount": "A String", # Output only. Number of inserted Rows. Populated by DML INSERT and MERGE statements
+ "updatedRowCount": "A String", # Output only. Number of updated Rows. Populated by DML UPDATE and MERGE statements.
+ },
+ "estimatedBytesProcessed": "A String", # Output only. The original estimate of bytes processed for the job.
+ "exportDataStatistics": { # Statistics for the EXPORT DATA statement as part of Query Job. EXTRACT JOB statistics are populated in JobStatistics4. # Output only. Stats for EXPORT DATA statement.
+ "fileCount": "A String", # Number of destination files generated in case of EXPORT DATA statement only.
+ "rowCount": "A String", # [Alpha] Number of destination rows generated in case of EXPORT DATA statement only.
+ },
+ "externalServiceCosts": [ # Output only. Job cost breakdown as bigquery internal cost and external service costs.
+ { # The external service cost is a portion of the total cost, these costs are not additive with total_bytes_billed. Moreover, this field only track external service costs that will show up as BigQuery costs (e.g. training BigQuery ML job with google cloud CAIP or Automl Tables services), not other costs which may be accrued by running the query (e.g. reading from Bigtable or Cloud Storage). The external service costs with different billing sku (e.g. CAIP job is charged based on VM usage) are converted to BigQuery billed_bytes and slot_ms with equivalent amount of US dollars. Services may not directly correlate to these metrics, but these are the equivalents for billing purposes. Output only.
+ "bytesBilled": "A String", # External service cost in terms of bigquery bytes billed.
+ "bytesProcessed": "A String", # External service cost in terms of bigquery bytes processed.
+ "externalService": "A String", # External service name.
+ "reservedSlotCount": "A String", # Non-preemptable reserved slots used for external job. For example, reserved slots for Cloua AI Platform job are the VM usages converted to BigQuery slot with equivalent mount of price.
+ "slotMs": "A String", # External service cost in terms of bigquery slot milliseconds.
+ },
+ ],
+ "loadQueryStatistics": { # Statistics for a LOAD query. # Output only. Statistics for a LOAD query.
+ "badRecords": "A String", # Output only. The number of bad records encountered while processing a LOAD query. Note that if the job has failed because of more bad records encountered than the maximum allowed in the load job configuration, then this number can be less than the total number of bad records present in the input data.
+ "bytesTransferred": "A String", # Output only. This field is deprecated. The number of bytes of source data copied over the network for a `LOAD` query. `transferred_bytes` has the canonical value for physical transferred bytes, which is used for BigQuery Omni billing.
+ "inputFileBytes": "A String", # Output only. Number of bytes of source data in a LOAD query.
+ "inputFiles": "A String", # Output only. Number of source files in a LOAD query.
+ "outputBytes": "A String", # Output only. Size of the loaded data in bytes. Note that while a LOAD query is in the running state, this value may change.
+ "outputRows": "A String", # Output only. Number of rows imported in a LOAD query. Note that while a LOAD query is in the running state, this value may change.
+ },
+ "materializedViewStatistics": { # Statistics of materialized views considered in a query job. # Output only. Statistics of materialized views of a query job.
+ "materializedView": [ # Materialized views considered for the query job. Only certain materialized views are used. For a detailed list, see the child message. If many materialized views are considered, then the list might be incomplete.
+ { # A materialized view considered for a query job.
+ "chosen": True or False, # Whether the materialized view is chosen for the query. A materialized view can be chosen to rewrite multiple parts of the same query. If a materialized view is chosen to rewrite any part of the query, then this field is true, even if the materialized view was not chosen to rewrite others parts.
+ "estimatedBytesSaved": "A String", # If present, specifies a best-effort estimation of the bytes saved by using the materialized view rather than its base tables.
+ "rejectedReason": "A String", # If present, specifies the reason why the materialized view was not chosen for the query.
+ "tableReference": { # The candidate materialized view.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
},
],
- "maxIterations": "A String", # Maximum number of iterations specified as max_iterations in the 'CREATE MODEL' query. The actual number of iterations may be less than this number due to early stop.
},
- "modelTraining": { # [Output only, Beta] Information about create model query job progress.
- "currentIteration": 42, # [Output-only, Beta] Index of current ML training iteration. Updated during create model query job to show job progress.
- "expectedTotalIterations": "A String", # [Output-only, Beta] Expected number of iterations for the create model query job specified as num_iterations in the input query. The actual total number of iterations may be less than this number due to early stop.
+ "metadataCacheStatistics": { # Statistics for metadata caching in BigLake tables. # Output only. Statistics of metadata cache usage in a query for BigLake tables.
+ "tableMetadataCacheUsage": [ # Set for the Metadata caching eligible tables referenced in the query.
+ { # Table level detail on the usage of metadata caching. Only set for Metadata caching eligible tables referenced in the query.
+ "explanation": "A String", # Free form human-readable reason metadata caching was unused for the job.
+ "tableReference": { # Metadata caching eligible table referenced in the query.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ "tableType": "A String", # [Table type](/bigquery/docs/reference/rest/v2/tables#Table.FIELDS.type).
+ "unusedReason": "A String", # Reason for not using metadata caching for the table.
+ },
+ ],
},
- "modelTrainingCurrentIteration": 42, # [Output only, Beta] Deprecated; do not use.
- "modelTrainingExpectedTotalIteration": "A String", # [Output only, Beta] Deprecated; do not use.
- "numDmlAffectedRows": "A String", # [Output only] The number of rows affected by a DML statement. Present only for DML statements INSERT, UPDATE or DELETE.
- "queryPlan": [ # [Output only] Describes execution plan for the query.
- {
- "completedParallelInputs": "A String", # Number of parallel input segments completed.
- "computeMsAvg": "A String", # Milliseconds the average shard spent on CPU-bound tasks.
- "computeMsMax": "A String", # Milliseconds the slowest shard spent on CPU-bound tasks.
- "computeRatioAvg": 3.14, # Relative amount of time the average shard spent on CPU-bound tasks.
- "computeRatioMax": 3.14, # Relative amount of time the slowest shard spent on CPU-bound tasks.
- "endMs": "A String", # Stage end time represented as milliseconds since epoch.
- "id": "A String", # Unique ID for stage within plan.
- "inputStages": [ # IDs for stages that are inputs to this stage.
- "A String",
- ],
- "name": "A String", # Human-readable name for stage.
- "parallelInputs": "A String", # Number of parallel input segments to be processed.
+ "mlStatistics": { # Job statistics specific to a BigQuery ML training job. # Output only. Statistics of a BigQuery ML training job.
+ "hparamTrials": [ # Output only. Trials of a [hyperparameter tuning job](/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview) sorted by trial_id.
+ { # Training info of a trial in [hyperparameter tuning](/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview) models.
+ "endTimeMs": "A String", # Ending time of the trial.
+ "errorMessage": "A String", # Error message for FAILED and INFEASIBLE trial.
+ "evalLoss": 3.14, # Loss computed on the eval data at the end of trial.
+ "evaluationMetrics": { # Evaluation metrics of a model. These are either computed on all training data or just the eval data based on whether eval data was used during training. These are not present for imported models. # Evaluation metrics of this trial calculated on the test data. Empty in Job API.
+ "arimaForecastingMetrics": { # Model evaluation metrics for ARIMA forecasting models. # Populated for ARIMA models.
+ "arimaFittingMetrics": [ # Arima model fitting metrics.
+ { # ARIMA model fitting metrics.
+ "aic": 3.14, # AIC.
+ "logLikelihood": 3.14, # Log-likelihood.
+ "variance": 3.14, # Variance.
+ },
+ ],
+ "arimaSingleModelForecastingMetrics": [ # Repeated as there can be many metric sets (one for each model) in auto-arima and the large-scale case.
+ { # Model evaluation metrics for a single ARIMA forecasting model.
+ "arimaFittingMetrics": { # ARIMA model fitting metrics. # Arima fitting metrics.
+ "aic": 3.14, # AIC.
+ "logLikelihood": 3.14, # Log-likelihood.
+ "variance": 3.14, # Variance.
+ },
+ "hasDrift": True or False, # Is arima model fitted with drift or not. It is always false when d is not 1.
+ "hasHolidayEffect": True or False, # If true, holiday_effect is a part of time series decomposition result.
+ "hasSpikesAndDips": True or False, # If true, spikes_and_dips is a part of time series decomposition result.
+ "hasStepChanges": True or False, # If true, step_changes is a part of time series decomposition result.
+ "nonSeasonalOrder": { # Arima order, can be used for both non-seasonal and seasonal parts. # Non-seasonal order.
+ "d": "A String", # Order of the differencing part.
+ "p": "A String", # Order of the autoregressive part.
+ "q": "A String", # Order of the moving-average part.
+ },
+ "seasonalPeriods": [ # Seasonal periods. Repeated because multiple periods are supported for one time series.
+ "A String",
+ ],
+ "timeSeriesId": "A String", # The time_series_id value for this time series. It will be one of the unique values from the time_series_id_column specified during ARIMA model training. Only present when time_series_id_column training option was used.
+ "timeSeriesIds": [ # The tuple of time_series_ids identifying this time series. It will be one of the unique tuples of values present in the time_series_id_columns specified during ARIMA model training. Only present when time_series_id_columns training option was used and the order of values here are same as the order of time_series_id_columns.
+ "A String",
+ ],
+ },
+ ],
+ "hasDrift": [ # Whether Arima model fitted with drift or not. It is always false when d is not 1.
+ True or False,
+ ],
+ "nonSeasonalOrder": [ # Non-seasonal order.
+ { # Arima order, can be used for both non-seasonal and seasonal parts.
+ "d": "A String", # Order of the differencing part.
+ "p": "A String", # Order of the autoregressive part.
+ "q": "A String", # Order of the moving-average part.
+ },
+ ],
+ "seasonalPeriods": [ # Seasonal periods. Repeated because multiple periods are supported for one time series.
+ "A String",
+ ],
+ "timeSeriesId": [ # Id to differentiate different time series for the large-scale case.
+ "A String",
+ ],
+ },
+ "binaryClassificationMetrics": { # Evaluation metrics for binary classification/classifier models. # Populated for binary classification/classifier models.
+ "aggregateClassificationMetrics": { # Aggregate metrics for classification/classifier models. For multi-class models, the metrics are either macro-averaged or micro-averaged. When macro-averaged, the metrics are calculated for each label and then an unweighted average is taken of those values. When micro-averaged, the metric is calculated globally by counting the total number of correctly predicted rows. # Aggregate classification metrics.
+ "accuracy": 3.14, # Accuracy is the fraction of predictions given the correct label. For multiclass this is a micro-averaged metric.
+ "f1Score": 3.14, # The F1 score is an average of recall and precision. For multiclass this is a macro-averaged metric.
+ "logLoss": 3.14, # Logarithmic Loss. For multiclass this is a macro-averaged metric.
+ "precision": 3.14, # Precision is the fraction of actual positive predictions that had positive actual labels. For multiclass this is a macro-averaged metric treating each class as a binary classifier.
+ "recall": 3.14, # Recall is the fraction of actual positive labels that were given a positive prediction. For multiclass this is a macro-averaged metric.
+ "rocAuc": 3.14, # Area Under a ROC Curve. For multiclass this is a macro-averaged metric.
+ "threshold": 3.14, # Threshold at which the metrics are computed. For binary classification models this is the positive class threshold. For multi-class classfication models this is the confidence threshold.
+ },
+ "binaryConfusionMatrixList": [ # Binary confusion matrix at multiple thresholds.
+ { # Confusion matrix for binary classification models.
+ "accuracy": 3.14, # The fraction of predictions given the correct label.
+ "f1Score": 3.14, # The equally weighted average of recall and precision.
+ "falseNegatives": "A String", # Number of false samples predicted as false.
+ "falsePositives": "A String", # Number of false samples predicted as true.
+ "positiveClassThreshold": 3.14, # Threshold value used when computing each of the following metric.
+ "precision": 3.14, # The fraction of actual positive predictions that had positive actual labels.
+ "recall": 3.14, # The fraction of actual positive labels that were given a positive prediction.
+ "trueNegatives": "A String", # Number of true samples predicted as false.
+ "truePositives": "A String", # Number of true samples predicted as true.
+ },
+ ],
+ "negativeLabel": "A String", # Label representing the negative class.
+ "positiveLabel": "A String", # Label representing the positive class.
+ },
+ "clusteringMetrics": { # Evaluation metrics for clustering models. # Populated for clustering models.
+ "clusters": [ # Information for all clusters.
+ { # Message containing the information about one cluster.
+ "centroidId": "A String", # Centroid id.
+ "count": "A String", # Count of training data rows that were assigned to this cluster.
+ "featureValues": [ # Values of highly variant features for this cluster.
+ { # Representative value of a single feature within the cluster.
+ "categoricalValue": { # Representative value of a categorical feature. # The categorical feature value.
+ "categoryCounts": [ # Counts of all categories for the categorical feature. If there are more than ten categories, we return top ten (by count) and return one more CategoryCount with category "_OTHER_" and count as aggregate counts of remaining categories.
+ { # Represents the count of a single category within the cluster.
+ "category": "A String", # The name of category.
+ "count": "A String", # The count of training samples matching the category within the cluster.
+ },
+ ],
+ },
+ "featureColumn": "A String", # The feature column name.
+ "numericalValue": 3.14, # The numerical feature value. This is the centroid value for this feature.
+ },
+ ],
+ },
+ ],
+ "daviesBouldinIndex": 3.14, # Davies-Bouldin index.
+ "meanSquaredDistance": 3.14, # Mean of squared distances between each sample to its cluster centroid.
+ },
+ "dimensionalityReductionMetrics": { # Model evaluation metrics for dimensionality reduction models. # Evaluation metrics when the model is a dimensionality reduction model, which currently includes PCA.
+ "totalExplainedVarianceRatio": 3.14, # Total percentage of variance explained by the selected principal components.
+ },
+ "multiClassClassificationMetrics": { # Evaluation metrics for multi-class classification/classifier models. # Populated for multi-class classification/classifier models.
+ "aggregateClassificationMetrics": { # Aggregate metrics for classification/classifier models. For multi-class models, the metrics are either macro-averaged or micro-averaged. When macro-averaged, the metrics are calculated for each label and then an unweighted average is taken of those values. When micro-averaged, the metric is calculated globally by counting the total number of correctly predicted rows. # Aggregate classification metrics.
+ "accuracy": 3.14, # Accuracy is the fraction of predictions given the correct label. For multiclass this is a micro-averaged metric.
+ "f1Score": 3.14, # The F1 score is an average of recall and precision. For multiclass this is a macro-averaged metric.
+ "logLoss": 3.14, # Logarithmic Loss. For multiclass this is a macro-averaged metric.
+ "precision": 3.14, # Precision is the fraction of actual positive predictions that had positive actual labels. For multiclass this is a macro-averaged metric treating each class as a binary classifier.
+ "recall": 3.14, # Recall is the fraction of actual positive labels that were given a positive prediction. For multiclass this is a macro-averaged metric.
+ "rocAuc": 3.14, # Area Under a ROC Curve. For multiclass this is a macro-averaged metric.
+ "threshold": 3.14, # Threshold at which the metrics are computed. For binary classification models this is the positive class threshold. For multi-class classfication models this is the confidence threshold.
+ },
+ "confusionMatrixList": [ # Confusion matrix at different thresholds.
+ { # Confusion matrix for multi-class classification models.
+ "confidenceThreshold": 3.14, # Confidence threshold used when computing the entries of the confusion matrix.
+ "rows": [ # One row per actual label.
+ { # A single row in the confusion matrix.
+ "actualLabel": "A String", # The original label of this row.
+ "entries": [ # Info describing predicted label distribution.
+ { # A single entry in the confusion matrix.
+ "itemCount": "A String", # Number of items being predicted as this label.
+ "predictedLabel": "A String", # The predicted label. For confidence_threshold > 0, we will also add an entry indicating the number of items under the confidence threshold.
+ },
+ ],
+ },
+ ],
+ },
+ ],
+ },
+ "rankingMetrics": { # Evaluation metrics used by weighted-ALS models specified by feedback_type=implicit. # Populated for implicit feedback type matrix factorization models.
+ "averageRank": 3.14, # Determines the goodness of a ranking by computing the percentile rank from the predicted confidence and dividing it by the original rank.
+ "meanAveragePrecision": 3.14, # Calculates a precision per user for all the items by ranking them and then averages all the precisions across all the users.
+ "meanSquaredError": 3.14, # Similar to the mean squared error computed in regression and explicit recommendation models except instead of computing the rating directly, the output from evaluate is computed against a preference which is 1 or 0 depending on if the rating exists or not.
+ "normalizedDiscountedCumulativeGain": 3.14, # A metric to determine the goodness of a ranking calculated from the predicted confidence by comparing it to an ideal rank measured by the original ratings.
+ },
+ "regressionMetrics": { # Evaluation metrics for regression and explicit feedback type matrix factorization models. # Populated for regression models and explicit feedback type matrix factorization models.
+ "meanAbsoluteError": 3.14, # Mean absolute error.
+ "meanSquaredError": 3.14, # Mean squared error.
+ "meanSquaredLogError": 3.14, # Mean squared log error.
+ "medianAbsoluteError": 3.14, # Median absolute error.
+ "rSquared": 3.14, # R^2 score. This corresponds to r2_score in ML.EVALUATE.
+ },
+ },
+ "hparamTuningEvaluationMetrics": { # Evaluation metrics of a model. These are either computed on all training data or just the eval data based on whether eval data was used during training. These are not present for imported models. # Hyperparameter tuning evaluation metrics of this trial calculated on the eval data. Unlike evaluation_metrics, only the fields corresponding to the hparam_tuning_objectives are set.
+ "arimaForecastingMetrics": { # Model evaluation metrics for ARIMA forecasting models. # Populated for ARIMA models.
+ "arimaFittingMetrics": [ # Arima model fitting metrics.
+ { # ARIMA model fitting metrics.
+ "aic": 3.14, # AIC.
+ "logLikelihood": 3.14, # Log-likelihood.
+ "variance": 3.14, # Variance.
+ },
+ ],
+ "arimaSingleModelForecastingMetrics": [ # Repeated as there can be many metric sets (one for each model) in auto-arima and the large-scale case.
+ { # Model evaluation metrics for a single ARIMA forecasting model.
+ "arimaFittingMetrics": { # ARIMA model fitting metrics. # Arima fitting metrics.
+ "aic": 3.14, # AIC.
+ "logLikelihood": 3.14, # Log-likelihood.
+ "variance": 3.14, # Variance.
+ },
+ "hasDrift": True or False, # Is arima model fitted with drift or not. It is always false when d is not 1.
+ "hasHolidayEffect": True or False, # If true, holiday_effect is a part of time series decomposition result.
+ "hasSpikesAndDips": True or False, # If true, spikes_and_dips is a part of time series decomposition result.
+ "hasStepChanges": True or False, # If true, step_changes is a part of time series decomposition result.
+ "nonSeasonalOrder": { # Arima order, can be used for both non-seasonal and seasonal parts. # Non-seasonal order.
+ "d": "A String", # Order of the differencing part.
+ "p": "A String", # Order of the autoregressive part.
+ "q": "A String", # Order of the moving-average part.
+ },
+ "seasonalPeriods": [ # Seasonal periods. Repeated because multiple periods are supported for one time series.
+ "A String",
+ ],
+ "timeSeriesId": "A String", # The time_series_id value for this time series. It will be one of the unique values from the time_series_id_column specified during ARIMA model training. Only present when time_series_id_column training option was used.
+ "timeSeriesIds": [ # The tuple of time_series_ids identifying this time series. It will be one of the unique tuples of values present in the time_series_id_columns specified during ARIMA model training. Only present when time_series_id_columns training option was used and the order of values here are same as the order of time_series_id_columns.
+ "A String",
+ ],
+ },
+ ],
+ "hasDrift": [ # Whether Arima model fitted with drift or not. It is always false when d is not 1.
+ True or False,
+ ],
+ "nonSeasonalOrder": [ # Non-seasonal order.
+ { # Arima order, can be used for both non-seasonal and seasonal parts.
+ "d": "A String", # Order of the differencing part.
+ "p": "A String", # Order of the autoregressive part.
+ "q": "A String", # Order of the moving-average part.
+ },
+ ],
+ "seasonalPeriods": [ # Seasonal periods. Repeated because multiple periods are supported for one time series.
+ "A String",
+ ],
+ "timeSeriesId": [ # Id to differentiate different time series for the large-scale case.
+ "A String",
+ ],
+ },
+ "binaryClassificationMetrics": { # Evaluation metrics for binary classification/classifier models. # Populated for binary classification/classifier models.
+ "aggregateClassificationMetrics": { # Aggregate metrics for classification/classifier models. For multi-class models, the metrics are either macro-averaged or micro-averaged. When macro-averaged, the metrics are calculated for each label and then an unweighted average is taken of those values. When micro-averaged, the metric is calculated globally by counting the total number of correctly predicted rows. # Aggregate classification metrics.
+ "accuracy": 3.14, # Accuracy is the fraction of predictions given the correct label. For multiclass this is a micro-averaged metric.
+ "f1Score": 3.14, # The F1 score is an average of recall and precision. For multiclass this is a macro-averaged metric.
+ "logLoss": 3.14, # Logarithmic Loss. For multiclass this is a macro-averaged metric.
+ "precision": 3.14, # Precision is the fraction of actual positive predictions that had positive actual labels. For multiclass this is a macro-averaged metric treating each class as a binary classifier.
+ "recall": 3.14, # Recall is the fraction of actual positive labels that were given a positive prediction. For multiclass this is a macro-averaged metric.
+ "rocAuc": 3.14, # Area Under a ROC Curve. For multiclass this is a macro-averaged metric.
+ "threshold": 3.14, # Threshold at which the metrics are computed. For binary classification models this is the positive class threshold. For multi-class classfication models this is the confidence threshold.
+ },
+ "binaryConfusionMatrixList": [ # Binary confusion matrix at multiple thresholds.
+ { # Confusion matrix for binary classification models.
+ "accuracy": 3.14, # The fraction of predictions given the correct label.
+ "f1Score": 3.14, # The equally weighted average of recall and precision.
+ "falseNegatives": "A String", # Number of false samples predicted as false.
+ "falsePositives": "A String", # Number of false samples predicted as true.
+ "positiveClassThreshold": 3.14, # Threshold value used when computing each of the following metric.
+ "precision": 3.14, # The fraction of actual positive predictions that had positive actual labels.
+ "recall": 3.14, # The fraction of actual positive labels that were given a positive prediction.
+ "trueNegatives": "A String", # Number of true samples predicted as false.
+ "truePositives": "A String", # Number of true samples predicted as true.
+ },
+ ],
+ "negativeLabel": "A String", # Label representing the negative class.
+ "positiveLabel": "A String", # Label representing the positive class.
+ },
+ "clusteringMetrics": { # Evaluation metrics for clustering models. # Populated for clustering models.
+ "clusters": [ # Information for all clusters.
+ { # Message containing the information about one cluster.
+ "centroidId": "A String", # Centroid id.
+ "count": "A String", # Count of training data rows that were assigned to this cluster.
+ "featureValues": [ # Values of highly variant features for this cluster.
+ { # Representative value of a single feature within the cluster.
+ "categoricalValue": { # Representative value of a categorical feature. # The categorical feature value.
+ "categoryCounts": [ # Counts of all categories for the categorical feature. If there are more than ten categories, we return top ten (by count) and return one more CategoryCount with category "_OTHER_" and count as aggregate counts of remaining categories.
+ { # Represents the count of a single category within the cluster.
+ "category": "A String", # The name of category.
+ "count": "A String", # The count of training samples matching the category within the cluster.
+ },
+ ],
+ },
+ "featureColumn": "A String", # The feature column name.
+ "numericalValue": 3.14, # The numerical feature value. This is the centroid value for this feature.
+ },
+ ],
+ },
+ ],
+ "daviesBouldinIndex": 3.14, # Davies-Bouldin index.
+ "meanSquaredDistance": 3.14, # Mean of squared distances between each sample to its cluster centroid.
+ },
+ "dimensionalityReductionMetrics": { # Model evaluation metrics for dimensionality reduction models. # Evaluation metrics when the model is a dimensionality reduction model, which currently includes PCA.
+ "totalExplainedVarianceRatio": 3.14, # Total percentage of variance explained by the selected principal components.
+ },
+ "multiClassClassificationMetrics": { # Evaluation metrics for multi-class classification/classifier models. # Populated for multi-class classification/classifier models.
+ "aggregateClassificationMetrics": { # Aggregate metrics for classification/classifier models. For multi-class models, the metrics are either macro-averaged or micro-averaged. When macro-averaged, the metrics are calculated for each label and then an unweighted average is taken of those values. When micro-averaged, the metric is calculated globally by counting the total number of correctly predicted rows. # Aggregate classification metrics.
+ "accuracy": 3.14, # Accuracy is the fraction of predictions given the correct label. For multiclass this is a micro-averaged metric.
+ "f1Score": 3.14, # The F1 score is an average of recall and precision. For multiclass this is a macro-averaged metric.
+ "logLoss": 3.14, # Logarithmic Loss. For multiclass this is a macro-averaged metric.
+ "precision": 3.14, # Precision is the fraction of actual positive predictions that had positive actual labels. For multiclass this is a macro-averaged metric treating each class as a binary classifier.
+ "recall": 3.14, # Recall is the fraction of actual positive labels that were given a positive prediction. For multiclass this is a macro-averaged metric.
+ "rocAuc": 3.14, # Area Under a ROC Curve. For multiclass this is a macro-averaged metric.
+ "threshold": 3.14, # Threshold at which the metrics are computed. For binary classification models this is the positive class threshold. For multi-class classfication models this is the confidence threshold.
+ },
+ "confusionMatrixList": [ # Confusion matrix at different thresholds.
+ { # Confusion matrix for multi-class classification models.
+ "confidenceThreshold": 3.14, # Confidence threshold used when computing the entries of the confusion matrix.
+ "rows": [ # One row per actual label.
+ { # A single row in the confusion matrix.
+ "actualLabel": "A String", # The original label of this row.
+ "entries": [ # Info describing predicted label distribution.
+ { # A single entry in the confusion matrix.
+ "itemCount": "A String", # Number of items being predicted as this label.
+ "predictedLabel": "A String", # The predicted label. For confidence_threshold > 0, we will also add an entry indicating the number of items under the confidence threshold.
+ },
+ ],
+ },
+ ],
+ },
+ ],
+ },
+ "rankingMetrics": { # Evaluation metrics used by weighted-ALS models specified by feedback_type=implicit. # Populated for implicit feedback type matrix factorization models.
+ "averageRank": 3.14, # Determines the goodness of a ranking by computing the percentile rank from the predicted confidence and dividing it by the original rank.
+ "meanAveragePrecision": 3.14, # Calculates a precision per user for all the items by ranking them and then averages all the precisions across all the users.
+ "meanSquaredError": 3.14, # Similar to the mean squared error computed in regression and explicit recommendation models except instead of computing the rating directly, the output from evaluate is computed against a preference which is 1 or 0 depending on if the rating exists or not.
+ "normalizedDiscountedCumulativeGain": 3.14, # A metric to determine the goodness of a ranking calculated from the predicted confidence by comparing it to an ideal rank measured by the original ratings.
+ },
+ "regressionMetrics": { # Evaluation metrics for regression and explicit feedback type matrix factorization models. # Populated for regression models and explicit feedback type matrix factorization models.
+ "meanAbsoluteError": 3.14, # Mean absolute error.
+ "meanSquaredError": 3.14, # Mean squared error.
+ "meanSquaredLogError": 3.14, # Mean squared log error.
+ "medianAbsoluteError": 3.14, # Median absolute error.
+ "rSquared": 3.14, # R^2 score. This corresponds to r2_score in ML.EVALUATE.
+ },
+ },
+ "hparams": { # Options used in model training. # The hyperprameters selected for this trial.
+ "activationFn": "A String", # Activation function of the neural nets.
+ "adjustStepChanges": True or False, # If true, detect step changes and make data adjustment in the input time series.
+ "approxGlobalFeatureContrib": True or False, # Whether to use approximate feature contribution method in XGBoost model explanation for global explain.
+ "autoArima": True or False, # Whether to enable auto ARIMA or not.
+ "autoArimaMaxOrder": "A String", # The max value of the sum of non-seasonal p and q.
+ "autoArimaMinOrder": "A String", # The min value of the sum of non-seasonal p and q.
+ "autoClassWeights": True or False, # Whether to calculate class weights automatically based on the popularity of each label.
+ "batchSize": "A String", # Batch size for dnn models.
+ "boosterType": "A String", # Booster type for boosted tree models.
+ "budgetHours": 3.14, # Budget in hours for AutoML training.
+ "calculatePValues": True or False, # Whether or not p-value test should be computed for this model. Only available for linear and logistic regression models.
+ "categoryEncodingMethod": "A String", # Categorical feature encoding method.
+ "cleanSpikesAndDips": True or False, # If true, clean spikes and dips in the input time series.
+ "colorSpace": "A String", # Enums for color space, used for processing images in Object Table. See more details at https://www.tensorflow.org/io/tutorials/colorspace.
+ "colsampleBylevel": 3.14, # Subsample ratio of columns for each level for boosted tree models.
+ "colsampleBynode": 3.14, # Subsample ratio of columns for each node(split) for boosted tree models.
+ "colsampleBytree": 3.14, # Subsample ratio of columns when constructing each tree for boosted tree models.
+ "dartNormalizeType": "A String", # Type of normalization algorithm for boosted tree models using dart booster.
+ "dataFrequency": "A String", # The data frequency of a time series.
+ "dataSplitColumn": "A String", # The column to split data with. This column won't be used as a feature. 1. When data_split_method is CUSTOM, the corresponding column should be boolean. The rows with true value tag are eval data, and the false are training data. 2. When data_split_method is SEQ, the first DATA_SPLIT_EVAL_FRACTION rows (from smallest to largest) in the corresponding column are used as training data, and the rest are eval data. It respects the order in Orderable data types: https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types#data-type-properties
+ "dataSplitEvalFraction": 3.14, # The fraction of evaluation data over the whole input data. The rest of data will be used as training data. The format should be double. Accurate to two decimal places. Default value is 0.2.
+ "dataSplitMethod": "A String", # The data split type for training and evaluation, e.g. RANDOM.
+ "decomposeTimeSeries": True or False, # If true, perform decompose time series and save the results.
+ "distanceType": "A String", # Distance type for clustering models.
+ "dropout": 3.14, # Dropout probability for dnn models.
+ "earlyStop": True or False, # Whether to stop early when the loss doesn't improve significantly any more (compared to min_relative_progress). Used only for iterative training algorithms.
+ "enableGlobalExplain": True or False, # If true, enable global explanation during training.
+ "feedbackType": "A String", # Feedback type that specifies which algorithm to run for matrix factorization.
+ "fitIntercept": True or False, # Whether the model should include intercept during model training.
+ "hiddenUnits": [ # Hidden units for dnn models.
+ "A String",
+ ],
+ "holidayRegion": "A String", # The geographical region based on which the holidays are considered in time series modeling. If a valid value is specified, then holiday effects modeling is enabled.
+ "holidayRegions": [ # A list of geographical regions that are used for time series modeling.
+ "A String",
+ ],
+ "horizon": "A String", # The number of periods ahead that need to be forecasted.
+ "hparamTuningObjectives": [ # The target evaluation metrics to optimize the hyperparameters for.
+ "A String",
+ ],
+ "includeDrift": True or False, # Include drift when fitting an ARIMA model.
+ "initialLearnRate": 3.14, # Specifies the initial learning rate for the line search learn rate strategy.
+ "inputLabelColumns": [ # Name of input label columns in training data.
+ "A String",
+ ],
+ "instanceWeightColumn": "A String", # Name of the instance weight column for training data. This column isn't be used as a feature.
+ "integratedGradientsNumSteps": "A String", # Number of integral steps for the integrated gradients explain method.
+ "itemColumn": "A String", # Item column specified for matrix factorization models.
+ "kmeansInitializationColumn": "A String", # The column used to provide the initial centroids for kmeans algorithm when kmeans_initialization_method is CUSTOM.
+ "kmeansInitializationMethod": "A String", # The method used to initialize the centroids for kmeans algorithm.
+ "l1RegActivation": 3.14, # L1 regularization coefficient to activations.
+ "l1Regularization": 3.14, # L1 regularization coefficient.
+ "l2Regularization": 3.14, # L2 regularization coefficient.
+ "labelClassWeights": { # Weights associated with each label class, for rebalancing the training data. Only applicable for classification models.
+ "a_key": 3.14,
+ },
+ "learnRate": 3.14, # Learning rate in training. Used only for iterative training algorithms.
+ "learnRateStrategy": "A String", # The strategy to determine learn rate for the current iteration.
+ "lossType": "A String", # Type of loss function used during training run.
+ "maxIterations": "A String", # The maximum number of iterations in training. Used only for iterative training algorithms.
+ "maxParallelTrials": "A String", # Maximum number of trials to run in parallel.
+ "maxTimeSeriesLength": "A String", # The maximum number of time points in a time series that can be used in modeling the trend component of the time series. Don't use this option with the `timeSeriesLengthFraction` or `minTimeSeriesLength` options.
+ "maxTreeDepth": "A String", # Maximum depth of a tree for boosted tree models.
+ "minRelativeProgress": 3.14, # When early_stop is true, stops training when accuracy improvement is less than 'min_relative_progress'. Used only for iterative training algorithms.
+ "minSplitLoss": 3.14, # Minimum split loss for boosted tree models.
+ "minTimeSeriesLength": "A String", # The minimum number of time points in a time series that are used in modeling the trend component of the time series. If you use this option you must also set the `timeSeriesLengthFraction` option. This training option ensures that enough time points are available when you use `timeSeriesLengthFraction` in trend modeling. This is particularly important when forecasting multiple time series in a single query using `timeSeriesIdColumn`. If the total number of time points is less than the `minTimeSeriesLength` value, then the query uses all available time points.
+ "minTreeChildWeight": "A String", # Minimum sum of instance weight needed in a child for boosted tree models.
+ "modelRegistry": "A String", # The model registry.
+ "modelUri": "A String", # Google Cloud Storage URI from which the model was imported. Only applicable for imported models.
+ "nonSeasonalOrder": { # Arima order, can be used for both non-seasonal and seasonal parts. # A specification of the non-seasonal part of the ARIMA model: the three components (p, d, q) are the AR order, the degree of differencing, and the MA order.
+ "d": "A String", # Order of the differencing part.
+ "p": "A String", # Order of the autoregressive part.
+ "q": "A String", # Order of the moving-average part.
+ },
+ "numClusters": "A String", # Number of clusters for clustering models.
+ "numFactors": "A String", # Num factors specified for matrix factorization models.
+ "numParallelTree": "A String", # Number of parallel trees constructed during each iteration for boosted tree models.
+ "numPrincipalComponents": "A String", # Number of principal components to keep in the PCA model. Must be <= the number of features.
+ "numTrials": "A String", # Number of trials to run this hyperparameter tuning job.
+ "optimizationStrategy": "A String", # Optimization strategy for training linear regression models.
+ "optimizer": "A String", # Optimizer used for training the neural nets.
+ "pcaExplainedVarianceRatio": 3.14, # The minimum ratio of cumulative explained variance that needs to be given by the PCA model.
+ "pcaSolver": "A String", # The solver for PCA.
+ "sampledShapleyNumPaths": "A String", # Number of paths for the sampled Shapley explain method.
+ "scaleFeatures": True or False, # If true, scale the feature values by dividing the feature standard deviation. Currently only apply to PCA.
+ "standardizeFeatures": True or False, # Whether to standardize numerical features. Default to true.
+ "subsample": 3.14, # Subsample fraction of the training data to grow tree to prevent overfitting for boosted tree models.
+ "tfVersion": "A String", # Based on the selected TF version, the corresponding docker image is used to train external models.
+ "timeSeriesDataColumn": "A String", # Column to be designated as time series data for ARIMA model.
+ "timeSeriesIdColumn": "A String", # The time series id column that was used during ARIMA model training.
+ "timeSeriesIdColumns": [ # The time series id columns that were used during ARIMA model training.
+ "A String",
+ ],
+ "timeSeriesLengthFraction": 3.14, # The fraction of the interpolated length of the time series that's used to model the time series trend component. All of the time points of the time series are used to model the non-trend component. This training option accelerates modeling training without sacrificing much forecasting accuracy. You can use this option with `minTimeSeriesLength` but not with `maxTimeSeriesLength`.
+ "timeSeriesTimestampColumn": "A String", # Column to be designated as time series timestamp for ARIMA model.
+ "treeMethod": "A String", # Tree construction algorithm for boosted tree models.
+ "trendSmoothingWindowSize": "A String", # Smoothing window size for the trend component. When a positive value is specified, a center moving average smoothing is applied on the history trend. When the smoothing window is out of the boundary at the beginning or the end of the trend, the first element or the last element is padded to fill the smoothing window before the average is applied.
+ "userColumn": "A String", # User column specified for matrix factorization models.
+ "vertexAiModelVersionAliases": [ # The version aliases to apply in Vertex AI model registry. Always overwrite if the version aliases exists in a existing model.
+ "A String",
+ ],
+ "walsAlpha": 3.14, # Hyperparameter for matrix factoration when implicit feedback type is specified.
+ "warmStart": True or False, # Whether to train a model from the last checkpoint.
+ "xgboostVersion": "A String", # User-selected XGBoost versions for training of XGBoost models.
+ },
+ "startTimeMs": "A String", # Starting time of the trial.
+ "status": "A String", # The status of the trial.
+ "trainingLoss": 3.14, # Loss computed on the training data at the end of trial.
+ "trialId": "A String", # 1-based index of the trial.
+ },
+ ],
+ "iterationResults": [ # Results for all completed iterations. Empty for [hyperparameter tuning jobs](/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview).
+ { # Information about a single iteration of the training run.
+ "arimaResult": { # (Auto-)arima fitting result. Wrap everything in ArimaResult for easier refactoring if we want to use model-specific iteration results. # Arima result.
+ "arimaModelInfo": [ # This message is repeated because there are multiple arima models fitted in auto-arima. For non-auto-arima model, its size is one.
+ { # Arima model information.
+ "arimaCoefficients": { # Arima coefficients. # Arima coefficients.
+ "autoRegressiveCoefficients": [ # Auto-regressive coefficients, an array of double.
+ 3.14,
+ ],
+ "interceptCoefficient": 3.14, # Intercept coefficient, just a double not an array.
+ "movingAverageCoefficients": [ # Moving-average coefficients, an array of double.
+ 3.14,
+ ],
+ },
+ "arimaFittingMetrics": { # ARIMA model fitting metrics. # Arima fitting metrics.
+ "aic": 3.14, # AIC.
+ "logLikelihood": 3.14, # Log-likelihood.
+ "variance": 3.14, # Variance.
+ },
+ "hasDrift": True or False, # Whether Arima model fitted with drift or not. It is always false when d is not 1.
+ "hasHolidayEffect": True or False, # If true, holiday_effect is a part of time series decomposition result.
+ "hasSpikesAndDips": True or False, # If true, spikes_and_dips is a part of time series decomposition result.
+ "hasStepChanges": True or False, # If true, step_changes is a part of time series decomposition result.
+ "nonSeasonalOrder": { # Arima order, can be used for both non-seasonal and seasonal parts. # Non-seasonal order.
+ "d": "A String", # Order of the differencing part.
+ "p": "A String", # Order of the autoregressive part.
+ "q": "A String", # Order of the moving-average part.
+ },
+ "seasonalPeriods": [ # Seasonal periods. Repeated because multiple periods are supported for one time series.
+ "A String",
+ ],
+ "timeSeriesId": "A String", # The time_series_id value for this time series. It will be one of the unique values from the time_series_id_column specified during ARIMA model training. Only present when time_series_id_column training option was used.
+ "timeSeriesIds": [ # The tuple of time_series_ids identifying this time series. It will be one of the unique tuples of values present in the time_series_id_columns specified during ARIMA model training. Only present when time_series_id_columns training option was used and the order of values here are same as the order of time_series_id_columns.
+ "A String",
+ ],
+ },
+ ],
+ "seasonalPeriods": [ # Seasonal periods. Repeated because multiple periods are supported for one time series.
+ "A String",
+ ],
+ },
+ "clusterInfos": [ # Information about top clusters for clustering models.
+ { # Information about a single cluster for clustering model.
+ "centroidId": "A String", # Centroid id.
+ "clusterRadius": 3.14, # Cluster radius, the average distance from centroid to each point assigned to the cluster.
+ "clusterSize": "A String", # Cluster size, the total number of points assigned to the cluster.
+ },
+ ],
+ "durationMs": "A String", # Time taken to run the iteration in milliseconds.
+ "evalLoss": 3.14, # Loss computed on the eval data at the end of iteration.
+ "index": 42, # Index of the iteration, 0 based.
+ "learnRate": 3.14, # Learn rate used for this iteration.
+ "principalComponentInfos": [ # The information of the principal components.
+ { # Principal component infos, used only for eigen decomposition based models, e.g., PCA. Ordered by explained_variance in the descending order.
+ "cumulativeExplainedVarianceRatio": 3.14, # The explained_variance is pre-ordered in the descending order to compute the cumulative explained variance ratio.
+ "explainedVariance": 3.14, # Explained variance by this principal component, which is simply the eigenvalue.
+ "explainedVarianceRatio": 3.14, # Explained_variance over the total explained variance.
+ "principalComponentId": "A String", # Id of the principal component.
+ },
+ ],
+ "trainingLoss": 3.14, # Loss computed on the training data at the end of iteration.
+ },
+ ],
+ "maxIterations": "A String", # Output only. Maximum number of iterations specified as max_iterations in the 'CREATE MODEL' query. The actual number of iterations may be less than this number due to early stop.
+ "modelType": "A String", # Output only. The type of the model that is being trained.
+ "trainingType": "A String", # Output only. Training type of the job.
+ },
+ "modelTraining": { # Deprecated.
+ "currentIteration": 42, # Deprecated.
+ "expectedTotalIterations": "A String", # Deprecated.
+ },
+ "modelTrainingCurrentIteration": 42, # Deprecated.
+ "modelTrainingExpectedTotalIteration": "A String", # Deprecated.
+ "numDmlAffectedRows": "A String", # Output only. The number of rows affected by a DML statement. Present only for DML statements INSERT, UPDATE or DELETE.
+ "performanceInsights": { # Performance insights for the job. # Output only. Performance insights.
+ "avgPreviousExecutionMs": "A String", # Output only. Average execution ms of previous runs. Indicates the job ran slow compared to previous executions. To find previous executions, use INFORMATION_SCHEMA tables and filter jobs with same query hash.
+ "stagePerformanceChangeInsights": [ # Output only. Query stage performance insights compared to previous runs, for diagnosing performance regression.
+ { # Performance insights compared to the previous executions for a specific stage.
+ "inputDataChange": { # Details about the input data change insight. # Output only. Input data change insight of the query stage.
+ "recordsReadDiffPercentage": 3.14, # Output only. Records read difference percentage compared to a previous run.
+ },
+ "stageId": "A String", # Output only. The stage id that the insight mapped to.
+ },
+ ],
+ "stagePerformanceStandaloneInsights": [ # Output only. Standalone query stage performance insights, for exploring potential improvements.
+ { # Standalone performance insights for a specific stage.
+ "biEngineReasons": [ # Output only. If present, the stage had the following reasons for being disqualified from BI Engine execution.
+ { # Reason why BI Engine didn't accelerate the query (or sub-query).
+ "code": "A String", # Output only. High-level BI Engine reason for partial or disabled acceleration
+ "message": "A String", # Output only. Free form human-readable reason for partial or disabled acceleration.
+ },
+ ],
+ "highCardinalityJoins": [ # Output only. High cardinality joins in the stage.
+ { # High cardinality join detailed information.
+ "leftRows": "A String", # Output only. Count of left input rows.
+ "outputRows": "A String", # Output only. Count of the output rows.
+ "rightRows": "A String", # Output only. Count of right input rows.
+ "stepIndex": 42, # Output only. The index of the join operator in the ExplainQueryStep lists.
+ },
+ ],
+ "insufficientShuffleQuota": True or False, # Output only. True if the stage has insufficient shuffle quota.
+ "slotContention": True or False, # Output only. True if the stage has a slot contention issue.
+ "stageId": "A String", # Output only. The stage id that the insight mapped to.
+ },
+ ],
+ },
+ "queryInfo": { # Query optimization information for a QUERY job. # Output only. Query optimization information for a QUERY job.
+ "optimizationDetails": { # Output only. Information about query optimizations.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "queryPlan": [ # Output only. Describes execution plan for the query.
+ { # A single stage of query execution.
+ "completedParallelInputs": "A String", # Number of parallel input segments completed.
+ "computeMode": "A String", # Output only. Compute mode for this stage.
+ "computeMsAvg": "A String", # Milliseconds the average shard spent on CPU-bound tasks.
+ "computeMsMax": "A String", # Milliseconds the slowest shard spent on CPU-bound tasks.
+ "computeRatioAvg": 3.14, # Relative amount of time the average shard spent on CPU-bound tasks.
+ "computeRatioMax": 3.14, # Relative amount of time the slowest shard spent on CPU-bound tasks.
+ "endMs": "A String", # Stage end time represented as milliseconds since the epoch.
+ "id": "A String", # Unique ID for the stage within the plan.
+ "inputStages": [ # IDs for stages that are inputs to this stage.
+ "A String",
+ ],
+ "name": "A String", # Human-readable name for the stage.
+ "parallelInputs": "A String", # Number of parallel input segments to be processed
"readMsAvg": "A String", # Milliseconds the average shard spent reading input.
"readMsMax": "A String", # Milliseconds the slowest shard spent reading input.
"readRatioAvg": 3.14, # Relative amount of time the average shard spent reading input.
@@ -1347,12 +2612,12 @@ Method Details
"shuffleOutputBytes": "A String", # Total number of bytes written to shuffle.
"shuffleOutputBytesSpilled": "A String", # Total number of bytes written to shuffle and spilled to disk.
"slotMs": "A String", # Slot-milliseconds used by the stage.
- "startMs": "A String", # Stage start time represented as milliseconds since epoch.
- "status": "A String", # Current status for the stage.
+ "startMs": "A String", # Stage start time represented as milliseconds since the epoch.
+ "status": "A String", # Current status for this stage.
"steps": [ # List of operations within the stage in dependency order (approximately chronological).
- {
+ { # An operation within a stage.
"kind": "A String", # Machine-readable operation type.
- "substeps": [ # Human-readable stage descriptions.
+ "substeps": [ # Human-readable description of the step(s).
"A String",
],
},
@@ -1367,209 +2632,231 @@ Method Details
"writeRatioMax": 3.14, # Relative amount of time the slowest shard spent on writing output.
},
],
- "referencedRoutines": [ # [Output only] Referenced routines (persistent user-defined functions and stored procedures) for the job.
- {
+ "referencedRoutines": [ # Output only. Referenced routines for the job.
+ { # Id path of a routine.
"datasetId": "A String", # Required. The ID of the dataset containing this routine.
"projectId": "A String", # Required. The ID of the project containing this routine.
"routineId": "A String", # Required. The ID of the routine. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 256 characters.
},
],
- "referencedTables": [ # [Output only] Referenced tables for the job. Queries that reference more than 50 tables will not have a complete list.
+ "referencedTables": [ # Output only. Referenced tables for the job. Queries that reference more than 50 tables will not have a complete list.
{
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
],
- "reservationUsage": [ # [Output only] Job resource usage breakdown by reservation.
- {
- "name": "A String", # [Output only] Reservation name or "unreserved" for on-demand resources usage.
- "slotMs": "A String", # [Output only] Slot-milliseconds the job spent in the given reservation.
+ "reservationUsage": [ # Output only. Job resource usage breakdown by reservation. This field reported misleading information and will no longer be populated.
+ { # Job resource usage breakdown by reservation.
+ "name": "A String", # Reservation name or "unreserved" for on-demand resources usage.
+ "slotMs": "A String", # Total slot milliseconds used by the reservation for a particular job.
},
],
- "schema": { # [Output only] The schema of the results. Present only for successful dry run of non-legacy SQL queries.
+ "schema": { # Schema of a table # Output only. The schema of the results. Present only for successful dry run of non-legacy SQL queries.
"fields": [ # Describes the fields in a table.
- {
- "categories": { # [Optional] The categories attached to this field, used for field-level access control.
- "names": [ # A list of category resource names. For example, "projects/1/taxonomies/2/categories/3". At most 5 categories are allowed.
+ { # A field in TableSchema
+ "categories": { # Deprecated.
+ "names": [ # Deprecated.
"A String",
],
},
- "collation": "A String", # Optional. Collation specification of the field. It only can be set on string type field.
- "defaultValueExpression": "A String", # Optional. A SQL expression to specify the default value for this field. It can only be set for top level fields (columns). You can use struct or array expression to specify default value for the entire struct or array. The valid SQL expressions are: - Literals for all data types, including STRUCT and ARRAY. - Following functions: - CURRENT_TIMESTAMP - CURRENT_TIME - CURRENT_DATE - CURRENT_DATETIME - GENERATE_UUID - RAND - SESSION_USER - ST_GEOGPOINT - Struct or array composed with the above allowed functions, for example, [CURRENT_DATE(), DATE '2020-01-01']
- "description": "A String", # [Optional] The field description. The maximum length is 1,024 characters.
- "fields": [ # [Optional] Describes the nested schema fields if the type property is set to RECORD.
+ "collation": "A String", # Optional. Field collation can be set only when the type of field is STRING. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.
+ "defaultValueExpression": "A String", # Optional. A SQL expression to specify the [default value] (https://cloud.google.com/bigquery/docs/default-values) for this field.
+ "description": "A String", # Optional. The field description. The maximum length is 1,024 characters.
+ "fields": [ # Optional. Describes the nested schema fields if the type property is set to RECORD.
# Object with schema name: TableFieldSchema
],
- "maxLength": "A String", # [Optional] Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
- "mode": "A String", # [Optional] The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
- "name": "A String", # [Required] The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
- "policyTags": {
- "names": [ # A list of category resource names. For example, "projects/1/location/eu/taxonomies/2/policyTags/3". At most 1 policy tag is allowed.
+ "maxLength": "A String", # Optional. Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
+ "mode": "A String", # Optional. The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
+ "name": "A String", # Required. The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
+ "policyTags": { # Optional. The policy tags attached to this field, used for field-level access control. If not set, defaults to empty policy_tags.
+ "names": [ # A list of policy tag resource names. For example, "projects/1/locations/eu/taxonomies/2/policyTags/3". At most 1 policy tag is currently allowed.
"A String",
],
},
- "precision": "A String", # [Optional] Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: - Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] - Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: - If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. - If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): - If type = "NUMERIC": 1 ≤ precision ≤ 29. - If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
- "rangeElementType": { # Optional. The subtype of the RANGE, if the type of this field is RANGE. If the type is RANGE, this field is required. Possible values for the field element type of a RANGE include: - DATE - DATETIME - TIMESTAMP
- "type": "A String", # The field element type of a RANGE
+ "precision": "A String", # Optional. Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: * Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] * Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: * If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. * If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): * If type = "NUMERIC": 1 ≤ precision ≤ 29. * If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
+ "rangeElementType": { # Represents the type of a field element.
+ "type": "A String", # Required. The type of a field element. See TableFieldSchema.type.
},
- "roundingMode": "A String", # Optional. Rounding Mode specification of the field. It only can be set on NUMERIC or BIGNUMERIC type fields.
- "scale": "A String", # [Optional] See documentation for precision.
- "type": "A String", # [Required] The field data type. Possible values include STRING, BYTES, INTEGER, INT64 (same as INTEGER), FLOAT, FLOAT64 (same as FLOAT), NUMERIC, BIGNUMERIC, BOOLEAN, BOOL (same as BOOLEAN), TIMESTAMP, DATE, TIME, DATETIME, INTERVAL, RECORD (where RECORD indicates that the field contains a nested schema) or STRUCT (same as RECORD).
+ "roundingMode": "A String", # Optional. Specifies the rounding mode to be used when storing values of NUMERIC and BIGNUMERIC type.
+ "scale": "A String", # Optional. See documentation for precision.
+ "type": "A String", # Required. The field data type. Possible values include: * STRING * BYTES * INTEGER (or INT64) * FLOAT (or FLOAT64) * BOOLEAN (or BOOL) * TIMESTAMP * DATE * TIME * DATETIME * GEOGRAPHY * NUMERIC * BIGNUMERIC * JSON * RECORD (or STRUCT) Use of RECORD/STRUCT indicates that the field contains a nested schema.
},
],
},
- "searchStatistics": { # [Output only] Search query specific statistics.
- "indexUnusedReasons": [ # When index_usage_mode is UNUSED or PARTIALLY_USED, this field explains why index was not used in all or part of the search query. If index_usage_mode is FULLLY_USED, this field is not populated.
- {
- "baseTable": { # [Output-only] Specifies the base table involved in the reason that no search index was used.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "searchStatistics": { # Statistics for a search query. Populated as part of JobStatistics2. # Output only. Search query specific statistics.
+ "indexUnusedReasons": [ # When `indexUsageMode` is `UNUSED` or `PARTIALLY_USED`, this field explains why indexes were not used in all or part of the search query. If `indexUsageMode` is `FULLY_USED`, this field is not populated.
+ { # Reason about why no search index was used in the search query (or sub-query).
+ "baseTable": { # Specifies the base table involved in the reason that no search index was used.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
- "code": "$(reason.code)", # [Output-only] Specifies the high-level reason for the scenario when no search index was used.
- "indexName": "$(reason.index_name)", # [Output-only] Specifies the name of the unused search index, if available.
- "message": "$(reason.message)", # [Output-only] Free form human-readable reason for the scenario when no search index was used.
+ "code": "A String", # Specifies the high-level reason for the scenario when no search index was used.
+ "indexName": "A String", # Specifies the name of the unused search index, if available.
+ "message": "A String", # Free form human-readable reason for the scenario when no search index was used.
},
],
- "indexUsageMode": "A String", # Specifies index usage mode for the query.
+ "indexUsageMode": "A String", # Specifies the index usage mode for the query.
},
- "sparkStatistics": { # [Output only] Statistics of a Spark procedure job.
- "endpoints": { # [Output-only] Endpoints generated for the Spark job.
+ "sparkStatistics": { # Statistics for a BigSpark query. Populated as part of JobStatistics2 # Output only. Statistics of a Spark procedure job.
+ "endpoints": { # Output only. Endpoints returned from Dataproc. Key list: - history_server_endpoint: A link to Spark job UI.
"a_key": "A String",
},
- "loggingInfo": { # [Output-only] Logging info is used to generate a link to Cloud Logging.
- "projectId": "A String", # [Output-only] Project ID used for logging
- "resourceType": "A String", # [Output-only] Resource type used for logging
+ "gcsStagingBucket": "A String", # Output only. The Google Cloud Storage bucket that is used as the default filesystem by the Spark application. This fields is only filled when the Spark procedure uses the INVOKER security mode. It is inferred from the system variable @@spark_proc_properties.staging_bucket if it is provided. Otherwise, BigQuery creates a default staging bucket for the job and returns the bucket name in this field. Example: * `gs://[bucket_name]`
+ "kmsKeyName": "A String", # Output only. The Cloud KMS encryption key that is used to protect the resources created by the Spark job. If the Spark procedure uses DEFINER security mode, the Cloud KMS key is inferred from the Spark connection associated with the procedure if it is provided. Otherwise the key is inferred from the default key of the Spark connection's project if the CMEK organization policy is enforced. If the Spark procedure uses INVOKER security mode, the Cloud KMS encryption key is inferred from the system variable @@spark_proc_properties.kms_key_name if it is provided. Otherwise, the key is inferred fromt he default key of the BigQuery job's project if the CMEK organization policy is enforced. Example: * `projects/[kms_project_id]/locations/[region]/keyRings/[key_region]/cryptoKeys/[key]`
+ "loggingInfo": { # Spark job logs can be filtered by these fields in Cloud Logging. # Output only. Logging info is used to generate a link to Cloud Logging.
+ "projectId": "A String", # Output only. Project ID where the Spark logs were written.
+ "resourceType": "A String", # Output only. Resource type used for logging.
},
- "sparkJobId": "A String", # [Output-only] Spark job id if a Spark job is created successfully.
- "sparkJobLocation": "A String", # [Output-only] Location where the Spark job is executed.
+ "sparkJobId": "A String", # Output only. Spark job ID if a Spark job is created successfully.
+ "sparkJobLocation": "A String", # Output only. Location where the Spark job is executed. A location is selected by BigQueury for jobs configured to run in a multi-region.
},
- "statementType": "A String", # The type of query statement, if valid. Possible values (new values might be added in the future): "SELECT": SELECT query. "INSERT": INSERT query; see https://cloud.google.com/bigquery/docs/reference/standard-sql/data-manipulation-language. "UPDATE": UPDATE query; see https://cloud.google.com/bigquery/docs/reference/standard-sql/data-manipulation-language. "DELETE": DELETE query; see https://cloud.google.com/bigquery/docs/reference/standard-sql/data-manipulation-language. "MERGE": MERGE query; see https://cloud.google.com/bigquery/docs/reference/standard-sql/data-manipulation-language. "ALTER_TABLE": ALTER TABLE query. "ALTER_VIEW": ALTER VIEW query. "ASSERT": ASSERT condition AS 'description'. "CREATE_FUNCTION": CREATE FUNCTION query. "CREATE_MODEL": CREATE [OR REPLACE] MODEL ... AS SELECT ... . "CREATE_PROCEDURE": CREATE PROCEDURE query. "CREATE_TABLE": CREATE [OR REPLACE] TABLE without AS SELECT. "CREATE_TABLE_AS_SELECT": CREATE [OR REPLACE] TABLE ... AS SELECT ... . "CREATE_VIEW": CREATE [OR REPLACE] VIEW ... AS SELECT ... . "DROP_FUNCTION" : DROP FUNCTION query. "DROP_PROCEDURE": DROP PROCEDURE query. "DROP_TABLE": DROP TABLE query. "DROP_VIEW": DROP VIEW query.
- "timeline": [ # [Output only] [Beta] Describes a timeline of job execution.
- {
- "activeUnits": "A String", # Total number of units currently being processed by workers. This does not correspond directly to slot usage. This is the largest value observed since the last sample.
+ "statementType": "A String", # Output only. The type of query statement, if valid. Possible values: * `SELECT`: [`SELECT`](/bigquery/docs/reference/standard-sql/query-syntax#select_list) statement. * `ASSERT`: [`ASSERT`](/bigquery/docs/reference/standard-sql/debugging-statements#assert) statement. * `INSERT`: [`INSERT`](/bigquery/docs/reference/standard-sql/dml-syntax#insert_statement) statement. * `UPDATE`: [`UPDATE`](/bigquery/docs/reference/standard-sql/query-syntax#update_statement) statement. * `DELETE`: [`DELETE`](/bigquery/docs/reference/standard-sql/data-manipulation-language) statement. * `MERGE`: [`MERGE`](/bigquery/docs/reference/standard-sql/data-manipulation-language) statement. * `CREATE_TABLE`: [`CREATE TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#create_table_statement) statement, without `AS SELECT`. * `CREATE_TABLE_AS_SELECT`: [`CREATE TABLE AS SELECT`](/bigquery/docs/reference/standard-sql/data-definition-language#query_statement) statement. * `CREATE_VIEW`: [`CREATE VIEW`](/bigquery/docs/reference/standard-sql/data-definition-language#create_view_statement) statement. * `CREATE_MODEL`: [`CREATE MODEL`](/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-create#create_model_statement) statement. * `CREATE_MATERIALIZED_VIEW`: [`CREATE MATERIALIZED VIEW`](/bigquery/docs/reference/standard-sql/data-definition-language#create_materialized_view_statement) statement. * `CREATE_FUNCTION`: [`CREATE FUNCTION`](/bigquery/docs/reference/standard-sql/data-definition-language#create_function_statement) statement. * `CREATE_TABLE_FUNCTION`: [`CREATE TABLE FUNCTION`](/bigquery/docs/reference/standard-sql/data-definition-language#create_table_function_statement) statement. * `CREATE_PROCEDURE`: [`CREATE PROCEDURE`](/bigquery/docs/reference/standard-sql/data-definition-language#create_procedure) statement. * `CREATE_ROW_ACCESS_POLICY`: [`CREATE ROW ACCESS POLICY`](/bigquery/docs/reference/standard-sql/data-definition-language#create_row_access_policy_statement) statement. * `CREATE_SCHEMA`: [`CREATE SCHEMA`](/bigquery/docs/reference/standard-sql/data-definition-language#create_schema_statement) statement. * `CREATE_SNAPSHOT_TABLE`: [`CREATE SNAPSHOT TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#create_snapshot_table_statement) statement. * `CREATE_SEARCH_INDEX`: [`CREATE SEARCH INDEX`](/bigquery/docs/reference/standard-sql/data-definition-language#create_search_index_statement) statement. * `DROP_TABLE`: [`DROP TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_table_statement) statement. * `DROP_EXTERNAL_TABLE`: [`DROP EXTERNAL TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_external_table_statement) statement. * `DROP_VIEW`: [`DROP VIEW`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_view_statement) statement. * `DROP_MODEL`: [`DROP MODEL`](/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-drop-model) statement. * `DROP_MATERIALIZED_VIEW`: [`DROP MATERIALIZED VIEW`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_materialized_view_statement) statement. * `DROP_FUNCTION` : [`DROP FUNCTION`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_function_statement) statement. * `DROP_TABLE_FUNCTION` : [`DROP TABLE FUNCTION`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_table_function) statement. * `DROP_PROCEDURE`: [`DROP PROCEDURE`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_procedure_statement) statement. * `DROP_SEARCH_INDEX`: [`DROP SEARCH INDEX`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_search_index) statement. * `DROP_SCHEMA`: [`DROP SCHEMA`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_schema_statement) statement. * `DROP_SNAPSHOT_TABLE`: [`DROP SNAPSHOT TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_snapshot_table_statement) statement. * `DROP_ROW_ACCESS_POLICY`: [`DROP [ALL] ROW ACCESS POLICY|POLICIES`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_row_access_policy_statement) statement. * `ALTER_TABLE`: [`ALTER TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#alter_table_set_options_statement) statement. * `ALTER_VIEW`: [`ALTER VIEW`](/bigquery/docs/reference/standard-sql/data-definition-language#alter_view_set_options_statement) statement. * `ALTER_MATERIALIZED_VIEW`: [`ALTER MATERIALIZED VIEW`](/bigquery/docs/reference/standard-sql/data-definition-language#alter_materialized_view_set_options_statement) statement. * `ALTER_SCHEMA`: [`ALTER SCHEMA`](/bigquery/docs/reference/standard-sql/data-definition-language#aalter_schema_set_options_statement) statement. * `SCRIPT`: [`SCRIPT`](/bigquery/docs/reference/standard-sql/procedural-language). * `TRUNCATE_TABLE`: [`TRUNCATE TABLE`](/bigquery/docs/reference/standard-sql/dml-syntax#truncate_table_statement) statement. * `CREATE_EXTERNAL_TABLE`: [`CREATE EXTERNAL TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#create_external_table_statement) statement. * `EXPORT_DATA`: [`EXPORT DATA`](/bigquery/docs/reference/standard-sql/other-statements#export_data_statement) statement. * `EXPORT_MODEL`: [`EXPORT MODEL`](/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-export-model) statement. * `LOAD_DATA`: [`LOAD DATA`](/bigquery/docs/reference/standard-sql/other-statements#load_data_statement) statement. * `CALL`: [`CALL`](/bigquery/docs/reference/standard-sql/procedural-language#call) statement.
+ "timeline": [ # Output only. Describes a timeline of job execution.
+ { # Summary of the state of query execution at a given time.
+ "activeUnits": "A String", # Total number of active workers. This does not correspond directly to slot usage. This is the largest value observed since the last sample.
"completedUnits": "A String", # Total parallel units of work completed by this query.
"elapsedMs": "A String", # Milliseconds elapsed since the start of query execution.
- "estimatedRunnableUnits": "A String", # Units of work that can be scheduled immediately. Providing additional slots for these units of work will speed up the query, provided no other query in the reservation needs additional slots.
+ "estimatedRunnableUnits": "A String", # Units of work that can be scheduled immediately. Providing additional slots for these units of work will accelerate the query, if no other query in the reservation needs additional slots.
"pendingUnits": "A String", # Total units of work remaining for the query. This number can be revised (increased or decreased) while the query is running.
"totalSlotMs": "A String", # Cumulative slot-ms consumed by the query.
},
],
- "totalBytesBilled": "A String", # [Output only] Total bytes billed for the job.
- "totalBytesProcessed": "A String", # [Output only] Total bytes processed for the job.
- "totalBytesProcessedAccuracy": "A String", # [Output only] For dry-run jobs, totalBytesProcessed is an estimate and this field specifies the accuracy of the estimate. Possible values can be: UNKNOWN: accuracy of the estimate is unknown. PRECISE: estimate is precise. LOWER_BOUND: estimate is lower bound of what the query would cost. UPPER_BOUND: estimate is upper bound of what the query would cost.
- "totalPartitionsProcessed": "A String", # [Output only] Total number of partitions processed from all partitioned tables referenced in the job.
- "totalSlotMs": "A String", # [Output only] Slot-milliseconds for the job.
- "transferredBytes": "A String", # [Output-only] Total bytes transferred for cross-cloud queries such as Cross Cloud Transfer and CREATE TABLE AS SELECT (CTAS).
- "undeclaredQueryParameters": [ # Standard SQL only: list of undeclared query parameters detected during a dry run validation.
- {
- "name": "A String", # [Optional] If unset, this is a positional parameter. Otherwise, should be unique within a query.
- "parameterType": { # [Required] The type of this parameter.
- "arrayType": # Object with schema name: QueryParameterType # [Optional] The type of the array's elements, if this is an array.
- "rangeElementType": # Object with schema name: QueryParameterType # [Optional] The element type of the range, if this is a range.
- "structTypes": [ # [Optional] The types of the fields of this struct, in order, if this is a struct.
- {
- "description": "A String", # [Optional] Human-oriented description of the field.
- "name": "A String", # [Optional] The name of this field.
- "type": # Object with schema name: QueryParameterType # [Required] The type of this field.
+ "totalBytesBilled": "A String", # Output only. If the project is configured to use on-demand pricing, then this field contains the total bytes billed for the job. If the project is configured to use flat-rate pricing, then you are not billed for bytes and this field is informational only.
+ "totalBytesProcessed": "A String", # Output only. Total bytes processed for the job.
+ "totalBytesProcessedAccuracy": "A String", # Output only. For dry-run jobs, totalBytesProcessed is an estimate and this field specifies the accuracy of the estimate. Possible values can be: UNKNOWN: accuracy of the estimate is unknown. PRECISE: estimate is precise. LOWER_BOUND: estimate is lower bound of what the query would cost. UPPER_BOUND: estimate is upper bound of what the query would cost.
+ "totalPartitionsProcessed": "A String", # Output only. Total number of partitions processed from all partitioned tables referenced in the job.
+ "totalSlotMs": "A String", # Output only. Slot-milliseconds for the job.
+ "transferredBytes": "A String", # Output only. Total bytes transferred for cross-cloud queries such as Cross Cloud Transfer and CREATE TABLE AS SELECT (CTAS).
+ "undeclaredQueryParameters": [ # Output only. GoogleSQL only: list of undeclared query parameters detected during a dry run validation.
+ { # A parameter given to a query.
+ "name": "A String", # Optional. If unset, this is a positional parameter. Otherwise, should be unique within a query.
+ "parameterType": { # The type of a query parameter. # Required. The type of this parameter.
+ "arrayType": # Object with schema name: QueryParameterType # Optional. The type of the array's elements, if this is an array.
+ "rangeElementType": # Object with schema name: QueryParameterType # Optional. The element type of the range, if this is a range.
+ "structTypes": [ # Optional. The types of the fields of this struct, in order, if this is a struct.
+ { # The type of a struct parameter.
+ "description": "A String", # Optional. Human-oriented description of the field.
+ "name": "A String", # Optional. The name of this field.
+ "type": # Object with schema name: QueryParameterType # Required. The type of this field.
},
],
- "type": "A String", # [Required] The top level type of this field.
+ "type": "A String", # Required. The top level type of this field.
},
- "parameterValue": { # [Required] The value of this parameter.
- "arrayValues": [ # [Optional] The array values, if this is an array type.
+ "parameterValue": { # The value of a query parameter. # Required. The value of this parameter.
+ "arrayValues": [ # Optional. The array values, if this is an array type.
# Object with schema name: QueryParameterValue
],
- "rangeValue": { # [Optional] The range value, if this is a range type.
- "end": # Object with schema name: QueryParameterValue
- "start": # Object with schema name: QueryParameterValue
+ "rangeValue": { # Represents the value of a range. # Optional. The range value, if this is a range type.
+ "end": # Object with schema name: QueryParameterValue # Optional. The end value of the range. A missing value represents an unbounded end.
+ "start": # Object with schema name: QueryParameterValue # Optional. The start value of the range. A missing value represents an unbounded start.
},
- "structValues": { # [Optional] The struct field values, in order of the struct type's declaration.
+ "structValues": { # The struct field values.
"a_key": # Object with schema name: QueryParameterValue
},
- "value": "A String", # [Optional] The value of this value, if a simple scalar type.
+ "value": "A String", # Optional. The value of this value, if a simple scalar type.
},
},
],
+ "vectorSearchStatistics": { # Statistics for a vector search query. Populated as part of JobStatistics2. # Output only. Search query specific statistics.
+ "indexUnusedReasons": [ # When `indexUsageMode` is `UNUSED` or `PARTIALLY_USED`, this field explains why indexes were not used in all or part of the vector search query. If `indexUsageMode` is `FULLY_USED`, this field is not populated.
+ { # Reason about why no search index was used in the search query (or sub-query).
+ "baseTable": { # Specifies the base table involved in the reason that no search index was used.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ "code": "A String", # Specifies the high-level reason for the scenario when no search index was used.
+ "indexName": "A String", # Specifies the name of the unused search index, if available.
+ "message": "A String", # Free form human-readable reason for the scenario when no search index was used.
+ },
+ ],
+ "indexUsageMode": "A String", # Specifies the index usage mode for the query.
+ },
},
- "quotaDeferments": [ # [Output-only] Quotas which delayed this job's start time.
+ "quotaDeferments": [ # Output only. Quotas which delayed this job's start time.
"A String",
],
- "reservationUsage": [ # [Output-only] Job resource usage breakdown by reservation.
- {
- "name": "A String", # [Output-only] Reservation name or "unreserved" for on-demand resources usage.
- "slotMs": "A String", # [Output-only] Slot-milliseconds the job spent in the given reservation.
+ "reservationUsage": [ # Output only. Job resource usage breakdown by reservation. This field reported misleading information and will no longer be populated.
+ { # Job resource usage breakdown by reservation.
+ "name": "A String", # Reservation name or "unreserved" for on-demand resources usage.
+ "slotMs": "A String", # Total slot milliseconds used by the reservation for a particular job.
},
],
- "reservation_id": "A String", # [Output-only] Name of the primary reservation assigned to this job. Note that this could be different than reservations reported in the reservation usage field if parent reservations were used to execute this job.
- "rowLevelSecurityStatistics": { # [Output-only] [Preview] Statistics for row-level security. Present only for query and extract jobs.
- "rowLevelSecurityApplied": True or False, # [Output-only] [Preview] Whether any accessed data was protected by row access policies.
+ "reservation_id": "A String", # Output only. Name of the primary reservation assigned to this job. Note that this could be different than reservations reported in the reservation usage field if parent reservations were used to execute this job.
+ "rowLevelSecurityStatistics": { # Statistics for row-level security. # Output only. Statistics for row-level security. Present only for query and extract jobs.
+ "rowLevelSecurityApplied": True or False, # Whether any accessed data was protected by row access policies.
},
- "scriptStatistics": { # [Output-only] Statistics for a child job of a script.
- "evaluationKind": "A String", # [Output-only] Whether this child job was a statement or expression.
+ "scriptStatistics": { # Job statistics specific to the child job of a script. # Output only. If this a child job of a script, specifies information about the context of this job within the script.
+ "evaluationKind": "A String", # Whether this child job was a statement or expression.
"stackFrames": [ # Stack trace showing the line/column/procedure name of each frame on the stack at the point where the current evaluation happened. The leaf frame is first, the primary script is last. Never empty.
- {
- "endColumn": 42, # [Output-only] One-based end column.
- "endLine": 42, # [Output-only] One-based end line.
- "procedureId": "A String", # [Output-only] Name of the active procedure, empty if in a top-level script.
- "startColumn": 42, # [Output-only] One-based start column.
- "startLine": 42, # [Output-only] One-based start line.
- "text": "A String", # [Output-only] Text of the current statement/expression.
+ { # Represents the location of the statement/expression being evaluated. Line and column numbers are defined as follows: - Line and column numbers start with one. That is, line 1 column 1 denotes the start of the script. - When inside a stored procedure, all line/column numbers are relative to the procedure body, not the script in which the procedure was defined. - Start/end positions exclude leading/trailing comments and whitespace. The end position always ends with a ";", when present. - Multi-byte Unicode characters are treated as just one column. - If the original script (or procedure definition) contains TAB characters, a tab "snaps" the indentation forward to the nearest multiple of 8 characters, plus 1. For example, a TAB on column 1, 2, 3, 4, 5, 6 , or 8 will advance the next character to column 9. A TAB on column 9, 10, 11, 12, 13, 14, 15, or 16 will advance the next character to column 17.
+ "endColumn": 42, # Output only. One-based end column.
+ "endLine": 42, # Output only. One-based end line.
+ "procedureId": "A String", # Output only. Name of the active procedure, empty if in a top-level script.
+ "startColumn": 42, # Output only. One-based start column.
+ "startLine": 42, # Output only. One-based start line.
+ "text": "A String", # Output only. Text of the current statement/expression.
},
],
},
- "sessionInfo": { # [Output-only] [Preview] Information of the session if this job is part of one.
- "sessionId": "A String", # [Output-only] // [Preview] Id of the session.
+ "sessionInfo": { # [Preview] Information related to sessions. # Output only. Information of the session if this job is part of one.
+ "sessionId": "A String", # Output only. The id of the session.
},
- "startTime": "A String", # [Output-only] Start time of this job, in milliseconds since the epoch. This field will be present when the job transitions from the PENDING state to either RUNNING or DONE.
- "totalBytesProcessed": "A String", # [Output-only] [Deprecated] Use the bytes processed in the query statistics instead.
- "totalSlotMs": "A String", # [Output-only] Slot-milliseconds for the job.
- "transactionInfo": { # [Output-only] [Alpha] Information of the multi-statement transaction if this job is part of one.
- "transactionId": "A String", # [Output-only] // [Alpha] Id of the transaction.
+ "startTime": "A String", # Output only. Start time of this job, in milliseconds since the epoch. This field will be present when the job transitions from the PENDING state to either RUNNING or DONE.
+ "totalBytesProcessed": "A String", # Output only. Total bytes processed for the job.
+ "totalSlotMs": "A String", # Output only. Slot-milliseconds for the job.
+ "transactionInfo": { # [Alpha] Information of a multi-statement transaction. # Output only. [Alpha] Information of the multi-statement transaction if this job is part of one. This property is only expected on a child job or a job that is in a session. A script parent job is not part of the transaction started in the script.
+ "transactionId": "A String", # Output only. [Alpha] Id of the transaction.
},
},
- "status": { # [Output-only] The status of this job. Examine this value when polling an asynchronous job to see if the job is complete.
- "errorResult": { # [Output-only] Final error result of the job. If present, indicates that the job has completed and was unsuccessful.
+ "status": { # Output only. The status of this job. Examine this value when polling an asynchronous job to see if the job is complete.
+ "errorResult": { # Error details. # Output only. Final error result of the job. If present, indicates that the job has completed and was unsuccessful.
"debugInfo": "A String", # Debugging information. This property is internal to Google and should not be used.
"location": "A String", # Specifies where the error occurred, if present.
"message": "A String", # A human-readable description of the error.
"reason": "A String", # A short error code that summarizes the error.
},
- "errors": [ # [Output-only] The first errors encountered during the running of the job. The final message includes the number of errors that caused the process to stop. Errors here do not necessarily mean that the job has completed or was unsuccessful.
- {
+ "errors": [ # Output only. The first errors encountered during the running of the job. The final message includes the number of errors that caused the process to stop. Errors here do not necessarily mean that the job has not completed or was unsuccessful.
+ { # Error details.
"debugInfo": "A String", # Debugging information. This property is internal to Google and should not be used.
"location": "A String", # Specifies where the error occurred, if present.
"message": "A String", # A human-readable description of the error.
"reason": "A String", # A short error code that summarizes the error.
},
],
- "state": "A String", # [Output-only] Running state of the job.
+ "state": "A String", # Output only. Running state of the job. Valid states include 'PENDING', 'RUNNING', and 'DONE'.
},
- "user_email": "A String", # [Output-only] Email address of the user who ran the job.
+ "user_email": "A String", # Output only. Email address of the user who ran the job.
}
getQueryResults(projectId, jobId, location=None, maxResults=None, pageToken=None, startIndex=None, timeoutMs=None)
- Retrieves the results of a query job. +getQueryResults(projectId, jobId, formatOptions_useInt64Timestamp=None, location=None, maxResults=None, pageToken=None, startIndex=None, timeoutMs=None, x__xgafv=None)+RPC to get the results of a query job. Args: - projectId: string, [Required] Project ID of the query job (required) - jobId: string, [Required] Job ID of the query job (required) - location: string, The geographic location where the job should run. Required except for US and EU. See details at https://cloud.google.com/bigquery/docs/locations#specifying_your_location. - maxResults: integer, Maximum number of results to read - pageToken: string, Page token, returned by a previous call, to request the next page of results - startIndex: string, Zero-based index of the starting row - timeoutMs: integer, How long to wait for the query to complete, in milliseconds, before returning. Default is 10 seconds. If the timeout passes before the job completes, the 'jobComplete' field in the response will be false + projectId: string, Required. Project ID of the query job. (required) + jobId: string, Required. Job ID of the query job. (required) + formatOptions_useInt64Timestamp: boolean, Optional. Output timestamp as usec int64. Default is false. + location: string, The geographic location of the job. You must specify the location to run the job for the following scenarios: - If the location to run a job is not in the `us` or the `eu` multi-regional location - If the job's location is in a single region (for example, `us-central1`) For more information, see https://cloud.google.com/bigquery/docs/locations#specifying_your_location. + maxResults: integer, Maximum number of results to read. + pageToken: string, Page token, returned by a previous call, to request the next page of results. + startIndex: string, Zero-based index of the starting row. + timeoutMs: integer, Optional: Specifies the maximum amount of time, in milliseconds, that the client is willing to wait for the query to complete. By default, this limit is 10 seconds (10,000 milliseconds). If the query is complete, the jobComplete field in the response is true. If the query has not yet completed, jobComplete is false. You can request a longer timeout period in the timeoutMs field. However, the call is not guaranteed to wait for the specified timeout; it typically returns after around 200 seconds (200,000 milliseconds), even if the query is not complete. If jobComplete is false, you can continue to wait for the query to complete by calling the getQueryResults method until the jobComplete field in the getQueryResults response is true. + x__xgafv: string, V1 error format. + Allowed values + 1 - v1 error format + 2 - v2 error format Returns: An object of the form: - { + { # Response object of GetQueryResults. "cacheHit": True or False, # Whether the query result was fetched from the query cache. - "errors": [ # [Output-only] The first errors or warnings encountered during the running of the job. The final message includes the number of errors that caused the process to stop. Errors here do not necessarily mean that the job has completed or was unsuccessful. - { + "errors": [ # Output only. The first errors or warnings encountered during the running of the job. The final message includes the number of errors that caused the process to stop. Errors here do not necessarily mean that the job has completed or was unsuccessful. For more information about error messages, see [Error messages](https://cloud.google.com/bigquery/docs/error-messages). + { # Error details. "debugInfo": "A String", # Debugging information. This property is internal to Google and should not be used. "location": "A String", # Specifies where the error occurred, if present. "message": "A String", # A human-readable description of the error. @@ -1578,15 +2865,15 @@Method Details
], "etag": "A String", # A hash of this response. "jobComplete": True or False, # Whether the query has completed or not. If rows or totalRows are present, this will always be true. If this is false, totalRows will not be available. - "jobReference": { # Reference to the BigQuery Job that was created to run the query. This field will be present even if the original request timed out, in which case GetQueryResults can be used to read the results once the query has completed. Since this API only returns the first page of results, subsequent pages can be fetched via the same mechanism (GetQueryResults). - "jobId": "A String", # [Required] The ID of the job. The ID must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), or dashes (-). The maximum length is 1,024 characters. - "location": "A String", # The geographic location of the job. See details at https://cloud.google.com/bigquery/docs/locations#specifying_your_location. - "projectId": "A String", # [Required] The ID of the project containing this job. + "jobReference": { # A job reference is a fully qualified identifier for referring to a job. # Reference to the BigQuery Job that was created to run the query. This field will be present even if the original request timed out, in which case GetQueryResults can be used to read the results once the query has completed. Since this API only returns the first page of results, subsequent pages can be fetched via the same mechanism (GetQueryResults). + "jobId": "A String", # Required. The ID of the job. The ID must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), or dashes (-). The maximum length is 1,024 characters. + "location": "A String", # Optional. The geographic location of the job. The default value is US. For more information about BigQuery locations, see: https://cloud.google.com/bigquery/docs/locations + "projectId": "A String", # Required. The ID of the project containing this job. }, "kind": "bigquery#getQueryResultsResponse", # The resource type of the response. - "numDmlAffectedRows": "A String", # [Output-only] The number of rows affected by a DML statement. Present only for DML statements INSERT, UPDATE or DELETE. - "pageToken": "A String", # A token used for paging results. - "rows": [ # An object with as many results as can be contained within the maximum permitted reply size. To get any additional rows, you can call GetQueryResults and specify the jobReference returned above. Present only when the query completes successfully. + "numDmlAffectedRows": "A String", # Output only. The number of rows affected by a DML statement. Present only for DML statements INSERT, UPDATE or DELETE. + "pageToken": "A String", # A token used for paging results. When this token is non-empty, it indicates additional results are available. + "rows": [ # An object with as many results as can be contained within the maximum permitted reply size. To get any additional rows, you can call GetQueryResults and specify the jobReference returned above. Present only when the query completes successfully. The REST-based representation of this data leverages a series of JSON f,v objects for indicating fields and values. { "f": [ # Represents a single row in the result set, consisting of one or more fields. { @@ -1595,35 +2882,35 @@Method Details
], }, ], - "schema": { # The schema of the results. Present only when the query completes successfully. + "schema": { # Schema of a table # The schema of the results. Present only when the query completes successfully. "fields": [ # Describes the fields in a table. - { - "categories": { # [Optional] The categories attached to this field, used for field-level access control. - "names": [ # A list of category resource names. For example, "projects/1/taxonomies/2/categories/3". At most 5 categories are allowed. + { # A field in TableSchema + "categories": { # Deprecated. + "names": [ # Deprecated. "A String", ], }, - "collation": "A String", # Optional. Collation specification of the field. It only can be set on string type field. - "defaultValueExpression": "A String", # Optional. A SQL expression to specify the default value for this field. It can only be set for top level fields (columns). You can use struct or array expression to specify default value for the entire struct or array. The valid SQL expressions are: - Literals for all data types, including STRUCT and ARRAY. - Following functions: - CURRENT_TIMESTAMP - CURRENT_TIME - CURRENT_DATE - CURRENT_DATETIME - GENERATE_UUID - RAND - SESSION_USER - ST_GEOGPOINT - Struct or array composed with the above allowed functions, for example, [CURRENT_DATE(), DATE '2020-01-01'] - "description": "A String", # [Optional] The field description. The maximum length is 1,024 characters. - "fields": [ # [Optional] Describes the nested schema fields if the type property is set to RECORD. + "collation": "A String", # Optional. Field collation can be set only when the type of field is STRING. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior. + "defaultValueExpression": "A String", # Optional. A SQL expression to specify the [default value] (https://cloud.google.com/bigquery/docs/default-values) for this field. + "description": "A String", # Optional. The field description. The maximum length is 1,024 characters. + "fields": [ # Optional. Describes the nested schema fields if the type property is set to RECORD. # Object with schema name: TableFieldSchema ], - "maxLength": "A String", # [Optional] Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES". - "mode": "A String", # [Optional] The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE. - "name": "A String", # [Required] The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters. - "policyTags": { - "names": [ # A list of category resource names. For example, "projects/1/location/eu/taxonomies/2/policyTags/3". At most 1 policy tag is allowed. + "maxLength": "A String", # Optional. Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES". + "mode": "A String", # Optional. The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE. + "name": "A String", # Required. The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters. + "policyTags": { # Optional. The policy tags attached to this field, used for field-level access control. If not set, defaults to empty policy_tags. + "names": [ # A list of policy tag resource names. For example, "projects/1/locations/eu/taxonomies/2/policyTags/3". At most 1 policy tag is currently allowed. "A String", ], }, - "precision": "A String", # [Optional] Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: - Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] - Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: - If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. - If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): - If type = "NUMERIC": 1 ≤ precision ≤ 29. - If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid. - "rangeElementType": { # Optional. The subtype of the RANGE, if the type of this field is RANGE. If the type is RANGE, this field is required. Possible values for the field element type of a RANGE include: - DATE - DATETIME - TIMESTAMP - "type": "A String", # The field element type of a RANGE + "precision": "A String", # Optional. Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: * Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] * Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: * If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. * If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): * If type = "NUMERIC": 1 ≤ precision ≤ 29. * If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid. + "rangeElementType": { # Represents the type of a field element. + "type": "A String", # Required. The type of a field element. See TableFieldSchema.type. }, - "roundingMode": "A String", # Optional. Rounding Mode specification of the field. It only can be set on NUMERIC or BIGNUMERIC type fields. - "scale": "A String", # [Optional] See documentation for precision. - "type": "A String", # [Required] The field data type. Possible values include STRING, BYTES, INTEGER, INT64 (same as INTEGER), FLOAT, FLOAT64 (same as FLOAT), NUMERIC, BIGNUMERIC, BOOLEAN, BOOL (same as BOOLEAN), TIMESTAMP, DATE, TIME, DATETIME, INTERVAL, RECORD (where RECORD indicates that the field contains a nested schema) or STRUCT (same as RECORD). + "roundingMode": "A String", # Optional. Specifies the rounding mode to be used when storing values of NUMERIC and BIGNUMERIC type. + "scale": "A String", # Optional. See documentation for precision. + "type": "A String", # Required. The field data type. Possible values include: * STRING * BYTES * INTEGER (or INT64) * FLOAT (or FLOAT64) * BOOLEAN (or BOOL) * TIMESTAMP * DATE * TIME * DATETIME * GEOGRAPHY * NUMERIC * BIGNUMERIC * JSON * RECORD (or STRUCT) Use of RECORD/STRUCT indicates that the field contains a nested schema. }, ], }, @@ -1647,1209 +2934,2466 @@Method Details
insert(projectId, body=None, media_body=None, media_mime_type=None)
- Starts a new asynchronous job. Requires the Can View project role. +insert(projectId, body=None, media_body=None, media_mime_type=None, x__xgafv=None)+Starts a new asynchronous job. This API has two different kinds of endpoint URIs, as this method supports a variety of use cases. * The *Metadata* URI is used for most interactions, as it accepts the job configuration directly. * The *Upload* URI is ONLY for the case when you're sending both a load job configuration and a data stream together. In this case, the Upload URI accepts the job configuration and the data as two distinct multipart MIME parts. Args: - projectId: string, Project ID of the project that will be billed for the job (required) + projectId: string, Project ID of project that will be billed for the job. (required) body: object, The request body. The object takes the form of: { - "configuration": { # [Required] Describes the job configuration. - "copy": { # [Pick one] Copies a table. - "createDisposition": "A String", # [Optional] Specifies whether the job is allowed to create new tables. The following values are supported: CREATE_IF_NEEDED: If the table does not exist, BigQuery creates the table. CREATE_NEVER: The table must already exist. If it does not, a 'notFound' error is returned in the job result. The default value is CREATE_IF_NEEDED. Creation, truncation and append actions occur as one atomic update upon job completion. + "configuration": { # Required. Describes the job configuration. + "copy": { # JobConfigurationTableCopy configures a job that copies data from one table to another. For more information on copying tables, see [Copy a table](https://cloud.google.com/bigquery/docs/managing-tables#copy-table). # [Pick one] Copies a table. + "createDisposition": "A String", # Optional. Specifies whether the job is allowed to create new tables. The following values are supported: * CREATE_IF_NEEDED: If the table does not exist, BigQuery creates the table. * CREATE_NEVER: The table must already exist. If it does not, a 'notFound' error is returned in the job result. The default value is CREATE_IF_NEEDED. Creation, truncation and append actions occur as one atomic update upon job completion. "destinationEncryptionConfiguration": { # Custom encryption configuration (e.g., Cloud KMS keys). "kmsKeyName": "A String", # Optional. Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key. }, - "destinationExpirationTime": "", # [Optional] The time when the destination table expires. Expired tables will be deleted and their storage reclaimed. - "destinationTable": { # [Required] The destination table - "datasetId": "A String", # [Required] The ID of the dataset containing this table. - "projectId": "A String", # [Required] The ID of the project containing this table. - "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. + "destinationExpirationTime": "A String", # Optional. The time when the destination table expires. Expired tables will be deleted and their storage reclaimed. + "destinationTable": { # [Required] The destination table. + "datasetId": "A String", # Required. The ID of the dataset containing this table. + "projectId": "A String", # Required. The ID of the project containing this table. + "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`. }, - "operationType": "A String", # [Optional] Supported operation types in table copy job. + "operationType": "A String", # Optional. Supported operation types in table copy job. "sourceTable": { # [Pick one] Source table to copy. - "datasetId": "A String", # [Required] The ID of the dataset containing this table. - "projectId": "A String", # [Required] The ID of the project containing this table. - "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. + "datasetId": "A String", # Required. The ID of the dataset containing this table. + "projectId": "A String", # Required. The ID of the project containing this table. + "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`. }, "sourceTables": [ # [Pick one] Source tables to copy. { - "datasetId": "A String", # [Required] The ID of the dataset containing this table. - "projectId": "A String", # [Required] The ID of the project containing this table. - "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. + "datasetId": "A String", # Required. The ID of the dataset containing this table. + "projectId": "A String", # Required. The ID of the project containing this table. + "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`. }, ], - "writeDisposition": "A String", # [Optional] Specifies the action that occurs if the destination table already exists. The following values are supported: WRITE_TRUNCATE: If the table already exists, BigQuery overwrites the table data. WRITE_APPEND: If the table already exists, BigQuery appends the data to the table. WRITE_EMPTY: If the table already exists and contains data, a 'duplicate' error is returned in the job result. The default value is WRITE_EMPTY. Each action is atomic and only occurs if BigQuery is able to complete the job successfully. Creation, truncation and append actions occur as one atomic update upon job completion. + "writeDisposition": "A String", # Optional. Specifies the action that occurs if the destination table already exists. The following values are supported: * WRITE_TRUNCATE: If the table already exists, BigQuery overwrites the table data and uses the schema and table constraints from the source table. * WRITE_APPEND: If the table already exists, BigQuery appends the data to the table. * WRITE_EMPTY: If the table already exists and contains data, a 'duplicate' error is returned in the job result. The default value is WRITE_EMPTY. Each action is atomic and only occurs if BigQuery is able to complete the job successfully. Creation, truncation and append actions occur as one atomic update upon job completion. }, - "dryRun": True or False, # [Optional] If set, don't actually run this job. A valid query will return a mostly empty response with some processing statistics, while an invalid query will return the same error it would if it wasn't a dry run. Behavior of non-query jobs is undefined. - "extract": { # [Pick one] Configures an extract job. - "compression": "A String", # [Optional] The compression type to use for exported files. Possible values include GZIP, DEFLATE, SNAPPY, and NONE. The default value is NONE. DEFLATE and SNAPPY are only supported for Avro. Not applicable when extracting models. - "destinationFormat": "A String", # [Optional] The exported file format. Possible values include CSV, NEWLINE_DELIMITED_JSON, PARQUET or AVRO for tables and ML_TF_SAVED_MODEL or ML_XGBOOST_BOOSTER for models. The default value for tables is CSV. Tables with nested or repeated fields cannot be exported as CSV. The default value for models is ML_TF_SAVED_MODEL. + "dryRun": True or False, # Optional. If set, don't actually run this job. A valid query will return a mostly empty response with some processing statistics, while an invalid query will return the same error it would if it wasn't a dry run. Behavior of non-query jobs is undefined. + "extract": { # JobConfigurationExtract configures a job that exports data from a BigQuery table into Google Cloud Storage. # [Pick one] Configures an extract job. + "compression": "A String", # Optional. The compression type to use for exported files. Possible values include DEFLATE, GZIP, NONE, SNAPPY, and ZSTD. The default value is NONE. Not all compression formats are support for all file formats. DEFLATE is only supported for Avro. ZSTD is only supported for Parquet. Not applicable when extracting models. + "destinationFormat": "A String", # Optional. The exported file format. Possible values include CSV, NEWLINE_DELIMITED_JSON, PARQUET, or AVRO for tables and ML_TF_SAVED_MODEL or ML_XGBOOST_BOOSTER for models. The default value for tables is CSV. Tables with nested or repeated fields cannot be exported as CSV. The default value for models is ML_TF_SAVED_MODEL. "destinationUri": "A String", # [Pick one] DEPRECATED: Use destinationUris instead, passing only one URI as necessary. The fully-qualified Google Cloud Storage URI where the extracted table should be written. "destinationUris": [ # [Pick one] A list of fully-qualified Google Cloud Storage URIs where the extracted table should be written. "A String", ], - "fieldDelimiter": "A String", # [Optional] Delimiter to use between fields in the exported data. Default is ','. Not applicable when extracting models. - "printHeader": true, # [Optional] Whether to print out a header row in the results. Default is true. Not applicable when extracting models. - "sourceModel": { # A reference to the model being exported. + "fieldDelimiter": "A String", # Optional. When extracting data in CSV format, this defines the delimiter to use between fields in the exported data. Default is ','. Not applicable when extracting models. + "modelExtractOptions": { # Options related to model extraction. # Optional. Model extract options only applicable when extracting models. + "trialId": "A String", # The 1-based ID of the trial to be exported from a hyperparameter tuning model. If not specified, the trial with id = [Model](/bigquery/docs/reference/rest/v2/models#resource:-model).defaultTrialId is exported. This field is ignored for models not trained with hyperparameter tuning. + }, + "printHeader": true, # Optional. Whether to print out a header row in the results. Default is true. Not applicable when extracting models. + "sourceModel": { # Id path of a model. # A reference to the model being exported. "datasetId": "A String", # Required. The ID of the dataset containing this model. "modelId": "A String", # Required. The ID of the model. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. "projectId": "A String", # Required. The ID of the project containing this model. }, "sourceTable": { # A reference to the table being exported. - "datasetId": "A String", # [Required] The ID of the dataset containing this table. - "projectId": "A String", # [Required] The ID of the project containing this table. - "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. + "datasetId": "A String", # Required. The ID of the dataset containing this table. + "projectId": "A String", # Required. The ID of the project containing this table. + "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`. }, - "useAvroLogicalTypes": True or False, # [Optional] If destinationFormat is set to "AVRO", this flag indicates whether to enable extracting applicable column types (such as TIMESTAMP) to their corresponding AVRO logical types (timestamp-micros), instead of only using their raw types (avro-long). Not applicable when extracting models. + "useAvroLogicalTypes": True or False, # Whether to use logical types when extracting to AVRO format. Not applicable when extracting models. }, - "jobTimeoutMs": "A String", # [Optional] Job timeout in milliseconds. If this time limit is exceeded, BigQuery may attempt to terminate the job. - "jobType": "A String", # [Output-only] The type of the job. Can be QUERY, LOAD, EXTRACT, COPY or UNKNOWN. + "jobTimeoutMs": "A String", # Optional. Job timeout in milliseconds. If this time limit is exceeded, BigQuery might attempt to stop the job. + "jobType": "A String", # Output only. The type of the job. Can be QUERY, LOAD, EXTRACT, COPY or UNKNOWN. "labels": { # The labels associated with this job. You can use these to organize and group your jobs. Label keys and values can be no longer than 63 characters, can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. Label values are optional. Label keys must start with a letter and each label in the list must have a different key. "a_key": "A String", }, - "load": { # [Pick one] Configures a load job. - "allowJaggedRows": True or False, # [Optional] Accept rows that are missing trailing optional columns. The missing values are treated as nulls. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. Only applicable to CSV, ignored for other formats. + "load": { # JobConfigurationLoad contains the configuration properties for loading data into a destination table. # [Pick one] Configures a load job. + "allowJaggedRows": True or False, # Optional. Accept rows that are missing trailing optional columns. The missing values are treated as nulls. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. Only applicable to CSV, ignored for other formats. "allowQuotedNewlines": True or False, # Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false. - "autodetect": True or False, # [Optional] Indicates if we should automatically infer the options and schema for CSV and JSON sources. - "clustering": { # [Beta] Clustering specification for the destination table. Must be specified with time-based partitioning, data in the table will be first partitioned and subsequently clustered. - "fields": [ # [Repeated] One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. When you cluster a table using multiple columns, the order of columns you specify is important. The order of the specified columns determines the sort order of the data. + "autodetect": True or False, # Optional. Indicates if we should automatically infer the options and schema for CSV and JSON sources. + "clustering": { # Configures table clustering. # Clustering specification for the destination table. + "fields": [ # One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. The ordering of the clustering fields should be prioritized from most to least important for filtering purposes. Additional information on limitations can be found here: https://cloud.google.com/bigquery/docs/creating-clustered-tables#limitations "A String", ], }, - "connectionProperties": [ # Connection properties. - { - "key": "A String", # [Required] Name of the connection property to set. - "value": "A String", # [Required] Value of the connection property. + "connectionProperties": [ # Optional. Connection properties which can modify the load job behavior. Currently, only the 'session_id' connection property is supported, and is used to resolve _SESSION appearing as the dataset id. + { # A connection-level property to customize query behavior. Under JDBC, these correspond directly to connection properties passed to the DriverManager. Under ODBC, these correspond to properties in the connection string. Currently supported connection properties: * **dataset_project_id**: represents the default project for datasets that are used in the query. Setting the system variable `@@dataset_project_id` achieves the same behavior. For more information about system variables, see: https://cloud.google.com/bigquery/docs/reference/system-variables * **time_zone**: represents the default timezone used to run the query. * **session_id**: associates the query with a given session. * **query_label**: associates the query with a given job label. If set, all subsequent queries in a script or session will have this label. For the format in which a you can specify a query label, see labels in the JobConfiguration resource type: https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#jobconfiguration Additional properties are allowed, but ignored. Specifying multiple connection properties with the same key returns an error. + "key": "A String", # The key of the property to set. + "value": "A String", # The value of the property to set. }, ], - "createDisposition": "A String", # [Optional] Specifies whether the job is allowed to create new tables. The following values are supported: CREATE_IF_NEEDED: If the table does not exist, BigQuery creates the table. CREATE_NEVER: The table must already exist. If it does not, a 'notFound' error is returned in the job result. The default value is CREATE_IF_NEEDED. Creation, truncation and append actions occur as one atomic update upon job completion. - "createSession": True or False, # If true, creates a new session, where session id will be a server generated random id. If false, runs query with an existing session_id passed in ConnectionProperty, otherwise runs the load job in non-session mode. - "decimalTargetTypes": [ # [Optional] Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown. Example: Suppose the value of this field is ["NUMERIC", "BIGNUMERIC"]. If (precision,scale) is: (38,9) -> NUMERIC; (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits); (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits); (76,38) -> BIGNUMERIC; (77,38) -> BIGNUMERIC (error if value exeeds supported range). This field cannot contain duplicate types. The order of the types in this field is ignored. For example, ["BIGNUMERIC", "NUMERIC"] is the same as ["NUMERIC", "BIGNUMERIC"] and NUMERIC always takes precedence over BIGNUMERIC. Defaults to ["NUMERIC", "STRING"] for ORC and ["NUMERIC"] for the other file formats. + "createDisposition": "A String", # Optional. Specifies whether the job is allowed to create new tables. The following values are supported: * CREATE_IF_NEEDED: If the table does not exist, BigQuery creates the table. * CREATE_NEVER: The table must already exist. If it does not, a 'notFound' error is returned in the job result. The default value is CREATE_IF_NEEDED. Creation, truncation and append actions occur as one atomic update upon job completion. + "createSession": True or False, # Optional. If this property is true, the job creates a new session using a randomly generated session_id. To continue using a created session with subsequent queries, pass the existing session identifier as a `ConnectionProperty` value. The session identifier is returned as part of the `SessionInfo` message within the query statistics. The new session's location will be set to `Job.JobReference.location` if it is present, otherwise it's set to the default location based on existing routing logic. + "decimalTargetTypes": [ # Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown. Example: Suppose the value of this field is ["NUMERIC", "BIGNUMERIC"]. If (precision,scale) is: * (38,9) -> NUMERIC; * (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits); * (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits); * (76,38) -> BIGNUMERIC; * (77,38) -> BIGNUMERIC (error if value exeeds supported range). This field cannot contain duplicate types. The order of the types in this field is ignored. For example, ["BIGNUMERIC", "NUMERIC"] is the same as ["NUMERIC", "BIGNUMERIC"] and NUMERIC always takes precedence over BIGNUMERIC. Defaults to ["NUMERIC", "STRING"] for ORC and ["NUMERIC"] for the other file formats. "A String", ], - "destinationEncryptionConfiguration": { # Custom encryption configuration (e.g., Cloud KMS keys). + "destinationEncryptionConfiguration": { # Custom encryption configuration (e.g., Cloud KMS keys) "kmsKeyName": "A String", # Optional. Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key. }, "destinationTable": { # [Required] The destination table to load the data into. - "datasetId": "A String", # [Required] The ID of the dataset containing this table. - "projectId": "A String", # [Required] The ID of the project containing this table. - "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. - }, - "destinationTableProperties": { # [Beta] [Optional] Properties with which to create the destination table if it is new. - "description": "A String", # [Optional] The description for the destination table. This will only be used if the destination table is newly created. If the table already exists and a value different than the current description is provided, the job will fail. - "expirationTime": "A String", # [Internal] This field is for Google internal use only. - "friendlyName": "A String", # [Optional] The friendly name for the destination table. This will only be used if the destination table is newly created. If the table already exists and a value different than the current friendly name is provided, the job will fail. - "labels": { # [Optional] The labels associated with this table. You can use these to organize and group your tables. This will only be used if the destination table is newly created. If the table already exists and labels are different than the current labels are provided, the job will fail. + "datasetId": "A String", # Required. The ID of the dataset containing this table. + "projectId": "A String", # Required. The ID of the project containing this table. + "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`. + }, + "destinationTableProperties": { # Properties for the destination table. # Optional. [Experimental] Properties with which to create the destination table if it is new. + "description": "A String", # Optional. The description for the destination table. This will only be used if the destination table is newly created. If the table already exists and a value different than the current description is provided, the job will fail. + "expirationTime": "A String", # Internal use only. + "friendlyName": "A String", # Optional. Friendly name for the destination table. If the table already exists, it should be same as the existing friendly name. + "labels": { # Optional. The labels associated with this table. You can use these to organize and group your tables. This will only be used if the destination table is newly created. If the table already exists and labels are different than the current labels are provided, the job will fail. "a_key": "A String", }, }, - "encoding": "A String", # [Optional] The character encoding of the data. The supported values are UTF-8 or ISO-8859-1. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the quote and fieldDelimiter properties. - "fieldDelimiter": "A String", # [Optional] The separator for fields in a CSV file. The separator can be any ISO-8859-1 single-byte character. To use a character in the range 128-255, you must encode the character as UTF8. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. BigQuery also supports the escape sequence "\t" to specify a tab separator. The default value is a comma (','). - "fileSetSpecType": "A String", # [Optional] Specifies how source URIs are interpreted for constructing the file set to load. By default source URIs are expanded against the underlying storage. Other options include specifying manifest files. Only applicable to object storage systems. - "hivePartitioningOptions": { # [Optional] Options to configure hive partitioning support. - "fields": [ # [Output-only] For permanent external tables, this field is populated with the hive partition keys in the order they were inferred. The types of the partition keys can be deduced by checking the table schema (which will include the partition keys). Not every API will populate this field in the output. For example, Tables.Get will populate it, but Tables.List will not contain this field. + "encoding": "A String", # Optional. The character encoding of the data. The supported values are UTF-8, ISO-8859-1, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the `quote` and `fieldDelimiter` properties. If you don't specify an encoding, or if you specify a UTF-8 encoding when the CSV file is not UTF-8 encoded, BigQuery attempts to convert the data to UTF-8. Generally, your data loads successfully, but it may not match byte-for-byte what you expect. To avoid this, specify the correct encoding by using the `--encoding` flag. If BigQuery can't convert a character other than the ASCII `0` character, BigQuery converts the character to the standard Unicode replacement character: �. + "fieldDelimiter": "A String", # Optional. The separator character for fields in a CSV file. The separator is interpreted as a single byte. For files encoded in ISO-8859-1, any single character can be used as a separator. For files encoded in UTF-8, characters represented in decimal range 1-127 (U+0001-U+007F) can be used without any modification. UTF-8 characters encoded with multiple bytes (i.e. U+0080 and above) will have only the first byte used for separating fields. The remaining bytes will be treated as a part of the field. BigQuery also supports the escape sequence "\t" (U+0009) to specify a tab separator. The default value is comma (",", U+002C). + "fileSetSpecType": "A String", # Optional. Specifies how source URIs are interpreted for constructing the file set to load. By default, source URIs are expanded against the underlying storage. You can also specify manifest files to control how the file set is constructed. This option is only applicable to object storage systems. + "hivePartitioningOptions": { # Options for configuring hive partitioning detect. # Optional. When set, configures hive partitioning support. Not all storage formats support hive partitioning -- requesting hive partitioning on an unsupported format will lead to an error, as will providing an invalid specification. + "fields": [ # Output only. For permanent external tables, this field is populated with the hive partition keys in the order they were inferred. The types of the partition keys can be deduced by checking the table schema (which will include the partition keys). Not every API will populate this field in the output. For example, Tables.Get will populate it, but Tables.List will not contain this field. "A String", ], - "mode": "A String", # [Optional] When set, what mode of hive partitioning to use when reading data. The following modes are supported. (1) AUTO: automatically infer partition key name(s) and type(s). (2) STRINGS: automatically infer partition key name(s). All types are interpreted as strings. (3) CUSTOM: partition key schema is encoded in the source URI prefix. Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported types include: AVRO, CSV, JSON, ORC and Parquet. - "requirePartitionFilter": True or False, # [Optional] If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. Note that this field should only be true when creating a permanent external table or querying a temporary external table. Hive-partitioned loads with requirePartitionFilter explicitly set to true will fail. - "sourceUriPrefix": "A String", # [Optional] When hive partition detection is requested, a common prefix for all source uris should be supplied. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout. gs://bucket/path_to_table/dt=2019-01-01/country=BR/id=7/file.avro gs://bucket/path_to_table/dt=2018-12-31/country=CA/id=3/file.avro When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/ (trailing slash does not matter). - }, - "ignoreUnknownValues": True or False, # [Optional] Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names - "jsonExtension": "A String", # [Optional] If sourceFormat is set to newline-delimited JSON, indicates whether it should be processed as a JSON variant such as GeoJSON. For a sourceFormat other than JSON, omit this field. If the sourceFormat is newline-delimited JSON: - for newline-delimited GeoJSON: set to GEOJSON. - "maxBadRecords": 42, # [Optional] The maximum number of bad records that BigQuery can ignore when running the job. If the number of bad records exceeds this value, an invalid error is returned in the job result. This is only valid for CSV and JSON. The default value is 0, which requires that all records are valid. - "nullMarker": "A String", # [Optional] Specifies a string that represents a null value in a CSV file. For example, if you specify "\N", BigQuery interprets "\N" as a null value when loading a CSV file. The default value is the empty string. If you set this property to a custom value, BigQuery throws an error if an empty string is present for all data types except for STRING and BYTE. For STRING and BYTE columns, BigQuery interprets the empty string as an empty value. - "parquetOptions": { # [Optional] Options to configure parquet support. - "enableListInference": True or False, # [Optional] Indicates whether to use schema inference specifically for Parquet LIST logical type. - "enumAsString": True or False, # [Optional] Indicates whether to infer Parquet ENUM logical type as STRING instead of BYTES by default. - }, - "preserveAsciiControlCharacters": True or False, # [Optional] Preserves the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\x00' to '\x1F') when loading from CSV. Only applicable to CSV, ignored for other formats. + "mode": "A String", # Optional. When set, what mode of hive partitioning to use when reading data. The following modes are supported: * AUTO: automatically infer partition key name(s) and type(s). * STRINGS: automatically infer partition key name(s). All types are strings. * CUSTOM: partition key schema is encoded in the source URI prefix. Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported formats are: JSON, CSV, ORC, Avro and Parquet. + "requirePartitionFilter": false, # Optional. If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. Note that this field should only be true when creating a permanent external table or querying a temporary external table. Hive-partitioned loads with require_partition_filter explicitly set to true will fail. + "sourceUriPrefix": "A String", # Optional. When hive partition detection is requested, a common prefix for all source uris must be required. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout: gs://bucket/path_to_table/dt=2019-06-01/country=USA/id=7/file.avro gs://bucket/path_to_table/dt=2019-05-31/country=CA/id=3/file.avro When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/. CUSTOM detection requires encoding the partitioning schema immediately after the common prefix. For CUSTOM, any of * gs://bucket/path_to_table/{dt:DATE}/{country:STRING}/{id:INTEGER} * gs://bucket/path_to_table/{dt:STRING}/{country:STRING}/{id:INTEGER} * gs://bucket/path_to_table/{dt:DATE}/{country:STRING}/{id:STRING} would all be valid source URI prefixes. + }, + "ignoreUnknownValues": True or False, # Optional. Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names in the table schema Avro, Parquet, ORC: Fields in the file schema that don't exist in the table schema. + "jsonExtension": "A String", # Optional. Load option to be used together with source_format newline-delimited JSON to indicate that a variant of JSON is being loaded. To load newline-delimited GeoJSON, specify GEOJSON (and source_format must be set to NEWLINE_DELIMITED_JSON). + "maxBadRecords": 42, # Optional. The maximum number of bad records that BigQuery can ignore when running the job. If the number of bad records exceeds this value, an invalid error is returned in the job result. The default value is 0, which requires that all records are valid. This is only supported for CSV and NEWLINE_DELIMITED_JSON file formats. + "nullMarker": "A String", # Optional. Specifies a string that represents a null value in a CSV file. For example, if you specify "\N", BigQuery interprets "\N" as a null value when loading a CSV file. The default value is the empty string. If you set this property to a custom value, BigQuery throws an error if an empty string is present for all data types except for STRING and BYTE. For STRING and BYTE columns, BigQuery interprets the empty string as an empty value. + "parquetOptions": { # Parquet Options for load and make external tables. # Optional. Additional properties to set if sourceFormat is set to PARQUET. + "enableListInference": True or False, # Optional. Indicates whether to use schema inference specifically for Parquet LIST logical type. + "enumAsString": True or False, # Optional. Indicates whether to infer Parquet ENUM logical type as STRING instead of BYTES by default. + }, + "preserveAsciiControlCharacters": True or False, # Optional. When sourceFormat is set to "CSV", this indicates whether the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\x00' to '\x1F') are preserved. "projectionFields": [ # If sourceFormat is set to "DATASTORE_BACKUP", indicates which entity properties to load into BigQuery from a Cloud Datastore backup. Property names are case sensitive and must be top-level properties. If no properties are specified, BigQuery loads all properties. If any named property isn't found in the Cloud Datastore backup, an invalid error is returned in the job result. "A String", ], - "quote": """, # [Optional] The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ('"'). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true. - "rangePartitioning": { # [TrustedTester] Range partitioning specification for this table. Only one of timePartitioning and rangePartitioning should be specified. - "field": "A String", # [TrustedTester] [Required] The table is partitioned by this field. The field must be a top-level NULLABLE/REQUIRED field. The only supported type is INTEGER/INT64. - "range": { # [TrustedTester] [Required] Defines the ranges for range partitioning. - "end": "A String", # [TrustedTester] [Required] The end of range partitioning, exclusive. - "interval": "A String", # [TrustedTester] [Required] The width of each interval. - "start": "A String", # [TrustedTester] [Required] The start of range partitioning, inclusive. + "quote": """, # Optional. The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ('"'). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true. To include the specific quote character within a quoted value, precede it with an additional matching quote character. For example, if you want to escape the default character ' " ', use ' "" '. @default " + "rangePartitioning": { # Range partitioning specification for the destination table. Only one of timePartitioning and rangePartitioning should be specified. + "field": "A String", # Required. [Experimental] The table is partitioned by this field. The field must be a top-level NULLABLE/REQUIRED field. The only supported type is INTEGER/INT64. + "range": { # [Experimental] Defines the ranges for range partitioning. + "end": "A String", # [Experimental] The end of range partitioning, exclusive. + "interval": "A String", # [Experimental] The width of each interval. + "start": "A String", # [Experimental] The start of range partitioning, inclusive. }, }, - "referenceFileSchemaUri": "A String", # User provided referencing file with the expected reader schema, Available for the format: AVRO, PARQUET, ORC. - "schema": { # [Optional] The schema for the destination table. The schema can be omitted if the destination table already exists, or if you're loading data from Google Cloud Datastore. + "referenceFileSchemaUri": "A String", # Optional. The user can provide a reference file with the reader schema. This file is only loaded if it is part of source URIs, but is not loaded otherwise. It is enabled for the following formats: AVRO, PARQUET, ORC. + "schema": { # Schema of a table # Optional. The schema for the destination table. The schema can be omitted if the destination table already exists, or if you're loading data from Google Cloud Datastore. "fields": [ # Describes the fields in a table. - { - "categories": { # [Optional] The categories attached to this field, used for field-level access control. - "names": [ # A list of category resource names. For example, "projects/1/taxonomies/2/categories/3". At most 5 categories are allowed. + { # A field in TableSchema + "categories": { # Deprecated. + "names": [ # Deprecated. "A String", ], }, - "collation": "A String", # Optional. Collation specification of the field. It only can be set on string type field. - "defaultValueExpression": "A String", # Optional. A SQL expression to specify the default value for this field. It can only be set for top level fields (columns). You can use struct or array expression to specify default value for the entire struct or array. The valid SQL expressions are: - Literals for all data types, including STRUCT and ARRAY. - Following functions: - CURRENT_TIMESTAMP - CURRENT_TIME - CURRENT_DATE - CURRENT_DATETIME - GENERATE_UUID - RAND - SESSION_USER - ST_GEOGPOINT - Struct or array composed with the above allowed functions, for example, [CURRENT_DATE(), DATE '2020-01-01'] - "description": "A String", # [Optional] The field description. The maximum length is 1,024 characters. - "fields": [ # [Optional] Describes the nested schema fields if the type property is set to RECORD. + "collation": "A String", # Optional. Field collation can be set only when the type of field is STRING. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior. + "defaultValueExpression": "A String", # Optional. A SQL expression to specify the [default value] (https://cloud.google.com/bigquery/docs/default-values) for this field. + "description": "A String", # Optional. The field description. The maximum length is 1,024 characters. + "fields": [ # Optional. Describes the nested schema fields if the type property is set to RECORD. # Object with schema name: TableFieldSchema ], - "maxLength": "A String", # [Optional] Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES". - "mode": "A String", # [Optional] The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE. - "name": "A String", # [Required] The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters. - "policyTags": { - "names": [ # A list of category resource names. For example, "projects/1/location/eu/taxonomies/2/policyTags/3". At most 1 policy tag is allowed. + "maxLength": "A String", # Optional. Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES". + "mode": "A String", # Optional. The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE. + "name": "A String", # Required. The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters. + "policyTags": { # Optional. The policy tags attached to this field, used for field-level access control. If not set, defaults to empty policy_tags. + "names": [ # A list of policy tag resource names. For example, "projects/1/locations/eu/taxonomies/2/policyTags/3". At most 1 policy tag is currently allowed. "A String", ], }, - "precision": "A String", # [Optional] Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: - Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] - Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: - If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. - If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): - If type = "NUMERIC": 1 ≤ precision ≤ 29. - If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid. - "rangeElementType": { # Optional. The subtype of the RANGE, if the type of this field is RANGE. If the type is RANGE, this field is required. Possible values for the field element type of a RANGE include: - DATE - DATETIME - TIMESTAMP - "type": "A String", # The field element type of a RANGE + "precision": "A String", # Optional. Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: * Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] * Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: * If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. * If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): * If type = "NUMERIC": 1 ≤ precision ≤ 29. * If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid. + "rangeElementType": { # Represents the type of a field element. + "type": "A String", # Required. The type of a field element. See TableFieldSchema.type. }, - "roundingMode": "A String", # Optional. Rounding Mode specification of the field. It only can be set on NUMERIC or BIGNUMERIC type fields. - "scale": "A String", # [Optional] See documentation for precision. - "type": "A String", # [Required] The field data type. Possible values include STRING, BYTES, INTEGER, INT64 (same as INTEGER), FLOAT, FLOAT64 (same as FLOAT), NUMERIC, BIGNUMERIC, BOOLEAN, BOOL (same as BOOLEAN), TIMESTAMP, DATE, TIME, DATETIME, INTERVAL, RECORD (where RECORD indicates that the field contains a nested schema) or STRUCT (same as RECORD). + "roundingMode": "A String", # Optional. Specifies the rounding mode to be used when storing values of NUMERIC and BIGNUMERIC type. + "scale": "A String", # Optional. See documentation for precision. + "type": "A String", # Required. The field data type. Possible values include: * STRING * BYTES * INTEGER (or INT64) * FLOAT (or FLOAT64) * BOOLEAN (or BOOL) * TIMESTAMP * DATE * TIME * DATETIME * GEOGRAPHY * NUMERIC * BIGNUMERIC * JSON * RECORD (or STRUCT) Use of RECORD/STRUCT indicates that the field contains a nested schema. }, ], }, "schemaInline": "A String", # [Deprecated] The inline schema. For CSV schemas, specify as "Field1:Type1[,Field2:Type2]*". For example, "foo:STRING, bar:INTEGER, baz:FLOAT". "schemaInlineFormat": "A String", # [Deprecated] The format of the schemaInline property. - "schemaUpdateOptions": [ # Allows the schema of the destination table to be updated as a side effect of the load job if a schema is autodetected or supplied in the job configuration. Schema update options are supported in two cases: when writeDisposition is WRITE_APPEND; when writeDisposition is WRITE_TRUNCATE and the destination table is a partition of a table, specified by partition decorators. For normal tables, WRITE_TRUNCATE will always overwrite the schema. One or more of the following values are specified: ALLOW_FIELD_ADDITION: allow adding a nullable field to the schema. ALLOW_FIELD_RELAXATION: allow relaxing a required field in the original schema to nullable. + "schemaUpdateOptions": [ # Allows the schema of the destination table to be updated as a side effect of the load job if a schema is autodetected or supplied in the job configuration. Schema update options are supported in two cases: when writeDisposition is WRITE_APPEND; when writeDisposition is WRITE_TRUNCATE and the destination table is a partition of a table, specified by partition decorators. For normal tables, WRITE_TRUNCATE will always overwrite the schema. One or more of the following values are specified: * ALLOW_FIELD_ADDITION: allow adding a nullable field to the schema. * ALLOW_FIELD_RELAXATION: allow relaxing a required field in the original schema to nullable. "A String", ], - "skipLeadingRows": 42, # [Optional] The number of rows at the top of a CSV file that BigQuery will skip when loading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped. - "sourceFormat": "A String", # [Optional] The format of the data files. For CSV files, specify "CSV". For datastore backups, specify "DATASTORE_BACKUP". For newline-delimited JSON, specify "NEWLINE_DELIMITED_JSON". For Avro, specify "AVRO". For parquet, specify "PARQUET". For orc, specify "ORC". The default value is CSV. + "skipLeadingRows": 42, # Optional. The number of rows at the top of a CSV file that BigQuery will skip when loading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema. + "sourceFormat": "A String", # Optional. The format of the data files. For CSV files, specify "CSV". For datastore backups, specify "DATASTORE_BACKUP". For newline-delimited JSON, specify "NEWLINE_DELIMITED_JSON". For Avro, specify "AVRO". For parquet, specify "PARQUET". For orc, specify "ORC". The default value is CSV. "sourceUris": [ # [Required] The fully-qualified URIs that point to your data in Google Cloud. For Google Cloud Storage URIs: Each URI can contain one '*' wildcard character and it must come after the 'bucket' name. Size limits related to load jobs apply to external data sources. For Google Cloud Bigtable URIs: Exactly one URI can be specified and it has be a fully specified and valid HTTPS URL for a Google Cloud Bigtable table. For Google Cloud Datastore backups: Exactly one URI can be specified. Also, the '*' wildcard character is not allowed. "A String", ], "timePartitioning": { # Time-based partitioning specification for the destination table. Only one of timePartitioning and rangePartitioning should be specified. - "expirationMs": "A String", # [Optional] Number of milliseconds for which to keep the storage for partitions in the table. The storage in a partition will have an expiration time of its partition time plus this value. - "field": "A String", # [Beta] [Optional] If not set, the table is partitioned by pseudo column, referenced via either '_PARTITIONTIME' as TIMESTAMP type, or '_PARTITIONDATE' as DATE type. If field is specified, the table is instead partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED. - "requirePartitionFilter": True or False, - "type": "A String", # [Required] The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively. When the type is not specified, the default behavior is DAY. + "expirationMs": "A String", # Optional. Number of milliseconds for which to keep the storage for a partition. A wrapper is used here because 0 is an invalid value. + "field": "A String", # Optional. If not set, the table is partitioned by pseudo column '_PARTITIONTIME'; if set, the table is partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED. A wrapper is used here because an empty string is an invalid value. + "requirePartitionFilter": false, # If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. This field is deprecated; please set the field with the same name on the table itself instead. This field needs a wrapper because we want to output the default value, false, if the user explicitly set it. + "type": "A String", # Required. The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively. }, - "useAvroLogicalTypes": True or False, # [Optional] If sourceFormat is set to "AVRO", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER). - "writeDisposition": "A String", # [Optional] Specifies the action that occurs if the destination table already exists. The following values are supported: WRITE_TRUNCATE: If the table already exists, BigQuery overwrites the table data. WRITE_APPEND: If the table already exists, BigQuery appends the data to the table. WRITE_EMPTY: If the table already exists and contains data, a 'duplicate' error is returned in the job result. The default value is WRITE_APPEND. Each action is atomic and only occurs if BigQuery is able to complete the job successfully. Creation, truncation and append actions occur as one atomic update upon job completion. + "useAvroLogicalTypes": True or False, # Optional. If sourceFormat is set to "AVRO", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER). + "writeDisposition": "A String", # Optional. Specifies the action that occurs if the destination table already exists. The following values are supported: * WRITE_TRUNCATE: If the table already exists, BigQuery overwrites the data, removes the constraints and uses the schema from the load job. * WRITE_APPEND: If the table already exists, BigQuery appends the data to the table. * WRITE_EMPTY: If the table already exists and contains data, a 'duplicate' error is returned in the job result. The default value is WRITE_APPEND. Each action is atomic and only occurs if BigQuery is able to complete the job successfully. Creation, truncation and append actions occur as one atomic update upon job completion. }, - "query": { # [Pick one] Configures a query job. - "allowLargeResults": false, # [Optional] If true and query uses legacy SQL dialect, allows the query to produce arbitrarily large result tables at a slight cost in performance. Requires destinationTable to be set. For standard SQL queries, this flag is ignored and large results are always allowed. However, you must still set destinationTable when result size exceeds the allowed maximum response size. - "clustering": { # [Beta] Clustering specification for the destination table. Must be specified with time-based partitioning, data in the table will be first partitioned and subsequently clustered. - "fields": [ # [Repeated] One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. When you cluster a table using multiple columns, the order of columns you specify is important. The order of the specified columns determines the sort order of the data. + "query": { # JobConfigurationQuery configures a BigQuery query job. # [Pick one] Configures a query job. + "allowLargeResults": false, # Optional. If true and query uses legacy SQL dialect, allows the query to produce arbitrarily large result tables at a slight cost in performance. Requires destinationTable to be set. For GoogleSQL queries, this flag is ignored and large results are always allowed. However, you must still set destinationTable when result size exceeds the allowed maximum response size. + "clustering": { # Configures table clustering. # Clustering specification for the destination table. + "fields": [ # One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. The ordering of the clustering fields should be prioritized from most to least important for filtering purposes. Additional information on limitations can be found here: https://cloud.google.com/bigquery/docs/creating-clustered-tables#limitations "A String", ], }, - "connectionProperties": [ # Connection properties. - { - "key": "A String", # [Required] Name of the connection property to set. - "value": "A String", # [Required] Value of the connection property. + "connectionProperties": [ # Connection properties which can modify the query behavior. + { # A connection-level property to customize query behavior. Under JDBC, these correspond directly to connection properties passed to the DriverManager. Under ODBC, these correspond to properties in the connection string. Currently supported connection properties: * **dataset_project_id**: represents the default project for datasets that are used in the query. Setting the system variable `@@dataset_project_id` achieves the same behavior. For more information about system variables, see: https://cloud.google.com/bigquery/docs/reference/system-variables * **time_zone**: represents the default timezone used to run the query. * **session_id**: associates the query with a given session. * **query_label**: associates the query with a given job label. If set, all subsequent queries in a script or session will have this label. For the format in which a you can specify a query label, see labels in the JobConfiguration resource type: https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#jobconfiguration Additional properties are allowed, but ignored. Specifying multiple connection properties with the same key returns an error. + "key": "A String", # The key of the property to set. + "value": "A String", # The value of the property to set. }, ], "continuous": True or False, # [Optional] Specifies whether the query should be executed as a continuous query. The default value is false. - "createDisposition": "A String", # [Optional] Specifies whether the job is allowed to create new tables. The following values are supported: CREATE_IF_NEEDED: If the table does not exist, BigQuery creates the table. CREATE_NEVER: The table must already exist. If it does not, a 'notFound' error is returned in the job result. The default value is CREATE_IF_NEEDED. Creation, truncation and append actions occur as one atomic update upon job completion. - "createSession": True or False, # If true, creates a new session, where session id will be a server generated random id. If false, runs query with an existing session_id passed in ConnectionProperty, otherwise runs query in non-session mode. - "defaultDataset": { # [Optional] Specifies the default dataset to use for unqualified table names in the query. Note that this does not alter behavior of unqualified dataset names. - "datasetId": "A String", # [Required] A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. - "projectId": "A String", # [Optional] The ID of the project containing this dataset. + "createDisposition": "A String", # Optional. Specifies whether the job is allowed to create new tables. The following values are supported: * CREATE_IF_NEEDED: If the table does not exist, BigQuery creates the table. * CREATE_NEVER: The table must already exist. If it does not, a 'notFound' error is returned in the job result. The default value is CREATE_IF_NEEDED. Creation, truncation and append actions occur as one atomic update upon job completion. + "createSession": True or False, # If this property is true, the job creates a new session using a randomly generated session_id. To continue using a created session with subsequent queries, pass the existing session identifier as a `ConnectionProperty` value. The session identifier is returned as part of the `SessionInfo` message within the query statistics. The new session's location will be set to `Job.JobReference.location` if it is present, otherwise it's set to the default location based on existing routing logic. + "defaultDataset": { # Optional. Specifies the default dataset to use for unqualified table names in the query. This setting does not alter behavior of unqualified dataset names. Setting the system variable `@@dataset_id` achieves the same behavior. See https://cloud.google.com/bigquery/docs/reference/system-variables for more information on system variables. + "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. + "projectId": "A String", # Optional. The ID of the project containing this dataset. }, - "destinationEncryptionConfiguration": { # Custom encryption configuration (e.g., Cloud KMS keys). + "destinationEncryptionConfiguration": { # Custom encryption configuration (e.g., Cloud KMS keys) "kmsKeyName": "A String", # Optional. Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key. }, - "destinationTable": { # [Optional] Describes the table where the query results should be stored. If not present, a new table will be created to store the results. This property must be set for large results that exceed the maximum response size. - "datasetId": "A String", # [Required] The ID of the dataset containing this table. - "projectId": "A String", # [Required] The ID of the project containing this table. - "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. + "destinationTable": { # Optional. Describes the table where the query results should be stored. This property must be set for large results that exceed the maximum response size. For queries that produce anonymous (cached) results, this field will be populated by BigQuery. + "datasetId": "A String", # Required. The ID of the dataset containing this table. + "projectId": "A String", # Required. The ID of the project containing this table. + "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`. }, - "flattenResults": true, # [Optional] If true and query uses legacy SQL dialect, flattens all nested and repeated fields in the query results. allowLargeResults must be true if this is set to false. For standard SQL queries, this flag is ignored and results are never flattened. - "maximumBillingTier": 1, # [Optional] Limits the billing tier for this job. Queries that have resource usage beyond this tier will fail (without incurring a charge). If unspecified, this will be set to your project default. - "maximumBytesBilled": "A String", # [Optional] Limits the bytes billed for this job. Queries that will have bytes billed beyond this limit will fail (without incurring a charge). If unspecified, this will be set to your project default. - "parameterMode": "A String", # Standard SQL only. Set to POSITIONAL to use positional (?) query parameters or to NAMED to use named (@myparam) query parameters in this query. + "flattenResults": true, # Optional. If true and query uses legacy SQL dialect, flattens all nested and repeated fields in the query results. allowLargeResults must be true if this is set to false. For GoogleSQL queries, this flag is ignored and results are never flattened. + "maximumBillingTier": 1, # Optional. [Deprecated] Maximum billing tier allowed for this query. The billing tier controls the amount of compute resources allotted to the query, and multiplies the on-demand cost of the query accordingly. A query that runs within its allotted resources will succeed and indicate its billing tier in statistics.query.billingTier, but if the query exceeds its allotted resources, it will fail with billingTierLimitExceeded. WARNING: The billed byte amount can be multiplied by an amount up to this number! Most users should not need to alter this setting, and we recommend that you avoid introducing new uses of it. + "maximumBytesBilled": "A String", # Limits the bytes billed for this job. Queries that will have bytes billed beyond this limit will fail (without incurring a charge). If unspecified, this will be set to your project default. + "parameterMode": "A String", # GoogleSQL only. Set to POSITIONAL to use positional (?) query parameters or to NAMED to use named (@myparam) query parameters in this query. "preserveNulls": True or False, # [Deprecated] This property is deprecated. - "priority": "A String", # [Optional] Specifies a priority for the query. Possible values include INTERACTIVE and BATCH. The default value is INTERACTIVE. - "query": "A String", # [Required] SQL query text to execute. The useLegacySql field can be used to indicate whether the query uses legacy SQL or standard SQL. - "queryParameters": [ # Query parameters for standard SQL queries. - { - "name": "A String", # [Optional] If unset, this is a positional parameter. Otherwise, should be unique within a query. - "parameterType": { # [Required] The type of this parameter. - "arrayType": # Object with schema name: QueryParameterType # [Optional] The type of the array's elements, if this is an array. - "rangeElementType": # Object with schema name: QueryParameterType # [Optional] The element type of the range, if this is a range. - "structTypes": [ # [Optional] The types of the fields of this struct, in order, if this is a struct. - { - "description": "A String", # [Optional] Human-oriented description of the field. - "name": "A String", # [Optional] The name of this field. - "type": # Object with schema name: QueryParameterType # [Required] The type of this field. + "priority": "A String", # Optional. Specifies a priority for the query. Possible values include INTERACTIVE and BATCH. The default value is INTERACTIVE. + "query": "A String", # [Required] SQL query text to execute. The useLegacySql field can be used to indicate whether the query uses legacy SQL or GoogleSQL. + "queryParameters": [ # Query parameters for GoogleSQL queries. + { # A parameter given to a query. + "name": "A String", # Optional. If unset, this is a positional parameter. Otherwise, should be unique within a query. + "parameterType": { # The type of a query parameter. # Required. The type of this parameter. + "arrayType": # Object with schema name: QueryParameterType # Optional. The type of the array's elements, if this is an array. + "rangeElementType": # Object with schema name: QueryParameterType # Optional. The element type of the range, if this is a range. + "structTypes": [ # Optional. The types of the fields of this struct, in order, if this is a struct. + { # The type of a struct parameter. + "description": "A String", # Optional. Human-oriented description of the field. + "name": "A String", # Optional. The name of this field. + "type": # Object with schema name: QueryParameterType # Required. The type of this field. }, ], - "type": "A String", # [Required] The top level type of this field. + "type": "A String", # Required. The top level type of this field. }, - "parameterValue": { # [Required] The value of this parameter. - "arrayValues": [ # [Optional] The array values, if this is an array type. + "parameterValue": { # The value of a query parameter. # Required. The value of this parameter. + "arrayValues": [ # Optional. The array values, if this is an array type. # Object with schema name: QueryParameterValue ], - "rangeValue": { # [Optional] The range value, if this is a range type. - "end": # Object with schema name: QueryParameterValue - "start": # Object with schema name: QueryParameterValue + "rangeValue": { # Represents the value of a range. # Optional. The range value, if this is a range type. + "end": # Object with schema name: QueryParameterValue # Optional. The end value of the range. A missing value represents an unbounded end. + "start": # Object with schema name: QueryParameterValue # Optional. The start value of the range. A missing value represents an unbounded start. }, - "structValues": { # [Optional] The struct field values, in order of the struct type's declaration. + "structValues": { # The struct field values. "a_key": # Object with schema name: QueryParameterValue }, - "value": "A String", # [Optional] The value of this value, if a simple scalar type. + "value": "A String", # Optional. The value of this value, if a simple scalar type. }, }, ], - "rangePartitioning": { # [TrustedTester] Range partitioning specification for this table. Only one of timePartitioning and rangePartitioning should be specified. - "field": "A String", # [TrustedTester] [Required] The table is partitioned by this field. The field must be a top-level NULLABLE/REQUIRED field. The only supported type is INTEGER/INT64. - "range": { # [TrustedTester] [Required] Defines the ranges for range partitioning. - "end": "A String", # [TrustedTester] [Required] The end of range partitioning, exclusive. - "interval": "A String", # [TrustedTester] [Required] The width of each interval. - "start": "A String", # [TrustedTester] [Required] The start of range partitioning, inclusive. + "rangePartitioning": { # Range partitioning specification for the destination table. Only one of timePartitioning and rangePartitioning should be specified. + "field": "A String", # Required. [Experimental] The table is partitioned by this field. The field must be a top-level NULLABLE/REQUIRED field. The only supported type is INTEGER/INT64. + "range": { # [Experimental] Defines the ranges for range partitioning. + "end": "A String", # [Experimental] The end of range partitioning, exclusive. + "interval": "A String", # [Experimental] The width of each interval. + "start": "A String", # [Experimental] The start of range partitioning, inclusive. }, }, - "schemaUpdateOptions": [ # Allows the schema of the destination table to be updated as a side effect of the query job. Schema update options are supported in two cases: when writeDisposition is WRITE_APPEND; when writeDisposition is WRITE_TRUNCATE and the destination table is a partition of a table, specified by partition decorators. For normal tables, WRITE_TRUNCATE will always overwrite the schema. One or more of the following values are specified: ALLOW_FIELD_ADDITION: allow adding a nullable field to the schema. ALLOW_FIELD_RELAXATION: allow relaxing a required field in the original schema to nullable. + "schemaUpdateOptions": [ # Allows the schema of the destination table to be updated as a side effect of the query job. Schema update options are supported in two cases: when writeDisposition is WRITE_APPEND; when writeDisposition is WRITE_TRUNCATE and the destination table is a partition of a table, specified by partition decorators. For normal tables, WRITE_TRUNCATE will always overwrite the schema. One or more of the following values are specified: * ALLOW_FIELD_ADDITION: allow adding a nullable field to the schema. * ALLOW_FIELD_RELAXATION: allow relaxing a required field in the original schema to nullable. "A String", ], - "tableDefinitions": { # [Optional] If querying an external data source outside of BigQuery, describes the data format, location and other properties of the data source. By defining these properties, the data source can then be queried as if it were a standard BigQuery table. + "scriptOptions": { # Options related to script execution. # Options controlling the execution of scripts. + "keyResultStatement": "A String", # Determines which statement in the script represents the "key result", used to populate the schema and query results of the script job. Default is LAST. + "statementByteBudget": "A String", # Limit on the number of bytes billed per statement. Exceeding this budget results in an error. + "statementTimeoutMs": "A String", # Timeout period for each statement in a script. + }, + "systemVariables": { # System variables given to a query. # Output only. System variables for GoogleSQL queries. A system variable is output if the variable is settable and its value differs from the system default. "@@" prefix is not included in the name of the System variables. + "types": { # Output only. Data type for each system variable. + "a_key": { # The data type of a variable such as a function argument. Examples include: * INT64: `{"typeKind": "INT64"}` * ARRAY: { "typeKind": "ARRAY", "arrayElementType": {"typeKind": "STRING"} } * STRUCT>: { "typeKind": "STRUCT", "structType": { "fields": [ { "name": "x", "type": {"typeKind": "STRING"} }, { "name": "y", "type": { "typeKind": "ARRAY", "arrayElementType": {"typeKind": "DATE"} } } ] } } + "arrayElementType": # Object with schema name: StandardSqlDataType # The type of the array's elements, if type_kind = "ARRAY". + "rangeElementType": # Object with schema name: StandardSqlDataType # The type of the range's elements, if type_kind = "RANGE". + "structType": { # The representation of a SQL STRUCT type. # The fields of this struct, in order, if type_kind = "STRUCT". + "fields": [ # Fields within the struct. + { # A field or a column. + "name": "A String", # Optional. The name of this field. Can be absent for struct fields. + "type": # Object with schema name: StandardSqlDataType # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field). + }, + ], + }, + "typeKind": "A String", # Required. The top level type of this field. Can be any GoogleSQL data type (e.g., "INT64", "DATE", "ARRAY"). + }, + }, + "values": { # Output only. Value for each system variable. + "a_key": "", # Properties of the object. + }, + }, + "tableDefinitions": { # Optional. You can specify external table definitions, which operate as ephemeral tables that can be queried. These definitions are configured using a JSON map, where the string key represents the table identifier, and the value is the corresponding external data configuration object. "a_key": { "autodetect": True or False, # Try to detect schema and format options automatically. Any option specified explicitly will be honored. - "avroOptions": { # Additional properties to set if sourceFormat is set to Avro. - "useAvroLogicalTypes": True or False, # [Optional] If sourceFormat is set to "AVRO", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER). - }, - "bigtableOptions": { # [Optional] Additional options if sourceFormat is set to BIGTABLE. - "columnFamilies": [ # [Optional] List of column families to expose in the table schema along with their types. This list restricts the column families that can be referenced in queries and specifies their value types. You can use this list to do type conversions - see the 'type' field for more details. If you leave this list empty, all column families are present in the table schema and their values are read as BYTES. During a query only the column families referenced in that query are read from Bigtable. - { - "columns": [ # [Optional] Lists of columns that should be exposed as individual fields as opposed to a list of (column name, value) pairs. All columns whose qualifier matches a qualifier in this list can be accessed as .. Other columns can be accessed as a list through .Column field. - { - "encoding": "A String", # [Optional] The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. 'encoding' can also be set at the column family level. However, the setting at this level takes precedence if 'encoding' is set at both levels. - "fieldName": "A String", # [Optional] If the qualifier is not a valid BigQuery field identifier i.e. does not match [a-zA-Z][a-zA-Z0-9_]*, a valid identifier must be provided as the column field name and is used as field name in queries. - "onlyReadLatest": True or False, # [Optional] If this is set, only the latest version of value in this column are exposed. 'onlyReadLatest' can also be set at the column family level. However, the setting at this level takes precedence if 'onlyReadLatest' is set at both levels. - "qualifierEncoded": "A String", # [Required] Qualifier of the column. Columns in the parent column family that has this exact qualifier are exposed as . field. If the qualifier is valid UTF-8 string, it can be specified in the qualifier_string field. Otherwise, a base-64 encoded value must be set to qualifier_encoded. The column field name is the same as the column qualifier. However, if the qualifier is not a valid BigQuery field identifier i.e. does not match [a-zA-Z][a-zA-Z0-9_]*, a valid identifier must be provided as field_name. - "qualifierString": "A String", - "type": "A String", # [Optional] The type to convert the value in cells of this column. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive) - BYTES STRING INTEGER FLOAT BOOLEAN Default type is BYTES. 'type' can also be set at the column family level. However, the setting at this level takes precedence if 'type' is set at both levels. - }, - ], - "encoding": "A String", # [Optional] The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. This can be overridden for a specific column by listing that column in 'columns' and specifying an encoding for it. + "avroOptions": { # Options for external data sources. # Optional. Additional properties to set if sourceFormat is set to AVRO. + "useAvroLogicalTypes": True or False, # Optional. If sourceFormat is set to "AVRO", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER). + }, + "bigtableOptions": { # Options specific to Google Cloud Bigtable data sources. # Optional. Additional options if sourceFormat is set to BIGTABLE. + "columnFamilies": [ # Optional. List of column families to expose in the table schema along with their types. This list restricts the column families that can be referenced in queries and specifies their value types. You can use this list to do type conversions - see the 'type' field for more details. If you leave this list empty, all column families are present in the table schema and their values are read as BYTES. During a query only the column families referenced in that query are read from Bigtable. + { # Information related to a Bigtable column family. + "columns": [ # Optional. Lists of columns that should be exposed as individual fields as opposed to a list of (column name, value) pairs. All columns whose qualifier matches a qualifier in this list can be accessed as .. Other columns can be accessed as a list through .Column field. + { # Information related to a Bigtable column. + "encoding": "A String", # Optional. The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. 'encoding' can also be set at the column family level. However, the setting at this level takes precedence if 'encoding' is set at both levels. + "fieldName": "A String", # Optional. If the qualifier is not a valid BigQuery field identifier i.e. does not match a-zA-Z*, a valid identifier must be provided as the column field name and is used as field name in queries. + "onlyReadLatest": True or False, # Optional. If this is set, only the latest version of value in this column are exposed. 'onlyReadLatest' can also be set at the column family level. However, the setting at this level takes precedence if 'onlyReadLatest' is set at both levels. + "qualifierEncoded": "A String", # [Required] Qualifier of the column. Columns in the parent column family that has this exact qualifier are exposed as . field. If the qualifier is valid UTF-8 string, it can be specified in the qualifier_string field. Otherwise, a base-64 encoded value must be set to qualifier_encoded. The column field name is the same as the column qualifier. However, if the qualifier is not a valid BigQuery field identifier i.e. does not match a-zA-Z*, a valid identifier must be provided as field_name. + "qualifierString": "A String", # Qualifier string. + "type": "A String", # Optional. The type to convert the value in cells of this column. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive): * BYTES * STRING * INTEGER * FLOAT * BOOLEAN * JSON Default type is BYTES. 'type' can also be set at the column family level. However, the setting at this level takes precedence if 'type' is set at both levels. + }, + ], + "encoding": "A String", # Optional. The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. This can be overridden for a specific column by listing that column in 'columns' and specifying an encoding for it. "familyId": "A String", # Identifier of the column family. - "onlyReadLatest": True or False, # [Optional] If this is set only the latest version of value are exposed for all columns in this column family. This can be overridden for a specific column by listing that column in 'columns' and specifying a different setting for that column. - "type": "A String", # [Optional] The type to convert the value in cells of this column family. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive) - BYTES STRING INTEGER FLOAT BOOLEAN Default type is BYTES. This can be overridden for a specific column by listing that column in 'columns' and specifying a type for it. + "onlyReadLatest": True or False, # Optional. If this is set only the latest version of value are exposed for all columns in this column family. This can be overridden for a specific column by listing that column in 'columns' and specifying a different setting for that column. + "type": "A String", # Optional. The type to convert the value in cells of this column family. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive): * BYTES * STRING * INTEGER * FLOAT * BOOLEAN * JSON Default type is BYTES. This can be overridden for a specific column by listing that column in 'columns' and specifying a type for it. }, ], - "ignoreUnspecifiedColumnFamilies": True or False, # [Optional] If field is true, then the column families that are not specified in columnFamilies list are not exposed in the table schema. Otherwise, they are read with BYTES type values. The default value is false. - "readRowkeyAsString": True or False, # [Optional] If field is true, then the rowkey column families will be read and converted to string. Otherwise they are read with BYTES type values and users need to manually cast them with CAST if necessary. The default value is false. - }, - "compression": "A String", # [Optional] The compression type of the data source. Possible values include GZIP and NONE. The default value is NONE. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups and Avro formats. - "connectionId": "A String", # [Optional, Trusted Tester] Connection for external data source. - "csvOptions": { # Additional properties to set if sourceFormat is set to CSV. - "allowJaggedRows": True or False, # [Optional] Indicates if BigQuery should accept rows that are missing trailing optional columns. If true, BigQuery treats missing trailing columns as null values. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. - "allowQuotedNewlines": True or False, # [Optional] Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false. - "encoding": "A String", # [Optional] The character encoding of the data. The supported values are UTF-8 or ISO-8859-1. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the quote and fieldDelimiter properties. - "fieldDelimiter": "A String", # [Optional] The separator for fields in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. BigQuery also supports the escape sequence "\t" to specify a tab separator. The default value is a comma (','). - "nullMarker": "A String", # [Optional] An custom string that will represent a NULL value in CSV import data. - "preserveAsciiControlCharacters": True or False, # [Optional] Preserves the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\x00' to '\x1F') when loading from CSV. Only applicable to CSV, ignored for other formats. - "quote": """, # [Optional] The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ('"'). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true. - "skipLeadingRows": "A String", # [Optional] The number of rows at the top of a CSV file that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema. - }, - "decimalTargetTypes": [ # [Optional] Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown. Example: Suppose the value of this field is ["NUMERIC", "BIGNUMERIC"]. If (precision,scale) is: (38,9) -> NUMERIC; (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits); (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits); (76,38) -> BIGNUMERIC; (77,38) -> BIGNUMERIC (error if value exeeds supported range). This field cannot contain duplicate types. The order of the types in this field is ignored. For example, ["BIGNUMERIC", "NUMERIC"] is the same as ["NUMERIC", "BIGNUMERIC"] and NUMERIC always takes precedence over BIGNUMERIC. Defaults to ["NUMERIC", "STRING"] for ORC and ["NUMERIC"] for the other file formats. + "ignoreUnspecifiedColumnFamilies": True or False, # Optional. If field is true, then the column families that are not specified in columnFamilies list are not exposed in the table schema. Otherwise, they are read with BYTES type values. The default value is false. + "outputColumnFamiliesAsJson": True or False, # Optional. If field is true, then each column family will be read as a single JSON column. Otherwise they are read as a repeated cell structure containing timestamp/value tuples. The default value is false. + "readRowkeyAsString": True or False, # Optional. If field is true, then the rowkey column families will be read and converted to string. Otherwise they are read with BYTES type values and users need to manually cast them with CAST if necessary. The default value is false. + }, + "compression": "A String", # Optional. The compression type of the data source. Possible values include GZIP and NONE. The default value is NONE. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups, Avro, ORC and Parquet formats. An empty string is an invalid value. + "connectionId": "A String", # Optional. The connection specifying the credentials to be used to read external storage, such as Azure Blob, Cloud Storage, or S3. The connection_id can have the form "<project\_id>.<location\_id>.<connection\_id>" or "projects/<project\_id>/locations/<location\_id>/connections/<connection\_id>". + "csvOptions": { # Information related to a CSV data source. # Optional. Additional properties to set if sourceFormat is set to CSV. + "allowJaggedRows": True or False, # Optional. Indicates if BigQuery should accept rows that are missing trailing optional columns. If true, BigQuery treats missing trailing columns as null values. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. + "allowQuotedNewlines": True or False, # Optional. Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false. + "encoding": "A String", # Optional. The character encoding of the data. The supported values are UTF-8, ISO-8859-1, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the quote and fieldDelimiter properties. + "fieldDelimiter": "A String", # Optional. The separator character for fields in a CSV file. The separator is interpreted as a single byte. For files encoded in ISO-8859-1, any single character can be used as a separator. For files encoded in UTF-8, characters represented in decimal range 1-127 (U+0001-U+007F) can be used without any modification. UTF-8 characters encoded with multiple bytes (i.e. U+0080 and above) will have only the first byte used for separating fields. The remaining bytes will be treated as a part of the field. BigQuery also supports the escape sequence "\t" (U+0009) to specify a tab separator. The default value is comma (",", U+002C). + "nullMarker": "A String", # [Optional] A custom string that will represent a NULL value in CSV import data. + "preserveAsciiControlCharacters": True or False, # Optional. Indicates if the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\x00' to '\x1F') are preserved. + "quote": """, # Optional. The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ("). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true. To include the specific quote character within a quoted value, precede it with an additional matching quote character. For example, if you want to escape the default character ' " ', use ' "" '. + "skipLeadingRows": "A String", # Optional. The number of rows at the top of a CSV file that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema. + }, + "decimalTargetTypes": [ # Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown. Example: Suppose the value of this field is ["NUMERIC", "BIGNUMERIC"]. If (precision,scale) is: * (38,9) -> NUMERIC; * (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits); * (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits); * (76,38) -> BIGNUMERIC; * (77,38) -> BIGNUMERIC (error if value exeeds supported range). This field cannot contain duplicate types. The order of the types in this field is ignored. For example, ["BIGNUMERIC", "NUMERIC"] is the same as ["NUMERIC", "BIGNUMERIC"] and NUMERIC always takes precedence over BIGNUMERIC. Defaults to ["NUMERIC", "STRING"] for ORC and ["NUMERIC"] for the other file formats. "A String", ], - "fileSetSpecType": "A String", # [Optional] Specifies how source URIs are interpreted for constructing the file set to load. By default source URIs are expanded against the underlying storage. Other options include specifying manifest files. Only applicable to object storage systems. - "googleSheetsOptions": { # [Optional] Additional options if sourceFormat is set to GOOGLE_SHEETS. - "range": "A String", # [Optional] Range of a sheet to query from. Only used when non-empty. Typical format: sheet_name!top_left_cell_id:bottom_right_cell_id For example: sheet1!A1:B20 - "skipLeadingRows": "A String", # [Optional] The number of rows at the top of a sheet that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows that should be skipped. When autodetect is on, behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema. + "fileSetSpecType": "A String", # Optional. Specifies how source URIs are interpreted for constructing the file set to load. By default source URIs are expanded against the underlying storage. Other options include specifying manifest files. Only applicable to object storage systems. + "googleSheetsOptions": { # Options specific to Google Sheets data sources. # Optional. Additional options if sourceFormat is set to GOOGLE_SHEETS. + "range": "A String", # Optional. Range of a sheet to query from. Only used when non-empty. Typical format: sheet_name!top_left_cell_id:bottom_right_cell_id For example: sheet1!A1:B20 + "skipLeadingRows": "A String", # Optional. The number of rows at the top of a sheet that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema. }, - "hivePartitioningOptions": { # [Optional] Options to configure hive partitioning support. - "fields": [ # [Output-only] For permanent external tables, this field is populated with the hive partition keys in the order they were inferred. The types of the partition keys can be deduced by checking the table schema (which will include the partition keys). Not every API will populate this field in the output. For example, Tables.Get will populate it, but Tables.List will not contain this field. + "hivePartitioningOptions": { # Options for configuring hive partitioning detect. # Optional. When set, configures hive partitioning support. Not all storage formats support hive partitioning -- requesting hive partitioning on an unsupported format will lead to an error, as will providing an invalid specification. + "fields": [ # Output only. For permanent external tables, this field is populated with the hive partition keys in the order they were inferred. The types of the partition keys can be deduced by checking the table schema (which will include the partition keys). Not every API will populate this field in the output. For example, Tables.Get will populate it, but Tables.List will not contain this field. "A String", ], - "mode": "A String", # [Optional] When set, what mode of hive partitioning to use when reading data. The following modes are supported. (1) AUTO: automatically infer partition key name(s) and type(s). (2) STRINGS: automatically infer partition key name(s). All types are interpreted as strings. (3) CUSTOM: partition key schema is encoded in the source URI prefix. Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported types include: AVRO, CSV, JSON, ORC and Parquet. - "requirePartitionFilter": True or False, # [Optional] If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. Note that this field should only be true when creating a permanent external table or querying a temporary external table. Hive-partitioned loads with requirePartitionFilter explicitly set to true will fail. - "sourceUriPrefix": "A String", # [Optional] When hive partition detection is requested, a common prefix for all source uris should be supplied. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout. gs://bucket/path_to_table/dt=2019-01-01/country=BR/id=7/file.avro gs://bucket/path_to_table/dt=2018-12-31/country=CA/id=3/file.avro When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/ (trailing slash does not matter). - }, - "ignoreUnknownValues": True or False, # [Optional] Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names Google Cloud Bigtable: This setting is ignored. Google Cloud Datastore backups: This setting is ignored. Avro: This setting is ignored. - "jsonOptions": { # Additional properties to set if `sourceFormat` is set to `NEWLINE_DELIMITED_JSON`. - "encoding": "A String", # [Optional] The character encoding of the data. The supported values are UTF-8, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8. - }, - "maxBadRecords": 42, # [Optional] The maximum number of bad records that BigQuery can ignore when reading data. If the number of bad records exceeds this value, an invalid error is returned in the job result. This is only valid for CSV, JSON, and Google Sheets. The default value is 0, which requires that all records are valid. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups and Avro formats. - "metadataCacheMode": "A String", # [Optional] Metadata Cache Mode for the table. Set this to enable caching of metadata from external data source. - "objectMetadata": "A String", # ObjectMetadata is used to create Object Tables. Object Tables contain a listing of objects (with their metadata) found at the source_uris. If ObjectMetadata is set, source_format should be omitted. Currently SIMPLE is the only supported Object Metadata type. - "parquetOptions": { # Additional properties to set if sourceFormat is set to Parquet. - "enableListInference": True or False, # [Optional] Indicates whether to use schema inference specifically for Parquet LIST logical type. - "enumAsString": True or False, # [Optional] Indicates whether to infer Parquet ENUM logical type as STRING instead of BYTES by default. - }, - "referenceFileSchemaUri": "A String", # [Optional] Provide a referencing file with the expected table schema. Enabled for the format: AVRO, PARQUET, ORC. - "schema": { # [Optional] The schema for the data. Schema is required for CSV and JSON formats. Schema is disallowed for Google Cloud Bigtable, Cloud Datastore backups, and Avro formats. + "mode": "A String", # Optional. When set, what mode of hive partitioning to use when reading data. The following modes are supported: * AUTO: automatically infer partition key name(s) and type(s). * STRINGS: automatically infer partition key name(s). All types are strings. * CUSTOM: partition key schema is encoded in the source URI prefix. Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported formats are: JSON, CSV, ORC, Avro and Parquet. + "requirePartitionFilter": false, # Optional. If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. Note that this field should only be true when creating a permanent external table or querying a temporary external table. Hive-partitioned loads with require_partition_filter explicitly set to true will fail. + "sourceUriPrefix": "A String", # Optional. When hive partition detection is requested, a common prefix for all source uris must be required. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout: gs://bucket/path_to_table/dt=2019-06-01/country=USA/id=7/file.avro gs://bucket/path_to_table/dt=2019-05-31/country=CA/id=3/file.avro When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/. CUSTOM detection requires encoding the partitioning schema immediately after the common prefix. For CUSTOM, any of * gs://bucket/path_to_table/{dt:DATE}/{country:STRING}/{id:INTEGER} * gs://bucket/path_to_table/{dt:STRING}/{country:STRING}/{id:INTEGER} * gs://bucket/path_to_table/{dt:DATE}/{country:STRING}/{id:STRING} would all be valid source URI prefixes. + }, + "ignoreUnknownValues": True or False, # Optional. Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names Google Cloud Bigtable: This setting is ignored. Google Cloud Datastore backups: This setting is ignored. Avro: This setting is ignored. ORC: This setting is ignored. Parquet: This setting is ignored. + "jsonExtension": "A String", # Optional. Load option to be used together with source_format newline-delimited JSON to indicate that a variant of JSON is being loaded. To load newline-delimited GeoJSON, specify GEOJSON (and source_format must be set to NEWLINE_DELIMITED_JSON). + "jsonOptions": { # Json Options for load and make external tables. # Optional. Additional properties to set if sourceFormat is set to JSON. + "encoding": "A String", # Optional. The character encoding of the data. The supported values are UTF-8, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8. + }, + "maxBadRecords": 42, # Optional. The maximum number of bad records that BigQuery can ignore when reading data. If the number of bad records exceeds this value, an invalid error is returned in the job result. The default value is 0, which requires that all records are valid. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups, Avro, ORC and Parquet formats. + "metadataCacheMode": "A String", # Optional. Metadata Cache Mode for the table. Set this to enable caching of metadata from external data source. + "objectMetadata": "A String", # Optional. ObjectMetadata is used to create Object Tables. Object Tables contain a listing of objects (with their metadata) found at the source_uris. If ObjectMetadata is set, source_format should be omitted. Currently SIMPLE is the only supported Object Metadata type. + "parquetOptions": { # Parquet Options for load and make external tables. # Optional. Additional properties to set if sourceFormat is set to PARQUET. + "enableListInference": True or False, # Optional. Indicates whether to use schema inference specifically for Parquet LIST logical type. + "enumAsString": True or False, # Optional. Indicates whether to infer Parquet ENUM logical type as STRING instead of BYTES by default. + }, + "referenceFileSchemaUri": "A String", # Optional. When creating an external table, the user can provide a reference file with the table schema. This is enabled for the following formats: AVRO, PARQUET, ORC. + "schema": { # Schema of a table # Optional. The schema for the data. Schema is required for CSV and JSON formats if autodetect is not on. Schema is disallowed for Google Cloud Bigtable, Cloud Datastore backups, Avro, ORC and Parquet formats. "fields": [ # Describes the fields in a table. - { - "categories": { # [Optional] The categories attached to this field, used for field-level access control. - "names": [ # A list of category resource names. For example, "projects/1/taxonomies/2/categories/3". At most 5 categories are allowed. + { # A field in TableSchema + "categories": { # Deprecated. + "names": [ # Deprecated. "A String", ], }, - "collation": "A String", # Optional. Collation specification of the field. It only can be set on string type field. - "defaultValueExpression": "A String", # Optional. A SQL expression to specify the default value for this field. It can only be set for top level fields (columns). You can use struct or array expression to specify default value for the entire struct or array. The valid SQL expressions are: - Literals for all data types, including STRUCT and ARRAY. - Following functions: - CURRENT_TIMESTAMP - CURRENT_TIME - CURRENT_DATE - CURRENT_DATETIME - GENERATE_UUID - RAND - SESSION_USER - ST_GEOGPOINT - Struct or array composed with the above allowed functions, for example, [CURRENT_DATE(), DATE '2020-01-01'] - "description": "A String", # [Optional] The field description. The maximum length is 1,024 characters. - "fields": [ # [Optional] Describes the nested schema fields if the type property is set to RECORD. + "collation": "A String", # Optional. Field collation can be set only when the type of field is STRING. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior. + "defaultValueExpression": "A String", # Optional. A SQL expression to specify the [default value] (https://cloud.google.com/bigquery/docs/default-values) for this field. + "description": "A String", # Optional. The field description. The maximum length is 1,024 characters. + "fields": [ # Optional. Describes the nested schema fields if the type property is set to RECORD. # Object with schema name: TableFieldSchema ], - "maxLength": "A String", # [Optional] Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES". - "mode": "A String", # [Optional] The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE. - "name": "A String", # [Required] The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters. - "policyTags": { - "names": [ # A list of category resource names. For example, "projects/1/location/eu/taxonomies/2/policyTags/3". At most 1 policy tag is allowed. + "maxLength": "A String", # Optional. Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES". + "mode": "A String", # Optional. The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE. + "name": "A String", # Required. The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters. + "policyTags": { # Optional. The policy tags attached to this field, used for field-level access control. If not set, defaults to empty policy_tags. + "names": [ # A list of policy tag resource names. For example, "projects/1/locations/eu/taxonomies/2/policyTags/3". At most 1 policy tag is currently allowed. "A String", ], }, - "precision": "A String", # [Optional] Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: - Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] - Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: - If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. - If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): - If type = "NUMERIC": 1 ≤ precision ≤ 29. - If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid. - "rangeElementType": { # Optional. The subtype of the RANGE, if the type of this field is RANGE. If the type is RANGE, this field is required. Possible values for the field element type of a RANGE include: - DATE - DATETIME - TIMESTAMP - "type": "A String", # The field element type of a RANGE + "precision": "A String", # Optional. Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: * Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] * Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: * If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. * If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): * If type = "NUMERIC": 1 ≤ precision ≤ 29. * If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid. + "rangeElementType": { # Represents the type of a field element. + "type": "A String", # Required. The type of a field element. See TableFieldSchema.type. }, - "roundingMode": "A String", # Optional. Rounding Mode specification of the field. It only can be set on NUMERIC or BIGNUMERIC type fields. - "scale": "A String", # [Optional] See documentation for precision. - "type": "A String", # [Required] The field data type. Possible values include STRING, BYTES, INTEGER, INT64 (same as INTEGER), FLOAT, FLOAT64 (same as FLOAT), NUMERIC, BIGNUMERIC, BOOLEAN, BOOL (same as BOOLEAN), TIMESTAMP, DATE, TIME, DATETIME, INTERVAL, RECORD (where RECORD indicates that the field contains a nested schema) or STRUCT (same as RECORD). + "roundingMode": "A String", # Optional. Specifies the rounding mode to be used when storing values of NUMERIC and BIGNUMERIC type. + "scale": "A String", # Optional. See documentation for precision. + "type": "A String", # Required. The field data type. Possible values include: * STRING * BYTES * INTEGER (or INT64) * FLOAT (or FLOAT64) * BOOLEAN (or BOOL) * TIMESTAMP * DATE * TIME * DATETIME * GEOGRAPHY * NUMERIC * BIGNUMERIC * JSON * RECORD (or STRUCT) Use of RECORD/STRUCT indicates that the field contains a nested schema. }, ], }, - "sourceFormat": "A String", # [Required] The data format. For CSV files, specify "CSV". For Google sheets, specify "GOOGLE_SHEETS". For newline-delimited JSON, specify "NEWLINE_DELIMITED_JSON". For Avro files, specify "AVRO". For Google Cloud Datastore backups, specify "DATASTORE_BACKUP". [Beta] For Google Cloud Bigtable, specify "BIGTABLE". + "sourceFormat": "A String", # [Required] The data format. For CSV files, specify "CSV". For Google sheets, specify "GOOGLE_SHEETS". For newline-delimited JSON, specify "NEWLINE_DELIMITED_JSON". For Avro files, specify "AVRO". For Google Cloud Datastore backups, specify "DATASTORE_BACKUP". For Apache Iceberg tables, specify "ICEBERG". For ORC files, specify "ORC". For Parquet files, specify "PARQUET". [Beta] For Google Cloud Bigtable, specify "BIGTABLE". "sourceUris": [ # [Required] The fully-qualified URIs that point to your data in Google Cloud. For Google Cloud Storage URIs: Each URI can contain one '*' wildcard character and it must come after the 'bucket' name. Size limits related to load jobs apply to external data sources. For Google Cloud Bigtable URIs: Exactly one URI can be specified and it has be a fully specified and valid HTTPS URL for a Google Cloud Bigtable table. For Google Cloud Datastore backups, exactly one URI can be specified. Also, the '*' wildcard character is not allowed. "A String", ], }, }, "timePartitioning": { # Time-based partitioning specification for the destination table. Only one of timePartitioning and rangePartitioning should be specified. - "expirationMs": "A String", # [Optional] Number of milliseconds for which to keep the storage for partitions in the table. The storage in a partition will have an expiration time of its partition time plus this value. - "field": "A String", # [Beta] [Optional] If not set, the table is partitioned by pseudo column, referenced via either '_PARTITIONTIME' as TIMESTAMP type, or '_PARTITIONDATE' as DATE type. If field is specified, the table is instead partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED. - "requirePartitionFilter": True or False, - "type": "A String", # [Required] The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively. When the type is not specified, the default behavior is DAY. + "expirationMs": "A String", # Optional. Number of milliseconds for which to keep the storage for a partition. A wrapper is used here because 0 is an invalid value. + "field": "A String", # Optional. If not set, the table is partitioned by pseudo column '_PARTITIONTIME'; if set, the table is partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED. A wrapper is used here because an empty string is an invalid value. + "requirePartitionFilter": false, # If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. This field is deprecated; please set the field with the same name on the table itself instead. This field needs a wrapper because we want to output the default value, false, if the user explicitly set it. + "type": "A String", # Required. The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively. }, - "useLegacySql": true, # Specifies whether to use BigQuery's legacy SQL dialect for this query. The default value is true. If set to false, the query will use BigQuery's standard SQL: https://cloud.google.com/bigquery/sql-reference/ When useLegacySql is set to false, the value of flattenResults is ignored; query will be run as if flattenResults is false. - "useQueryCache": true, # [Optional] Whether to look for the result in the query cache. The query cache is a best-effort cache that will be flushed whenever tables in the query are modified. Moreover, the query cache is only available when a query does not have a destination table specified. The default value is true. + "useLegacySql": true, # Optional. Specifies whether to use BigQuery's legacy SQL dialect for this query. The default value is true. If set to false, the query will use BigQuery's GoogleSQL: https://cloud.google.com/bigquery/sql-reference/ When useLegacySql is set to false, the value of flattenResults is ignored; query will be run as if flattenResults is false. + "useQueryCache": true, # Optional. Whether to look for the result in the query cache. The query cache is a best-effort cache that will be flushed whenever tables in the query are modified. Moreover, the query cache is only available when a query does not have a destination table specified. The default value is true. "userDefinedFunctionResources": [ # Describes user-defined function resources used in the query. - { # This is used for defining User Defined Function (UDF) resources only when using legacy SQL. Users of Standard SQL should leverage either DDL (e.g. CREATE [TEMPORARY] FUNCTION ... ) or the Routines API to define UDF resources. For additional information on migrating, see: https://cloud.google.com/bigquery/docs/reference/standard-sql/migrating-from-legacy-sql#differences_in_user-defined_javascript_functions + { # This is used for defining User Defined Function (UDF) resources only when using legacy SQL. Users of GoogleSQL should leverage either DDL (e.g. CREATE [TEMPORARY] FUNCTION ... ) or the Routines API to define UDF resources. For additional information on migrating, see: https://cloud.google.com/bigquery/docs/reference/standard-sql/migrating-from-legacy-sql#differences_in_user-defined_javascript_functions "inlineCode": "A String", # [Pick one] An inline resource that contains code for a user-defined function (UDF). Providing a inline code resource is equivalent to providing a URI for a file containing the same code. "resourceUri": "A String", # [Pick one] A code resource to load from a Google Cloud Storage URI (gs://bucket/path). }, ], - "writeDisposition": "A String", # [Optional] Specifies the action that occurs if the destination table already exists. The following values are supported: WRITE_TRUNCATE: If the table already exists, BigQuery overwrites the table data and uses the schema from the query result. WRITE_APPEND: If the table already exists, BigQuery appends the data to the table. WRITE_EMPTY: If the table already exists and contains data, a 'duplicate' error is returned in the job result. The default value is WRITE_EMPTY. Each action is atomic and only occurs if BigQuery is able to complete the job successfully. Creation, truncation and append actions occur as one atomic update upon job completion. + "writeDisposition": "A String", # Optional. Specifies the action that occurs if the destination table already exists. The following values are supported: * WRITE_TRUNCATE: If the table already exists, BigQuery overwrites the data, removes the constraints, and uses the schema from the query result. * WRITE_APPEND: If the table already exists, BigQuery appends the data to the table. * WRITE_EMPTY: If the table already exists and contains data, a 'duplicate' error is returned in the job result. The default value is WRITE_EMPTY. Each action is atomic and only occurs if BigQuery is able to complete the job successfully. Creation, truncation and append actions occur as one atomic update upon job completion. }, }, - "etag": "A String", # [Output-only] A hash of this resource. - "id": "A String", # [Output-only] Opaque ID field of the job - "jobCreationReason": "", # [Output-only] If set, it provides the reason why a Job was created. If not set, it should be treated as the default: REQUESTED. This feature is not yet available. Jobs will always be created. - "jobReference": { # [Optional] Reference describing the unique-per-user name of the job. - "jobId": "A String", # [Required] The ID of the job. The ID must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), or dashes (-). The maximum length is 1,024 characters. - "location": "A String", # The geographic location of the job. See details at https://cloud.google.com/bigquery/docs/locations#specifying_your_location. - "projectId": "A String", # [Required] The ID of the project containing this job. + "etag": "A String", # Output only. A hash of this resource. + "id": "A String", # Output only. Opaque ID field of the job. + "jobCreationReason": { # Reason about why a Job was created from a [`jobs.query`](https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs/query) method when used with `JOB_CREATION_OPTIONAL` Job creation mode. For [`jobs.insert`](https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs/insert) method calls it will always be `REQUESTED`. This feature is not yet available. Jobs will always be created. # Output only. If set, it provides the reason why a Job was created. If not set, it should be treated as the default: REQUESTED. This feature is not yet available. Jobs will always be created. + "code": "A String", # Output only. Specifies the high level reason why a Job was created. + }, + "jobReference": { # A job reference is a fully qualified identifier for referring to a job. # Optional. Reference describing the unique-per-user name of the job. + "jobId": "A String", # Required. The ID of the job. The ID must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), or dashes (-). The maximum length is 1,024 characters. + "location": "A String", # Optional. The geographic location of the job. The default value is US. For more information about BigQuery locations, see: https://cloud.google.com/bigquery/docs/locations + "projectId": "A String", # Required. The ID of the project containing this job. }, - "kind": "bigquery#job", # [Output-only] The type of the resource. - "selfLink": "A String", # [Output-only] A URL that can be used to access this resource again. - "statistics": { # [Output-only] Information about the job, including starting time and ending time of the job. - "completionRatio": 3.14, # [TrustedTester] [Output-only] Job progress (0.0 -> 1.0) for LOAD and EXTRACT jobs. - "copy": { # [Output-only] Statistics for a copy job. - "copiedLogicalBytes": "A String", # [Output-only] Number of logical bytes copied to the destination table. - "copiedRows": "A String", # [Output-only] Number of rows copied to the destination table. + "kind": "bigquery#job", # Output only. The type of the resource. + "principal_subject": "A String", # Output only. [Full-projection-only] String representation of identity of requesting party. Populated for both first- and third-party identities. Only present for APIs that support third-party identities. + "selfLink": "A String", # Output only. A URL that can be used to access the resource again. + "statistics": { # Statistics for a single job execution. # Output only. Information about the job, including starting time and ending time of the job. + "completionRatio": 3.14, # Output only. [TrustedTester] Job progress (0.0 -> 1.0) for LOAD and EXTRACT jobs. + "copy": { # Statistics for a copy job. # Output only. Statistics for a copy job. + "copiedLogicalBytes": "A String", # Output only. Number of logical bytes copied to the destination table. + "copiedRows": "A String", # Output only. Number of rows copied to the destination table. }, - "creationTime": "A String", # [Output-only] Creation time of this job, in milliseconds since the epoch. This field will be present on all jobs. - "dataMaskingStatistics": { # [Output-only] Statistics for data masking. Present only for query and extract jobs. - "dataMaskingApplied": false, # [Output-only] [Preview] Whether any accessed data was protected by data masking. The actual evaluation is done by accessStats.masked_field_count > 0. Since this is only used for the discovery_doc generation purpose, as long as the type (boolean) matches, client library can leverage this. The actual evaluation of the variable is done else-where. + "creationTime": "A String", # Output only. Creation time of this job, in milliseconds since the epoch. This field will be present on all jobs. + "dataMaskingStatistics": { # Statistics for data-masking. # Output only. Statistics for data-masking. Present only for query and extract jobs. + "dataMaskingApplied": True or False, # Whether any accessed data was protected by the data masking. }, - "endTime": "A String", # [Output-only] End time of this job, in milliseconds since the epoch. This field will be present whenever a job is in the DONE state. - "extract": { # [Output-only] Statistics for an extract job. - "destinationUriFileCounts": [ # [Output-only] Number of files per destination URI or URI pattern specified in the extract configuration. These values will be in the same order as the URIs specified in the 'destinationUris' field. + "endTime": "A String", # Output only. End time of this job, in milliseconds since the epoch. This field will be present whenever a job is in the DONE state. + "extract": { # Statistics for an extract job. # Output only. Statistics for an extract job. + "destinationUriFileCounts": [ # Output only. Number of files per destination URI or URI pattern specified in the extract configuration. These values will be in the same order as the URIs specified in the 'destinationUris' field. "A String", ], - "inputBytes": "A String", # [Output-only] Number of user bytes extracted into the result. This is the byte count as computed by BigQuery for billing purposes. + "inputBytes": "A String", # Output only. Number of user bytes extracted into the result. This is the byte count as computed by BigQuery for billing purposes and doesn't have any relationship with the number of actual result bytes extracted in the desired format. + "timeline": [ # Output only. Describes a timeline of job execution. + { # Summary of the state of query execution at a given time. + "activeUnits": "A String", # Total number of active workers. This does not correspond directly to slot usage. This is the largest value observed since the last sample. + "completedUnits": "A String", # Total parallel units of work completed by this query. + "elapsedMs": "A String", # Milliseconds elapsed since the start of query execution. + "estimatedRunnableUnits": "A String", # Units of work that can be scheduled immediately. Providing additional slots for these units of work will accelerate the query, if no other query in the reservation needs additional slots. + "pendingUnits": "A String", # Total units of work remaining for the query. This number can be revised (increased or decreased) while the query is running. + "totalSlotMs": "A String", # Cumulative slot-ms consumed by the query. + }, + ], }, - "load": { # [Output-only] Statistics for a load job. - "badRecords": "A String", # [Output-only] The number of bad records encountered. Note that if the job has failed because of more bad records encountered than the maximum allowed in the load job configuration, then this number can be less than the total number of bad records present in the input data. - "inputFileBytes": "A String", # [Output-only] Number of bytes of source data in a load job. - "inputFiles": "A String", # [Output-only] Number of source files in a load job. - "outputBytes": "A String", # [Output-only] Size of the loaded data in bytes. Note that while a load job is in the running state, this value may change. - "outputRows": "A String", # [Output-only] Number of rows imported in a load job. Note that while an import job is in the running state, this value may change. + "finalExecutionDurationMs": "A String", # Output only. The duration in milliseconds of the execution of the final attempt of this job, as BigQuery may internally re-attempt to execute the job. + "load": { # Statistics for a load job. # Output only. Statistics for a load job. + "badRecords": "A String", # Output only. The number of bad records encountered. Note that if the job has failed because of more bad records encountered than the maximum allowed in the load job configuration, then this number can be less than the total number of bad records present in the input data. + "inputFileBytes": "A String", # Output only. Number of bytes of source data in a load job. + "inputFiles": "A String", # Output only. Number of source files in a load job. + "outputBytes": "A String", # Output only. Size of the loaded data in bytes. Note that while a load job is in the running state, this value may change. + "outputRows": "A String", # Output only. Number of rows imported in a load job. Note that while an import job is in the running state, this value may change. + "timeline": [ # Output only. Describes a timeline of job execution. + { # Summary of the state of query execution at a given time. + "activeUnits": "A String", # Total number of active workers. This does not correspond directly to slot usage. This is the largest value observed since the last sample. + "completedUnits": "A String", # Total parallel units of work completed by this query. + "elapsedMs": "A String", # Milliseconds elapsed since the start of query execution. + "estimatedRunnableUnits": "A String", # Units of work that can be scheduled immediately. Providing additional slots for these units of work will accelerate the query, if no other query in the reservation needs additional slots. + "pendingUnits": "A String", # Total units of work remaining for the query. This number can be revised (increased or decreased) while the query is running. + "totalSlotMs": "A String", # Cumulative slot-ms consumed by the query. + }, + ], }, - "numChildJobs": "A String", # [Output-only] Number of child jobs executed. - "parentJobId": "A String", # [Output-only] If this is a child job, the id of the parent. - "query": { # [Output-only] Statistics for a query job. - "biEngineStatistics": { # BI Engine specific Statistics. [Output only] BI Engine specific Statistics. - "accelerationMode": "", # [Output-only] Specifies which mode of BI Engine acceleration was performed (if any). - "biEngineMode": "", # [Output-only] Specifies which mode of BI Engine acceleration was performed (if any). + "numChildJobs": "A String", # Output only. Number of child jobs executed. + "parentJobId": "A String", # Output only. If this is a child job, specifies the job ID of the parent. + "query": { # Statistics for a query job. # Output only. Statistics for a query job. + "biEngineStatistics": { # Statistics for a BI Engine specific query. Populated as part of JobStatistics2 # Output only. BI Engine specific Statistics. + "accelerationMode": "A String", # Output only. Specifies which mode of BI Engine acceleration was performed (if any). + "biEngineMode": "A String", # Output only. Specifies which mode of BI Engine acceleration was performed (if any). "biEngineReasons": [ # In case of DISABLED or PARTIAL bi_engine_mode, these contain the explanatory reasons as to why BI Engine could not accelerate. In case the full query was accelerated, this field is not populated. - { - "code": "", # [Output-only] High-level BI Engine reason for partial or disabled acceleration. - "message": "", # [Output-only] Free form human-readable reason for partial or disabled acceleration. + { # Reason why BI Engine didn't accelerate the query (or sub-query). + "code": "A String", # Output only. High-level BI Engine reason for partial or disabled acceleration + "message": "A String", # Output only. Free form human-readable reason for partial or disabled acceleration. }, ], }, - "billingTier": 42, # [Output only] Billing tier for the job. - "cacheHit": True or False, # [Output only] Whether the query result was fetched from the query cache. - "ddlAffectedRowAccessPolicyCount": "A String", # [Output only] [Preview] The number of row access policies affected by a DDL statement. Present only for DROP ALL ROW ACCESS POLICIES queries. - "ddlDestinationTable": { # [Output only] The DDL destination table. Present only for ALTER TABLE RENAME TO queries. Note that ddl_target_table is used just for its type information. - "datasetId": "A String", # [Required] The ID of the dataset containing this table. - "projectId": "A String", # [Required] The ID of the project containing this table. - "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. - }, - "ddlOperationPerformed": "A String", # The DDL operation performed, possibly dependent on the pre-existence of the DDL target. Possible values (new values might be added in the future): "CREATE": The query created the DDL target. "SKIP": No-op. Example cases: the query is CREATE TABLE IF NOT EXISTS while the table already exists, or the query is DROP TABLE IF EXISTS while the table does not exist. "REPLACE": The query replaced the DDL target. Example case: the query is CREATE OR REPLACE TABLE, and the table already exists. "DROP": The query deleted the DDL target. - "ddlTargetDataset": { # [Output only] The DDL target dataset. Present only for CREATE/ALTER/DROP/UNDROP SCHEMA queries. - "datasetId": "A String", # [Required] A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. - "projectId": "A String", # [Optional] The ID of the project containing this dataset. - }, - "ddlTargetRoutine": { # The DDL target routine. Present only for CREATE/DROP FUNCTION/PROCEDURE queries. + "billingTier": 42, # Output only. Billing tier for the job. This is a BigQuery-specific concept which is not related to the Google Cloud notion of "free tier". The value here is a measure of the query's resource consumption relative to the amount of data scanned. For on-demand queries, the limit is 100, and all queries within this limit are billed at the standard on-demand rates. On-demand queries that exceed this limit will fail with a billingTierLimitExceeded error. + "cacheHit": True or False, # Output only. Whether the query result was fetched from the query cache. + "dclTargetDataset": { # Output only. Referenced dataset for DCL statement. + "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. + "projectId": "A String", # Optional. The ID of the project containing this dataset. + }, + "dclTargetTable": { # Output only. Referenced table for DCL statement. + "datasetId": "A String", # Required. The ID of the dataset containing this table. + "projectId": "A String", # Required. The ID of the project containing this table. + "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`. + }, + "dclTargetView": { # Output only. Referenced view for DCL statement. + "datasetId": "A String", # Required. The ID of the dataset containing this table. + "projectId": "A String", # Required. The ID of the project containing this table. + "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`. + }, + "ddlAffectedRowAccessPolicyCount": "A String", # Output only. The number of row access policies affected by a DDL statement. Present only for DROP ALL ROW ACCESS POLICIES queries. + "ddlDestinationTable": { # Output only. The table after rename. Present only for ALTER TABLE RENAME TO query. + "datasetId": "A String", # Required. The ID of the dataset containing this table. + "projectId": "A String", # Required. The ID of the project containing this table. + "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`. + }, + "ddlOperationPerformed": "A String", # Output only. The DDL operation performed, possibly dependent on the pre-existence of the DDL target. + "ddlTargetDataset": { # Output only. The DDL target dataset. Present only for CREATE/ALTER/DROP SCHEMA(dataset) queries. + "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. + "projectId": "A String", # Optional. The ID of the project containing this dataset. + }, + "ddlTargetRoutine": { # Id path of a routine. # Output only. [Beta] The DDL target routine. Present only for CREATE/DROP FUNCTION/PROCEDURE queries. "datasetId": "A String", # Required. The ID of the dataset containing this routine. "projectId": "A String", # Required. The ID of the project containing this routine. "routineId": "A String", # Required. The ID of the routine. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 256 characters. }, - "ddlTargetRowAccessPolicy": { # [Output only] [Preview] The DDL target row access policy. Present only for CREATE/DROP ROW ACCESS POLICY queries. + "ddlTargetRowAccessPolicy": { # Id path of a row access policy. # Output only. The DDL target row access policy. Present only for CREATE/DROP ROW ACCESS POLICY queries. "datasetId": "A String", # Required. The ID of the dataset containing this row access policy. "policyId": "A String", # Required. The ID of the row access policy. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 256 characters. "projectId": "A String", # Required. The ID of the project containing this row access policy. "tableId": "A String", # Required. The ID of the table containing this row access policy. }, - "ddlTargetTable": { # [Output only] The DDL target table. Present only for CREATE/DROP TABLE/VIEW and DROP ALL ROW ACCESS POLICIES queries. - "datasetId": "A String", # [Required] The ID of the dataset containing this table. - "projectId": "A String", # [Required] The ID of the project containing this table. - "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. - }, - "dmlStats": { # [Output only] Detailed statistics for DML statements Present only for DML statements INSERT, UPDATE, DELETE or TRUNCATE. - "deletedRowCount": "A String", # Number of deleted Rows. populated by DML DELETE, MERGE and TRUNCATE statements. - "insertedRowCount": "A String", # Number of inserted Rows. Populated by DML INSERT and MERGE statements. - "updatedRowCount": "A String", # Number of updated Rows. Populated by DML UPDATE and MERGE statements. - }, - "estimatedBytesProcessed": "A String", # [Output only] The original estimate of bytes processed for the job. - "mlStatistics": { # [Output only] Statistics of a BigQuery ML training job. - "iterationResults": [ # Results for all completed iterations. - { - "durationMs": "A String", # Time taken to run the iteration in milliseconds. - "evalLoss": 3.14, # Loss computed on the eval data at the end of iteration. - "index": 42, # Index of the iteration, 0 based. - "learnRate": 3.14, # Learn rate used for this iteration. - "trainingLoss": 3.14, # Loss computed on the training data at the end of iteration. + "ddlTargetTable": { # Output only. The DDL target table. Present only for CREATE/DROP TABLE/VIEW and DROP ALL ROW ACCESS POLICIES queries. + "datasetId": "A String", # Required. The ID of the dataset containing this table. + "projectId": "A String", # Required. The ID of the project containing this table. + "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`. + }, + "dmlStats": { # Detailed statistics for DML statements # Output only. Detailed statistics for DML statements INSERT, UPDATE, DELETE, MERGE or TRUNCATE. + "deletedRowCount": "A String", # Output only. Number of deleted Rows. populated by DML DELETE, MERGE and TRUNCATE statements. + "insertedRowCount": "A String", # Output only. Number of inserted Rows. Populated by DML INSERT and MERGE statements + "updatedRowCount": "A String", # Output only. Number of updated Rows. Populated by DML UPDATE and MERGE statements. + }, + "estimatedBytesProcessed": "A String", # Output only. The original estimate of bytes processed for the job. + "exportDataStatistics": { # Statistics for the EXPORT DATA statement as part of Query Job. EXTRACT JOB statistics are populated in JobStatistics4. # Output only. Stats for EXPORT DATA statement. + "fileCount": "A String", # Number of destination files generated in case of EXPORT DATA statement only. + "rowCount": "A String", # [Alpha] Number of destination rows generated in case of EXPORT DATA statement only. + }, + "externalServiceCosts": [ # Output only. Job cost breakdown as bigquery internal cost and external service costs. + { # The external service cost is a portion of the total cost, these costs are not additive with total_bytes_billed. Moreover, this field only track external service costs that will show up as BigQuery costs (e.g. training BigQuery ML job with google cloud CAIP or Automl Tables services), not other costs which may be accrued by running the query (e.g. reading from Bigtable or Cloud Storage). The external service costs with different billing sku (e.g. CAIP job is charged based on VM usage) are converted to BigQuery billed_bytes and slot_ms with equivalent amount of US dollars. Services may not directly correlate to these metrics, but these are the equivalents for billing purposes. Output only. + "bytesBilled": "A String", # External service cost in terms of bigquery bytes billed. + "bytesProcessed": "A String", # External service cost in terms of bigquery bytes processed. + "externalService": "A String", # External service name. + "reservedSlotCount": "A String", # Non-preemptable reserved slots used for external job. For example, reserved slots for Cloua AI Platform job are the VM usages converted to BigQuery slot with equivalent mount of price. + "slotMs": "A String", # External service cost in terms of bigquery slot milliseconds. + }, + ], + "loadQueryStatistics": { # Statistics for a LOAD query. # Output only. Statistics for a LOAD query. + "badRecords": "A String", # Output only. The number of bad records encountered while processing a LOAD query. Note that if the job has failed because of more bad records encountered than the maximum allowed in the load job configuration, then this number can be less than the total number of bad records present in the input data. + "bytesTransferred": "A String", # Output only. This field is deprecated. The number of bytes of source data copied over the network for a `LOAD` query. `transferred_bytes` has the canonical value for physical transferred bytes, which is used for BigQuery Omni billing. + "inputFileBytes": "A String", # Output only. Number of bytes of source data in a LOAD query. + "inputFiles": "A String", # Output only. Number of source files in a LOAD query. + "outputBytes": "A String", # Output only. Size of the loaded data in bytes. Note that while a LOAD query is in the running state, this value may change. + "outputRows": "A String", # Output only. Number of rows imported in a LOAD query. Note that while a LOAD query is in the running state, this value may change. + }, + "materializedViewStatistics": { # Statistics of materialized views considered in a query job. # Output only. Statistics of materialized views of a query job. + "materializedView": [ # Materialized views considered for the query job. Only certain materialized views are used. For a detailed list, see the child message. If many materialized views are considered, then the list might be incomplete. + { # A materialized view considered for a query job. + "chosen": True or False, # Whether the materialized view is chosen for the query. A materialized view can be chosen to rewrite multiple parts of the same query. If a materialized view is chosen to rewrite any part of the query, then this field is true, even if the materialized view was not chosen to rewrite others parts. + "estimatedBytesSaved": "A String", # If present, specifies a best-effort estimation of the bytes saved by using the materialized view rather than its base tables. + "rejectedReason": "A String", # If present, specifies the reason why the materialized view was not chosen for the query. + "tableReference": { # The candidate materialized view. + "datasetId": "A String", # Required. The ID of the dataset containing this table. + "projectId": "A String", # Required. The ID of the project containing this table. + "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`. + }, }, ], - "maxIterations": "A String", # Maximum number of iterations specified as max_iterations in the 'CREATE MODEL' query. The actual number of iterations may be less than this number due to early stop. }, - "modelTraining": { # [Output only, Beta] Information about create model query job progress. - "currentIteration": 42, # [Output-only, Beta] Index of current ML training iteration. Updated during create model query job to show job progress. - "expectedTotalIterations": "A String", # [Output-only, Beta] Expected number of iterations for the create model query job specified as num_iterations in the input query. The actual total number of iterations may be less than this number due to early stop. - }, - "modelTrainingCurrentIteration": 42, # [Output only, Beta] Deprecated; do not use. - "modelTrainingExpectedTotalIteration": "A String", # [Output only, Beta] Deprecated; do not use. - "numDmlAffectedRows": "A String", # [Output only] The number of rows affected by a DML statement. Present only for DML statements INSERT, UPDATE or DELETE. - "queryPlan": [ # [Output only] Describes execution plan for the query. - { - "completedParallelInputs": "A String", # Number of parallel input segments completed. - "computeMsAvg": "A String", # Milliseconds the average shard spent on CPU-bound tasks. - "computeMsMax": "A String", # Milliseconds the slowest shard spent on CPU-bound tasks. - "computeRatioAvg": 3.14, # Relative amount of time the average shard spent on CPU-bound tasks. - "computeRatioMax": 3.14, # Relative amount of time the slowest shard spent on CPU-bound tasks. - "endMs": "A String", # Stage end time represented as milliseconds since epoch. - "id": "A String", # Unique ID for stage within plan. - "inputStages": [ # IDs for stages that are inputs to this stage. - "A String", - ], - "name": "A String", # Human-readable name for stage. - "parallelInputs": "A String", # Number of parallel input segments to be processed. - "readMsAvg": "A String", # Milliseconds the average shard spent reading input. - "readMsMax": "A String", # Milliseconds the slowest shard spent reading input. - "readRatioAvg": 3.14, # Relative amount of time the average shard spent reading input. - "readRatioMax": 3.14, # Relative amount of time the slowest shard spent reading input. - "recordsRead": "A String", # Number of records read into the stage. - "recordsWritten": "A String", # Number of records written by the stage. - "shuffleOutputBytes": "A String", # Total number of bytes written to shuffle. - "shuffleOutputBytesSpilled": "A String", # Total number of bytes written to shuffle and spilled to disk. - "slotMs": "A String", # Slot-milliseconds used by the stage. - "startMs": "A String", # Stage start time represented as milliseconds since epoch. - "status": "A String", # Current status for the stage. - "steps": [ # List of operations within the stage in dependency order (approximately chronological). - { - "kind": "A String", # Machine-readable operation type. - "substeps": [ # Human-readable stage descriptions. - "A String", - ], - }, - ], - "waitMsAvg": "A String", # Milliseconds the average shard spent waiting to be scheduled. - "waitMsMax": "A String", # Milliseconds the slowest shard spent waiting to be scheduled. - "waitRatioAvg": 3.14, # Relative amount of time the average shard spent waiting to be scheduled. - "waitRatioMax": 3.14, # Relative amount of time the slowest shard spent waiting to be scheduled. - "writeMsAvg": "A String", # Milliseconds the average shard spent on writing output. - "writeMsMax": "A String", # Milliseconds the slowest shard spent on writing output. - "writeRatioAvg": 3.14, # Relative amount of time the average shard spent on writing output. - "writeRatioMax": 3.14, # Relative amount of time the slowest shard spent on writing output. - }, - ], - "referencedRoutines": [ # [Output only] Referenced routines (persistent user-defined functions and stored procedures) for the job. - { - "datasetId": "A String", # Required. The ID of the dataset containing this routine. - "projectId": "A String", # Required. The ID of the project containing this routine. - "routineId": "A String", # Required. The ID of the routine. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 256 characters. - }, - ], - "referencedTables": [ # [Output only] Referenced tables for the job. Queries that reference more than 50 tables will not have a complete list. - { - "datasetId": "A String", # [Required] The ID of the dataset containing this table. - "projectId": "A String", # [Required] The ID of the project containing this table. - "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. - }, - ], - "reservationUsage": [ # [Output only] Job resource usage breakdown by reservation. - { - "name": "A String", # [Output only] Reservation name or "unreserved" for on-demand resources usage. - "slotMs": "A String", # [Output only] Slot-milliseconds the job spent in the given reservation. - }, - ], - "schema": { # [Output only] The schema of the results. Present only for successful dry run of non-legacy SQL queries. - "fields": [ # Describes the fields in a table. - { - "categories": { # [Optional] The categories attached to this field, used for field-level access control. - "names": [ # A list of category resource names. For example, "projects/1/taxonomies/2/categories/3". At most 5 categories are allowed. - "A String", - ], + "metadataCacheStatistics": { # Statistics for metadata caching in BigLake tables. # Output only. Statistics of metadata cache usage in a query for BigLake tables. + "tableMetadataCacheUsage": [ # Set for the Metadata caching eligible tables referenced in the query. + { # Table level detail on the usage of metadata caching. Only set for Metadata caching eligible tables referenced in the query. + "explanation": "A String", # Free form human-readable reason metadata caching was unused for the job. + "tableReference": { # Metadata caching eligible table referenced in the query. + "datasetId": "A String", # Required. The ID of the dataset containing this table. + "projectId": "A String", # Required. The ID of the project containing this table. + "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`. }, - "collation": "A String", # Optional. Collation specification of the field. It only can be set on string type field. - "defaultValueExpression": "A String", # Optional. A SQL expression to specify the default value for this field. It can only be set for top level fields (columns). You can use struct or array expression to specify default value for the entire struct or array. The valid SQL expressions are: - Literals for all data types, including STRUCT and ARRAY. - Following functions: - CURRENT_TIMESTAMP - CURRENT_TIME - CURRENT_DATE - CURRENT_DATETIME - GENERATE_UUID - RAND - SESSION_USER - ST_GEOGPOINT - Struct or array composed with the above allowed functions, for example, [CURRENT_DATE(), DATE '2020-01-01'] - "description": "A String", # [Optional] The field description. The maximum length is 1,024 characters. - "fields": [ # [Optional] Describes the nested schema fields if the type property is set to RECORD. - # Object with schema name: TableFieldSchema - ], - "maxLength": "A String", # [Optional] Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES". - "mode": "A String", # [Optional] The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE. - "name": "A String", # [Required] The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters. - "policyTags": { - "names": [ # A list of category resource names. For example, "projects/1/location/eu/taxonomies/2/policyTags/3". At most 1 policy tag is allowed. + "tableType": "A String", # [Table type](/bigquery/docs/reference/rest/v2/tables#Table.FIELDS.type). + "unusedReason": "A String", # Reason for not using metadata caching for the table. + }, + ], + }, + "mlStatistics": { # Job statistics specific to a BigQuery ML training job. # Output only. Statistics of a BigQuery ML training job. + "hparamTrials": [ # Output only. Trials of a [hyperparameter tuning job](/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview) sorted by trial_id. + { # Training info of a trial in [hyperparameter tuning](/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview) models. + "endTimeMs": "A String", # Ending time of the trial. + "errorMessage": "A String", # Error message for FAILED and INFEASIBLE trial. + "evalLoss": 3.14, # Loss computed on the eval data at the end of trial. + "evaluationMetrics": { # Evaluation metrics of a model. These are either computed on all training data or just the eval data based on whether eval data was used during training. These are not present for imported models. # Evaluation metrics of this trial calculated on the test data. Empty in Job API. + "arimaForecastingMetrics": { # Model evaluation metrics for ARIMA forecasting models. # Populated for ARIMA models. + "arimaFittingMetrics": [ # Arima model fitting metrics. + { # ARIMA model fitting metrics. + "aic": 3.14, # AIC. + "logLikelihood": 3.14, # Log-likelihood. + "variance": 3.14, # Variance. + }, + ], + "arimaSingleModelForecastingMetrics": [ # Repeated as there can be many metric sets (one for each model) in auto-arima and the large-scale case. + { # Model evaluation metrics for a single ARIMA forecasting model. + "arimaFittingMetrics": { # ARIMA model fitting metrics. # Arima fitting metrics. + "aic": 3.14, # AIC. + "logLikelihood": 3.14, # Log-likelihood. + "variance": 3.14, # Variance. + }, + "hasDrift": True or False, # Is arima model fitted with drift or not. It is always false when d is not 1. + "hasHolidayEffect": True or False, # If true, holiday_effect is a part of time series decomposition result. + "hasSpikesAndDips": True or False, # If true, spikes_and_dips is a part of time series decomposition result. + "hasStepChanges": True or False, # If true, step_changes is a part of time series decomposition result. + "nonSeasonalOrder": { # Arima order, can be used for both non-seasonal and seasonal parts. # Non-seasonal order. + "d": "A String", # Order of the differencing part. + "p": "A String", # Order of the autoregressive part. + "q": "A String", # Order of the moving-average part. + }, + "seasonalPeriods": [ # Seasonal periods. Repeated because multiple periods are supported for one time series. + "A String", + ], + "timeSeriesId": "A String", # The time_series_id value for this time series. It will be one of the unique values from the time_series_id_column specified during ARIMA model training. Only present when time_series_id_column training option was used. + "timeSeriesIds": [ # The tuple of time_series_ids identifying this time series. It will be one of the unique tuples of values present in the time_series_id_columns specified during ARIMA model training. Only present when time_series_id_columns training option was used and the order of values here are same as the order of time_series_id_columns. + "A String", + ], + }, + ], + "hasDrift": [ # Whether Arima model fitted with drift or not. It is always false when d is not 1. + True or False, + ], + "nonSeasonalOrder": [ # Non-seasonal order. + { # Arima order, can be used for both non-seasonal and seasonal parts. + "d": "A String", # Order of the differencing part. + "p": "A String", # Order of the autoregressive part. + "q": "A String", # Order of the moving-average part. + }, + ], + "seasonalPeriods": [ # Seasonal periods. Repeated because multiple periods are supported for one time series. + "A String", + ], + "timeSeriesId": [ # Id to differentiate different time series for the large-scale case. + "A String", + ], + }, + "binaryClassificationMetrics": { # Evaluation metrics for binary classification/classifier models. # Populated for binary classification/classifier models. + "aggregateClassificationMetrics": { # Aggregate metrics for classification/classifier models. For multi-class models, the metrics are either macro-averaged or micro-averaged. When macro-averaged, the metrics are calculated for each label and then an unweighted average is taken of those values. When micro-averaged, the metric is calculated globally by counting the total number of correctly predicted rows. # Aggregate classification metrics. + "accuracy": 3.14, # Accuracy is the fraction of predictions given the correct label. For multiclass this is a micro-averaged metric. + "f1Score": 3.14, # The F1 score is an average of recall and precision. For multiclass this is a macro-averaged metric. + "logLoss": 3.14, # Logarithmic Loss. For multiclass this is a macro-averaged metric. + "precision": 3.14, # Precision is the fraction of actual positive predictions that had positive actual labels. For multiclass this is a macro-averaged metric treating each class as a binary classifier. + "recall": 3.14, # Recall is the fraction of actual positive labels that were given a positive prediction. For multiclass this is a macro-averaged metric. + "rocAuc": 3.14, # Area Under a ROC Curve. For multiclass this is a macro-averaged metric. + "threshold": 3.14, # Threshold at which the metrics are computed. For binary classification models this is the positive class threshold. For multi-class classfication models this is the confidence threshold. + }, + "binaryConfusionMatrixList": [ # Binary confusion matrix at multiple thresholds. + { # Confusion matrix for binary classification models. + "accuracy": 3.14, # The fraction of predictions given the correct label. + "f1Score": 3.14, # The equally weighted average of recall and precision. + "falseNegatives": "A String", # Number of false samples predicted as false. + "falsePositives": "A String", # Number of false samples predicted as true. + "positiveClassThreshold": 3.14, # Threshold value used when computing each of the following metric. + "precision": 3.14, # The fraction of actual positive predictions that had positive actual labels. + "recall": 3.14, # The fraction of actual positive labels that were given a positive prediction. + "trueNegatives": "A String", # Number of true samples predicted as false. + "truePositives": "A String", # Number of true samples predicted as true. + }, + ], + "negativeLabel": "A String", # Label representing the negative class. + "positiveLabel": "A String", # Label representing the positive class. + }, + "clusteringMetrics": { # Evaluation metrics for clustering models. # Populated for clustering models. + "clusters": [ # Information for all clusters. + { # Message containing the information about one cluster. + "centroidId": "A String", # Centroid id. + "count": "A String", # Count of training data rows that were assigned to this cluster. + "featureValues": [ # Values of highly variant features for this cluster. + { # Representative value of a single feature within the cluster. + "categoricalValue": { # Representative value of a categorical feature. # The categorical feature value. + "categoryCounts": [ # Counts of all categories for the categorical feature. If there are more than ten categories, we return top ten (by count) and return one more CategoryCount with category "_OTHER_" and count as aggregate counts of remaining categories. + { # Represents the count of a single category within the cluster. + "category": "A String", # The name of category. + "count": "A String", # The count of training samples matching the category within the cluster. + }, + ], + }, + "featureColumn": "A String", # The feature column name. + "numericalValue": 3.14, # The numerical feature value. This is the centroid value for this feature. + }, + ], + }, + ], + "daviesBouldinIndex": 3.14, # Davies-Bouldin index. + "meanSquaredDistance": 3.14, # Mean of squared distances between each sample to its cluster centroid. + }, + "dimensionalityReductionMetrics": { # Model evaluation metrics for dimensionality reduction models. # Evaluation metrics when the model is a dimensionality reduction model, which currently includes PCA. + "totalExplainedVarianceRatio": 3.14, # Total percentage of variance explained by the selected principal components. + }, + "multiClassClassificationMetrics": { # Evaluation metrics for multi-class classification/classifier models. # Populated for multi-class classification/classifier models. + "aggregateClassificationMetrics": { # Aggregate metrics for classification/classifier models. For multi-class models, the metrics are either macro-averaged or micro-averaged. When macro-averaged, the metrics are calculated for each label and then an unweighted average is taken of those values. When micro-averaged, the metric is calculated globally by counting the total number of correctly predicted rows. # Aggregate classification metrics. + "accuracy": 3.14, # Accuracy is the fraction of predictions given the correct label. For multiclass this is a micro-averaged metric. + "f1Score": 3.14, # The F1 score is an average of recall and precision. For multiclass this is a macro-averaged metric. + "logLoss": 3.14, # Logarithmic Loss. For multiclass this is a macro-averaged metric. + "precision": 3.14, # Precision is the fraction of actual positive predictions that had positive actual labels. For multiclass this is a macro-averaged metric treating each class as a binary classifier. + "recall": 3.14, # Recall is the fraction of actual positive labels that were given a positive prediction. For multiclass this is a macro-averaged metric. + "rocAuc": 3.14, # Area Under a ROC Curve. For multiclass this is a macro-averaged metric. + "threshold": 3.14, # Threshold at which the metrics are computed. For binary classification models this is the positive class threshold. For multi-class classfication models this is the confidence threshold. + }, + "confusionMatrixList": [ # Confusion matrix at different thresholds. + { # Confusion matrix for multi-class classification models. + "confidenceThreshold": 3.14, # Confidence threshold used when computing the entries of the confusion matrix. + "rows": [ # One row per actual label. + { # A single row in the confusion matrix. + "actualLabel": "A String", # The original label of this row. + "entries": [ # Info describing predicted label distribution. + { # A single entry in the confusion matrix. + "itemCount": "A String", # Number of items being predicted as this label. + "predictedLabel": "A String", # The predicted label. For confidence_threshold > 0, we will also add an entry indicating the number of items under the confidence threshold. + }, + ], + }, + ], + }, + ], + }, + "rankingMetrics": { # Evaluation metrics used by weighted-ALS models specified by feedback_type=implicit. # Populated for implicit feedback type matrix factorization models. + "averageRank": 3.14, # Determines the goodness of a ranking by computing the percentile rank from the predicted confidence and dividing it by the original rank. + "meanAveragePrecision": 3.14, # Calculates a precision per user for all the items by ranking them and then averages all the precisions across all the users. + "meanSquaredError": 3.14, # Similar to the mean squared error computed in regression and explicit recommendation models except instead of computing the rating directly, the output from evaluate is computed against a preference which is 1 or 0 depending on if the rating exists or not. + "normalizedDiscountedCumulativeGain": 3.14, # A metric to determine the goodness of a ranking calculated from the predicted confidence by comparing it to an ideal rank measured by the original ratings. + }, + "regressionMetrics": { # Evaluation metrics for regression and explicit feedback type matrix factorization models. # Populated for regression models and explicit feedback type matrix factorization models. + "meanAbsoluteError": 3.14, # Mean absolute error. + "meanSquaredError": 3.14, # Mean squared error. + "meanSquaredLogError": 3.14, # Mean squared log error. + "medianAbsoluteError": 3.14, # Median absolute error. + "rSquared": 3.14, # R^2 score. This corresponds to r2_score in ML.EVALUATE. + }, + }, + "hparamTuningEvaluationMetrics": { # Evaluation metrics of a model. These are either computed on all training data or just the eval data based on whether eval data was used during training. These are not present for imported models. # Hyperparameter tuning evaluation metrics of this trial calculated on the eval data. Unlike evaluation_metrics, only the fields corresponding to the hparam_tuning_objectives are set. + "arimaForecastingMetrics": { # Model evaluation metrics for ARIMA forecasting models. # Populated for ARIMA models. + "arimaFittingMetrics": [ # Arima model fitting metrics. + { # ARIMA model fitting metrics. + "aic": 3.14, # AIC. + "logLikelihood": 3.14, # Log-likelihood. + "variance": 3.14, # Variance. + }, + ], + "arimaSingleModelForecastingMetrics": [ # Repeated as there can be many metric sets (one for each model) in auto-arima and the large-scale case. + { # Model evaluation metrics for a single ARIMA forecasting model. + "arimaFittingMetrics": { # ARIMA model fitting metrics. # Arima fitting metrics. + "aic": 3.14, # AIC. + "logLikelihood": 3.14, # Log-likelihood. + "variance": 3.14, # Variance. + }, + "hasDrift": True or False, # Is arima model fitted with drift or not. It is always false when d is not 1. + "hasHolidayEffect": True or False, # If true, holiday_effect is a part of time series decomposition result. + "hasSpikesAndDips": True or False, # If true, spikes_and_dips is a part of time series decomposition result. + "hasStepChanges": True or False, # If true, step_changes is a part of time series decomposition result. + "nonSeasonalOrder": { # Arima order, can be used for both non-seasonal and seasonal parts. # Non-seasonal order. + "d": "A String", # Order of the differencing part. + "p": "A String", # Order of the autoregressive part. + "q": "A String", # Order of the moving-average part. + }, + "seasonalPeriods": [ # Seasonal periods. Repeated because multiple periods are supported for one time series. + "A String", + ], + "timeSeriesId": "A String", # The time_series_id value for this time series. It will be one of the unique values from the time_series_id_column specified during ARIMA model training. Only present when time_series_id_column training option was used. + "timeSeriesIds": [ # The tuple of time_series_ids identifying this time series. It will be one of the unique tuples of values present in the time_series_id_columns specified during ARIMA model training. Only present when time_series_id_columns training option was used and the order of values here are same as the order of time_series_id_columns. + "A String", + ], + }, + ], + "hasDrift": [ # Whether Arima model fitted with drift or not. It is always false when d is not 1. + True or False, + ], + "nonSeasonalOrder": [ # Non-seasonal order. + { # Arima order, can be used for both non-seasonal and seasonal parts. + "d": "A String", # Order of the differencing part. + "p": "A String", # Order of the autoregressive part. + "q": "A String", # Order of the moving-average part. + }, + ], + "seasonalPeriods": [ # Seasonal periods. Repeated because multiple periods are supported for one time series. + "A String", + ], + "timeSeriesId": [ # Id to differentiate different time series for the large-scale case. + "A String", + ], + }, + "binaryClassificationMetrics": { # Evaluation metrics for binary classification/classifier models. # Populated for binary classification/classifier models. + "aggregateClassificationMetrics": { # Aggregate metrics for classification/classifier models. For multi-class models, the metrics are either macro-averaged or micro-averaged. When macro-averaged, the metrics are calculated for each label and then an unweighted average is taken of those values. When micro-averaged, the metric is calculated globally by counting the total number of correctly predicted rows. # Aggregate classification metrics. + "accuracy": 3.14, # Accuracy is the fraction of predictions given the correct label. For multiclass this is a micro-averaged metric. + "f1Score": 3.14, # The F1 score is an average of recall and precision. For multiclass this is a macro-averaged metric. + "logLoss": 3.14, # Logarithmic Loss. For multiclass this is a macro-averaged metric. + "precision": 3.14, # Precision is the fraction of actual positive predictions that had positive actual labels. For multiclass this is a macro-averaged metric treating each class as a binary classifier. + "recall": 3.14, # Recall is the fraction of actual positive labels that were given a positive prediction. For multiclass this is a macro-averaged metric. + "rocAuc": 3.14, # Area Under a ROC Curve. For multiclass this is a macro-averaged metric. + "threshold": 3.14, # Threshold at which the metrics are computed. For binary classification models this is the positive class threshold. For multi-class classfication models this is the confidence threshold. + }, + "binaryConfusionMatrixList": [ # Binary confusion matrix at multiple thresholds. + { # Confusion matrix for binary classification models. + "accuracy": 3.14, # The fraction of predictions given the correct label. + "f1Score": 3.14, # The equally weighted average of recall and precision. + "falseNegatives": "A String", # Number of false samples predicted as false. + "falsePositives": "A String", # Number of false samples predicted as true. + "positiveClassThreshold": 3.14, # Threshold value used when computing each of the following metric. + "precision": 3.14, # The fraction of actual positive predictions that had positive actual labels. + "recall": 3.14, # The fraction of actual positive labels that were given a positive prediction. + "trueNegatives": "A String", # Number of true samples predicted as false. + "truePositives": "A String", # Number of true samples predicted as true. + }, + ], + "negativeLabel": "A String", # Label representing the negative class. + "positiveLabel": "A String", # Label representing the positive class. + }, + "clusteringMetrics": { # Evaluation metrics for clustering models. # Populated for clustering models. + "clusters": [ # Information for all clusters. + { # Message containing the information about one cluster. + "centroidId": "A String", # Centroid id. + "count": "A String", # Count of training data rows that were assigned to this cluster. + "featureValues": [ # Values of highly variant features for this cluster. + { # Representative value of a single feature within the cluster. + "categoricalValue": { # Representative value of a categorical feature. # The categorical feature value. + "categoryCounts": [ # Counts of all categories for the categorical feature. If there are more than ten categories, we return top ten (by count) and return one more CategoryCount with category "_OTHER_" and count as aggregate counts of remaining categories. + { # Represents the count of a single category within the cluster. + "category": "A String", # The name of category. + "count": "A String", # The count of training samples matching the category within the cluster. + }, + ], + }, + "featureColumn": "A String", # The feature column name. + "numericalValue": 3.14, # The numerical feature value. This is the centroid value for this feature. + }, + ], + }, + ], + "daviesBouldinIndex": 3.14, # Davies-Bouldin index. + "meanSquaredDistance": 3.14, # Mean of squared distances between each sample to its cluster centroid. + }, + "dimensionalityReductionMetrics": { # Model evaluation metrics for dimensionality reduction models. # Evaluation metrics when the model is a dimensionality reduction model, which currently includes PCA. + "totalExplainedVarianceRatio": 3.14, # Total percentage of variance explained by the selected principal components. + }, + "multiClassClassificationMetrics": { # Evaluation metrics for multi-class classification/classifier models. # Populated for multi-class classification/classifier models. + "aggregateClassificationMetrics": { # Aggregate metrics for classification/classifier models. For multi-class models, the metrics are either macro-averaged or micro-averaged. When macro-averaged, the metrics are calculated for each label and then an unweighted average is taken of those values. When micro-averaged, the metric is calculated globally by counting the total number of correctly predicted rows. # Aggregate classification metrics. + "accuracy": 3.14, # Accuracy is the fraction of predictions given the correct label. For multiclass this is a micro-averaged metric. + "f1Score": 3.14, # The F1 score is an average of recall and precision. For multiclass this is a macro-averaged metric. + "logLoss": 3.14, # Logarithmic Loss. For multiclass this is a macro-averaged metric. + "precision": 3.14, # Precision is the fraction of actual positive predictions that had positive actual labels. For multiclass this is a macro-averaged metric treating each class as a binary classifier. + "recall": 3.14, # Recall is the fraction of actual positive labels that were given a positive prediction. For multiclass this is a macro-averaged metric. + "rocAuc": 3.14, # Area Under a ROC Curve. For multiclass this is a macro-averaged metric. + "threshold": 3.14, # Threshold at which the metrics are computed. For binary classification models this is the positive class threshold. For multi-class classfication models this is the confidence threshold. + }, + "confusionMatrixList": [ # Confusion matrix at different thresholds. + { # Confusion matrix for multi-class classification models. + "confidenceThreshold": 3.14, # Confidence threshold used when computing the entries of the confusion matrix. + "rows": [ # One row per actual label. + { # A single row in the confusion matrix. + "actualLabel": "A String", # The original label of this row. + "entries": [ # Info describing predicted label distribution. + { # A single entry in the confusion matrix. + "itemCount": "A String", # Number of items being predicted as this label. + "predictedLabel": "A String", # The predicted label. For confidence_threshold > 0, we will also add an entry indicating the number of items under the confidence threshold. + }, + ], + }, + ], + }, + ], + }, + "rankingMetrics": { # Evaluation metrics used by weighted-ALS models specified by feedback_type=implicit. # Populated for implicit feedback type matrix factorization models. + "averageRank": 3.14, # Determines the goodness of a ranking by computing the percentile rank from the predicted confidence and dividing it by the original rank. + "meanAveragePrecision": 3.14, # Calculates a precision per user for all the items by ranking them and then averages all the precisions across all the users. + "meanSquaredError": 3.14, # Similar to the mean squared error computed in regression and explicit recommendation models except instead of computing the rating directly, the output from evaluate is computed against a preference which is 1 or 0 depending on if the rating exists or not. + "normalizedDiscountedCumulativeGain": 3.14, # A metric to determine the goodness of a ranking calculated from the predicted confidence by comparing it to an ideal rank measured by the original ratings. + }, + "regressionMetrics": { # Evaluation metrics for regression and explicit feedback type matrix factorization models. # Populated for regression models and explicit feedback type matrix factorization models. + "meanAbsoluteError": 3.14, # Mean absolute error. + "meanSquaredError": 3.14, # Mean squared error. + "meanSquaredLogError": 3.14, # Mean squared log error. + "medianAbsoluteError": 3.14, # Median absolute error. + "rSquared": 3.14, # R^2 score. This corresponds to r2_score in ML.EVALUATE. + }, + }, + "hparams": { # Options used in model training. # The hyperprameters selected for this trial. + "activationFn": "A String", # Activation function of the neural nets. + "adjustStepChanges": True or False, # If true, detect step changes and make data adjustment in the input time series. + "approxGlobalFeatureContrib": True or False, # Whether to use approximate feature contribution method in XGBoost model explanation for global explain. + "autoArima": True or False, # Whether to enable auto ARIMA or not. + "autoArimaMaxOrder": "A String", # The max value of the sum of non-seasonal p and q. + "autoArimaMinOrder": "A String", # The min value of the sum of non-seasonal p and q. + "autoClassWeights": True or False, # Whether to calculate class weights automatically based on the popularity of each label. + "batchSize": "A String", # Batch size for dnn models. + "boosterType": "A String", # Booster type for boosted tree models. + "budgetHours": 3.14, # Budget in hours for AutoML training. + "calculatePValues": True or False, # Whether or not p-value test should be computed for this model. Only available for linear and logistic regression models. + "categoryEncodingMethod": "A String", # Categorical feature encoding method. + "cleanSpikesAndDips": True or False, # If true, clean spikes and dips in the input time series. + "colorSpace": "A String", # Enums for color space, used for processing images in Object Table. See more details at https://www.tensorflow.org/io/tutorials/colorspace. + "colsampleBylevel": 3.14, # Subsample ratio of columns for each level for boosted tree models. + "colsampleBynode": 3.14, # Subsample ratio of columns for each node(split) for boosted tree models. + "colsampleBytree": 3.14, # Subsample ratio of columns when constructing each tree for boosted tree models. + "dartNormalizeType": "A String", # Type of normalization algorithm for boosted tree models using dart booster. + "dataFrequency": "A String", # The data frequency of a time series. + "dataSplitColumn": "A String", # The column to split data with. This column won't be used as a feature. 1. When data_split_method is CUSTOM, the corresponding column should be boolean. The rows with true value tag are eval data, and the false are training data. 2. When data_split_method is SEQ, the first DATA_SPLIT_EVAL_FRACTION rows (from smallest to largest) in the corresponding column are used as training data, and the rest are eval data. It respects the order in Orderable data types: https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types#data-type-properties + "dataSplitEvalFraction": 3.14, # The fraction of evaluation data over the whole input data. The rest of data will be used as training data. The format should be double. Accurate to two decimal places. Default value is 0.2. + "dataSplitMethod": "A String", # The data split type for training and evaluation, e.g. RANDOM. + "decomposeTimeSeries": True or False, # If true, perform decompose time series and save the results. + "distanceType": "A String", # Distance type for clustering models. + "dropout": 3.14, # Dropout probability for dnn models. + "earlyStop": True or False, # Whether to stop early when the loss doesn't improve significantly any more (compared to min_relative_progress). Used only for iterative training algorithms. + "enableGlobalExplain": True or False, # If true, enable global explanation during training. + "feedbackType": "A String", # Feedback type that specifies which algorithm to run for matrix factorization. + "fitIntercept": True or False, # Whether the model should include intercept during model training. + "hiddenUnits": [ # Hidden units for dnn models. + "A String", + ], + "holidayRegion": "A String", # The geographical region based on which the holidays are considered in time series modeling. If a valid value is specified, then holiday effects modeling is enabled. + "holidayRegions": [ # A list of geographical regions that are used for time series modeling. + "A String", + ], + "horizon": "A String", # The number of periods ahead that need to be forecasted. + "hparamTuningObjectives": [ # The target evaluation metrics to optimize the hyperparameters for. + "A String", + ], + "includeDrift": True or False, # Include drift when fitting an ARIMA model. + "initialLearnRate": 3.14, # Specifies the initial learning rate for the line search learn rate strategy. + "inputLabelColumns": [ # Name of input label columns in training data. "A String", ], + "instanceWeightColumn": "A String", # Name of the instance weight column for training data. This column isn't be used as a feature. + "integratedGradientsNumSteps": "A String", # Number of integral steps for the integrated gradients explain method. + "itemColumn": "A String", # Item column specified for matrix factorization models. + "kmeansInitializationColumn": "A String", # The column used to provide the initial centroids for kmeans algorithm when kmeans_initialization_method is CUSTOM. + "kmeansInitializationMethod": "A String", # The method used to initialize the centroids for kmeans algorithm. + "l1RegActivation": 3.14, # L1 regularization coefficient to activations. + "l1Regularization": 3.14, # L1 regularization coefficient. + "l2Regularization": 3.14, # L2 regularization coefficient. + "labelClassWeights": { # Weights associated with each label class, for rebalancing the training data. Only applicable for classification models. + "a_key": 3.14, + }, + "learnRate": 3.14, # Learning rate in training. Used only for iterative training algorithms. + "learnRateStrategy": "A String", # The strategy to determine learn rate for the current iteration. + "lossType": "A String", # Type of loss function used during training run. + "maxIterations": "A String", # The maximum number of iterations in training. Used only for iterative training algorithms. + "maxParallelTrials": "A String", # Maximum number of trials to run in parallel. + "maxTimeSeriesLength": "A String", # The maximum number of time points in a time series that can be used in modeling the trend component of the time series. Don't use this option with the `timeSeriesLengthFraction` or `minTimeSeriesLength` options. + "maxTreeDepth": "A String", # Maximum depth of a tree for boosted tree models. + "minRelativeProgress": 3.14, # When early_stop is true, stops training when accuracy improvement is less than 'min_relative_progress'. Used only for iterative training algorithms. + "minSplitLoss": 3.14, # Minimum split loss for boosted tree models. + "minTimeSeriesLength": "A String", # The minimum number of time points in a time series that are used in modeling the trend component of the time series. If you use this option you must also set the `timeSeriesLengthFraction` option. This training option ensures that enough time points are available when you use `timeSeriesLengthFraction` in trend modeling. This is particularly important when forecasting multiple time series in a single query using `timeSeriesIdColumn`. If the total number of time points is less than the `minTimeSeriesLength` value, then the query uses all available time points. + "minTreeChildWeight": "A String", # Minimum sum of instance weight needed in a child for boosted tree models. + "modelRegistry": "A String", # The model registry. + "modelUri": "A String", # Google Cloud Storage URI from which the model was imported. Only applicable for imported models. + "nonSeasonalOrder": { # Arima order, can be used for both non-seasonal and seasonal parts. # A specification of the non-seasonal part of the ARIMA model: the three components (p, d, q) are the AR order, the degree of differencing, and the MA order. + "d": "A String", # Order of the differencing part. + "p": "A String", # Order of the autoregressive part. + "q": "A String", # Order of the moving-average part. + }, + "numClusters": "A String", # Number of clusters for clustering models. + "numFactors": "A String", # Num factors specified for matrix factorization models. + "numParallelTree": "A String", # Number of parallel trees constructed during each iteration for boosted tree models. + "numPrincipalComponents": "A String", # Number of principal components to keep in the PCA model. Must be <= the number of features. + "numTrials": "A String", # Number of trials to run this hyperparameter tuning job. + "optimizationStrategy": "A String", # Optimization strategy for training linear regression models. + "optimizer": "A String", # Optimizer used for training the neural nets. + "pcaExplainedVarianceRatio": 3.14, # The minimum ratio of cumulative explained variance that needs to be given by the PCA model. + "pcaSolver": "A String", # The solver for PCA. + "sampledShapleyNumPaths": "A String", # Number of paths for the sampled Shapley explain method. + "scaleFeatures": True or False, # If true, scale the feature values by dividing the feature standard deviation. Currently only apply to PCA. + "standardizeFeatures": True or False, # Whether to standardize numerical features. Default to true. + "subsample": 3.14, # Subsample fraction of the training data to grow tree to prevent overfitting for boosted tree models. + "tfVersion": "A String", # Based on the selected TF version, the corresponding docker image is used to train external models. + "timeSeriesDataColumn": "A String", # Column to be designated as time series data for ARIMA model. + "timeSeriesIdColumn": "A String", # The time series id column that was used during ARIMA model training. + "timeSeriesIdColumns": [ # The time series id columns that were used during ARIMA model training. + "A String", + ], + "timeSeriesLengthFraction": 3.14, # The fraction of the interpolated length of the time series that's used to model the time series trend component. All of the time points of the time series are used to model the non-trend component. This training option accelerates modeling training without sacrificing much forecasting accuracy. You can use this option with `minTimeSeriesLength` but not with `maxTimeSeriesLength`. + "timeSeriesTimestampColumn": "A String", # Column to be designated as time series timestamp for ARIMA model. + "treeMethod": "A String", # Tree construction algorithm for boosted tree models. + "trendSmoothingWindowSize": "A String", # Smoothing window size for the trend component. When a positive value is specified, a center moving average smoothing is applied on the history trend. When the smoothing window is out of the boundary at the beginning or the end of the trend, the first element or the last element is padded to fill the smoothing window before the average is applied. + "userColumn": "A String", # User column specified for matrix factorization models. + "vertexAiModelVersionAliases": [ # The version aliases to apply in Vertex AI model registry. Always overwrite if the version aliases exists in a existing model. + "A String", + ], + "walsAlpha": 3.14, # Hyperparameter for matrix factoration when implicit feedback type is specified. + "warmStart": True or False, # Whether to train a model from the last checkpoint. + "xgboostVersion": "A String", # User-selected XGBoost versions for training of XGBoost models. }, - "precision": "A String", # [Optional] Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: - Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] - Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: - If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. - If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): - If type = "NUMERIC": 1 ≤ precision ≤ 29. - If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid. - "rangeElementType": { # Optional. The subtype of the RANGE, if the type of this field is RANGE. If the type is RANGE, this field is required. Possible values for the field element type of a RANGE include: - DATE - DATETIME - TIMESTAMP - "type": "A String", # The field element type of a RANGE + "startTimeMs": "A String", # Starting time of the trial. + "status": "A String", # The status of the trial. + "trainingLoss": 3.14, # Loss computed on the training data at the end of trial. + "trialId": "A String", # 1-based index of the trial. + }, + ], + "iterationResults": [ # Results for all completed iterations. Empty for [hyperparameter tuning jobs](/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview). + { # Information about a single iteration of the training run. + "arimaResult": { # (Auto-)arima fitting result. Wrap everything in ArimaResult for easier refactoring if we want to use model-specific iteration results. # Arima result. + "arimaModelInfo": [ # This message is repeated because there are multiple arima models fitted in auto-arima. For non-auto-arima model, its size is one. + { # Arima model information. + "arimaCoefficients": { # Arima coefficients. # Arima coefficients. + "autoRegressiveCoefficients": [ # Auto-regressive coefficients, an array of double. + 3.14, + ], + "interceptCoefficient": 3.14, # Intercept coefficient, just a double not an array. + "movingAverageCoefficients": [ # Moving-average coefficients, an array of double. + 3.14, + ], + }, + "arimaFittingMetrics": { # ARIMA model fitting metrics. # Arima fitting metrics. + "aic": 3.14, # AIC. + "logLikelihood": 3.14, # Log-likelihood. + "variance": 3.14, # Variance. + }, + "hasDrift": True or False, # Whether Arima model fitted with drift or not. It is always false when d is not 1. + "hasHolidayEffect": True or False, # If true, holiday_effect is a part of time series decomposition result. + "hasSpikesAndDips": True or False, # If true, spikes_and_dips is a part of time series decomposition result. + "hasStepChanges": True or False, # If true, step_changes is a part of time series decomposition result. + "nonSeasonalOrder": { # Arima order, can be used for both non-seasonal and seasonal parts. # Non-seasonal order. + "d": "A String", # Order of the differencing part. + "p": "A String", # Order of the autoregressive part. + "q": "A String", # Order of the moving-average part. + }, + "seasonalPeriods": [ # Seasonal periods. Repeated because multiple periods are supported for one time series. + "A String", + ], + "timeSeriesId": "A String", # The time_series_id value for this time series. It will be one of the unique values from the time_series_id_column specified during ARIMA model training. Only present when time_series_id_column training option was used. + "timeSeriesIds": [ # The tuple of time_series_ids identifying this time series. It will be one of the unique tuples of values present in the time_series_id_columns specified during ARIMA model training. Only present when time_series_id_columns training option was used and the order of values here are same as the order of time_series_id_columns. + "A String", + ], + }, + ], + "seasonalPeriods": [ # Seasonal periods. Repeated because multiple periods are supported for one time series. + "A String", + ], + }, + "clusterInfos": [ # Information about top clusters for clustering models. + { # Information about a single cluster for clustering model. + "centroidId": "A String", # Centroid id. + "clusterRadius": 3.14, # Cluster radius, the average distance from centroid to each point assigned to the cluster. + "clusterSize": "A String", # Cluster size, the total number of points assigned to the cluster. + }, + ], + "durationMs": "A String", # Time taken to run the iteration in milliseconds. + "evalLoss": 3.14, # Loss computed on the eval data at the end of iteration. + "index": 42, # Index of the iteration, 0 based. + "learnRate": 3.14, # Learn rate used for this iteration. + "principalComponentInfos": [ # The information of the principal components. + { # Principal component infos, used only for eigen decomposition based models, e.g., PCA. Ordered by explained_variance in the descending order. + "cumulativeExplainedVarianceRatio": 3.14, # The explained_variance is pre-ordered in the descending order to compute the cumulative explained variance ratio. + "explainedVariance": 3.14, # Explained variance by this principal component, which is simply the eigenvalue. + "explainedVarianceRatio": 3.14, # Explained_variance over the total explained variance. + "principalComponentId": "A String", # Id of the principal component. + }, + ], + "trainingLoss": 3.14, # Loss computed on the training data at the end of iteration. + }, + ], + "maxIterations": "A String", # Output only. Maximum number of iterations specified as max_iterations in the 'CREATE MODEL' query. The actual number of iterations may be less than this number due to early stop. + "modelType": "A String", # Output only. The type of the model that is being trained. + "trainingType": "A String", # Output only. Training type of the job. + }, + "modelTraining": { # Deprecated. + "currentIteration": 42, # Deprecated. + "expectedTotalIterations": "A String", # Deprecated. + }, + "modelTrainingCurrentIteration": 42, # Deprecated. + "modelTrainingExpectedTotalIteration": "A String", # Deprecated. + "numDmlAffectedRows": "A String", # Output only. The number of rows affected by a DML statement. Present only for DML statements INSERT, UPDATE or DELETE. + "performanceInsights": { # Performance insights for the job. # Output only. Performance insights. + "avgPreviousExecutionMs": "A String", # Output only. Average execution ms of previous runs. Indicates the job ran slow compared to previous executions. To find previous executions, use INFORMATION_SCHEMA tables and filter jobs with same query hash. + "stagePerformanceChangeInsights": [ # Output only. Query stage performance insights compared to previous runs, for diagnosing performance regression. + { # Performance insights compared to the previous executions for a specific stage. + "inputDataChange": { # Details about the input data change insight. # Output only. Input data change insight of the query stage. + "recordsReadDiffPercentage": 3.14, # Output only. Records read difference percentage compared to a previous run. }, - "roundingMode": "A String", # Optional. Rounding Mode specification of the field. It only can be set on NUMERIC or BIGNUMERIC type fields. - "scale": "A String", # [Optional] See documentation for precision. - "type": "A String", # [Required] The field data type. Possible values include STRING, BYTES, INTEGER, INT64 (same as INTEGER), FLOAT, FLOAT64 (same as FLOAT), NUMERIC, BIGNUMERIC, BOOLEAN, BOOL (same as BOOLEAN), TIMESTAMP, DATE, TIME, DATETIME, INTERVAL, RECORD (where RECORD indicates that the field contains a nested schema) or STRUCT (same as RECORD). + "stageId": "A String", # Output only. The stage id that the insight mapped to. + }, + ], + "stagePerformanceStandaloneInsights": [ # Output only. Standalone query stage performance insights, for exploring potential improvements. + { # Standalone performance insights for a specific stage. + "biEngineReasons": [ # Output only. If present, the stage had the following reasons for being disqualified from BI Engine execution. + { # Reason why BI Engine didn't accelerate the query (or sub-query). + "code": "A String", # Output only. High-level BI Engine reason for partial or disabled acceleration + "message": "A String", # Output only. Free form human-readable reason for partial or disabled acceleration. + }, + ], + "highCardinalityJoins": [ # Output only. High cardinality joins in the stage. + { # High cardinality join detailed information. + "leftRows": "A String", # Output only. Count of left input rows. + "outputRows": "A String", # Output only. Count of the output rows. + "rightRows": "A String", # Output only. Count of right input rows. + "stepIndex": 42, # Output only. The index of the join operator in the ExplainQueryStep lists. + }, + ], + "insufficientShuffleQuota": True or False, # Output only. True if the stage has insufficient shuffle quota. + "slotContention": True or False, # Output only. True if the stage has a slot contention issue. + "stageId": "A String", # Output only. The stage id that the insight mapped to. }, ], }, - "searchStatistics": { # [Output only] Search query specific statistics. - "indexUnusedReasons": [ # When index_usage_mode is UNUSED or PARTIALLY_USED, this field explains why index was not used in all or part of the search query. If index_usage_mode is FULLLY_USED, this field is not populated. - { - "baseTable": { # [Output-only] Specifies the base table involved in the reason that no search index was used. - "datasetId": "A String", # [Required] The ID of the dataset containing this table. - "projectId": "A String", # [Required] The ID of the project containing this table. - "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. + "queryInfo": { # Query optimization information for a QUERY job. # Output only. Query optimization information for a QUERY job. + "optimizationDetails": { # Output only. Information about query optimizations. + "a_key": "", # Properties of the object. + }, + }, + "queryPlan": [ # Output only. Describes execution plan for the query. + { # A single stage of query execution. + "completedParallelInputs": "A String", # Number of parallel input segments completed. + "computeMode": "A String", # Output only. Compute mode for this stage. + "computeMsAvg": "A String", # Milliseconds the average shard spent on CPU-bound tasks. + "computeMsMax": "A String", # Milliseconds the slowest shard spent on CPU-bound tasks. + "computeRatioAvg": 3.14, # Relative amount of time the average shard spent on CPU-bound tasks. + "computeRatioMax": 3.14, # Relative amount of time the slowest shard spent on CPU-bound tasks. + "endMs": "A String", # Stage end time represented as milliseconds since the epoch. + "id": "A String", # Unique ID for the stage within the plan. + "inputStages": [ # IDs for stages that are inputs to this stage. + "A String", + ], + "name": "A String", # Human-readable name for the stage. + "parallelInputs": "A String", # Number of parallel input segments to be processed + "readMsAvg": "A String", # Milliseconds the average shard spent reading input. + "readMsMax": "A String", # Milliseconds the slowest shard spent reading input. + "readRatioAvg": 3.14, # Relative amount of time the average shard spent reading input. + "readRatioMax": 3.14, # Relative amount of time the slowest shard spent reading input. + "recordsRead": "A String", # Number of records read into the stage. + "recordsWritten": "A String", # Number of records written by the stage. + "shuffleOutputBytes": "A String", # Total number of bytes written to shuffle. + "shuffleOutputBytesSpilled": "A String", # Total number of bytes written to shuffle and spilled to disk. + "slotMs": "A String", # Slot-milliseconds used by the stage. + "startMs": "A String", # Stage start time represented as milliseconds since the epoch. + "status": "A String", # Current status for this stage. + "steps": [ # List of operations within the stage in dependency order (approximately chronological). + { # An operation within a stage. + "kind": "A String", # Machine-readable operation type. + "substeps": [ # Human-readable description of the step(s). + "A String", + ], + }, + ], + "waitMsAvg": "A String", # Milliseconds the average shard spent waiting to be scheduled. + "waitMsMax": "A String", # Milliseconds the slowest shard spent waiting to be scheduled. + "waitRatioAvg": 3.14, # Relative amount of time the average shard spent waiting to be scheduled. + "waitRatioMax": 3.14, # Relative amount of time the slowest shard spent waiting to be scheduled. + "writeMsAvg": "A String", # Milliseconds the average shard spent on writing output. + "writeMsMax": "A String", # Milliseconds the slowest shard spent on writing output. + "writeRatioAvg": 3.14, # Relative amount of time the average shard spent on writing output. + "writeRatioMax": 3.14, # Relative amount of time the slowest shard spent on writing output. + }, + ], + "referencedRoutines": [ # Output only. Referenced routines for the job. + { # Id path of a routine. + "datasetId": "A String", # Required. The ID of the dataset containing this routine. + "projectId": "A String", # Required. The ID of the project containing this routine. + "routineId": "A String", # Required. The ID of the routine. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 256 characters. + }, + ], + "referencedTables": [ # Output only. Referenced tables for the job. Queries that reference more than 50 tables will not have a complete list. + { + "datasetId": "A String", # Required. The ID of the dataset containing this table. + "projectId": "A String", # Required. The ID of the project containing this table. + "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`. + }, + ], + "reservationUsage": [ # Output only. Job resource usage breakdown by reservation. This field reported misleading information and will no longer be populated. + { # Job resource usage breakdown by reservation. + "name": "A String", # Reservation name or "unreserved" for on-demand resources usage. + "slotMs": "A String", # Total slot milliseconds used by the reservation for a particular job. + }, + ], + "schema": { # Schema of a table # Output only. The schema of the results. Present only for successful dry run of non-legacy SQL queries. + "fields": [ # Describes the fields in a table. + { # A field in TableSchema + "categories": { # Deprecated. + "names": [ # Deprecated. + "A String", + ], + }, + "collation": "A String", # Optional. Field collation can be set only when the type of field is STRING. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior. + "defaultValueExpression": "A String", # Optional. A SQL expression to specify the [default value] (https://cloud.google.com/bigquery/docs/default-values) for this field. + "description": "A String", # Optional. The field description. The maximum length is 1,024 characters. + "fields": [ # Optional. Describes the nested schema fields if the type property is set to RECORD. + # Object with schema name: TableFieldSchema + ], + "maxLength": "A String", # Optional. Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES". + "mode": "A String", # Optional. The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE. + "name": "A String", # Required. The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters. + "policyTags": { # Optional. The policy tags attached to this field, used for field-level access control. If not set, defaults to empty policy_tags. + "names": [ # A list of policy tag resource names. For example, "projects/1/locations/eu/taxonomies/2/policyTags/3". At most 1 policy tag is currently allowed. + "A String", + ], }, - "code": "$(reason.code)", # [Output-only] Specifies the high-level reason for the scenario when no search index was used. - "indexName": "$(reason.index_name)", # [Output-only] Specifies the name of the unused search index, if available. - "message": "$(reason.message)", # [Output-only] Free form human-readable reason for the scenario when no search index was used. + "precision": "A String", # Optional. Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: * Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] * Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: * If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. * If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): * If type = "NUMERIC": 1 ≤ precision ≤ 29. * If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid. + "rangeElementType": { # Represents the type of a field element. + "type": "A String", # Required. The type of a field element. See TableFieldSchema.type. + }, + "roundingMode": "A String", # Optional. Specifies the rounding mode to be used when storing values of NUMERIC and BIGNUMERIC type. + "scale": "A String", # Optional. See documentation for precision. + "type": "A String", # Required. The field data type. Possible values include: * STRING * BYTES * INTEGER (or INT64) * FLOAT (or FLOAT64) * BOOLEAN (or BOOL) * TIMESTAMP * DATE * TIME * DATETIME * GEOGRAPHY * NUMERIC * BIGNUMERIC * JSON * RECORD (or STRUCT) Use of RECORD/STRUCT indicates that the field contains a nested schema. + }, + ], + }, + "searchStatistics": { # Statistics for a search query. Populated as part of JobStatistics2. # Output only. Search query specific statistics. + "indexUnusedReasons": [ # When `indexUsageMode` is `UNUSED` or `PARTIALLY_USED`, this field explains why indexes were not used in all or part of the search query. If `indexUsageMode` is `FULLY_USED`, this field is not populated. + { # Reason about why no search index was used in the search query (or sub-query). + "baseTable": { # Specifies the base table involved in the reason that no search index was used. + "datasetId": "A String", # Required. The ID of the dataset containing this table. + "projectId": "A String", # Required. The ID of the project containing this table. + "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`. + }, + "code": "A String", # Specifies the high-level reason for the scenario when no search index was used. + "indexName": "A String", # Specifies the name of the unused search index, if available. + "message": "A String", # Free form human-readable reason for the scenario when no search index was used. }, ], - "indexUsageMode": "A String", # Specifies index usage mode for the query. + "indexUsageMode": "A String", # Specifies the index usage mode for the query. }, - "sparkStatistics": { # [Output only] Statistics of a Spark procedure job. - "endpoints": { # [Output-only] Endpoints generated for the Spark job. + "sparkStatistics": { # Statistics for a BigSpark query. Populated as part of JobStatistics2 # Output only. Statistics of a Spark procedure job. + "endpoints": { # Output only. Endpoints returned from Dataproc. Key list: - history_server_endpoint: A link to Spark job UI. "a_key": "A String", }, - "loggingInfo": { # [Output-only] Logging info is used to generate a link to Cloud Logging. - "projectId": "A String", # [Output-only] Project ID used for logging - "resourceType": "A String", # [Output-only] Resource type used for logging + "gcsStagingBucket": "A String", # Output only. The Google Cloud Storage bucket that is used as the default filesystem by the Spark application. This fields is only filled when the Spark procedure uses the INVOKER security mode. It is inferred from the system variable @@spark_proc_properties.staging_bucket if it is provided. Otherwise, BigQuery creates a default staging bucket for the job and returns the bucket name in this field. Example: * `gs://[bucket_name]` + "kmsKeyName": "A String", # Output only. The Cloud KMS encryption key that is used to protect the resources created by the Spark job. If the Spark procedure uses DEFINER security mode, the Cloud KMS key is inferred from the Spark connection associated with the procedure if it is provided. Otherwise the key is inferred from the default key of the Spark connection's project if the CMEK organization policy is enforced. If the Spark procedure uses INVOKER security mode, the Cloud KMS encryption key is inferred from the system variable @@spark_proc_properties.kms_key_name if it is provided. Otherwise, the key is inferred fromt he default key of the BigQuery job's project if the CMEK organization policy is enforced. Example: * `projects/[kms_project_id]/locations/[region]/keyRings/[key_region]/cryptoKeys/[key]` + "loggingInfo": { # Spark job logs can be filtered by these fields in Cloud Logging. # Output only. Logging info is used to generate a link to Cloud Logging. + "projectId": "A String", # Output only. Project ID where the Spark logs were written. + "resourceType": "A String", # Output only. Resource type used for logging. }, - "sparkJobId": "A String", # [Output-only] Spark job id if a Spark job is created successfully. - "sparkJobLocation": "A String", # [Output-only] Location where the Spark job is executed. + "sparkJobId": "A String", # Output only. Spark job ID if a Spark job is created successfully. + "sparkJobLocation": "A String", # Output only. Location where the Spark job is executed. A location is selected by BigQueury for jobs configured to run in a multi-region. }, - "statementType": "A String", # The type of query statement, if valid. Possible values (new values might be added in the future): "SELECT": SELECT query. "INSERT": INSERT query; see https://cloud.google.com/bigquery/docs/reference/standard-sql/data-manipulation-language. "UPDATE": UPDATE query; see https://cloud.google.com/bigquery/docs/reference/standard-sql/data-manipulation-language. "DELETE": DELETE query; see https://cloud.google.com/bigquery/docs/reference/standard-sql/data-manipulation-language. "MERGE": MERGE query; see https://cloud.google.com/bigquery/docs/reference/standard-sql/data-manipulation-language. "ALTER_TABLE": ALTER TABLE query. "ALTER_VIEW": ALTER VIEW query. "ASSERT": ASSERT condition AS 'description'. "CREATE_FUNCTION": CREATE FUNCTION query. "CREATE_MODEL": CREATE [OR REPLACE] MODEL ... AS SELECT ... . "CREATE_PROCEDURE": CREATE PROCEDURE query. "CREATE_TABLE": CREATE [OR REPLACE] TABLE without AS SELECT. "CREATE_TABLE_AS_SELECT": CREATE [OR REPLACE] TABLE ... AS SELECT ... . "CREATE_VIEW": CREATE [OR REPLACE] VIEW ... AS SELECT ... . "DROP_FUNCTION" : DROP FUNCTION query. "DROP_PROCEDURE": DROP PROCEDURE query. "DROP_TABLE": DROP TABLE query. "DROP_VIEW": DROP VIEW query. - "timeline": [ # [Output only] [Beta] Describes a timeline of job execution. - { - "activeUnits": "A String", # Total number of units currently being processed by workers. This does not correspond directly to slot usage. This is the largest value observed since the last sample. + "statementType": "A String", # Output only. The type of query statement, if valid. Possible values: * `SELECT`: [`SELECT`](/bigquery/docs/reference/standard-sql/query-syntax#select_list) statement. * `ASSERT`: [`ASSERT`](/bigquery/docs/reference/standard-sql/debugging-statements#assert) statement. * `INSERT`: [`INSERT`](/bigquery/docs/reference/standard-sql/dml-syntax#insert_statement) statement. * `UPDATE`: [`UPDATE`](/bigquery/docs/reference/standard-sql/query-syntax#update_statement) statement. * `DELETE`: [`DELETE`](/bigquery/docs/reference/standard-sql/data-manipulation-language) statement. * `MERGE`: [`MERGE`](/bigquery/docs/reference/standard-sql/data-manipulation-language) statement. * `CREATE_TABLE`: [`CREATE TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#create_table_statement) statement, without `AS SELECT`. * `CREATE_TABLE_AS_SELECT`: [`CREATE TABLE AS SELECT`](/bigquery/docs/reference/standard-sql/data-definition-language#query_statement) statement. * `CREATE_VIEW`: [`CREATE VIEW`](/bigquery/docs/reference/standard-sql/data-definition-language#create_view_statement) statement. * `CREATE_MODEL`: [`CREATE MODEL`](/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-create#create_model_statement) statement. * `CREATE_MATERIALIZED_VIEW`: [`CREATE MATERIALIZED VIEW`](/bigquery/docs/reference/standard-sql/data-definition-language#create_materialized_view_statement) statement. * `CREATE_FUNCTION`: [`CREATE FUNCTION`](/bigquery/docs/reference/standard-sql/data-definition-language#create_function_statement) statement. * `CREATE_TABLE_FUNCTION`: [`CREATE TABLE FUNCTION`](/bigquery/docs/reference/standard-sql/data-definition-language#create_table_function_statement) statement. * `CREATE_PROCEDURE`: [`CREATE PROCEDURE`](/bigquery/docs/reference/standard-sql/data-definition-language#create_procedure) statement. * `CREATE_ROW_ACCESS_POLICY`: [`CREATE ROW ACCESS POLICY`](/bigquery/docs/reference/standard-sql/data-definition-language#create_row_access_policy_statement) statement. * `CREATE_SCHEMA`: [`CREATE SCHEMA`](/bigquery/docs/reference/standard-sql/data-definition-language#create_schema_statement) statement. * `CREATE_SNAPSHOT_TABLE`: [`CREATE SNAPSHOT TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#create_snapshot_table_statement) statement. * `CREATE_SEARCH_INDEX`: [`CREATE SEARCH INDEX`](/bigquery/docs/reference/standard-sql/data-definition-language#create_search_index_statement) statement. * `DROP_TABLE`: [`DROP TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_table_statement) statement. * `DROP_EXTERNAL_TABLE`: [`DROP EXTERNAL TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_external_table_statement) statement. * `DROP_VIEW`: [`DROP VIEW`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_view_statement) statement. * `DROP_MODEL`: [`DROP MODEL`](/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-drop-model) statement. * `DROP_MATERIALIZED_VIEW`: [`DROP MATERIALIZED VIEW`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_materialized_view_statement) statement. * `DROP_FUNCTION` : [`DROP FUNCTION`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_function_statement) statement. * `DROP_TABLE_FUNCTION` : [`DROP TABLE FUNCTION`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_table_function) statement. * `DROP_PROCEDURE`: [`DROP PROCEDURE`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_procedure_statement) statement. * `DROP_SEARCH_INDEX`: [`DROP SEARCH INDEX`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_search_index) statement. * `DROP_SCHEMA`: [`DROP SCHEMA`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_schema_statement) statement. * `DROP_SNAPSHOT_TABLE`: [`DROP SNAPSHOT TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_snapshot_table_statement) statement. * `DROP_ROW_ACCESS_POLICY`: [`DROP [ALL] ROW ACCESS POLICY|POLICIES`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_row_access_policy_statement) statement. * `ALTER_TABLE`: [`ALTER TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#alter_table_set_options_statement) statement. * `ALTER_VIEW`: [`ALTER VIEW`](/bigquery/docs/reference/standard-sql/data-definition-language#alter_view_set_options_statement) statement. * `ALTER_MATERIALIZED_VIEW`: [`ALTER MATERIALIZED VIEW`](/bigquery/docs/reference/standard-sql/data-definition-language#alter_materialized_view_set_options_statement) statement. * `ALTER_SCHEMA`: [`ALTER SCHEMA`](/bigquery/docs/reference/standard-sql/data-definition-language#aalter_schema_set_options_statement) statement. * `SCRIPT`: [`SCRIPT`](/bigquery/docs/reference/standard-sql/procedural-language). * `TRUNCATE_TABLE`: [`TRUNCATE TABLE`](/bigquery/docs/reference/standard-sql/dml-syntax#truncate_table_statement) statement. * `CREATE_EXTERNAL_TABLE`: [`CREATE EXTERNAL TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#create_external_table_statement) statement. * `EXPORT_DATA`: [`EXPORT DATA`](/bigquery/docs/reference/standard-sql/other-statements#export_data_statement) statement. * `EXPORT_MODEL`: [`EXPORT MODEL`](/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-export-model) statement. * `LOAD_DATA`: [`LOAD DATA`](/bigquery/docs/reference/standard-sql/other-statements#load_data_statement) statement. * `CALL`: [`CALL`](/bigquery/docs/reference/standard-sql/procedural-language#call) statement. + "timeline": [ # Output only. Describes a timeline of job execution. + { # Summary of the state of query execution at a given time. + "activeUnits": "A String", # Total number of active workers. This does not correspond directly to slot usage. This is the largest value observed since the last sample. "completedUnits": "A String", # Total parallel units of work completed by this query. "elapsedMs": "A String", # Milliseconds elapsed since the start of query execution. - "estimatedRunnableUnits": "A String", # Units of work that can be scheduled immediately. Providing additional slots for these units of work will speed up the query, provided no other query in the reservation needs additional slots. + "estimatedRunnableUnits": "A String", # Units of work that can be scheduled immediately. Providing additional slots for these units of work will accelerate the query, if no other query in the reservation needs additional slots. "pendingUnits": "A String", # Total units of work remaining for the query. This number can be revised (increased or decreased) while the query is running. "totalSlotMs": "A String", # Cumulative slot-ms consumed by the query. }, ], - "totalBytesBilled": "A String", # [Output only] Total bytes billed for the job. - "totalBytesProcessed": "A String", # [Output only] Total bytes processed for the job. - "totalBytesProcessedAccuracy": "A String", # [Output only] For dry-run jobs, totalBytesProcessed is an estimate and this field specifies the accuracy of the estimate. Possible values can be: UNKNOWN: accuracy of the estimate is unknown. PRECISE: estimate is precise. LOWER_BOUND: estimate is lower bound of what the query would cost. UPPER_BOUND: estimate is upper bound of what the query would cost. - "totalPartitionsProcessed": "A String", # [Output only] Total number of partitions processed from all partitioned tables referenced in the job. - "totalSlotMs": "A String", # [Output only] Slot-milliseconds for the job. - "transferredBytes": "A String", # [Output-only] Total bytes transferred for cross-cloud queries such as Cross Cloud Transfer and CREATE TABLE AS SELECT (CTAS). - "undeclaredQueryParameters": [ # Standard SQL only: list of undeclared query parameters detected during a dry run validation. - { - "name": "A String", # [Optional] If unset, this is a positional parameter. Otherwise, should be unique within a query. - "parameterType": { # [Required] The type of this parameter. - "arrayType": # Object with schema name: QueryParameterType # [Optional] The type of the array's elements, if this is an array. - "rangeElementType": # Object with schema name: QueryParameterType # [Optional] The element type of the range, if this is a range. - "structTypes": [ # [Optional] The types of the fields of this struct, in order, if this is a struct. - { - "description": "A String", # [Optional] Human-oriented description of the field. - "name": "A String", # [Optional] The name of this field. - "type": # Object with schema name: QueryParameterType # [Required] The type of this field. + "totalBytesBilled": "A String", # Output only. If the project is configured to use on-demand pricing, then this field contains the total bytes billed for the job. If the project is configured to use flat-rate pricing, then you are not billed for bytes and this field is informational only. + "totalBytesProcessed": "A String", # Output only. Total bytes processed for the job. + "totalBytesProcessedAccuracy": "A String", # Output only. For dry-run jobs, totalBytesProcessed is an estimate and this field specifies the accuracy of the estimate. Possible values can be: UNKNOWN: accuracy of the estimate is unknown. PRECISE: estimate is precise. LOWER_BOUND: estimate is lower bound of what the query would cost. UPPER_BOUND: estimate is upper bound of what the query would cost. + "totalPartitionsProcessed": "A String", # Output only. Total number of partitions processed from all partitioned tables referenced in the job. + "totalSlotMs": "A String", # Output only. Slot-milliseconds for the job. + "transferredBytes": "A String", # Output only. Total bytes transferred for cross-cloud queries such as Cross Cloud Transfer and CREATE TABLE AS SELECT (CTAS). + "undeclaredQueryParameters": [ # Output only. GoogleSQL only: list of undeclared query parameters detected during a dry run validation. + { # A parameter given to a query. + "name": "A String", # Optional. If unset, this is a positional parameter. Otherwise, should be unique within a query. + "parameterType": { # The type of a query parameter. # Required. The type of this parameter. + "arrayType": # Object with schema name: QueryParameterType # Optional. The type of the array's elements, if this is an array. + "rangeElementType": # Object with schema name: QueryParameterType # Optional. The element type of the range, if this is a range. + "structTypes": [ # Optional. The types of the fields of this struct, in order, if this is a struct. + { # The type of a struct parameter. + "description": "A String", # Optional. Human-oriented description of the field. + "name": "A String", # Optional. The name of this field. + "type": # Object with schema name: QueryParameterType # Required. The type of this field. }, ], - "type": "A String", # [Required] The top level type of this field. + "type": "A String", # Required. The top level type of this field. }, - "parameterValue": { # [Required] The value of this parameter. - "arrayValues": [ # [Optional] The array values, if this is an array type. + "parameterValue": { # The value of a query parameter. # Required. The value of this parameter. + "arrayValues": [ # Optional. The array values, if this is an array type. # Object with schema name: QueryParameterValue ], - "rangeValue": { # [Optional] The range value, if this is a range type. - "end": # Object with schema name: QueryParameterValue - "start": # Object with schema name: QueryParameterValue + "rangeValue": { # Represents the value of a range. # Optional. The range value, if this is a range type. + "end": # Object with schema name: QueryParameterValue # Optional. The end value of the range. A missing value represents an unbounded end. + "start": # Object with schema name: QueryParameterValue # Optional. The start value of the range. A missing value represents an unbounded start. }, - "structValues": { # [Optional] The struct field values, in order of the struct type's declaration. + "structValues": { # The struct field values. "a_key": # Object with schema name: QueryParameterValue }, - "value": "A String", # [Optional] The value of this value, if a simple scalar type. + "value": "A String", # Optional. The value of this value, if a simple scalar type. }, }, ], + "vectorSearchStatistics": { # Statistics for a vector search query. Populated as part of JobStatistics2. # Output only. Search query specific statistics. + "indexUnusedReasons": [ # When `indexUsageMode` is `UNUSED` or `PARTIALLY_USED`, this field explains why indexes were not used in all or part of the vector search query. If `indexUsageMode` is `FULLY_USED`, this field is not populated. + { # Reason about why no search index was used in the search query (or sub-query). + "baseTable": { # Specifies the base table involved in the reason that no search index was used. + "datasetId": "A String", # Required. The ID of the dataset containing this table. + "projectId": "A String", # Required. The ID of the project containing this table. + "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`. + }, + "code": "A String", # Specifies the high-level reason for the scenario when no search index was used. + "indexName": "A String", # Specifies the name of the unused search index, if available. + "message": "A String", # Free form human-readable reason for the scenario when no search index was used. + }, + ], + "indexUsageMode": "A String", # Specifies the index usage mode for the query. + }, }, - "quotaDeferments": [ # [Output-only] Quotas which delayed this job's start time. + "quotaDeferments": [ # Output only. Quotas which delayed this job's start time. "A String", ], - "reservationUsage": [ # [Output-only] Job resource usage breakdown by reservation. - { - "name": "A String", # [Output-only] Reservation name or "unreserved" for on-demand resources usage. - "slotMs": "A String", # [Output-only] Slot-milliseconds the job spent in the given reservation. + "reservationUsage": [ # Output only. Job resource usage breakdown by reservation. This field reported misleading information and will no longer be populated. + { # Job resource usage breakdown by reservation. + "name": "A String", # Reservation name or "unreserved" for on-demand resources usage. + "slotMs": "A String", # Total slot milliseconds used by the reservation for a particular job. }, ], - "reservation_id": "A String", # [Output-only] Name of the primary reservation assigned to this job. Note that this could be different than reservations reported in the reservation usage field if parent reservations were used to execute this job. - "rowLevelSecurityStatistics": { # [Output-only] [Preview] Statistics for row-level security. Present only for query and extract jobs. - "rowLevelSecurityApplied": True or False, # [Output-only] [Preview] Whether any accessed data was protected by row access policies. + "reservation_id": "A String", # Output only. Name of the primary reservation assigned to this job. Note that this could be different than reservations reported in the reservation usage field if parent reservations were used to execute this job. + "rowLevelSecurityStatistics": { # Statistics for row-level security. # Output only. Statistics for row-level security. Present only for query and extract jobs. + "rowLevelSecurityApplied": True or False, # Whether any accessed data was protected by row access policies. }, - "scriptStatistics": { # [Output-only] Statistics for a child job of a script. - "evaluationKind": "A String", # [Output-only] Whether this child job was a statement or expression. + "scriptStatistics": { # Job statistics specific to the child job of a script. # Output only. If this a child job of a script, specifies information about the context of this job within the script. + "evaluationKind": "A String", # Whether this child job was a statement or expression. "stackFrames": [ # Stack trace showing the line/column/procedure name of each frame on the stack at the point where the current evaluation happened. The leaf frame is first, the primary script is last. Never empty. - { - "endColumn": 42, # [Output-only] One-based end column. - "endLine": 42, # [Output-only] One-based end line. - "procedureId": "A String", # [Output-only] Name of the active procedure, empty if in a top-level script. - "startColumn": 42, # [Output-only] One-based start column. - "startLine": 42, # [Output-only] One-based start line. - "text": "A String", # [Output-only] Text of the current statement/expression. + { # Represents the location of the statement/expression being evaluated. Line and column numbers are defined as follows: - Line and column numbers start with one. That is, line 1 column 1 denotes the start of the script. - When inside a stored procedure, all line/column numbers are relative to the procedure body, not the script in which the procedure was defined. - Start/end positions exclude leading/trailing comments and whitespace. The end position always ends with a ";", when present. - Multi-byte Unicode characters are treated as just one column. - If the original script (or procedure definition) contains TAB characters, a tab "snaps" the indentation forward to the nearest multiple of 8 characters, plus 1. For example, a TAB on column 1, 2, 3, 4, 5, 6 , or 8 will advance the next character to column 9. A TAB on column 9, 10, 11, 12, 13, 14, 15, or 16 will advance the next character to column 17. + "endColumn": 42, # Output only. One-based end column. + "endLine": 42, # Output only. One-based end line. + "procedureId": "A String", # Output only. Name of the active procedure, empty if in a top-level script. + "startColumn": 42, # Output only. One-based start column. + "startLine": 42, # Output only. One-based start line. + "text": "A String", # Output only. Text of the current statement/expression. }, ], }, - "sessionInfo": { # [Output-only] [Preview] Information of the session if this job is part of one. - "sessionId": "A String", # [Output-only] // [Preview] Id of the session. + "sessionInfo": { # [Preview] Information related to sessions. # Output only. Information of the session if this job is part of one. + "sessionId": "A String", # Output only. The id of the session. }, - "startTime": "A String", # [Output-only] Start time of this job, in milliseconds since the epoch. This field will be present when the job transitions from the PENDING state to either RUNNING or DONE. - "totalBytesProcessed": "A String", # [Output-only] [Deprecated] Use the bytes processed in the query statistics instead. - "totalSlotMs": "A String", # [Output-only] Slot-milliseconds for the job. - "transactionInfo": { # [Output-only] [Alpha] Information of the multi-statement transaction if this job is part of one. - "transactionId": "A String", # [Output-only] // [Alpha] Id of the transaction. + "startTime": "A String", # Output only. Start time of this job, in milliseconds since the epoch. This field will be present when the job transitions from the PENDING state to either RUNNING or DONE. + "totalBytesProcessed": "A String", # Output only. Total bytes processed for the job. + "totalSlotMs": "A String", # Output only. Slot-milliseconds for the job. + "transactionInfo": { # [Alpha] Information of a multi-statement transaction. # Output only. [Alpha] Information of the multi-statement transaction if this job is part of one. This property is only expected on a child job or a job that is in a session. A script parent job is not part of the transaction started in the script. + "transactionId": "A String", # Output only. [Alpha] Id of the transaction. }, }, - "status": { # [Output-only] The status of this job. Examine this value when polling an asynchronous job to see if the job is complete. - "errorResult": { # [Output-only] Final error result of the job. If present, indicates that the job has completed and was unsuccessful. + "status": { # Output only. The status of this job. Examine this value when polling an asynchronous job to see if the job is complete. + "errorResult": { # Error details. # Output only. Final error result of the job. If present, indicates that the job has completed and was unsuccessful. "debugInfo": "A String", # Debugging information. This property is internal to Google and should not be used. "location": "A String", # Specifies where the error occurred, if present. "message": "A String", # A human-readable description of the error. "reason": "A String", # A short error code that summarizes the error. }, - "errors": [ # [Output-only] The first errors encountered during the running of the job. The final message includes the number of errors that caused the process to stop. Errors here do not necessarily mean that the job has completed or was unsuccessful. - { + "errors": [ # Output only. The first errors encountered during the running of the job. The final message includes the number of errors that caused the process to stop. Errors here do not necessarily mean that the job has not completed or was unsuccessful. + { # Error details. "debugInfo": "A String", # Debugging information. This property is internal to Google and should not be used. "location": "A String", # Specifies where the error occurred, if present. "message": "A String", # A human-readable description of the error. "reason": "A String", # A short error code that summarizes the error. }, ], - "state": "A String", # [Output-only] Running state of the job. + "state": "A String", # Output only. Running state of the job. Valid states include 'PENDING', 'RUNNING', and 'DONE'. }, - "user_email": "A String", # [Output-only] Email address of the user who ran the job. + "user_email": "A String", # Output only. Email address of the user who ran the job. } media_body: string, The filename of the media request body, or an instance of a MediaUpload object. media_mime_type: string, The MIME type of the media request body, or an instance of a MediaUpload object. + x__xgafv: string, V1 error format. + Allowed values + 1 - v1 error format + 2 - v2 error format Returns: An object of the form: { - "configuration": { # [Required] Describes the job configuration. - "copy": { # [Pick one] Copies a table. - "createDisposition": "A String", # [Optional] Specifies whether the job is allowed to create new tables. The following values are supported: CREATE_IF_NEEDED: If the table does not exist, BigQuery creates the table. CREATE_NEVER: The table must already exist. If it does not, a 'notFound' error is returned in the job result. The default value is CREATE_IF_NEEDED. Creation, truncation and append actions occur as one atomic update upon job completion. + "configuration": { # Required. Describes the job configuration. + "copy": { # JobConfigurationTableCopy configures a job that copies data from one table to another. For more information on copying tables, see [Copy a table](https://cloud.google.com/bigquery/docs/managing-tables#copy-table). # [Pick one] Copies a table. + "createDisposition": "A String", # Optional. Specifies whether the job is allowed to create new tables. The following values are supported: * CREATE_IF_NEEDED: If the table does not exist, BigQuery creates the table. * CREATE_NEVER: The table must already exist. If it does not, a 'notFound' error is returned in the job result. The default value is CREATE_IF_NEEDED. Creation, truncation and append actions occur as one atomic update upon job completion. "destinationEncryptionConfiguration": { # Custom encryption configuration (e.g., Cloud KMS keys). "kmsKeyName": "A String", # Optional. Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key. }, - "destinationExpirationTime": "", # [Optional] The time when the destination table expires. Expired tables will be deleted and their storage reclaimed. - "destinationTable": { # [Required] The destination table - "datasetId": "A String", # [Required] The ID of the dataset containing this table. - "projectId": "A String", # [Required] The ID of the project containing this table. - "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. + "destinationExpirationTime": "A String", # Optional. The time when the destination table expires. Expired tables will be deleted and their storage reclaimed. + "destinationTable": { # [Required] The destination table. + "datasetId": "A String", # Required. The ID of the dataset containing this table. + "projectId": "A String", # Required. The ID of the project containing this table. + "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`. }, - "operationType": "A String", # [Optional] Supported operation types in table copy job. + "operationType": "A String", # Optional. Supported operation types in table copy job. "sourceTable": { # [Pick one] Source table to copy. - "datasetId": "A String", # [Required] The ID of the dataset containing this table. - "projectId": "A String", # [Required] The ID of the project containing this table. - "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. + "datasetId": "A String", # Required. The ID of the dataset containing this table. + "projectId": "A String", # Required. The ID of the project containing this table. + "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`. }, "sourceTables": [ # [Pick one] Source tables to copy. { - "datasetId": "A String", # [Required] The ID of the dataset containing this table. - "projectId": "A String", # [Required] The ID of the project containing this table. - "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. + "datasetId": "A String", # Required. The ID of the dataset containing this table. + "projectId": "A String", # Required. The ID of the project containing this table. + "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`. }, ], - "writeDisposition": "A String", # [Optional] Specifies the action that occurs if the destination table already exists. The following values are supported: WRITE_TRUNCATE: If the table already exists, BigQuery overwrites the table data. WRITE_APPEND: If the table already exists, BigQuery appends the data to the table. WRITE_EMPTY: If the table already exists and contains data, a 'duplicate' error is returned in the job result. The default value is WRITE_EMPTY. Each action is atomic and only occurs if BigQuery is able to complete the job successfully. Creation, truncation and append actions occur as one atomic update upon job completion. + "writeDisposition": "A String", # Optional. Specifies the action that occurs if the destination table already exists. The following values are supported: * WRITE_TRUNCATE: If the table already exists, BigQuery overwrites the table data and uses the schema and table constraints from the source table. * WRITE_APPEND: If the table already exists, BigQuery appends the data to the table. * WRITE_EMPTY: If the table already exists and contains data, a 'duplicate' error is returned in the job result. The default value is WRITE_EMPTY. Each action is atomic and only occurs if BigQuery is able to complete the job successfully. Creation, truncation and append actions occur as one atomic update upon job completion. }, - "dryRun": True or False, # [Optional] If set, don't actually run this job. A valid query will return a mostly empty response with some processing statistics, while an invalid query will return the same error it would if it wasn't a dry run. Behavior of non-query jobs is undefined. - "extract": { # [Pick one] Configures an extract job. - "compression": "A String", # [Optional] The compression type to use for exported files. Possible values include GZIP, DEFLATE, SNAPPY, and NONE. The default value is NONE. DEFLATE and SNAPPY are only supported for Avro. Not applicable when extracting models. - "destinationFormat": "A String", # [Optional] The exported file format. Possible values include CSV, NEWLINE_DELIMITED_JSON, PARQUET or AVRO for tables and ML_TF_SAVED_MODEL or ML_XGBOOST_BOOSTER for models. The default value for tables is CSV. Tables with nested or repeated fields cannot be exported as CSV. The default value for models is ML_TF_SAVED_MODEL. + "dryRun": True or False, # Optional. If set, don't actually run this job. A valid query will return a mostly empty response with some processing statistics, while an invalid query will return the same error it would if it wasn't a dry run. Behavior of non-query jobs is undefined. + "extract": { # JobConfigurationExtract configures a job that exports data from a BigQuery table into Google Cloud Storage. # [Pick one] Configures an extract job. + "compression": "A String", # Optional. The compression type to use for exported files. Possible values include DEFLATE, GZIP, NONE, SNAPPY, and ZSTD. The default value is NONE. Not all compression formats are support for all file formats. DEFLATE is only supported for Avro. ZSTD is only supported for Parquet. Not applicable when extracting models. + "destinationFormat": "A String", # Optional. The exported file format. Possible values include CSV, NEWLINE_DELIMITED_JSON, PARQUET, or AVRO for tables and ML_TF_SAVED_MODEL or ML_XGBOOST_BOOSTER for models. The default value for tables is CSV. Tables with nested or repeated fields cannot be exported as CSV. The default value for models is ML_TF_SAVED_MODEL. "destinationUri": "A String", # [Pick one] DEPRECATED: Use destinationUris instead, passing only one URI as necessary. The fully-qualified Google Cloud Storage URI where the extracted table should be written. "destinationUris": [ # [Pick one] A list of fully-qualified Google Cloud Storage URIs where the extracted table should be written. "A String", ], - "fieldDelimiter": "A String", # [Optional] Delimiter to use between fields in the exported data. Default is ','. Not applicable when extracting models. - "printHeader": true, # [Optional] Whether to print out a header row in the results. Default is true. Not applicable when extracting models. - "sourceModel": { # A reference to the model being exported. + "fieldDelimiter": "A String", # Optional. When extracting data in CSV format, this defines the delimiter to use between fields in the exported data. Default is ','. Not applicable when extracting models. + "modelExtractOptions": { # Options related to model extraction. # Optional. Model extract options only applicable when extracting models. + "trialId": "A String", # The 1-based ID of the trial to be exported from a hyperparameter tuning model. If not specified, the trial with id = [Model](/bigquery/docs/reference/rest/v2/models#resource:-model).defaultTrialId is exported. This field is ignored for models not trained with hyperparameter tuning. + }, + "printHeader": true, # Optional. Whether to print out a header row in the results. Default is true. Not applicable when extracting models. + "sourceModel": { # Id path of a model. # A reference to the model being exported. "datasetId": "A String", # Required. The ID of the dataset containing this model. "modelId": "A String", # Required. The ID of the model. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. "projectId": "A String", # Required. The ID of the project containing this model. }, "sourceTable": { # A reference to the table being exported. - "datasetId": "A String", # [Required] The ID of the dataset containing this table. - "projectId": "A String", # [Required] The ID of the project containing this table. - "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. + "datasetId": "A String", # Required. The ID of the dataset containing this table. + "projectId": "A String", # Required. The ID of the project containing this table. + "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`. }, - "useAvroLogicalTypes": True or False, # [Optional] If destinationFormat is set to "AVRO", this flag indicates whether to enable extracting applicable column types (such as TIMESTAMP) to their corresponding AVRO logical types (timestamp-micros), instead of only using their raw types (avro-long). Not applicable when extracting models. + "useAvroLogicalTypes": True or False, # Whether to use logical types when extracting to AVRO format. Not applicable when extracting models. }, - "jobTimeoutMs": "A String", # [Optional] Job timeout in milliseconds. If this time limit is exceeded, BigQuery may attempt to terminate the job. - "jobType": "A String", # [Output-only] The type of the job. Can be QUERY, LOAD, EXTRACT, COPY or UNKNOWN. + "jobTimeoutMs": "A String", # Optional. Job timeout in milliseconds. If this time limit is exceeded, BigQuery might attempt to stop the job. + "jobType": "A String", # Output only. The type of the job. Can be QUERY, LOAD, EXTRACT, COPY or UNKNOWN. "labels": { # The labels associated with this job. You can use these to organize and group your jobs. Label keys and values can be no longer than 63 characters, can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. Label values are optional. Label keys must start with a letter and each label in the list must have a different key. "a_key": "A String", }, - "load": { # [Pick one] Configures a load job. - "allowJaggedRows": True or False, # [Optional] Accept rows that are missing trailing optional columns. The missing values are treated as nulls. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. Only applicable to CSV, ignored for other formats. + "load": { # JobConfigurationLoad contains the configuration properties for loading data into a destination table. # [Pick one] Configures a load job. + "allowJaggedRows": True or False, # Optional. Accept rows that are missing trailing optional columns. The missing values are treated as nulls. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. Only applicable to CSV, ignored for other formats. "allowQuotedNewlines": True or False, # Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false. - "autodetect": True or False, # [Optional] Indicates if we should automatically infer the options and schema for CSV and JSON sources. - "clustering": { # [Beta] Clustering specification for the destination table. Must be specified with time-based partitioning, data in the table will be first partitioned and subsequently clustered. - "fields": [ # [Repeated] One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. When you cluster a table using multiple columns, the order of columns you specify is important. The order of the specified columns determines the sort order of the data. + "autodetect": True or False, # Optional. Indicates if we should automatically infer the options and schema for CSV and JSON sources. + "clustering": { # Configures table clustering. # Clustering specification for the destination table. + "fields": [ # One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. The ordering of the clustering fields should be prioritized from most to least important for filtering purposes. Additional information on limitations can be found here: https://cloud.google.com/bigquery/docs/creating-clustered-tables#limitations "A String", ], }, - "connectionProperties": [ # Connection properties. - { - "key": "A String", # [Required] Name of the connection property to set. - "value": "A String", # [Required] Value of the connection property. + "connectionProperties": [ # Optional. Connection properties which can modify the load job behavior. Currently, only the 'session_id' connection property is supported, and is used to resolve _SESSION appearing as the dataset id. + { # A connection-level property to customize query behavior. Under JDBC, these correspond directly to connection properties passed to the DriverManager. Under ODBC, these correspond to properties in the connection string. Currently supported connection properties: * **dataset_project_id**: represents the default project for datasets that are used in the query. Setting the system variable `@@dataset_project_id` achieves the same behavior. For more information about system variables, see: https://cloud.google.com/bigquery/docs/reference/system-variables * **time_zone**: represents the default timezone used to run the query. * **session_id**: associates the query with a given session. * **query_label**: associates the query with a given job label. If set, all subsequent queries in a script or session will have this label. For the format in which a you can specify a query label, see labels in the JobConfiguration resource type: https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#jobconfiguration Additional properties are allowed, but ignored. Specifying multiple connection properties with the same key returns an error. + "key": "A String", # The key of the property to set. + "value": "A String", # The value of the property to set. }, ], - "createDisposition": "A String", # [Optional] Specifies whether the job is allowed to create new tables. The following values are supported: CREATE_IF_NEEDED: If the table does not exist, BigQuery creates the table. CREATE_NEVER: The table must already exist. If it does not, a 'notFound' error is returned in the job result. The default value is CREATE_IF_NEEDED. Creation, truncation and append actions occur as one atomic update upon job completion. - "createSession": True or False, # If true, creates a new session, where session id will be a server generated random id. If false, runs query with an existing session_id passed in ConnectionProperty, otherwise runs the load job in non-session mode. - "decimalTargetTypes": [ # [Optional] Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown. Example: Suppose the value of this field is ["NUMERIC", "BIGNUMERIC"]. If (precision,scale) is: (38,9) -> NUMERIC; (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits); (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits); (76,38) -> BIGNUMERIC; (77,38) -> BIGNUMERIC (error if value exeeds supported range). This field cannot contain duplicate types. The order of the types in this field is ignored. For example, ["BIGNUMERIC", "NUMERIC"] is the same as ["NUMERIC", "BIGNUMERIC"] and NUMERIC always takes precedence over BIGNUMERIC. Defaults to ["NUMERIC", "STRING"] for ORC and ["NUMERIC"] for the other file formats. + "createDisposition": "A String", # Optional. Specifies whether the job is allowed to create new tables. The following values are supported: * CREATE_IF_NEEDED: If the table does not exist, BigQuery creates the table. * CREATE_NEVER: The table must already exist. If it does not, a 'notFound' error is returned in the job result. The default value is CREATE_IF_NEEDED. Creation, truncation and append actions occur as one atomic update upon job completion. + "createSession": True or False, # Optional. If this property is true, the job creates a new session using a randomly generated session_id. To continue using a created session with subsequent queries, pass the existing session identifier as a `ConnectionProperty` value. The session identifier is returned as part of the `SessionInfo` message within the query statistics. The new session's location will be set to `Job.JobReference.location` if it is present, otherwise it's set to the default location based on existing routing logic. + "decimalTargetTypes": [ # Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown. Example: Suppose the value of this field is ["NUMERIC", "BIGNUMERIC"]. If (precision,scale) is: * (38,9) -> NUMERIC; * (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits); * (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits); * (76,38) -> BIGNUMERIC; * (77,38) -> BIGNUMERIC (error if value exeeds supported range). This field cannot contain duplicate types. The order of the types in this field is ignored. For example, ["BIGNUMERIC", "NUMERIC"] is the same as ["NUMERIC", "BIGNUMERIC"] and NUMERIC always takes precedence over BIGNUMERIC. Defaults to ["NUMERIC", "STRING"] for ORC and ["NUMERIC"] for the other file formats. "A String", ], - "destinationEncryptionConfiguration": { # Custom encryption configuration (e.g., Cloud KMS keys). + "destinationEncryptionConfiguration": { # Custom encryption configuration (e.g., Cloud KMS keys) "kmsKeyName": "A String", # Optional. Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key. }, "destinationTable": { # [Required] The destination table to load the data into. - "datasetId": "A String", # [Required] The ID of the dataset containing this table. - "projectId": "A String", # [Required] The ID of the project containing this table. - "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. - }, - "destinationTableProperties": { # [Beta] [Optional] Properties with which to create the destination table if it is new. - "description": "A String", # [Optional] The description for the destination table. This will only be used if the destination table is newly created. If the table already exists and a value different than the current description is provided, the job will fail. - "expirationTime": "A String", # [Internal] This field is for Google internal use only. - "friendlyName": "A String", # [Optional] The friendly name for the destination table. This will only be used if the destination table is newly created. If the table already exists and a value different than the current friendly name is provided, the job will fail. - "labels": { # [Optional] The labels associated with this table. You can use these to organize and group your tables. This will only be used if the destination table is newly created. If the table already exists and labels are different than the current labels are provided, the job will fail. + "datasetId": "A String", # Required. The ID of the dataset containing this table. + "projectId": "A String", # Required. The ID of the project containing this table. + "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`. + }, + "destinationTableProperties": { # Properties for the destination table. # Optional. [Experimental] Properties with which to create the destination table if it is new. + "description": "A String", # Optional. The description for the destination table. This will only be used if the destination table is newly created. If the table already exists and a value different than the current description is provided, the job will fail. + "expirationTime": "A String", # Internal use only. + "friendlyName": "A String", # Optional. Friendly name for the destination table. If the table already exists, it should be same as the existing friendly name. + "labels": { # Optional. The labels associated with this table. You can use these to organize and group your tables. This will only be used if the destination table is newly created. If the table already exists and labels are different than the current labels are provided, the job will fail. "a_key": "A String", }, }, - "encoding": "A String", # [Optional] The character encoding of the data. The supported values are UTF-8 or ISO-8859-1. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the quote and fieldDelimiter properties. - "fieldDelimiter": "A String", # [Optional] The separator for fields in a CSV file. The separator can be any ISO-8859-1 single-byte character. To use a character in the range 128-255, you must encode the character as UTF8. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. BigQuery also supports the escape sequence "\t" to specify a tab separator. The default value is a comma (','). - "fileSetSpecType": "A String", # [Optional] Specifies how source URIs are interpreted for constructing the file set to load. By default source URIs are expanded against the underlying storage. Other options include specifying manifest files. Only applicable to object storage systems. - "hivePartitioningOptions": { # [Optional] Options to configure hive partitioning support. - "fields": [ # [Output-only] For permanent external tables, this field is populated with the hive partition keys in the order they were inferred. The types of the partition keys can be deduced by checking the table schema (which will include the partition keys). Not every API will populate this field in the output. For example, Tables.Get will populate it, but Tables.List will not contain this field. + "encoding": "A String", # Optional. The character encoding of the data. The supported values are UTF-8, ISO-8859-1, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the `quote` and `fieldDelimiter` properties. If you don't specify an encoding, or if you specify a UTF-8 encoding when the CSV file is not UTF-8 encoded, BigQuery attempts to convert the data to UTF-8. Generally, your data loads successfully, but it may not match byte-for-byte what you expect. To avoid this, specify the correct encoding by using the `--encoding` flag. If BigQuery can't convert a character other than the ASCII `0` character, BigQuery converts the character to the standard Unicode replacement character: �. + "fieldDelimiter": "A String", # Optional. The separator character for fields in a CSV file. The separator is interpreted as a single byte. For files encoded in ISO-8859-1, any single character can be used as a separator. For files encoded in UTF-8, characters represented in decimal range 1-127 (U+0001-U+007F) can be used without any modification. UTF-8 characters encoded with multiple bytes (i.e. U+0080 and above) will have only the first byte used for separating fields. The remaining bytes will be treated as a part of the field. BigQuery also supports the escape sequence "\t" (U+0009) to specify a tab separator. The default value is comma (",", U+002C). + "fileSetSpecType": "A String", # Optional. Specifies how source URIs are interpreted for constructing the file set to load. By default, source URIs are expanded against the underlying storage. You can also specify manifest files to control how the file set is constructed. This option is only applicable to object storage systems. + "hivePartitioningOptions": { # Options for configuring hive partitioning detect. # Optional. When set, configures hive partitioning support. Not all storage formats support hive partitioning -- requesting hive partitioning on an unsupported format will lead to an error, as will providing an invalid specification. + "fields": [ # Output only. For permanent external tables, this field is populated with the hive partition keys in the order they were inferred. The types of the partition keys can be deduced by checking the table schema (which will include the partition keys). Not every API will populate this field in the output. For example, Tables.Get will populate it, but Tables.List will not contain this field. "A String", ], - "mode": "A String", # [Optional] When set, what mode of hive partitioning to use when reading data. The following modes are supported. (1) AUTO: automatically infer partition key name(s) and type(s). (2) STRINGS: automatically infer partition key name(s). All types are interpreted as strings. (3) CUSTOM: partition key schema is encoded in the source URI prefix. Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported types include: AVRO, CSV, JSON, ORC and Parquet. - "requirePartitionFilter": True or False, # [Optional] If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. Note that this field should only be true when creating a permanent external table or querying a temporary external table. Hive-partitioned loads with requirePartitionFilter explicitly set to true will fail. - "sourceUriPrefix": "A String", # [Optional] When hive partition detection is requested, a common prefix for all source uris should be supplied. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout. gs://bucket/path_to_table/dt=2019-01-01/country=BR/id=7/file.avro gs://bucket/path_to_table/dt=2018-12-31/country=CA/id=3/file.avro When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/ (trailing slash does not matter). - }, - "ignoreUnknownValues": True or False, # [Optional] Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names - "jsonExtension": "A String", # [Optional] If sourceFormat is set to newline-delimited JSON, indicates whether it should be processed as a JSON variant such as GeoJSON. For a sourceFormat other than JSON, omit this field. If the sourceFormat is newline-delimited JSON: - for newline-delimited GeoJSON: set to GEOJSON. - "maxBadRecords": 42, # [Optional] The maximum number of bad records that BigQuery can ignore when running the job. If the number of bad records exceeds this value, an invalid error is returned in the job result. This is only valid for CSV and JSON. The default value is 0, which requires that all records are valid. - "nullMarker": "A String", # [Optional] Specifies a string that represents a null value in a CSV file. For example, if you specify "\N", BigQuery interprets "\N" as a null value when loading a CSV file. The default value is the empty string. If you set this property to a custom value, BigQuery throws an error if an empty string is present for all data types except for STRING and BYTE. For STRING and BYTE columns, BigQuery interprets the empty string as an empty value. - "parquetOptions": { # [Optional] Options to configure parquet support. - "enableListInference": True or False, # [Optional] Indicates whether to use schema inference specifically for Parquet LIST logical type. - "enumAsString": True or False, # [Optional] Indicates whether to infer Parquet ENUM logical type as STRING instead of BYTES by default. - }, - "preserveAsciiControlCharacters": True or False, # [Optional] Preserves the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\x00' to '\x1F') when loading from CSV. Only applicable to CSV, ignored for other formats. + "mode": "A String", # Optional. When set, what mode of hive partitioning to use when reading data. The following modes are supported: * AUTO: automatically infer partition key name(s) and type(s). * STRINGS: automatically infer partition key name(s). All types are strings. * CUSTOM: partition key schema is encoded in the source URI prefix. Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported formats are: JSON, CSV, ORC, Avro and Parquet. + "requirePartitionFilter": false, # Optional. If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. Note that this field should only be true when creating a permanent external table or querying a temporary external table. Hive-partitioned loads with require_partition_filter explicitly set to true will fail. + "sourceUriPrefix": "A String", # Optional. When hive partition detection is requested, a common prefix for all source uris must be required. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout: gs://bucket/path_to_table/dt=2019-06-01/country=USA/id=7/file.avro gs://bucket/path_to_table/dt=2019-05-31/country=CA/id=3/file.avro When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/. CUSTOM detection requires encoding the partitioning schema immediately after the common prefix. For CUSTOM, any of * gs://bucket/path_to_table/{dt:DATE}/{country:STRING}/{id:INTEGER} * gs://bucket/path_to_table/{dt:STRING}/{country:STRING}/{id:INTEGER} * gs://bucket/path_to_table/{dt:DATE}/{country:STRING}/{id:STRING} would all be valid source URI prefixes. + }, + "ignoreUnknownValues": True or False, # Optional. Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names in the table schema Avro, Parquet, ORC: Fields in the file schema that don't exist in the table schema. + "jsonExtension": "A String", # Optional. Load option to be used together with source_format newline-delimited JSON to indicate that a variant of JSON is being loaded. To load newline-delimited GeoJSON, specify GEOJSON (and source_format must be set to NEWLINE_DELIMITED_JSON). + "maxBadRecords": 42, # Optional. The maximum number of bad records that BigQuery can ignore when running the job. If the number of bad records exceeds this value, an invalid error is returned in the job result. The default value is 0, which requires that all records are valid. This is only supported for CSV and NEWLINE_DELIMITED_JSON file formats. + "nullMarker": "A String", # Optional. Specifies a string that represents a null value in a CSV file. For example, if you specify "\N", BigQuery interprets "\N" as a null value when loading a CSV file. The default value is the empty string. If you set this property to a custom value, BigQuery throws an error if an empty string is present for all data types except for STRING and BYTE. For STRING and BYTE columns, BigQuery interprets the empty string as an empty value. + "parquetOptions": { # Parquet Options for load and make external tables. # Optional. Additional properties to set if sourceFormat is set to PARQUET. + "enableListInference": True or False, # Optional. Indicates whether to use schema inference specifically for Parquet LIST logical type. + "enumAsString": True or False, # Optional. Indicates whether to infer Parquet ENUM logical type as STRING instead of BYTES by default. + }, + "preserveAsciiControlCharacters": True or False, # Optional. When sourceFormat is set to "CSV", this indicates whether the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\x00' to '\x1F') are preserved. "projectionFields": [ # If sourceFormat is set to "DATASTORE_BACKUP", indicates which entity properties to load into BigQuery from a Cloud Datastore backup. Property names are case sensitive and must be top-level properties. If no properties are specified, BigQuery loads all properties. If any named property isn't found in the Cloud Datastore backup, an invalid error is returned in the job result. "A String", ], - "quote": """, # [Optional] The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ('"'). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true. - "rangePartitioning": { # [TrustedTester] Range partitioning specification for this table. Only one of timePartitioning and rangePartitioning should be specified. - "field": "A String", # [TrustedTester] [Required] The table is partitioned by this field. The field must be a top-level NULLABLE/REQUIRED field. The only supported type is INTEGER/INT64. - "range": { # [TrustedTester] [Required] Defines the ranges for range partitioning. - "end": "A String", # [TrustedTester] [Required] The end of range partitioning, exclusive. - "interval": "A String", # [TrustedTester] [Required] The width of each interval. - "start": "A String", # [TrustedTester] [Required] The start of range partitioning, inclusive. + "quote": """, # Optional. The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ('"'). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true. To include the specific quote character within a quoted value, precede it with an additional matching quote character. For example, if you want to escape the default character ' " ', use ' "" '. @default " + "rangePartitioning": { # Range partitioning specification for the destination table. Only one of timePartitioning and rangePartitioning should be specified. + "field": "A String", # Required. [Experimental] The table is partitioned by this field. The field must be a top-level NULLABLE/REQUIRED field. The only supported type is INTEGER/INT64. + "range": { # [Experimental] Defines the ranges for range partitioning. + "end": "A String", # [Experimental] The end of range partitioning, exclusive. + "interval": "A String", # [Experimental] The width of each interval. + "start": "A String", # [Experimental] The start of range partitioning, inclusive. }, }, - "referenceFileSchemaUri": "A String", # User provided referencing file with the expected reader schema, Available for the format: AVRO, PARQUET, ORC. - "schema": { # [Optional] The schema for the destination table. The schema can be omitted if the destination table already exists, or if you're loading data from Google Cloud Datastore. + "referenceFileSchemaUri": "A String", # Optional. The user can provide a reference file with the reader schema. This file is only loaded if it is part of source URIs, but is not loaded otherwise. It is enabled for the following formats: AVRO, PARQUET, ORC. + "schema": { # Schema of a table # Optional. The schema for the destination table. The schema can be omitted if the destination table already exists, or if you're loading data from Google Cloud Datastore. "fields": [ # Describes the fields in a table. - { - "categories": { # [Optional] The categories attached to this field, used for field-level access control. - "names": [ # A list of category resource names. For example, "projects/1/taxonomies/2/categories/3". At most 5 categories are allowed. + { # A field in TableSchema + "categories": { # Deprecated. + "names": [ # Deprecated. "A String", ], }, - "collation": "A String", # Optional. Collation specification of the field. It only can be set on string type field. - "defaultValueExpression": "A String", # Optional. A SQL expression to specify the default value for this field. It can only be set for top level fields (columns). You can use struct or array expression to specify default value for the entire struct or array. The valid SQL expressions are: - Literals for all data types, including STRUCT and ARRAY. - Following functions: - CURRENT_TIMESTAMP - CURRENT_TIME - CURRENT_DATE - CURRENT_DATETIME - GENERATE_UUID - RAND - SESSION_USER - ST_GEOGPOINT - Struct or array composed with the above allowed functions, for example, [CURRENT_DATE(), DATE '2020-01-01'] - "description": "A String", # [Optional] The field description. The maximum length is 1,024 characters. - "fields": [ # [Optional] Describes the nested schema fields if the type property is set to RECORD. + "collation": "A String", # Optional. Field collation can be set only when the type of field is STRING. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior. + "defaultValueExpression": "A String", # Optional. A SQL expression to specify the [default value] (https://cloud.google.com/bigquery/docs/default-values) for this field. + "description": "A String", # Optional. The field description. The maximum length is 1,024 characters. + "fields": [ # Optional. Describes the nested schema fields if the type property is set to RECORD. # Object with schema name: TableFieldSchema ], - "maxLength": "A String", # [Optional] Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES". - "mode": "A String", # [Optional] The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE. - "name": "A String", # [Required] The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters. - "policyTags": { - "names": [ # A list of category resource names. For example, "projects/1/location/eu/taxonomies/2/policyTags/3". At most 1 policy tag is allowed. + "maxLength": "A String", # Optional. Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES". + "mode": "A String", # Optional. The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE. + "name": "A String", # Required. The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters. + "policyTags": { # Optional. The policy tags attached to this field, used for field-level access control. If not set, defaults to empty policy_tags. + "names": [ # A list of policy tag resource names. For example, "projects/1/locations/eu/taxonomies/2/policyTags/3". At most 1 policy tag is currently allowed. "A String", ], }, - "precision": "A String", # [Optional] Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: - Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] - Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: - If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. - If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): - If type = "NUMERIC": 1 ≤ precision ≤ 29. - If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid. - "rangeElementType": { # Optional. The subtype of the RANGE, if the type of this field is RANGE. If the type is RANGE, this field is required. Possible values for the field element type of a RANGE include: - DATE - DATETIME - TIMESTAMP - "type": "A String", # The field element type of a RANGE + "precision": "A String", # Optional. Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: * Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] * Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: * If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. * If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): * If type = "NUMERIC": 1 ≤ precision ≤ 29. * If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid. + "rangeElementType": { # Represents the type of a field element. + "type": "A String", # Required. The type of a field element. See TableFieldSchema.type. }, - "roundingMode": "A String", # Optional. Rounding Mode specification of the field. It only can be set on NUMERIC or BIGNUMERIC type fields. - "scale": "A String", # [Optional] See documentation for precision. - "type": "A String", # [Required] The field data type. Possible values include STRING, BYTES, INTEGER, INT64 (same as INTEGER), FLOAT, FLOAT64 (same as FLOAT), NUMERIC, BIGNUMERIC, BOOLEAN, BOOL (same as BOOLEAN), TIMESTAMP, DATE, TIME, DATETIME, INTERVAL, RECORD (where RECORD indicates that the field contains a nested schema) or STRUCT (same as RECORD). + "roundingMode": "A String", # Optional. Specifies the rounding mode to be used when storing values of NUMERIC and BIGNUMERIC type. + "scale": "A String", # Optional. See documentation for precision. + "type": "A String", # Required. The field data type. Possible values include: * STRING * BYTES * INTEGER (or INT64) * FLOAT (or FLOAT64) * BOOLEAN (or BOOL) * TIMESTAMP * DATE * TIME * DATETIME * GEOGRAPHY * NUMERIC * BIGNUMERIC * JSON * RECORD (or STRUCT) Use of RECORD/STRUCT indicates that the field contains a nested schema. }, ], }, "schemaInline": "A String", # [Deprecated] The inline schema. For CSV schemas, specify as "Field1:Type1[,Field2:Type2]*". For example, "foo:STRING, bar:INTEGER, baz:FLOAT". "schemaInlineFormat": "A String", # [Deprecated] The format of the schemaInline property. - "schemaUpdateOptions": [ # Allows the schema of the destination table to be updated as a side effect of the load job if a schema is autodetected or supplied in the job configuration. Schema update options are supported in two cases: when writeDisposition is WRITE_APPEND; when writeDisposition is WRITE_TRUNCATE and the destination table is a partition of a table, specified by partition decorators. For normal tables, WRITE_TRUNCATE will always overwrite the schema. One or more of the following values are specified: ALLOW_FIELD_ADDITION: allow adding a nullable field to the schema. ALLOW_FIELD_RELAXATION: allow relaxing a required field in the original schema to nullable. + "schemaUpdateOptions": [ # Allows the schema of the destination table to be updated as a side effect of the load job if a schema is autodetected or supplied in the job configuration. Schema update options are supported in two cases: when writeDisposition is WRITE_APPEND; when writeDisposition is WRITE_TRUNCATE and the destination table is a partition of a table, specified by partition decorators. For normal tables, WRITE_TRUNCATE will always overwrite the schema. One or more of the following values are specified: * ALLOW_FIELD_ADDITION: allow adding a nullable field to the schema. * ALLOW_FIELD_RELAXATION: allow relaxing a required field in the original schema to nullable. "A String", ], - "skipLeadingRows": 42, # [Optional] The number of rows at the top of a CSV file that BigQuery will skip when loading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped. - "sourceFormat": "A String", # [Optional] The format of the data files. For CSV files, specify "CSV". For datastore backups, specify "DATASTORE_BACKUP". For newline-delimited JSON, specify "NEWLINE_DELIMITED_JSON". For Avro, specify "AVRO". For parquet, specify "PARQUET". For orc, specify "ORC". The default value is CSV. + "skipLeadingRows": 42, # Optional. The number of rows at the top of a CSV file that BigQuery will skip when loading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema. + "sourceFormat": "A String", # Optional. The format of the data files. For CSV files, specify "CSV". For datastore backups, specify "DATASTORE_BACKUP". For newline-delimited JSON, specify "NEWLINE_DELIMITED_JSON". For Avro, specify "AVRO". For parquet, specify "PARQUET". For orc, specify "ORC". The default value is CSV. "sourceUris": [ # [Required] The fully-qualified URIs that point to your data in Google Cloud. For Google Cloud Storage URIs: Each URI can contain one '*' wildcard character and it must come after the 'bucket' name. Size limits related to load jobs apply to external data sources. For Google Cloud Bigtable URIs: Exactly one URI can be specified and it has be a fully specified and valid HTTPS URL for a Google Cloud Bigtable table. For Google Cloud Datastore backups: Exactly one URI can be specified. Also, the '*' wildcard character is not allowed. "A String", ], "timePartitioning": { # Time-based partitioning specification for the destination table. Only one of timePartitioning and rangePartitioning should be specified. - "expirationMs": "A String", # [Optional] Number of milliseconds for which to keep the storage for partitions in the table. The storage in a partition will have an expiration time of its partition time plus this value. - "field": "A String", # [Beta] [Optional] If not set, the table is partitioned by pseudo column, referenced via either '_PARTITIONTIME' as TIMESTAMP type, or '_PARTITIONDATE' as DATE type. If field is specified, the table is instead partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED. - "requirePartitionFilter": True or False, - "type": "A String", # [Required] The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively. When the type is not specified, the default behavior is DAY. + "expirationMs": "A String", # Optional. Number of milliseconds for which to keep the storage for a partition. A wrapper is used here because 0 is an invalid value. + "field": "A String", # Optional. If not set, the table is partitioned by pseudo column '_PARTITIONTIME'; if set, the table is partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED. A wrapper is used here because an empty string is an invalid value. + "requirePartitionFilter": false, # If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. This field is deprecated; please set the field with the same name on the table itself instead. This field needs a wrapper because we want to output the default value, false, if the user explicitly set it. + "type": "A String", # Required. The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively. }, - "useAvroLogicalTypes": True or False, # [Optional] If sourceFormat is set to "AVRO", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER). - "writeDisposition": "A String", # [Optional] Specifies the action that occurs if the destination table already exists. The following values are supported: WRITE_TRUNCATE: If the table already exists, BigQuery overwrites the table data. WRITE_APPEND: If the table already exists, BigQuery appends the data to the table. WRITE_EMPTY: If the table already exists and contains data, a 'duplicate' error is returned in the job result. The default value is WRITE_APPEND. Each action is atomic and only occurs if BigQuery is able to complete the job successfully. Creation, truncation and append actions occur as one atomic update upon job completion. + "useAvroLogicalTypes": True or False, # Optional. If sourceFormat is set to "AVRO", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER). + "writeDisposition": "A String", # Optional. Specifies the action that occurs if the destination table already exists. The following values are supported: * WRITE_TRUNCATE: If the table already exists, BigQuery overwrites the data, removes the constraints and uses the schema from the load job. * WRITE_APPEND: If the table already exists, BigQuery appends the data to the table. * WRITE_EMPTY: If the table already exists and contains data, a 'duplicate' error is returned in the job result. The default value is WRITE_APPEND. Each action is atomic and only occurs if BigQuery is able to complete the job successfully. Creation, truncation and append actions occur as one atomic update upon job completion. }, - "query": { # [Pick one] Configures a query job. - "allowLargeResults": false, # [Optional] If true and query uses legacy SQL dialect, allows the query to produce arbitrarily large result tables at a slight cost in performance. Requires destinationTable to be set. For standard SQL queries, this flag is ignored and large results are always allowed. However, you must still set destinationTable when result size exceeds the allowed maximum response size. - "clustering": { # [Beta] Clustering specification for the destination table. Must be specified with time-based partitioning, data in the table will be first partitioned and subsequently clustered. - "fields": [ # [Repeated] One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. When you cluster a table using multiple columns, the order of columns you specify is important. The order of the specified columns determines the sort order of the data. + "query": { # JobConfigurationQuery configures a BigQuery query job. # [Pick one] Configures a query job. + "allowLargeResults": false, # Optional. If true and query uses legacy SQL dialect, allows the query to produce arbitrarily large result tables at a slight cost in performance. Requires destinationTable to be set. For GoogleSQL queries, this flag is ignored and large results are always allowed. However, you must still set destinationTable when result size exceeds the allowed maximum response size. + "clustering": { # Configures table clustering. # Clustering specification for the destination table. + "fields": [ # One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. The ordering of the clustering fields should be prioritized from most to least important for filtering purposes. Additional information on limitations can be found here: https://cloud.google.com/bigquery/docs/creating-clustered-tables#limitations "A String", ], }, - "connectionProperties": [ # Connection properties. - { - "key": "A String", # [Required] Name of the connection property to set. - "value": "A String", # [Required] Value of the connection property. + "connectionProperties": [ # Connection properties which can modify the query behavior. + { # A connection-level property to customize query behavior. Under JDBC, these correspond directly to connection properties passed to the DriverManager. Under ODBC, these correspond to properties in the connection string. Currently supported connection properties: * **dataset_project_id**: represents the default project for datasets that are used in the query. Setting the system variable `@@dataset_project_id` achieves the same behavior. For more information about system variables, see: https://cloud.google.com/bigquery/docs/reference/system-variables * **time_zone**: represents the default timezone used to run the query. * **session_id**: associates the query with a given session. * **query_label**: associates the query with a given job label. If set, all subsequent queries in a script or session will have this label. For the format in which a you can specify a query label, see labels in the JobConfiguration resource type: https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#jobconfiguration Additional properties are allowed, but ignored. Specifying multiple connection properties with the same key returns an error. + "key": "A String", # The key of the property to set. + "value": "A String", # The value of the property to set. }, ], "continuous": True or False, # [Optional] Specifies whether the query should be executed as a continuous query. The default value is false. - "createDisposition": "A String", # [Optional] Specifies whether the job is allowed to create new tables. The following values are supported: CREATE_IF_NEEDED: If the table does not exist, BigQuery creates the table. CREATE_NEVER: The table must already exist. If it does not, a 'notFound' error is returned in the job result. The default value is CREATE_IF_NEEDED. Creation, truncation and append actions occur as one atomic update upon job completion. - "createSession": True or False, # If true, creates a new session, where session id will be a server generated random id. If false, runs query with an existing session_id passed in ConnectionProperty, otherwise runs query in non-session mode. - "defaultDataset": { # [Optional] Specifies the default dataset to use for unqualified table names in the query. Note that this does not alter behavior of unqualified dataset names. - "datasetId": "A String", # [Required] A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. - "projectId": "A String", # [Optional] The ID of the project containing this dataset. + "createDisposition": "A String", # Optional. Specifies whether the job is allowed to create new tables. The following values are supported: * CREATE_IF_NEEDED: If the table does not exist, BigQuery creates the table. * CREATE_NEVER: The table must already exist. If it does not, a 'notFound' error is returned in the job result. The default value is CREATE_IF_NEEDED. Creation, truncation and append actions occur as one atomic update upon job completion. + "createSession": True or False, # If this property is true, the job creates a new session using a randomly generated session_id. To continue using a created session with subsequent queries, pass the existing session identifier as a `ConnectionProperty` value. The session identifier is returned as part of the `SessionInfo` message within the query statistics. The new session's location will be set to `Job.JobReference.location` if it is present, otherwise it's set to the default location based on existing routing logic. + "defaultDataset": { # Optional. Specifies the default dataset to use for unqualified table names in the query. This setting does not alter behavior of unqualified dataset names. Setting the system variable `@@dataset_id` achieves the same behavior. See https://cloud.google.com/bigquery/docs/reference/system-variables for more information on system variables. + "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. + "projectId": "A String", # Optional. The ID of the project containing this dataset. }, - "destinationEncryptionConfiguration": { # Custom encryption configuration (e.g., Cloud KMS keys). + "destinationEncryptionConfiguration": { # Custom encryption configuration (e.g., Cloud KMS keys) "kmsKeyName": "A String", # Optional. Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key. }, - "destinationTable": { # [Optional] Describes the table where the query results should be stored. If not present, a new table will be created to store the results. This property must be set for large results that exceed the maximum response size. - "datasetId": "A String", # [Required] The ID of the dataset containing this table. - "projectId": "A String", # [Required] The ID of the project containing this table. - "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. + "destinationTable": { # Optional. Describes the table where the query results should be stored. This property must be set for large results that exceed the maximum response size. For queries that produce anonymous (cached) results, this field will be populated by BigQuery. + "datasetId": "A String", # Required. The ID of the dataset containing this table. + "projectId": "A String", # Required. The ID of the project containing this table. + "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`. }, - "flattenResults": true, # [Optional] If true and query uses legacy SQL dialect, flattens all nested and repeated fields in the query results. allowLargeResults must be true if this is set to false. For standard SQL queries, this flag is ignored and results are never flattened. - "maximumBillingTier": 1, # [Optional] Limits the billing tier for this job. Queries that have resource usage beyond this tier will fail (without incurring a charge). If unspecified, this will be set to your project default. - "maximumBytesBilled": "A String", # [Optional] Limits the bytes billed for this job. Queries that will have bytes billed beyond this limit will fail (without incurring a charge). If unspecified, this will be set to your project default. - "parameterMode": "A String", # Standard SQL only. Set to POSITIONAL to use positional (?) query parameters or to NAMED to use named (@myparam) query parameters in this query. + "flattenResults": true, # Optional. If true and query uses legacy SQL dialect, flattens all nested and repeated fields in the query results. allowLargeResults must be true if this is set to false. For GoogleSQL queries, this flag is ignored and results are never flattened. + "maximumBillingTier": 1, # Optional. [Deprecated] Maximum billing tier allowed for this query. The billing tier controls the amount of compute resources allotted to the query, and multiplies the on-demand cost of the query accordingly. A query that runs within its allotted resources will succeed and indicate its billing tier in statistics.query.billingTier, but if the query exceeds its allotted resources, it will fail with billingTierLimitExceeded. WARNING: The billed byte amount can be multiplied by an amount up to this number! Most users should not need to alter this setting, and we recommend that you avoid introducing new uses of it. + "maximumBytesBilled": "A String", # Limits the bytes billed for this job. Queries that will have bytes billed beyond this limit will fail (without incurring a charge). If unspecified, this will be set to your project default. + "parameterMode": "A String", # GoogleSQL only. Set to POSITIONAL to use positional (?) query parameters or to NAMED to use named (@myparam) query parameters in this query. "preserveNulls": True or False, # [Deprecated] This property is deprecated. - "priority": "A String", # [Optional] Specifies a priority for the query. Possible values include INTERACTIVE and BATCH. The default value is INTERACTIVE. - "query": "A String", # [Required] SQL query text to execute. The useLegacySql field can be used to indicate whether the query uses legacy SQL or standard SQL. - "queryParameters": [ # Query parameters for standard SQL queries. - { - "name": "A String", # [Optional] If unset, this is a positional parameter. Otherwise, should be unique within a query. - "parameterType": { # [Required] The type of this parameter. - "arrayType": # Object with schema name: QueryParameterType # [Optional] The type of the array's elements, if this is an array. - "rangeElementType": # Object with schema name: QueryParameterType # [Optional] The element type of the range, if this is a range. - "structTypes": [ # [Optional] The types of the fields of this struct, in order, if this is a struct. - { - "description": "A String", # [Optional] Human-oriented description of the field. - "name": "A String", # [Optional] The name of this field. - "type": # Object with schema name: QueryParameterType # [Required] The type of this field. + "priority": "A String", # Optional. Specifies a priority for the query. Possible values include INTERACTIVE and BATCH. The default value is INTERACTIVE. + "query": "A String", # [Required] SQL query text to execute. The useLegacySql field can be used to indicate whether the query uses legacy SQL or GoogleSQL. + "queryParameters": [ # Query parameters for GoogleSQL queries. + { # A parameter given to a query. + "name": "A String", # Optional. If unset, this is a positional parameter. Otherwise, should be unique within a query. + "parameterType": { # The type of a query parameter. # Required. The type of this parameter. + "arrayType": # Object with schema name: QueryParameterType # Optional. The type of the array's elements, if this is an array. + "rangeElementType": # Object with schema name: QueryParameterType # Optional. The element type of the range, if this is a range. + "structTypes": [ # Optional. The types of the fields of this struct, in order, if this is a struct. + { # The type of a struct parameter. + "description": "A String", # Optional. Human-oriented description of the field. + "name": "A String", # Optional. The name of this field. + "type": # Object with schema name: QueryParameterType # Required. The type of this field. }, ], - "type": "A String", # [Required] The top level type of this field. + "type": "A String", # Required. The top level type of this field. }, - "parameterValue": { # [Required] The value of this parameter. - "arrayValues": [ # [Optional] The array values, if this is an array type. + "parameterValue": { # The value of a query parameter. # Required. The value of this parameter. + "arrayValues": [ # Optional. The array values, if this is an array type. # Object with schema name: QueryParameterValue ], - "rangeValue": { # [Optional] The range value, if this is a range type. - "end": # Object with schema name: QueryParameterValue - "start": # Object with schema name: QueryParameterValue + "rangeValue": { # Represents the value of a range. # Optional. The range value, if this is a range type. + "end": # Object with schema name: QueryParameterValue # Optional. The end value of the range. A missing value represents an unbounded end. + "start": # Object with schema name: QueryParameterValue # Optional. The start value of the range. A missing value represents an unbounded start. }, - "structValues": { # [Optional] The struct field values, in order of the struct type's declaration. + "structValues": { # The struct field values. "a_key": # Object with schema name: QueryParameterValue }, - "value": "A String", # [Optional] The value of this value, if a simple scalar type. + "value": "A String", # Optional. The value of this value, if a simple scalar type. }, }, ], - "rangePartitioning": { # [TrustedTester] Range partitioning specification for this table. Only one of timePartitioning and rangePartitioning should be specified. - "field": "A String", # [TrustedTester] [Required] The table is partitioned by this field. The field must be a top-level NULLABLE/REQUIRED field. The only supported type is INTEGER/INT64. - "range": { # [TrustedTester] [Required] Defines the ranges for range partitioning. - "end": "A String", # [TrustedTester] [Required] The end of range partitioning, exclusive. - "interval": "A String", # [TrustedTester] [Required] The width of each interval. - "start": "A String", # [TrustedTester] [Required] The start of range partitioning, inclusive. + "rangePartitioning": { # Range partitioning specification for the destination table. Only one of timePartitioning and rangePartitioning should be specified. + "field": "A String", # Required. [Experimental] The table is partitioned by this field. The field must be a top-level NULLABLE/REQUIRED field. The only supported type is INTEGER/INT64. + "range": { # [Experimental] Defines the ranges for range partitioning. + "end": "A String", # [Experimental] The end of range partitioning, exclusive. + "interval": "A String", # [Experimental] The width of each interval. + "start": "A String", # [Experimental] The start of range partitioning, inclusive. }, }, - "schemaUpdateOptions": [ # Allows the schema of the destination table to be updated as a side effect of the query job. Schema update options are supported in two cases: when writeDisposition is WRITE_APPEND; when writeDisposition is WRITE_TRUNCATE and the destination table is a partition of a table, specified by partition decorators. For normal tables, WRITE_TRUNCATE will always overwrite the schema. One or more of the following values are specified: ALLOW_FIELD_ADDITION: allow adding a nullable field to the schema. ALLOW_FIELD_RELAXATION: allow relaxing a required field in the original schema to nullable. + "schemaUpdateOptions": [ # Allows the schema of the destination table to be updated as a side effect of the query job. Schema update options are supported in two cases: when writeDisposition is WRITE_APPEND; when writeDisposition is WRITE_TRUNCATE and the destination table is a partition of a table, specified by partition decorators. For normal tables, WRITE_TRUNCATE will always overwrite the schema. One or more of the following values are specified: * ALLOW_FIELD_ADDITION: allow adding a nullable field to the schema. * ALLOW_FIELD_RELAXATION: allow relaxing a required field in the original schema to nullable. "A String", ], - "tableDefinitions": { # [Optional] If querying an external data source outside of BigQuery, describes the data format, location and other properties of the data source. By defining these properties, the data source can then be queried as if it were a standard BigQuery table. + "scriptOptions": { # Options related to script execution. # Options controlling the execution of scripts. + "keyResultStatement": "A String", # Determines which statement in the script represents the "key result", used to populate the schema and query results of the script job. Default is LAST. + "statementByteBudget": "A String", # Limit on the number of bytes billed per statement. Exceeding this budget results in an error. + "statementTimeoutMs": "A String", # Timeout period for each statement in a script. + }, + "systemVariables": { # System variables given to a query. # Output only. System variables for GoogleSQL queries. A system variable is output if the variable is settable and its value differs from the system default. "@@" prefix is not included in the name of the System variables. + "types": { # Output only. Data type for each system variable. + "a_key": { # The data type of a variable such as a function argument. Examples include: * INT64: `{"typeKind": "INT64"}` * ARRAY: { "typeKind": "ARRAY", "arrayElementType": {"typeKind": "STRING"} } * STRUCT>: { "typeKind": "STRUCT", "structType": { "fields": [ { "name": "x", "type": {"typeKind": "STRING"} }, { "name": "y", "type": { "typeKind": "ARRAY", "arrayElementType": {"typeKind": "DATE"} } } ] } } + "arrayElementType": # Object with schema name: StandardSqlDataType # The type of the array's elements, if type_kind = "ARRAY". + "rangeElementType": # Object with schema name: StandardSqlDataType # The type of the range's elements, if type_kind = "RANGE". + "structType": { # The representation of a SQL STRUCT type. # The fields of this struct, in order, if type_kind = "STRUCT". + "fields": [ # Fields within the struct. + { # A field or a column. + "name": "A String", # Optional. The name of this field. Can be absent for struct fields. + "type": # Object with schema name: StandardSqlDataType # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field). + }, + ], + }, + "typeKind": "A String", # Required. The top level type of this field. Can be any GoogleSQL data type (e.g., "INT64", "DATE", "ARRAY"). + }, + }, + "values": { # Output only. Value for each system variable. + "a_key": "", # Properties of the object. + }, + }, + "tableDefinitions": { # Optional. You can specify external table definitions, which operate as ephemeral tables that can be queried. These definitions are configured using a JSON map, where the string key represents the table identifier, and the value is the corresponding external data configuration object. "a_key": { "autodetect": True or False, # Try to detect schema and format options automatically. Any option specified explicitly will be honored. - "avroOptions": { # Additional properties to set if sourceFormat is set to Avro. - "useAvroLogicalTypes": True or False, # [Optional] If sourceFormat is set to "AVRO", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER). - }, - "bigtableOptions": { # [Optional] Additional options if sourceFormat is set to BIGTABLE. - "columnFamilies": [ # [Optional] List of column families to expose in the table schema along with their types. This list restricts the column families that can be referenced in queries and specifies their value types. You can use this list to do type conversions - see the 'type' field for more details. If you leave this list empty, all column families are present in the table schema and their values are read as BYTES. During a query only the column families referenced in that query are read from Bigtable. - { - "columns": [ # [Optional] Lists of columns that should be exposed as individual fields as opposed to a list of (column name, value) pairs. All columns whose qualifier matches a qualifier in this list can be accessed as .. Other columns can be accessed as a list through .Column field. - { - "encoding": "A String", # [Optional] The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. 'encoding' can also be set at the column family level. However, the setting at this level takes precedence if 'encoding' is set at both levels. - "fieldName": "A String", # [Optional] If the qualifier is not a valid BigQuery field identifier i.e. does not match [a-zA-Z][a-zA-Z0-9_]*, a valid identifier must be provided as the column field name and is used as field name in queries. - "onlyReadLatest": True or False, # [Optional] If this is set, only the latest version of value in this column are exposed. 'onlyReadLatest' can also be set at the column family level. However, the setting at this level takes precedence if 'onlyReadLatest' is set at both levels. - "qualifierEncoded": "A String", # [Required] Qualifier of the column. Columns in the parent column family that has this exact qualifier are exposed as . field. If the qualifier is valid UTF-8 string, it can be specified in the qualifier_string field. Otherwise, a base-64 encoded value must be set to qualifier_encoded. The column field name is the same as the column qualifier. However, if the qualifier is not a valid BigQuery field identifier i.e. does not match [a-zA-Z][a-zA-Z0-9_]*, a valid identifier must be provided as field_name. - "qualifierString": "A String", - "type": "A String", # [Optional] The type to convert the value in cells of this column. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive) - BYTES STRING INTEGER FLOAT BOOLEAN Default type is BYTES. 'type' can also be set at the column family level. However, the setting at this level takes precedence if 'type' is set at both levels. - }, - ], - "encoding": "A String", # [Optional] The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. This can be overridden for a specific column by listing that column in 'columns' and specifying an encoding for it. + "avroOptions": { # Options for external data sources. # Optional. Additional properties to set if sourceFormat is set to AVRO. + "useAvroLogicalTypes": True or False, # Optional. If sourceFormat is set to "AVRO", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER). + }, + "bigtableOptions": { # Options specific to Google Cloud Bigtable data sources. # Optional. Additional options if sourceFormat is set to BIGTABLE. + "columnFamilies": [ # Optional. List of column families to expose in the table schema along with their types. This list restricts the column families that can be referenced in queries and specifies their value types. You can use this list to do type conversions - see the 'type' field for more details. If you leave this list empty, all column families are present in the table schema and their values are read as BYTES. During a query only the column families referenced in that query are read from Bigtable. + { # Information related to a Bigtable column family. + "columns": [ # Optional. Lists of columns that should be exposed as individual fields as opposed to a list of (column name, value) pairs. All columns whose qualifier matches a qualifier in this list can be accessed as .. Other columns can be accessed as a list through .Column field. + { # Information related to a Bigtable column. + "encoding": "A String", # Optional. The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. 'encoding' can also be set at the column family level. However, the setting at this level takes precedence if 'encoding' is set at both levels. + "fieldName": "A String", # Optional. If the qualifier is not a valid BigQuery field identifier i.e. does not match a-zA-Z*, a valid identifier must be provided as the column field name and is used as field name in queries. + "onlyReadLatest": True or False, # Optional. If this is set, only the latest version of value in this column are exposed. 'onlyReadLatest' can also be set at the column family level. However, the setting at this level takes precedence if 'onlyReadLatest' is set at both levels. + "qualifierEncoded": "A String", # [Required] Qualifier of the column. Columns in the parent column family that has this exact qualifier are exposed as . field. If the qualifier is valid UTF-8 string, it can be specified in the qualifier_string field. Otherwise, a base-64 encoded value must be set to qualifier_encoded. The column field name is the same as the column qualifier. However, if the qualifier is not a valid BigQuery field identifier i.e. does not match a-zA-Z*, a valid identifier must be provided as field_name. + "qualifierString": "A String", # Qualifier string. + "type": "A String", # Optional. The type to convert the value in cells of this column. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive): * BYTES * STRING * INTEGER * FLOAT * BOOLEAN * JSON Default type is BYTES. 'type' can also be set at the column family level. However, the setting at this level takes precedence if 'type' is set at both levels. + }, + ], + "encoding": "A String", # Optional. The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. This can be overridden for a specific column by listing that column in 'columns' and specifying an encoding for it. "familyId": "A String", # Identifier of the column family. - "onlyReadLatest": True or False, # [Optional] If this is set only the latest version of value are exposed for all columns in this column family. This can be overridden for a specific column by listing that column in 'columns' and specifying a different setting for that column. - "type": "A String", # [Optional] The type to convert the value in cells of this column family. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive) - BYTES STRING INTEGER FLOAT BOOLEAN Default type is BYTES. This can be overridden for a specific column by listing that column in 'columns' and specifying a type for it. + "onlyReadLatest": True or False, # Optional. If this is set only the latest version of value are exposed for all columns in this column family. This can be overridden for a specific column by listing that column in 'columns' and specifying a different setting for that column. + "type": "A String", # Optional. The type to convert the value in cells of this column family. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive): * BYTES * STRING * INTEGER * FLOAT * BOOLEAN * JSON Default type is BYTES. This can be overridden for a specific column by listing that column in 'columns' and specifying a type for it. }, ], - "ignoreUnspecifiedColumnFamilies": True or False, # [Optional] If field is true, then the column families that are not specified in columnFamilies list are not exposed in the table schema. Otherwise, they are read with BYTES type values. The default value is false. - "readRowkeyAsString": True or False, # [Optional] If field is true, then the rowkey column families will be read and converted to string. Otherwise they are read with BYTES type values and users need to manually cast them with CAST if necessary. The default value is false. - }, - "compression": "A String", # [Optional] The compression type of the data source. Possible values include GZIP and NONE. The default value is NONE. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups and Avro formats. - "connectionId": "A String", # [Optional, Trusted Tester] Connection for external data source. - "csvOptions": { # Additional properties to set if sourceFormat is set to CSV. - "allowJaggedRows": True or False, # [Optional] Indicates if BigQuery should accept rows that are missing trailing optional columns. If true, BigQuery treats missing trailing columns as null values. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. - "allowQuotedNewlines": True or False, # [Optional] Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false. - "encoding": "A String", # [Optional] The character encoding of the data. The supported values are UTF-8 or ISO-8859-1. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the quote and fieldDelimiter properties. - "fieldDelimiter": "A String", # [Optional] The separator for fields in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. BigQuery also supports the escape sequence "\t" to specify a tab separator. The default value is a comma (','). - "nullMarker": "A String", # [Optional] An custom string that will represent a NULL value in CSV import data. - "preserveAsciiControlCharacters": True or False, # [Optional] Preserves the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\x00' to '\x1F') when loading from CSV. Only applicable to CSV, ignored for other formats. - "quote": """, # [Optional] The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ('"'). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true. - "skipLeadingRows": "A String", # [Optional] The number of rows at the top of a CSV file that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema. - }, - "decimalTargetTypes": [ # [Optional] Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown. Example: Suppose the value of this field is ["NUMERIC", "BIGNUMERIC"]. If (precision,scale) is: (38,9) -> NUMERIC; (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits); (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits); (76,38) -> BIGNUMERIC; (77,38) -> BIGNUMERIC (error if value exeeds supported range). This field cannot contain duplicate types. The order of the types in this field is ignored. For example, ["BIGNUMERIC", "NUMERIC"] is the same as ["NUMERIC", "BIGNUMERIC"] and NUMERIC always takes precedence over BIGNUMERIC. Defaults to ["NUMERIC", "STRING"] for ORC and ["NUMERIC"] for the other file formats. + "ignoreUnspecifiedColumnFamilies": True or False, # Optional. If field is true, then the column families that are not specified in columnFamilies list are not exposed in the table schema. Otherwise, they are read with BYTES type values. The default value is false. + "outputColumnFamiliesAsJson": True or False, # Optional. If field is true, then each column family will be read as a single JSON column. Otherwise they are read as a repeated cell structure containing timestamp/value tuples. The default value is false. + "readRowkeyAsString": True or False, # Optional. If field is true, then the rowkey column families will be read and converted to string. Otherwise they are read with BYTES type values and users need to manually cast them with CAST if necessary. The default value is false. + }, + "compression": "A String", # Optional. The compression type of the data source. Possible values include GZIP and NONE. The default value is NONE. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups, Avro, ORC and Parquet formats. An empty string is an invalid value. + "connectionId": "A String", # Optional. The connection specifying the credentials to be used to read external storage, such as Azure Blob, Cloud Storage, or S3. The connection_id can have the form "<project\_id>.<location\_id>.<connection\_id>" or "projects/<project\_id>/locations/<location\_id>/connections/<connection\_id>". + "csvOptions": { # Information related to a CSV data source. # Optional. Additional properties to set if sourceFormat is set to CSV. + "allowJaggedRows": True or False, # Optional. Indicates if BigQuery should accept rows that are missing trailing optional columns. If true, BigQuery treats missing trailing columns as null values. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. + "allowQuotedNewlines": True or False, # Optional. Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false. + "encoding": "A String", # Optional. The character encoding of the data. The supported values are UTF-8, ISO-8859-1, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the quote and fieldDelimiter properties. + "fieldDelimiter": "A String", # Optional. The separator character for fields in a CSV file. The separator is interpreted as a single byte. For files encoded in ISO-8859-1, any single character can be used as a separator. For files encoded in UTF-8, characters represented in decimal range 1-127 (U+0001-U+007F) can be used without any modification. UTF-8 characters encoded with multiple bytes (i.e. U+0080 and above) will have only the first byte used for separating fields. The remaining bytes will be treated as a part of the field. BigQuery also supports the escape sequence "\t" (U+0009) to specify a tab separator. The default value is comma (",", U+002C). + "nullMarker": "A String", # [Optional] A custom string that will represent a NULL value in CSV import data. + "preserveAsciiControlCharacters": True or False, # Optional. Indicates if the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\x00' to '\x1F') are preserved. + "quote": """, # Optional. The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ("). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true. To include the specific quote character within a quoted value, precede it with an additional matching quote character. For example, if you want to escape the default character ' " ', use ' "" '. + "skipLeadingRows": "A String", # Optional. The number of rows at the top of a CSV file that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema. + }, + "decimalTargetTypes": [ # Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown. Example: Suppose the value of this field is ["NUMERIC", "BIGNUMERIC"]. If (precision,scale) is: * (38,9) -> NUMERIC; * (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits); * (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits); * (76,38) -> BIGNUMERIC; * (77,38) -> BIGNUMERIC (error if value exeeds supported range). This field cannot contain duplicate types. The order of the types in this field is ignored. For example, ["BIGNUMERIC", "NUMERIC"] is the same as ["NUMERIC", "BIGNUMERIC"] and NUMERIC always takes precedence over BIGNUMERIC. Defaults to ["NUMERIC", "STRING"] for ORC and ["NUMERIC"] for the other file formats. "A String", ], - "fileSetSpecType": "A String", # [Optional] Specifies how source URIs are interpreted for constructing the file set to load. By default source URIs are expanded against the underlying storage. Other options include specifying manifest files. Only applicable to object storage systems. - "googleSheetsOptions": { # [Optional] Additional options if sourceFormat is set to GOOGLE_SHEETS. - "range": "A String", # [Optional] Range of a sheet to query from. Only used when non-empty. Typical format: sheet_name!top_left_cell_id:bottom_right_cell_id For example: sheet1!A1:B20 - "skipLeadingRows": "A String", # [Optional] The number of rows at the top of a sheet that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows that should be skipped. When autodetect is on, behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema. + "fileSetSpecType": "A String", # Optional. Specifies how source URIs are interpreted for constructing the file set to load. By default source URIs are expanded against the underlying storage. Other options include specifying manifest files. Only applicable to object storage systems. + "googleSheetsOptions": { # Options specific to Google Sheets data sources. # Optional. Additional options if sourceFormat is set to GOOGLE_SHEETS. + "range": "A String", # Optional. Range of a sheet to query from. Only used when non-empty. Typical format: sheet_name!top_left_cell_id:bottom_right_cell_id For example: sheet1!A1:B20 + "skipLeadingRows": "A String", # Optional. The number of rows at the top of a sheet that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema. }, - "hivePartitioningOptions": { # [Optional] Options to configure hive partitioning support. - "fields": [ # [Output-only] For permanent external tables, this field is populated with the hive partition keys in the order they were inferred. The types of the partition keys can be deduced by checking the table schema (which will include the partition keys). Not every API will populate this field in the output. For example, Tables.Get will populate it, but Tables.List will not contain this field. + "hivePartitioningOptions": { # Options for configuring hive partitioning detect. # Optional. When set, configures hive partitioning support. Not all storage formats support hive partitioning -- requesting hive partitioning on an unsupported format will lead to an error, as will providing an invalid specification. + "fields": [ # Output only. For permanent external tables, this field is populated with the hive partition keys in the order they were inferred. The types of the partition keys can be deduced by checking the table schema (which will include the partition keys). Not every API will populate this field in the output. For example, Tables.Get will populate it, but Tables.List will not contain this field. "A String", ], - "mode": "A String", # [Optional] When set, what mode of hive partitioning to use when reading data. The following modes are supported. (1) AUTO: automatically infer partition key name(s) and type(s). (2) STRINGS: automatically infer partition key name(s). All types are interpreted as strings. (3) CUSTOM: partition key schema is encoded in the source URI prefix. Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported types include: AVRO, CSV, JSON, ORC and Parquet. - "requirePartitionFilter": True or False, # [Optional] If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. Note that this field should only be true when creating a permanent external table or querying a temporary external table. Hive-partitioned loads with requirePartitionFilter explicitly set to true will fail. - "sourceUriPrefix": "A String", # [Optional] When hive partition detection is requested, a common prefix for all source uris should be supplied. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout. gs://bucket/path_to_table/dt=2019-01-01/country=BR/id=7/file.avro gs://bucket/path_to_table/dt=2018-12-31/country=CA/id=3/file.avro When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/ (trailing slash does not matter). - }, - "ignoreUnknownValues": True or False, # [Optional] Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names Google Cloud Bigtable: This setting is ignored. Google Cloud Datastore backups: This setting is ignored. Avro: This setting is ignored. - "jsonOptions": { # Additional properties to set if `sourceFormat` is set to `NEWLINE_DELIMITED_JSON`. - "encoding": "A String", # [Optional] The character encoding of the data. The supported values are UTF-8, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8. - }, - "maxBadRecords": 42, # [Optional] The maximum number of bad records that BigQuery can ignore when reading data. If the number of bad records exceeds this value, an invalid error is returned in the job result. This is only valid for CSV, JSON, and Google Sheets. The default value is 0, which requires that all records are valid. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups and Avro formats. - "metadataCacheMode": "A String", # [Optional] Metadata Cache Mode for the table. Set this to enable caching of metadata from external data source. - "objectMetadata": "A String", # ObjectMetadata is used to create Object Tables. Object Tables contain a listing of objects (with their metadata) found at the source_uris. If ObjectMetadata is set, source_format should be omitted. Currently SIMPLE is the only supported Object Metadata type. - "parquetOptions": { # Additional properties to set if sourceFormat is set to Parquet. - "enableListInference": True or False, # [Optional] Indicates whether to use schema inference specifically for Parquet LIST logical type. - "enumAsString": True or False, # [Optional] Indicates whether to infer Parquet ENUM logical type as STRING instead of BYTES by default. - }, - "referenceFileSchemaUri": "A String", # [Optional] Provide a referencing file with the expected table schema. Enabled for the format: AVRO, PARQUET, ORC. - "schema": { # [Optional] The schema for the data. Schema is required for CSV and JSON formats. Schema is disallowed for Google Cloud Bigtable, Cloud Datastore backups, and Avro formats. + "mode": "A String", # Optional. When set, what mode of hive partitioning to use when reading data. The following modes are supported: * AUTO: automatically infer partition key name(s) and type(s). * STRINGS: automatically infer partition key name(s). All types are strings. * CUSTOM: partition key schema is encoded in the source URI prefix. Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported formats are: JSON, CSV, ORC, Avro and Parquet. + "requirePartitionFilter": false, # Optional. If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. Note that this field should only be true when creating a permanent external table or querying a temporary external table. Hive-partitioned loads with require_partition_filter explicitly set to true will fail. + "sourceUriPrefix": "A String", # Optional. When hive partition detection is requested, a common prefix for all source uris must be required. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout: gs://bucket/path_to_table/dt=2019-06-01/country=USA/id=7/file.avro gs://bucket/path_to_table/dt=2019-05-31/country=CA/id=3/file.avro When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/. CUSTOM detection requires encoding the partitioning schema immediately after the common prefix. For CUSTOM, any of * gs://bucket/path_to_table/{dt:DATE}/{country:STRING}/{id:INTEGER} * gs://bucket/path_to_table/{dt:STRING}/{country:STRING}/{id:INTEGER} * gs://bucket/path_to_table/{dt:DATE}/{country:STRING}/{id:STRING} would all be valid source URI prefixes. + }, + "ignoreUnknownValues": True or False, # Optional. Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names Google Cloud Bigtable: This setting is ignored. Google Cloud Datastore backups: This setting is ignored. Avro: This setting is ignored. ORC: This setting is ignored. Parquet: This setting is ignored. + "jsonExtension": "A String", # Optional. Load option to be used together with source_format newline-delimited JSON to indicate that a variant of JSON is being loaded. To load newline-delimited GeoJSON, specify GEOJSON (and source_format must be set to NEWLINE_DELIMITED_JSON). + "jsonOptions": { # Json Options for load and make external tables. # Optional. Additional properties to set if sourceFormat is set to JSON. + "encoding": "A String", # Optional. The character encoding of the data. The supported values are UTF-8, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8. + }, + "maxBadRecords": 42, # Optional. The maximum number of bad records that BigQuery can ignore when reading data. If the number of bad records exceeds this value, an invalid error is returned in the job result. The default value is 0, which requires that all records are valid. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups, Avro, ORC and Parquet formats. + "metadataCacheMode": "A String", # Optional. Metadata Cache Mode for the table. Set this to enable caching of metadata from external data source. + "objectMetadata": "A String", # Optional. ObjectMetadata is used to create Object Tables. Object Tables contain a listing of objects (with their metadata) found at the source_uris. If ObjectMetadata is set, source_format should be omitted. Currently SIMPLE is the only supported Object Metadata type. + "parquetOptions": { # Parquet Options for load and make external tables. # Optional. Additional properties to set if sourceFormat is set to PARQUET. + "enableListInference": True or False, # Optional. Indicates whether to use schema inference specifically for Parquet LIST logical type. + "enumAsString": True or False, # Optional. Indicates whether to infer Parquet ENUM logical type as STRING instead of BYTES by default. + }, + "referenceFileSchemaUri": "A String", # Optional. When creating an external table, the user can provide a reference file with the table schema. This is enabled for the following formats: AVRO, PARQUET, ORC. + "schema": { # Schema of a table # Optional. The schema for the data. Schema is required for CSV and JSON formats if autodetect is not on. Schema is disallowed for Google Cloud Bigtable, Cloud Datastore backups, Avro, ORC and Parquet formats. "fields": [ # Describes the fields in a table. - { - "categories": { # [Optional] The categories attached to this field, used for field-level access control. - "names": [ # A list of category resource names. For example, "projects/1/taxonomies/2/categories/3". At most 5 categories are allowed. + { # A field in TableSchema + "categories": { # Deprecated. + "names": [ # Deprecated. + "A String", + ], + }, + "collation": "A String", # Optional. Field collation can be set only when the type of field is STRING. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior. + "defaultValueExpression": "A String", # Optional. A SQL expression to specify the [default value] (https://cloud.google.com/bigquery/docs/default-values) for this field. + "description": "A String", # Optional. The field description. The maximum length is 1,024 characters. + "fields": [ # Optional. Describes the nested schema fields if the type property is set to RECORD. + # Object with schema name: TableFieldSchema + ], + "maxLength": "A String", # Optional. Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES". + "mode": "A String", # Optional. The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE. + "name": "A String", # Required. The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters. + "policyTags": { # Optional. The policy tags attached to this field, used for field-level access control. If not set, defaults to empty policy_tags. + "names": [ # A list of policy tag resource names. For example, "projects/1/locations/eu/taxonomies/2/policyTags/3". At most 1 policy tag is currently allowed. + "A String", + ], + }, + "precision": "A String", # Optional. Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: * Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] * Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: * If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. * If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): * If type = "NUMERIC": 1 ≤ precision ≤ 29. * If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid. + "rangeElementType": { # Represents the type of a field element. + "type": "A String", # Required. The type of a field element. See TableFieldSchema.type. + }, + "roundingMode": "A String", # Optional. Specifies the rounding mode to be used when storing values of NUMERIC and BIGNUMERIC type. + "scale": "A String", # Optional. See documentation for precision. + "type": "A String", # Required. The field data type. Possible values include: * STRING * BYTES * INTEGER (or INT64) * FLOAT (or FLOAT64) * BOOLEAN (or BOOL) * TIMESTAMP * DATE * TIME * DATETIME * GEOGRAPHY * NUMERIC * BIGNUMERIC * JSON * RECORD (or STRUCT) Use of RECORD/STRUCT indicates that the field contains a nested schema. + }, + ], + }, + "sourceFormat": "A String", # [Required] The data format. For CSV files, specify "CSV". For Google sheets, specify "GOOGLE_SHEETS". For newline-delimited JSON, specify "NEWLINE_DELIMITED_JSON". For Avro files, specify "AVRO". For Google Cloud Datastore backups, specify "DATASTORE_BACKUP". For Apache Iceberg tables, specify "ICEBERG". For ORC files, specify "ORC". For Parquet files, specify "PARQUET". [Beta] For Google Cloud Bigtable, specify "BIGTABLE". + "sourceUris": [ # [Required] The fully-qualified URIs that point to your data in Google Cloud. For Google Cloud Storage URIs: Each URI can contain one '*' wildcard character and it must come after the 'bucket' name. Size limits related to load jobs apply to external data sources. For Google Cloud Bigtable URIs: Exactly one URI can be specified and it has be a fully specified and valid HTTPS URL for a Google Cloud Bigtable table. For Google Cloud Datastore backups, exactly one URI can be specified. Also, the '*' wildcard character is not allowed. + "A String", + ], + }, + }, + "timePartitioning": { # Time-based partitioning specification for the destination table. Only one of timePartitioning and rangePartitioning should be specified. + "expirationMs": "A String", # Optional. Number of milliseconds for which to keep the storage for a partition. A wrapper is used here because 0 is an invalid value. + "field": "A String", # Optional. If not set, the table is partitioned by pseudo column '_PARTITIONTIME'; if set, the table is partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED. A wrapper is used here because an empty string is an invalid value. + "requirePartitionFilter": false, # If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. This field is deprecated; please set the field with the same name on the table itself instead. This field needs a wrapper because we want to output the default value, false, if the user explicitly set it. + "type": "A String", # Required. The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively. + }, + "useLegacySql": true, # Optional. Specifies whether to use BigQuery's legacy SQL dialect for this query. The default value is true. If set to false, the query will use BigQuery's GoogleSQL: https://cloud.google.com/bigquery/sql-reference/ When useLegacySql is set to false, the value of flattenResults is ignored; query will be run as if flattenResults is false. + "useQueryCache": true, # Optional. Whether to look for the result in the query cache. The query cache is a best-effort cache that will be flushed whenever tables in the query are modified. Moreover, the query cache is only available when a query does not have a destination table specified. The default value is true. + "userDefinedFunctionResources": [ # Describes user-defined function resources used in the query. + { # This is used for defining User Defined Function (UDF) resources only when using legacy SQL. Users of GoogleSQL should leverage either DDL (e.g. CREATE [TEMPORARY] FUNCTION ... ) or the Routines API to define UDF resources. For additional information on migrating, see: https://cloud.google.com/bigquery/docs/reference/standard-sql/migrating-from-legacy-sql#differences_in_user-defined_javascript_functions + "inlineCode": "A String", # [Pick one] An inline resource that contains code for a user-defined function (UDF). Providing a inline code resource is equivalent to providing a URI for a file containing the same code. + "resourceUri": "A String", # [Pick one] A code resource to load from a Google Cloud Storage URI (gs://bucket/path). + }, + ], + "writeDisposition": "A String", # Optional. Specifies the action that occurs if the destination table already exists. The following values are supported: * WRITE_TRUNCATE: If the table already exists, BigQuery overwrites the data, removes the constraints, and uses the schema from the query result. * WRITE_APPEND: If the table already exists, BigQuery appends the data to the table. * WRITE_EMPTY: If the table already exists and contains data, a 'duplicate' error is returned in the job result. The default value is WRITE_EMPTY. Each action is atomic and only occurs if BigQuery is able to complete the job successfully. Creation, truncation and append actions occur as one atomic update upon job completion. + }, + }, + "etag": "A String", # Output only. A hash of this resource. + "id": "A String", # Output only. Opaque ID field of the job. + "jobCreationReason": { # Reason about why a Job was created from a [`jobs.query`](https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs/query) method when used with `JOB_CREATION_OPTIONAL` Job creation mode. For [`jobs.insert`](https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs/insert) method calls it will always be `REQUESTED`. This feature is not yet available. Jobs will always be created. # Output only. If set, it provides the reason why a Job was created. If not set, it should be treated as the default: REQUESTED. This feature is not yet available. Jobs will always be created. + "code": "A String", # Output only. Specifies the high level reason why a Job was created. + }, + "jobReference": { # A job reference is a fully qualified identifier for referring to a job. # Optional. Reference describing the unique-per-user name of the job. + "jobId": "A String", # Required. The ID of the job. The ID must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), or dashes (-). The maximum length is 1,024 characters. + "location": "A String", # Optional. The geographic location of the job. The default value is US. For more information about BigQuery locations, see: https://cloud.google.com/bigquery/docs/locations + "projectId": "A String", # Required. The ID of the project containing this job. + }, + "kind": "bigquery#job", # Output only. The type of the resource. + "principal_subject": "A String", # Output only. [Full-projection-only] String representation of identity of requesting party. Populated for both first- and third-party identities. Only present for APIs that support third-party identities. + "selfLink": "A String", # Output only. A URL that can be used to access the resource again. + "statistics": { # Statistics for a single job execution. # Output only. Information about the job, including starting time and ending time of the job. + "completionRatio": 3.14, # Output only. [TrustedTester] Job progress (0.0 -> 1.0) for LOAD and EXTRACT jobs. + "copy": { # Statistics for a copy job. # Output only. Statistics for a copy job. + "copiedLogicalBytes": "A String", # Output only. Number of logical bytes copied to the destination table. + "copiedRows": "A String", # Output only. Number of rows copied to the destination table. + }, + "creationTime": "A String", # Output only. Creation time of this job, in milliseconds since the epoch. This field will be present on all jobs. + "dataMaskingStatistics": { # Statistics for data-masking. # Output only. Statistics for data-masking. Present only for query and extract jobs. + "dataMaskingApplied": True or False, # Whether any accessed data was protected by the data masking. + }, + "endTime": "A String", # Output only. End time of this job, in milliseconds since the epoch. This field will be present whenever a job is in the DONE state. + "extract": { # Statistics for an extract job. # Output only. Statistics for an extract job. + "destinationUriFileCounts": [ # Output only. Number of files per destination URI or URI pattern specified in the extract configuration. These values will be in the same order as the URIs specified in the 'destinationUris' field. + "A String", + ], + "inputBytes": "A String", # Output only. Number of user bytes extracted into the result. This is the byte count as computed by BigQuery for billing purposes and doesn't have any relationship with the number of actual result bytes extracted in the desired format. + "timeline": [ # Output only. Describes a timeline of job execution. + { # Summary of the state of query execution at a given time. + "activeUnits": "A String", # Total number of active workers. This does not correspond directly to slot usage. This is the largest value observed since the last sample. + "completedUnits": "A String", # Total parallel units of work completed by this query. + "elapsedMs": "A String", # Milliseconds elapsed since the start of query execution. + "estimatedRunnableUnits": "A String", # Units of work that can be scheduled immediately. Providing additional slots for these units of work will accelerate the query, if no other query in the reservation needs additional slots. + "pendingUnits": "A String", # Total units of work remaining for the query. This number can be revised (increased or decreased) while the query is running. + "totalSlotMs": "A String", # Cumulative slot-ms consumed by the query. + }, + ], + }, + "finalExecutionDurationMs": "A String", # Output only. The duration in milliseconds of the execution of the final attempt of this job, as BigQuery may internally re-attempt to execute the job. + "load": { # Statistics for a load job. # Output only. Statistics for a load job. + "badRecords": "A String", # Output only. The number of bad records encountered. Note that if the job has failed because of more bad records encountered than the maximum allowed in the load job configuration, then this number can be less than the total number of bad records present in the input data. + "inputFileBytes": "A String", # Output only. Number of bytes of source data in a load job. + "inputFiles": "A String", # Output only. Number of source files in a load job. + "outputBytes": "A String", # Output only. Size of the loaded data in bytes. Note that while a load job is in the running state, this value may change. + "outputRows": "A String", # Output only. Number of rows imported in a load job. Note that while an import job is in the running state, this value may change. + "timeline": [ # Output only. Describes a timeline of job execution. + { # Summary of the state of query execution at a given time. + "activeUnits": "A String", # Total number of active workers. This does not correspond directly to slot usage. This is the largest value observed since the last sample. + "completedUnits": "A String", # Total parallel units of work completed by this query. + "elapsedMs": "A String", # Milliseconds elapsed since the start of query execution. + "estimatedRunnableUnits": "A String", # Units of work that can be scheduled immediately. Providing additional slots for these units of work will accelerate the query, if no other query in the reservation needs additional slots. + "pendingUnits": "A String", # Total units of work remaining for the query. This number can be revised (increased or decreased) while the query is running. + "totalSlotMs": "A String", # Cumulative slot-ms consumed by the query. + }, + ], + }, + "numChildJobs": "A String", # Output only. Number of child jobs executed. + "parentJobId": "A String", # Output only. If this is a child job, specifies the job ID of the parent. + "query": { # Statistics for a query job. # Output only. Statistics for a query job. + "biEngineStatistics": { # Statistics for a BI Engine specific query. Populated as part of JobStatistics2 # Output only. BI Engine specific Statistics. + "accelerationMode": "A String", # Output only. Specifies which mode of BI Engine acceleration was performed (if any). + "biEngineMode": "A String", # Output only. Specifies which mode of BI Engine acceleration was performed (if any). + "biEngineReasons": [ # In case of DISABLED or PARTIAL bi_engine_mode, these contain the explanatory reasons as to why BI Engine could not accelerate. In case the full query was accelerated, this field is not populated. + { # Reason why BI Engine didn't accelerate the query (or sub-query). + "code": "A String", # Output only. High-level BI Engine reason for partial or disabled acceleration + "message": "A String", # Output only. Free form human-readable reason for partial or disabled acceleration. + }, + ], + }, + "billingTier": 42, # Output only. Billing tier for the job. This is a BigQuery-specific concept which is not related to the Google Cloud notion of "free tier". The value here is a measure of the query's resource consumption relative to the amount of data scanned. For on-demand queries, the limit is 100, and all queries within this limit are billed at the standard on-demand rates. On-demand queries that exceed this limit will fail with a billingTierLimitExceeded error. + "cacheHit": True or False, # Output only. Whether the query result was fetched from the query cache. + "dclTargetDataset": { # Output only. Referenced dataset for DCL statement. + "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. + "projectId": "A String", # Optional. The ID of the project containing this dataset. + }, + "dclTargetTable": { # Output only. Referenced table for DCL statement. + "datasetId": "A String", # Required. The ID of the dataset containing this table. + "projectId": "A String", # Required. The ID of the project containing this table. + "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`. + }, + "dclTargetView": { # Output only. Referenced view for DCL statement. + "datasetId": "A String", # Required. The ID of the dataset containing this table. + "projectId": "A String", # Required. The ID of the project containing this table. + "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`. + }, + "ddlAffectedRowAccessPolicyCount": "A String", # Output only. The number of row access policies affected by a DDL statement. Present only for DROP ALL ROW ACCESS POLICIES queries. + "ddlDestinationTable": { # Output only. The table after rename. Present only for ALTER TABLE RENAME TO query. + "datasetId": "A String", # Required. The ID of the dataset containing this table. + "projectId": "A String", # Required. The ID of the project containing this table. + "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`. + }, + "ddlOperationPerformed": "A String", # Output only. The DDL operation performed, possibly dependent on the pre-existence of the DDL target. + "ddlTargetDataset": { # Output only. The DDL target dataset. Present only for CREATE/ALTER/DROP SCHEMA(dataset) queries. + "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. + "projectId": "A String", # Optional. The ID of the project containing this dataset. + }, + "ddlTargetRoutine": { # Id path of a routine. # Output only. [Beta] The DDL target routine. Present only for CREATE/DROP FUNCTION/PROCEDURE queries. + "datasetId": "A String", # Required. The ID of the dataset containing this routine. + "projectId": "A String", # Required. The ID of the project containing this routine. + "routineId": "A String", # Required. The ID of the routine. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 256 characters. + }, + "ddlTargetRowAccessPolicy": { # Id path of a row access policy. # Output only. The DDL target row access policy. Present only for CREATE/DROP ROW ACCESS POLICY queries. + "datasetId": "A String", # Required. The ID of the dataset containing this row access policy. + "policyId": "A String", # Required. The ID of the row access policy. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 256 characters. + "projectId": "A String", # Required. The ID of the project containing this row access policy. + "tableId": "A String", # Required. The ID of the table containing this row access policy. + }, + "ddlTargetTable": { # Output only. The DDL target table. Present only for CREATE/DROP TABLE/VIEW and DROP ALL ROW ACCESS POLICIES queries. + "datasetId": "A String", # Required. The ID of the dataset containing this table. + "projectId": "A String", # Required. The ID of the project containing this table. + "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`. + }, + "dmlStats": { # Detailed statistics for DML statements # Output only. Detailed statistics for DML statements INSERT, UPDATE, DELETE, MERGE or TRUNCATE. + "deletedRowCount": "A String", # Output only. Number of deleted Rows. populated by DML DELETE, MERGE and TRUNCATE statements. + "insertedRowCount": "A String", # Output only. Number of inserted Rows. Populated by DML INSERT and MERGE statements + "updatedRowCount": "A String", # Output only. Number of updated Rows. Populated by DML UPDATE and MERGE statements. + }, + "estimatedBytesProcessed": "A String", # Output only. The original estimate of bytes processed for the job. + "exportDataStatistics": { # Statistics for the EXPORT DATA statement as part of Query Job. EXTRACT JOB statistics are populated in JobStatistics4. # Output only. Stats for EXPORT DATA statement. + "fileCount": "A String", # Number of destination files generated in case of EXPORT DATA statement only. + "rowCount": "A String", # [Alpha] Number of destination rows generated in case of EXPORT DATA statement only. + }, + "externalServiceCosts": [ # Output only. Job cost breakdown as bigquery internal cost and external service costs. + { # The external service cost is a portion of the total cost, these costs are not additive with total_bytes_billed. Moreover, this field only track external service costs that will show up as BigQuery costs (e.g. training BigQuery ML job with google cloud CAIP or Automl Tables services), not other costs which may be accrued by running the query (e.g. reading from Bigtable or Cloud Storage). The external service costs with different billing sku (e.g. CAIP job is charged based on VM usage) are converted to BigQuery billed_bytes and slot_ms with equivalent amount of US dollars. Services may not directly correlate to these metrics, but these are the equivalents for billing purposes. Output only. + "bytesBilled": "A String", # External service cost in terms of bigquery bytes billed. + "bytesProcessed": "A String", # External service cost in terms of bigquery bytes processed. + "externalService": "A String", # External service name. + "reservedSlotCount": "A String", # Non-preemptable reserved slots used for external job. For example, reserved slots for Cloua AI Platform job are the VM usages converted to BigQuery slot with equivalent mount of price. + "slotMs": "A String", # External service cost in terms of bigquery slot milliseconds. + }, + ], + "loadQueryStatistics": { # Statistics for a LOAD query. # Output only. Statistics for a LOAD query. + "badRecords": "A String", # Output only. The number of bad records encountered while processing a LOAD query. Note that if the job has failed because of more bad records encountered than the maximum allowed in the load job configuration, then this number can be less than the total number of bad records present in the input data. + "bytesTransferred": "A String", # Output only. This field is deprecated. The number of bytes of source data copied over the network for a `LOAD` query. `transferred_bytes` has the canonical value for physical transferred bytes, which is used for BigQuery Omni billing. + "inputFileBytes": "A String", # Output only. Number of bytes of source data in a LOAD query. + "inputFiles": "A String", # Output only. Number of source files in a LOAD query. + "outputBytes": "A String", # Output only. Size of the loaded data in bytes. Note that while a LOAD query is in the running state, this value may change. + "outputRows": "A String", # Output only. Number of rows imported in a LOAD query. Note that while a LOAD query is in the running state, this value may change. + }, + "materializedViewStatistics": { # Statistics of materialized views considered in a query job. # Output only. Statistics of materialized views of a query job. + "materializedView": [ # Materialized views considered for the query job. Only certain materialized views are used. For a detailed list, see the child message. If many materialized views are considered, then the list might be incomplete. + { # A materialized view considered for a query job. + "chosen": True or False, # Whether the materialized view is chosen for the query. A materialized view can be chosen to rewrite multiple parts of the same query. If a materialized view is chosen to rewrite any part of the query, then this field is true, even if the materialized view was not chosen to rewrite others parts. + "estimatedBytesSaved": "A String", # If present, specifies a best-effort estimation of the bytes saved by using the materialized view rather than its base tables. + "rejectedReason": "A String", # If present, specifies the reason why the materialized view was not chosen for the query. + "tableReference": { # The candidate materialized view. + "datasetId": "A String", # Required. The ID of the dataset containing this table. + "projectId": "A String", # Required. The ID of the project containing this table. + "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`. + }, + }, + ], + }, + "metadataCacheStatistics": { # Statistics for metadata caching in BigLake tables. # Output only. Statistics of metadata cache usage in a query for BigLake tables. + "tableMetadataCacheUsage": [ # Set for the Metadata caching eligible tables referenced in the query. + { # Table level detail on the usage of metadata caching. Only set for Metadata caching eligible tables referenced in the query. + "explanation": "A String", # Free form human-readable reason metadata caching was unused for the job. + "tableReference": { # Metadata caching eligible table referenced in the query. + "datasetId": "A String", # Required. The ID of the dataset containing this table. + "projectId": "A String", # Required. The ID of the project containing this table. + "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`. + }, + "tableType": "A String", # [Table type](/bigquery/docs/reference/rest/v2/tables#Table.FIELDS.type). + "unusedReason": "A String", # Reason for not using metadata caching for the table. + }, + ], + }, + "mlStatistics": { # Job statistics specific to a BigQuery ML training job. # Output only. Statistics of a BigQuery ML training job. + "hparamTrials": [ # Output only. Trials of a [hyperparameter tuning job](/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview) sorted by trial_id. + { # Training info of a trial in [hyperparameter tuning](/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview) models. + "endTimeMs": "A String", # Ending time of the trial. + "errorMessage": "A String", # Error message for FAILED and INFEASIBLE trial. + "evalLoss": 3.14, # Loss computed on the eval data at the end of trial. + "evaluationMetrics": { # Evaluation metrics of a model. These are either computed on all training data or just the eval data based on whether eval data was used during training. These are not present for imported models. # Evaluation metrics of this trial calculated on the test data. Empty in Job API. + "arimaForecastingMetrics": { # Model evaluation metrics for ARIMA forecasting models. # Populated for ARIMA models. + "arimaFittingMetrics": [ # Arima model fitting metrics. + { # ARIMA model fitting metrics. + "aic": 3.14, # AIC. + "logLikelihood": 3.14, # Log-likelihood. + "variance": 3.14, # Variance. + }, + ], + "arimaSingleModelForecastingMetrics": [ # Repeated as there can be many metric sets (one for each model) in auto-arima and the large-scale case. + { # Model evaluation metrics for a single ARIMA forecasting model. + "arimaFittingMetrics": { # ARIMA model fitting metrics. # Arima fitting metrics. + "aic": 3.14, # AIC. + "logLikelihood": 3.14, # Log-likelihood. + "variance": 3.14, # Variance. + }, + "hasDrift": True or False, # Is arima model fitted with drift or not. It is always false when d is not 1. + "hasHolidayEffect": True or False, # If true, holiday_effect is a part of time series decomposition result. + "hasSpikesAndDips": True or False, # If true, spikes_and_dips is a part of time series decomposition result. + "hasStepChanges": True or False, # If true, step_changes is a part of time series decomposition result. + "nonSeasonalOrder": { # Arima order, can be used for both non-seasonal and seasonal parts. # Non-seasonal order. + "d": "A String", # Order of the differencing part. + "p": "A String", # Order of the autoregressive part. + "q": "A String", # Order of the moving-average part. + }, + "seasonalPeriods": [ # Seasonal periods. Repeated because multiple periods are supported for one time series. + "A String", + ], + "timeSeriesId": "A String", # The time_series_id value for this time series. It will be one of the unique values from the time_series_id_column specified during ARIMA model training. Only present when time_series_id_column training option was used. + "timeSeriesIds": [ # The tuple of time_series_ids identifying this time series. It will be one of the unique tuples of values present in the time_series_id_columns specified during ARIMA model training. Only present when time_series_id_columns training option was used and the order of values here are same as the order of time_series_id_columns. + "A String", + ], + }, + ], + "hasDrift": [ # Whether Arima model fitted with drift or not. It is always false when d is not 1. + True or False, + ], + "nonSeasonalOrder": [ # Non-seasonal order. + { # Arima order, can be used for both non-seasonal and seasonal parts. + "d": "A String", # Order of the differencing part. + "p": "A String", # Order of the autoregressive part. + "q": "A String", # Order of the moving-average part. + }, + ], + "seasonalPeriods": [ # Seasonal periods. Repeated because multiple periods are supported for one time series. + "A String", + ], + "timeSeriesId": [ # Id to differentiate different time series for the large-scale case. + "A String", + ], + }, + "binaryClassificationMetrics": { # Evaluation metrics for binary classification/classifier models. # Populated for binary classification/classifier models. + "aggregateClassificationMetrics": { # Aggregate metrics for classification/classifier models. For multi-class models, the metrics are either macro-averaged or micro-averaged. When macro-averaged, the metrics are calculated for each label and then an unweighted average is taken of those values. When micro-averaged, the metric is calculated globally by counting the total number of correctly predicted rows. # Aggregate classification metrics. + "accuracy": 3.14, # Accuracy is the fraction of predictions given the correct label. For multiclass this is a micro-averaged metric. + "f1Score": 3.14, # The F1 score is an average of recall and precision. For multiclass this is a macro-averaged metric. + "logLoss": 3.14, # Logarithmic Loss. For multiclass this is a macro-averaged metric. + "precision": 3.14, # Precision is the fraction of actual positive predictions that had positive actual labels. For multiclass this is a macro-averaged metric treating each class as a binary classifier. + "recall": 3.14, # Recall is the fraction of actual positive labels that were given a positive prediction. For multiclass this is a macro-averaged metric. + "rocAuc": 3.14, # Area Under a ROC Curve. For multiclass this is a macro-averaged metric. + "threshold": 3.14, # Threshold at which the metrics are computed. For binary classification models this is the positive class threshold. For multi-class classfication models this is the confidence threshold. + }, + "binaryConfusionMatrixList": [ # Binary confusion matrix at multiple thresholds. + { # Confusion matrix for binary classification models. + "accuracy": 3.14, # The fraction of predictions given the correct label. + "f1Score": 3.14, # The equally weighted average of recall and precision. + "falseNegatives": "A String", # Number of false samples predicted as false. + "falsePositives": "A String", # Number of false samples predicted as true. + "positiveClassThreshold": 3.14, # Threshold value used when computing each of the following metric. + "precision": 3.14, # The fraction of actual positive predictions that had positive actual labels. + "recall": 3.14, # The fraction of actual positive labels that were given a positive prediction. + "trueNegatives": "A String", # Number of true samples predicted as false. + "truePositives": "A String", # Number of true samples predicted as true. + }, + ], + "negativeLabel": "A String", # Label representing the negative class. + "positiveLabel": "A String", # Label representing the positive class. + }, + "clusteringMetrics": { # Evaluation metrics for clustering models. # Populated for clustering models. + "clusters": [ # Information for all clusters. + { # Message containing the information about one cluster. + "centroidId": "A String", # Centroid id. + "count": "A String", # Count of training data rows that were assigned to this cluster. + "featureValues": [ # Values of highly variant features for this cluster. + { # Representative value of a single feature within the cluster. + "categoricalValue": { # Representative value of a categorical feature. # The categorical feature value. + "categoryCounts": [ # Counts of all categories for the categorical feature. If there are more than ten categories, we return top ten (by count) and return one more CategoryCount with category "_OTHER_" and count as aggregate counts of remaining categories. + { # Represents the count of a single category within the cluster. + "category": "A String", # The name of category. + "count": "A String", # The count of training samples matching the category within the cluster. + }, + ], + }, + "featureColumn": "A String", # The feature column name. + "numericalValue": 3.14, # The numerical feature value. This is the centroid value for this feature. + }, + ], + }, + ], + "daviesBouldinIndex": 3.14, # Davies-Bouldin index. + "meanSquaredDistance": 3.14, # Mean of squared distances between each sample to its cluster centroid. + }, + "dimensionalityReductionMetrics": { # Model evaluation metrics for dimensionality reduction models. # Evaluation metrics when the model is a dimensionality reduction model, which currently includes PCA. + "totalExplainedVarianceRatio": 3.14, # Total percentage of variance explained by the selected principal components. + }, + "multiClassClassificationMetrics": { # Evaluation metrics for multi-class classification/classifier models. # Populated for multi-class classification/classifier models. + "aggregateClassificationMetrics": { # Aggregate metrics for classification/classifier models. For multi-class models, the metrics are either macro-averaged or micro-averaged. When macro-averaged, the metrics are calculated for each label and then an unweighted average is taken of those values. When micro-averaged, the metric is calculated globally by counting the total number of correctly predicted rows. # Aggregate classification metrics. + "accuracy": 3.14, # Accuracy is the fraction of predictions given the correct label. For multiclass this is a micro-averaged metric. + "f1Score": 3.14, # The F1 score is an average of recall and precision. For multiclass this is a macro-averaged metric. + "logLoss": 3.14, # Logarithmic Loss. For multiclass this is a macro-averaged metric. + "precision": 3.14, # Precision is the fraction of actual positive predictions that had positive actual labels. For multiclass this is a macro-averaged metric treating each class as a binary classifier. + "recall": 3.14, # Recall is the fraction of actual positive labels that were given a positive prediction. For multiclass this is a macro-averaged metric. + "rocAuc": 3.14, # Area Under a ROC Curve. For multiclass this is a macro-averaged metric. + "threshold": 3.14, # Threshold at which the metrics are computed. For binary classification models this is the positive class threshold. For multi-class classfication models this is the confidence threshold. + }, + "confusionMatrixList": [ # Confusion matrix at different thresholds. + { # Confusion matrix for multi-class classification models. + "confidenceThreshold": 3.14, # Confidence threshold used when computing the entries of the confusion matrix. + "rows": [ # One row per actual label. + { # A single row in the confusion matrix. + "actualLabel": "A String", # The original label of this row. + "entries": [ # Info describing predicted label distribution. + { # A single entry in the confusion matrix. + "itemCount": "A String", # Number of items being predicted as this label. + "predictedLabel": "A String", # The predicted label. For confidence_threshold > 0, we will also add an entry indicating the number of items under the confidence threshold. + }, + ], + }, + ], + }, + ], + }, + "rankingMetrics": { # Evaluation metrics used by weighted-ALS models specified by feedback_type=implicit. # Populated for implicit feedback type matrix factorization models. + "averageRank": 3.14, # Determines the goodness of a ranking by computing the percentile rank from the predicted confidence and dividing it by the original rank. + "meanAveragePrecision": 3.14, # Calculates a precision per user for all the items by ranking them and then averages all the precisions across all the users. + "meanSquaredError": 3.14, # Similar to the mean squared error computed in regression and explicit recommendation models except instead of computing the rating directly, the output from evaluate is computed against a preference which is 1 or 0 depending on if the rating exists or not. + "normalizedDiscountedCumulativeGain": 3.14, # A metric to determine the goodness of a ranking calculated from the predicted confidence by comparing it to an ideal rank measured by the original ratings. + }, + "regressionMetrics": { # Evaluation metrics for regression and explicit feedback type matrix factorization models. # Populated for regression models and explicit feedback type matrix factorization models. + "meanAbsoluteError": 3.14, # Mean absolute error. + "meanSquaredError": 3.14, # Mean squared error. + "meanSquaredLogError": 3.14, # Mean squared log error. + "medianAbsoluteError": 3.14, # Median absolute error. + "rSquared": 3.14, # R^2 score. This corresponds to r2_score in ML.EVALUATE. + }, + }, + "hparamTuningEvaluationMetrics": { # Evaluation metrics of a model. These are either computed on all training data or just the eval data based on whether eval data was used during training. These are not present for imported models. # Hyperparameter tuning evaluation metrics of this trial calculated on the eval data. Unlike evaluation_metrics, only the fields corresponding to the hparam_tuning_objectives are set. + "arimaForecastingMetrics": { # Model evaluation metrics for ARIMA forecasting models. # Populated for ARIMA models. + "arimaFittingMetrics": [ # Arima model fitting metrics. + { # ARIMA model fitting metrics. + "aic": 3.14, # AIC. + "logLikelihood": 3.14, # Log-likelihood. + "variance": 3.14, # Variance. + }, + ], + "arimaSingleModelForecastingMetrics": [ # Repeated as there can be many metric sets (one for each model) in auto-arima and the large-scale case. + { # Model evaluation metrics for a single ARIMA forecasting model. + "arimaFittingMetrics": { # ARIMA model fitting metrics. # Arima fitting metrics. + "aic": 3.14, # AIC. + "logLikelihood": 3.14, # Log-likelihood. + "variance": 3.14, # Variance. + }, + "hasDrift": True or False, # Is arima model fitted with drift or not. It is always false when d is not 1. + "hasHolidayEffect": True or False, # If true, holiday_effect is a part of time series decomposition result. + "hasSpikesAndDips": True or False, # If true, spikes_and_dips is a part of time series decomposition result. + "hasStepChanges": True or False, # If true, step_changes is a part of time series decomposition result. + "nonSeasonalOrder": { # Arima order, can be used for both non-seasonal and seasonal parts. # Non-seasonal order. + "d": "A String", # Order of the differencing part. + "p": "A String", # Order of the autoregressive part. + "q": "A String", # Order of the moving-average part. + }, + "seasonalPeriods": [ # Seasonal periods. Repeated because multiple periods are supported for one time series. + "A String", + ], + "timeSeriesId": "A String", # The time_series_id value for this time series. It will be one of the unique values from the time_series_id_column specified during ARIMA model training. Only present when time_series_id_column training option was used. + "timeSeriesIds": [ # The tuple of time_series_ids identifying this time series. It will be one of the unique tuples of values present in the time_series_id_columns specified during ARIMA model training. Only present when time_series_id_columns training option was used and the order of values here are same as the order of time_series_id_columns. + "A String", + ], + }, + ], + "hasDrift": [ # Whether Arima model fitted with drift or not. It is always false when d is not 1. + True or False, + ], + "nonSeasonalOrder": [ # Non-seasonal order. + { # Arima order, can be used for both non-seasonal and seasonal parts. + "d": "A String", # Order of the differencing part. + "p": "A String", # Order of the autoregressive part. + "q": "A String", # Order of the moving-average part. + }, + ], + "seasonalPeriods": [ # Seasonal periods. Repeated because multiple periods are supported for one time series. + "A String", + ], + "timeSeriesId": [ # Id to differentiate different time series for the large-scale case. + "A String", + ], + }, + "binaryClassificationMetrics": { # Evaluation metrics for binary classification/classifier models. # Populated for binary classification/classifier models. + "aggregateClassificationMetrics": { # Aggregate metrics for classification/classifier models. For multi-class models, the metrics are either macro-averaged or micro-averaged. When macro-averaged, the metrics are calculated for each label and then an unweighted average is taken of those values. When micro-averaged, the metric is calculated globally by counting the total number of correctly predicted rows. # Aggregate classification metrics. + "accuracy": 3.14, # Accuracy is the fraction of predictions given the correct label. For multiclass this is a micro-averaged metric. + "f1Score": 3.14, # The F1 score is an average of recall and precision. For multiclass this is a macro-averaged metric. + "logLoss": 3.14, # Logarithmic Loss. For multiclass this is a macro-averaged metric. + "precision": 3.14, # Precision is the fraction of actual positive predictions that had positive actual labels. For multiclass this is a macro-averaged metric treating each class as a binary classifier. + "recall": 3.14, # Recall is the fraction of actual positive labels that were given a positive prediction. For multiclass this is a macro-averaged metric. + "rocAuc": 3.14, # Area Under a ROC Curve. For multiclass this is a macro-averaged metric. + "threshold": 3.14, # Threshold at which the metrics are computed. For binary classification models this is the positive class threshold. For multi-class classfication models this is the confidence threshold. + }, + "binaryConfusionMatrixList": [ # Binary confusion matrix at multiple thresholds. + { # Confusion matrix for binary classification models. + "accuracy": 3.14, # The fraction of predictions given the correct label. + "f1Score": 3.14, # The equally weighted average of recall and precision. + "falseNegatives": "A String", # Number of false samples predicted as false. + "falsePositives": "A String", # Number of false samples predicted as true. + "positiveClassThreshold": 3.14, # Threshold value used when computing each of the following metric. + "precision": 3.14, # The fraction of actual positive predictions that had positive actual labels. + "recall": 3.14, # The fraction of actual positive labels that were given a positive prediction. + "trueNegatives": "A String", # Number of true samples predicted as false. + "truePositives": "A String", # Number of true samples predicted as true. + }, + ], + "negativeLabel": "A String", # Label representing the negative class. + "positiveLabel": "A String", # Label representing the positive class. + }, + "clusteringMetrics": { # Evaluation metrics for clustering models. # Populated for clustering models. + "clusters": [ # Information for all clusters. + { # Message containing the information about one cluster. + "centroidId": "A String", # Centroid id. + "count": "A String", # Count of training data rows that were assigned to this cluster. + "featureValues": [ # Values of highly variant features for this cluster. + { # Representative value of a single feature within the cluster. + "categoricalValue": { # Representative value of a categorical feature. # The categorical feature value. + "categoryCounts": [ # Counts of all categories for the categorical feature. If there are more than ten categories, we return top ten (by count) and return one more CategoryCount with category "_OTHER_" and count as aggregate counts of remaining categories. + { # Represents the count of a single category within the cluster. + "category": "A String", # The name of category. + "count": "A String", # The count of training samples matching the category within the cluster. + }, + ], + }, + "featureColumn": "A String", # The feature column name. + "numericalValue": 3.14, # The numerical feature value. This is the centroid value for this feature. + }, + ], + }, + ], + "daviesBouldinIndex": 3.14, # Davies-Bouldin index. + "meanSquaredDistance": 3.14, # Mean of squared distances between each sample to its cluster centroid. + }, + "dimensionalityReductionMetrics": { # Model evaluation metrics for dimensionality reduction models. # Evaluation metrics when the model is a dimensionality reduction model, which currently includes PCA. + "totalExplainedVarianceRatio": 3.14, # Total percentage of variance explained by the selected principal components. + }, + "multiClassClassificationMetrics": { # Evaluation metrics for multi-class classification/classifier models. # Populated for multi-class classification/classifier models. + "aggregateClassificationMetrics": { # Aggregate metrics for classification/classifier models. For multi-class models, the metrics are either macro-averaged or micro-averaged. When macro-averaged, the metrics are calculated for each label and then an unweighted average is taken of those values. When micro-averaged, the metric is calculated globally by counting the total number of correctly predicted rows. # Aggregate classification metrics. + "accuracy": 3.14, # Accuracy is the fraction of predictions given the correct label. For multiclass this is a micro-averaged metric. + "f1Score": 3.14, # The F1 score is an average of recall and precision. For multiclass this is a macro-averaged metric. + "logLoss": 3.14, # Logarithmic Loss. For multiclass this is a macro-averaged metric. + "precision": 3.14, # Precision is the fraction of actual positive predictions that had positive actual labels. For multiclass this is a macro-averaged metric treating each class as a binary classifier. + "recall": 3.14, # Recall is the fraction of actual positive labels that were given a positive prediction. For multiclass this is a macro-averaged metric. + "rocAuc": 3.14, # Area Under a ROC Curve. For multiclass this is a macro-averaged metric. + "threshold": 3.14, # Threshold at which the metrics are computed. For binary classification models this is the positive class threshold. For multi-class classfication models this is the confidence threshold. + }, + "confusionMatrixList": [ # Confusion matrix at different thresholds. + { # Confusion matrix for multi-class classification models. + "confidenceThreshold": 3.14, # Confidence threshold used when computing the entries of the confusion matrix. + "rows": [ # One row per actual label. + { # A single row in the confusion matrix. + "actualLabel": "A String", # The original label of this row. + "entries": [ # Info describing predicted label distribution. + { # A single entry in the confusion matrix. + "itemCount": "A String", # Number of items being predicted as this label. + "predictedLabel": "A String", # The predicted label. For confidence_threshold > 0, we will also add an entry indicating the number of items under the confidence threshold. + }, + ], + }, + ], + }, + ], + }, + "rankingMetrics": { # Evaluation metrics used by weighted-ALS models specified by feedback_type=implicit. # Populated for implicit feedback type matrix factorization models. + "averageRank": 3.14, # Determines the goodness of a ranking by computing the percentile rank from the predicted confidence and dividing it by the original rank. + "meanAveragePrecision": 3.14, # Calculates a precision per user for all the items by ranking them and then averages all the precisions across all the users. + "meanSquaredError": 3.14, # Similar to the mean squared error computed in regression and explicit recommendation models except instead of computing the rating directly, the output from evaluate is computed against a preference which is 1 or 0 depending on if the rating exists or not. + "normalizedDiscountedCumulativeGain": 3.14, # A metric to determine the goodness of a ranking calculated from the predicted confidence by comparing it to an ideal rank measured by the original ratings. + }, + "regressionMetrics": { # Evaluation metrics for regression and explicit feedback type matrix factorization models. # Populated for regression models and explicit feedback type matrix factorization models. + "meanAbsoluteError": 3.14, # Mean absolute error. + "meanSquaredError": 3.14, # Mean squared error. + "meanSquaredLogError": 3.14, # Mean squared log error. + "medianAbsoluteError": 3.14, # Median absolute error. + "rSquared": 3.14, # R^2 score. This corresponds to r2_score in ML.EVALUATE. + }, + }, + "hparams": { # Options used in model training. # The hyperprameters selected for this trial. + "activationFn": "A String", # Activation function of the neural nets. + "adjustStepChanges": True or False, # If true, detect step changes and make data adjustment in the input time series. + "approxGlobalFeatureContrib": True or False, # Whether to use approximate feature contribution method in XGBoost model explanation for global explain. + "autoArima": True or False, # Whether to enable auto ARIMA or not. + "autoArimaMaxOrder": "A String", # The max value of the sum of non-seasonal p and q. + "autoArimaMinOrder": "A String", # The min value of the sum of non-seasonal p and q. + "autoClassWeights": True or False, # Whether to calculate class weights automatically based on the popularity of each label. + "batchSize": "A String", # Batch size for dnn models. + "boosterType": "A String", # Booster type for boosted tree models. + "budgetHours": 3.14, # Budget in hours for AutoML training. + "calculatePValues": True or False, # Whether or not p-value test should be computed for this model. Only available for linear and logistic regression models. + "categoryEncodingMethod": "A String", # Categorical feature encoding method. + "cleanSpikesAndDips": True or False, # If true, clean spikes and dips in the input time series. + "colorSpace": "A String", # Enums for color space, used for processing images in Object Table. See more details at https://www.tensorflow.org/io/tutorials/colorspace. + "colsampleBylevel": 3.14, # Subsample ratio of columns for each level for boosted tree models. + "colsampleBynode": 3.14, # Subsample ratio of columns for each node(split) for boosted tree models. + "colsampleBytree": 3.14, # Subsample ratio of columns when constructing each tree for boosted tree models. + "dartNormalizeType": "A String", # Type of normalization algorithm for boosted tree models using dart booster. + "dataFrequency": "A String", # The data frequency of a time series. + "dataSplitColumn": "A String", # The column to split data with. This column won't be used as a feature. 1. When data_split_method is CUSTOM, the corresponding column should be boolean. The rows with true value tag are eval data, and the false are training data. 2. When data_split_method is SEQ, the first DATA_SPLIT_EVAL_FRACTION rows (from smallest to largest) in the corresponding column are used as training data, and the rest are eval data. It respects the order in Orderable data types: https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types#data-type-properties + "dataSplitEvalFraction": 3.14, # The fraction of evaluation data over the whole input data. The rest of data will be used as training data. The format should be double. Accurate to two decimal places. Default value is 0.2. + "dataSplitMethod": "A String", # The data split type for training and evaluation, e.g. RANDOM. + "decomposeTimeSeries": True or False, # If true, perform decompose time series and save the results. + "distanceType": "A String", # Distance type for clustering models. + "dropout": 3.14, # Dropout probability for dnn models. + "earlyStop": True or False, # Whether to stop early when the loss doesn't improve significantly any more (compared to min_relative_progress). Used only for iterative training algorithms. + "enableGlobalExplain": True or False, # If true, enable global explanation during training. + "feedbackType": "A String", # Feedback type that specifies which algorithm to run for matrix factorization. + "fitIntercept": True or False, # Whether the model should include intercept during model training. + "hiddenUnits": [ # Hidden units for dnn models. + "A String", + ], + "holidayRegion": "A String", # The geographical region based on which the holidays are considered in time series modeling. If a valid value is specified, then holiday effects modeling is enabled. + "holidayRegions": [ # A list of geographical regions that are used for time series modeling. + "A String", + ], + "horizon": "A String", # The number of periods ahead that need to be forecasted. + "hparamTuningObjectives": [ # The target evaluation metrics to optimize the hyperparameters for. + "A String", + ], + "includeDrift": True or False, # Include drift when fitting an ARIMA model. + "initialLearnRate": 3.14, # Specifies the initial learning rate for the line search learn rate strategy. + "inputLabelColumns": [ # Name of input label columns in training data. + "A String", + ], + "instanceWeightColumn": "A String", # Name of the instance weight column for training data. This column isn't be used as a feature. + "integratedGradientsNumSteps": "A String", # Number of integral steps for the integrated gradients explain method. + "itemColumn": "A String", # Item column specified for matrix factorization models. + "kmeansInitializationColumn": "A String", # The column used to provide the initial centroids for kmeans algorithm when kmeans_initialization_method is CUSTOM. + "kmeansInitializationMethod": "A String", # The method used to initialize the centroids for kmeans algorithm. + "l1RegActivation": 3.14, # L1 regularization coefficient to activations. + "l1Regularization": 3.14, # L1 regularization coefficient. + "l2Regularization": 3.14, # L2 regularization coefficient. + "labelClassWeights": { # Weights associated with each label class, for rebalancing the training data. Only applicable for classification models. + "a_key": 3.14, + }, + "learnRate": 3.14, # Learning rate in training. Used only for iterative training algorithms. + "learnRateStrategy": "A String", # The strategy to determine learn rate for the current iteration. + "lossType": "A String", # Type of loss function used during training run. + "maxIterations": "A String", # The maximum number of iterations in training. Used only for iterative training algorithms. + "maxParallelTrials": "A String", # Maximum number of trials to run in parallel. + "maxTimeSeriesLength": "A String", # The maximum number of time points in a time series that can be used in modeling the trend component of the time series. Don't use this option with the `timeSeriesLengthFraction` or `minTimeSeriesLength` options. + "maxTreeDepth": "A String", # Maximum depth of a tree for boosted tree models. + "minRelativeProgress": 3.14, # When early_stop is true, stops training when accuracy improvement is less than 'min_relative_progress'. Used only for iterative training algorithms. + "minSplitLoss": 3.14, # Minimum split loss for boosted tree models. + "minTimeSeriesLength": "A String", # The minimum number of time points in a time series that are used in modeling the trend component of the time series. If you use this option you must also set the `timeSeriesLengthFraction` option. This training option ensures that enough time points are available when you use `timeSeriesLengthFraction` in trend modeling. This is particularly important when forecasting multiple time series in a single query using `timeSeriesIdColumn`. If the total number of time points is less than the `minTimeSeriesLength` value, then the query uses all available time points. + "minTreeChildWeight": "A String", # Minimum sum of instance weight needed in a child for boosted tree models. + "modelRegistry": "A String", # The model registry. + "modelUri": "A String", # Google Cloud Storage URI from which the model was imported. Only applicable for imported models. + "nonSeasonalOrder": { # Arima order, can be used for both non-seasonal and seasonal parts. # A specification of the non-seasonal part of the ARIMA model: the three components (p, d, q) are the AR order, the degree of differencing, and the MA order. + "d": "A String", # Order of the differencing part. + "p": "A String", # Order of the autoregressive part. + "q": "A String", # Order of the moving-average part. + }, + "numClusters": "A String", # Number of clusters for clustering models. + "numFactors": "A String", # Num factors specified for matrix factorization models. + "numParallelTree": "A String", # Number of parallel trees constructed during each iteration for boosted tree models. + "numPrincipalComponents": "A String", # Number of principal components to keep in the PCA model. Must be <= the number of features. + "numTrials": "A String", # Number of trials to run this hyperparameter tuning job. + "optimizationStrategy": "A String", # Optimization strategy for training linear regression models. + "optimizer": "A String", # Optimizer used for training the neural nets. + "pcaExplainedVarianceRatio": 3.14, # The minimum ratio of cumulative explained variance that needs to be given by the PCA model. + "pcaSolver": "A String", # The solver for PCA. + "sampledShapleyNumPaths": "A String", # Number of paths for the sampled Shapley explain method. + "scaleFeatures": True or False, # If true, scale the feature values by dividing the feature standard deviation. Currently only apply to PCA. + "standardizeFeatures": True or False, # Whether to standardize numerical features. Default to true. + "subsample": 3.14, # Subsample fraction of the training data to grow tree to prevent overfitting for boosted tree models. + "tfVersion": "A String", # Based on the selected TF version, the corresponding docker image is used to train external models. + "timeSeriesDataColumn": "A String", # Column to be designated as time series data for ARIMA model. + "timeSeriesIdColumn": "A String", # The time series id column that was used during ARIMA model training. + "timeSeriesIdColumns": [ # The time series id columns that were used during ARIMA model training. + "A String", + ], + "timeSeriesLengthFraction": 3.14, # The fraction of the interpolated length of the time series that's used to model the time series trend component. All of the time points of the time series are used to model the non-trend component. This training option accelerates modeling training without sacrificing much forecasting accuracy. You can use this option with `minTimeSeriesLength` but not with `maxTimeSeriesLength`. + "timeSeriesTimestampColumn": "A String", # Column to be designated as time series timestamp for ARIMA model. + "treeMethod": "A String", # Tree construction algorithm for boosted tree models. + "trendSmoothingWindowSize": "A String", # Smoothing window size for the trend component. When a positive value is specified, a center moving average smoothing is applied on the history trend. When the smoothing window is out of the boundary at the beginning or the end of the trend, the first element or the last element is padded to fill the smoothing window before the average is applied. + "userColumn": "A String", # User column specified for matrix factorization models. + "vertexAiModelVersionAliases": [ # The version aliases to apply in Vertex AI model registry. Always overwrite if the version aliases exists in a existing model. + "A String", + ], + "walsAlpha": 3.14, # Hyperparameter for matrix factoration when implicit feedback type is specified. + "warmStart": True or False, # Whether to train a model from the last checkpoint. + "xgboostVersion": "A String", # User-selected XGBoost versions for training of XGBoost models. + }, + "startTimeMs": "A String", # Starting time of the trial. + "status": "A String", # The status of the trial. + "trainingLoss": 3.14, # Loss computed on the training data at the end of trial. + "trialId": "A String", # 1-based index of the trial. + }, + ], + "iterationResults": [ # Results for all completed iterations. Empty for [hyperparameter tuning jobs](/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview). + { # Information about a single iteration of the training run. + "arimaResult": { # (Auto-)arima fitting result. Wrap everything in ArimaResult for easier refactoring if we want to use model-specific iteration results. # Arima result. + "arimaModelInfo": [ # This message is repeated because there are multiple arima models fitted in auto-arima. For non-auto-arima model, its size is one. + { # Arima model information. + "arimaCoefficients": { # Arima coefficients. # Arima coefficients. + "autoRegressiveCoefficients": [ # Auto-regressive coefficients, an array of double. + 3.14, + ], + "interceptCoefficient": 3.14, # Intercept coefficient, just a double not an array. + "movingAverageCoefficients": [ # Moving-average coefficients, an array of double. + 3.14, + ], + }, + "arimaFittingMetrics": { # ARIMA model fitting metrics. # Arima fitting metrics. + "aic": 3.14, # AIC. + "logLikelihood": 3.14, # Log-likelihood. + "variance": 3.14, # Variance. + }, + "hasDrift": True or False, # Whether Arima model fitted with drift or not. It is always false when d is not 1. + "hasHolidayEffect": True or False, # If true, holiday_effect is a part of time series decomposition result. + "hasSpikesAndDips": True or False, # If true, spikes_and_dips is a part of time series decomposition result. + "hasStepChanges": True or False, # If true, step_changes is a part of time series decomposition result. + "nonSeasonalOrder": { # Arima order, can be used for both non-seasonal and seasonal parts. # Non-seasonal order. + "d": "A String", # Order of the differencing part. + "p": "A String", # Order of the autoregressive part. + "q": "A String", # Order of the moving-average part. + }, + "seasonalPeriods": [ # Seasonal periods. Repeated because multiple periods are supported for one time series. "A String", ], - }, - "collation": "A String", # Optional. Collation specification of the field. It only can be set on string type field. - "defaultValueExpression": "A String", # Optional. A SQL expression to specify the default value for this field. It can only be set for top level fields (columns). You can use struct or array expression to specify default value for the entire struct or array. The valid SQL expressions are: - Literals for all data types, including STRUCT and ARRAY. - Following functions: - CURRENT_TIMESTAMP - CURRENT_TIME - CURRENT_DATE - CURRENT_DATETIME - GENERATE_UUID - RAND - SESSION_USER - ST_GEOGPOINT - Struct or array composed with the above allowed functions, for example, [CURRENT_DATE(), DATE '2020-01-01'] - "description": "A String", # [Optional] The field description. The maximum length is 1,024 characters. - "fields": [ # [Optional] Describes the nested schema fields if the type property is set to RECORD. - # Object with schema name: TableFieldSchema - ], - "maxLength": "A String", # [Optional] Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES". - "mode": "A String", # [Optional] The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE. - "name": "A String", # [Required] The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters. - "policyTags": { - "names": [ # A list of category resource names. For example, "projects/1/location/eu/taxonomies/2/policyTags/3". At most 1 policy tag is allowed. + "timeSeriesId": "A String", # The time_series_id value for this time series. It will be one of the unique values from the time_series_id_column specified during ARIMA model training. Only present when time_series_id_column training option was used. + "timeSeriesIds": [ # The tuple of time_series_ids identifying this time series. It will be one of the unique tuples of values present in the time_series_id_columns specified during ARIMA model training. Only present when time_series_id_columns training option was used and the order of values here are same as the order of time_series_id_columns. "A String", ], }, - "precision": "A String", # [Optional] Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: - Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] - Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: - If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. - If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): - If type = "NUMERIC": 1 ≤ precision ≤ 29. - If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid. - "rangeElementType": { # Optional. The subtype of the RANGE, if the type of this field is RANGE. If the type is RANGE, this field is required. Possible values for the field element type of a RANGE include: - DATE - DATETIME - TIMESTAMP - "type": "A String", # The field element type of a RANGE - }, - "roundingMode": "A String", # Optional. Rounding Mode specification of the field. It only can be set on NUMERIC or BIGNUMERIC type fields. - "scale": "A String", # [Optional] See documentation for precision. - "type": "A String", # [Required] The field data type. Possible values include STRING, BYTES, INTEGER, INT64 (same as INTEGER), FLOAT, FLOAT64 (same as FLOAT), NUMERIC, BIGNUMERIC, BOOLEAN, BOOL (same as BOOLEAN), TIMESTAMP, DATE, TIME, DATETIME, INTERVAL, RECORD (where RECORD indicates that the field contains a nested schema) or STRUCT (same as RECORD). + ], + "seasonalPeriods": [ # Seasonal periods. Repeated because multiple periods are supported for one time series. + "A String", + ], + }, + "clusterInfos": [ # Information about top clusters for clustering models. + { # Information about a single cluster for clustering model. + "centroidId": "A String", # Centroid id. + "clusterRadius": 3.14, # Cluster radius, the average distance from centroid to each point assigned to the cluster. + "clusterSize": "A String", # Cluster size, the total number of points assigned to the cluster. }, ], - }, - "sourceFormat": "A String", # [Required] The data format. For CSV files, specify "CSV". For Google sheets, specify "GOOGLE_SHEETS". For newline-delimited JSON, specify "NEWLINE_DELIMITED_JSON". For Avro files, specify "AVRO". For Google Cloud Datastore backups, specify "DATASTORE_BACKUP". [Beta] For Google Cloud Bigtable, specify "BIGTABLE". - "sourceUris": [ # [Required] The fully-qualified URIs that point to your data in Google Cloud. For Google Cloud Storage URIs: Each URI can contain one '*' wildcard character and it must come after the 'bucket' name. Size limits related to load jobs apply to external data sources. For Google Cloud Bigtable URIs: Exactly one URI can be specified and it has be a fully specified and valid HTTPS URL for a Google Cloud Bigtable table. For Google Cloud Datastore backups, exactly one URI can be specified. Also, the '*' wildcard character is not allowed. - "A String", - ], - }, - }, - "timePartitioning": { # Time-based partitioning specification for the destination table. Only one of timePartitioning and rangePartitioning should be specified. - "expirationMs": "A String", # [Optional] Number of milliseconds for which to keep the storage for partitions in the table. The storage in a partition will have an expiration time of its partition time plus this value. - "field": "A String", # [Beta] [Optional] If not set, the table is partitioned by pseudo column, referenced via either '_PARTITIONTIME' as TIMESTAMP type, or '_PARTITIONDATE' as DATE type. If field is specified, the table is instead partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED. - "requirePartitionFilter": True or False, - "type": "A String", # [Required] The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively. When the type is not specified, the default behavior is DAY. - }, - "useLegacySql": true, # Specifies whether to use BigQuery's legacy SQL dialect for this query. The default value is true. If set to false, the query will use BigQuery's standard SQL: https://cloud.google.com/bigquery/sql-reference/ When useLegacySql is set to false, the value of flattenResults is ignored; query will be run as if flattenResults is false. - "useQueryCache": true, # [Optional] Whether to look for the result in the query cache. The query cache is a best-effort cache that will be flushed whenever tables in the query are modified. Moreover, the query cache is only available when a query does not have a destination table specified. The default value is true. - "userDefinedFunctionResources": [ # Describes user-defined function resources used in the query. - { # This is used for defining User Defined Function (UDF) resources only when using legacy SQL. Users of Standard SQL should leverage either DDL (e.g. CREATE [TEMPORARY] FUNCTION ... ) or the Routines API to define UDF resources. For additional information on migrating, see: https://cloud.google.com/bigquery/docs/reference/standard-sql/migrating-from-legacy-sql#differences_in_user-defined_javascript_functions - "inlineCode": "A String", # [Pick one] An inline resource that contains code for a user-defined function (UDF). Providing a inline code resource is equivalent to providing a URI for a file containing the same code. - "resourceUri": "A String", # [Pick one] A code resource to load from a Google Cloud Storage URI (gs://bucket/path). - }, - ], - "writeDisposition": "A String", # [Optional] Specifies the action that occurs if the destination table already exists. The following values are supported: WRITE_TRUNCATE: If the table already exists, BigQuery overwrites the table data and uses the schema from the query result. WRITE_APPEND: If the table already exists, BigQuery appends the data to the table. WRITE_EMPTY: If the table already exists and contains data, a 'duplicate' error is returned in the job result. The default value is WRITE_EMPTY. Each action is atomic and only occurs if BigQuery is able to complete the job successfully. Creation, truncation and append actions occur as one atomic update upon job completion. - }, - }, - "etag": "A String", # [Output-only] A hash of this resource. - "id": "A String", # [Output-only] Opaque ID field of the job - "jobCreationReason": "", # [Output-only] If set, it provides the reason why a Job was created. If not set, it should be treated as the default: REQUESTED. This feature is not yet available. Jobs will always be created. - "jobReference": { # [Optional] Reference describing the unique-per-user name of the job. - "jobId": "A String", # [Required] The ID of the job. The ID must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), or dashes (-). The maximum length is 1,024 characters. - "location": "A String", # The geographic location of the job. See details at https://cloud.google.com/bigquery/docs/locations#specifying_your_location. - "projectId": "A String", # [Required] The ID of the project containing this job. - }, - "kind": "bigquery#job", # [Output-only] The type of the resource. - "selfLink": "A String", # [Output-only] A URL that can be used to access this resource again. - "statistics": { # [Output-only] Information about the job, including starting time and ending time of the job. - "completionRatio": 3.14, # [TrustedTester] [Output-only] Job progress (0.0 -> 1.0) for LOAD and EXTRACT jobs. - "copy": { # [Output-only] Statistics for a copy job. - "copiedLogicalBytes": "A String", # [Output-only] Number of logical bytes copied to the destination table. - "copiedRows": "A String", # [Output-only] Number of rows copied to the destination table. - }, - "creationTime": "A String", # [Output-only] Creation time of this job, in milliseconds since the epoch. This field will be present on all jobs. - "dataMaskingStatistics": { # [Output-only] Statistics for data masking. Present only for query and extract jobs. - "dataMaskingApplied": false, # [Output-only] [Preview] Whether any accessed data was protected by data masking. The actual evaluation is done by accessStats.masked_field_count > 0. Since this is only used for the discovery_doc generation purpose, as long as the type (boolean) matches, client library can leverage this. The actual evaluation of the variable is done else-where. - }, - "endTime": "A String", # [Output-only] End time of this job, in milliseconds since the epoch. This field will be present whenever a job is in the DONE state. - "extract": { # [Output-only] Statistics for an extract job. - "destinationUriFileCounts": [ # [Output-only] Number of files per destination URI or URI pattern specified in the extract configuration. These values will be in the same order as the URIs specified in the 'destinationUris' field. - "A String", - ], - "inputBytes": "A String", # [Output-only] Number of user bytes extracted into the result. This is the byte count as computed by BigQuery for billing purposes. - }, - "load": { # [Output-only] Statistics for a load job. - "badRecords": "A String", # [Output-only] The number of bad records encountered. Note that if the job has failed because of more bad records encountered than the maximum allowed in the load job configuration, then this number can be less than the total number of bad records present in the input data. - "inputFileBytes": "A String", # [Output-only] Number of bytes of source data in a load job. - "inputFiles": "A String", # [Output-only] Number of source files in a load job. - "outputBytes": "A String", # [Output-only] Size of the loaded data in bytes. Note that while a load job is in the running state, this value may change. - "outputRows": "A String", # [Output-only] Number of rows imported in a load job. Note that while an import job is in the running state, this value may change. - }, - "numChildJobs": "A String", # [Output-only] Number of child jobs executed. - "parentJobId": "A String", # [Output-only] If this is a child job, the id of the parent. - "query": { # [Output-only] Statistics for a query job. - "biEngineStatistics": { # BI Engine specific Statistics. [Output only] BI Engine specific Statistics. - "accelerationMode": "", # [Output-only] Specifies which mode of BI Engine acceleration was performed (if any). - "biEngineMode": "", # [Output-only] Specifies which mode of BI Engine acceleration was performed (if any). - "biEngineReasons": [ # In case of DISABLED or PARTIAL bi_engine_mode, these contain the explanatory reasons as to why BI Engine could not accelerate. In case the full query was accelerated, this field is not populated. - { - "code": "", # [Output-only] High-level BI Engine reason for partial or disabled acceleration. - "message": "", # [Output-only] Free form human-readable reason for partial or disabled acceleration. - }, - ], - }, - "billingTier": 42, # [Output only] Billing tier for the job. - "cacheHit": True or False, # [Output only] Whether the query result was fetched from the query cache. - "ddlAffectedRowAccessPolicyCount": "A String", # [Output only] [Preview] The number of row access policies affected by a DDL statement. Present only for DROP ALL ROW ACCESS POLICIES queries. - "ddlDestinationTable": { # [Output only] The DDL destination table. Present only for ALTER TABLE RENAME TO queries. Note that ddl_target_table is used just for its type information. - "datasetId": "A String", # [Required] The ID of the dataset containing this table. - "projectId": "A String", # [Required] The ID of the project containing this table. - "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. - }, - "ddlOperationPerformed": "A String", # The DDL operation performed, possibly dependent on the pre-existence of the DDL target. Possible values (new values might be added in the future): "CREATE": The query created the DDL target. "SKIP": No-op. Example cases: the query is CREATE TABLE IF NOT EXISTS while the table already exists, or the query is DROP TABLE IF EXISTS while the table does not exist. "REPLACE": The query replaced the DDL target. Example case: the query is CREATE OR REPLACE TABLE, and the table already exists. "DROP": The query deleted the DDL target. - "ddlTargetDataset": { # [Output only] The DDL target dataset. Present only for CREATE/ALTER/DROP/UNDROP SCHEMA queries. - "datasetId": "A String", # [Required] A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. - "projectId": "A String", # [Optional] The ID of the project containing this dataset. - }, - "ddlTargetRoutine": { # The DDL target routine. Present only for CREATE/DROP FUNCTION/PROCEDURE queries. - "datasetId": "A String", # Required. The ID of the dataset containing this routine. - "projectId": "A String", # Required. The ID of the project containing this routine. - "routineId": "A String", # Required. The ID of the routine. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 256 characters. - }, - "ddlTargetRowAccessPolicy": { # [Output only] [Preview] The DDL target row access policy. Present only for CREATE/DROP ROW ACCESS POLICY queries. - "datasetId": "A String", # Required. The ID of the dataset containing this row access policy. - "policyId": "A String", # Required. The ID of the row access policy. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 256 characters. - "projectId": "A String", # Required. The ID of the project containing this row access policy. - "tableId": "A String", # Required. The ID of the table containing this row access policy. - }, - "ddlTargetTable": { # [Output only] The DDL target table. Present only for CREATE/DROP TABLE/VIEW and DROP ALL ROW ACCESS POLICIES queries. - "datasetId": "A String", # [Required] The ID of the dataset containing this table. - "projectId": "A String", # [Required] The ID of the project containing this table. - "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. - }, - "dmlStats": { # [Output only] Detailed statistics for DML statements Present only for DML statements INSERT, UPDATE, DELETE or TRUNCATE. - "deletedRowCount": "A String", # Number of deleted Rows. populated by DML DELETE, MERGE and TRUNCATE statements. - "insertedRowCount": "A String", # Number of inserted Rows. Populated by DML INSERT and MERGE statements. - "updatedRowCount": "A String", # Number of updated Rows. Populated by DML UPDATE and MERGE statements. - }, - "estimatedBytesProcessed": "A String", # [Output only] The original estimate of bytes processed for the job. - "mlStatistics": { # [Output only] Statistics of a BigQuery ML training job. - "iterationResults": [ # Results for all completed iterations. - { "durationMs": "A String", # Time taken to run the iteration in milliseconds. "evalLoss": 3.14, # Loss computed on the eval data at the end of iteration. "index": 42, # Index of the iteration, 0 based. "learnRate": 3.14, # Learn rate used for this iteration. + "principalComponentInfos": [ # The information of the principal components. + { # Principal component infos, used only for eigen decomposition based models, e.g., PCA. Ordered by explained_variance in the descending order. + "cumulativeExplainedVarianceRatio": 3.14, # The explained_variance is pre-ordered in the descending order to compute the cumulative explained variance ratio. + "explainedVariance": 3.14, # Explained variance by this principal component, which is simply the eigenvalue. + "explainedVarianceRatio": 3.14, # Explained_variance over the total explained variance. + "principalComponentId": "A String", # Id of the principal component. + }, + ], "trainingLoss": 3.14, # Loss computed on the training data at the end of iteration. }, ], - "maxIterations": "A String", # Maximum number of iterations specified as max_iterations in the 'CREATE MODEL' query. The actual number of iterations may be less than this number due to early stop. + "maxIterations": "A String", # Output only. Maximum number of iterations specified as max_iterations in the 'CREATE MODEL' query. The actual number of iterations may be less than this number due to early stop. + "modelType": "A String", # Output only. The type of the model that is being trained. + "trainingType": "A String", # Output only. Training type of the job. + }, + "modelTraining": { # Deprecated. + "currentIteration": 42, # Deprecated. + "expectedTotalIterations": "A String", # Deprecated. + }, + "modelTrainingCurrentIteration": 42, # Deprecated. + "modelTrainingExpectedTotalIteration": "A String", # Deprecated. + "numDmlAffectedRows": "A String", # Output only. The number of rows affected by a DML statement. Present only for DML statements INSERT, UPDATE or DELETE. + "performanceInsights": { # Performance insights for the job. # Output only. Performance insights. + "avgPreviousExecutionMs": "A String", # Output only. Average execution ms of previous runs. Indicates the job ran slow compared to previous executions. To find previous executions, use INFORMATION_SCHEMA tables and filter jobs with same query hash. + "stagePerformanceChangeInsights": [ # Output only. Query stage performance insights compared to previous runs, for diagnosing performance regression. + { # Performance insights compared to the previous executions for a specific stage. + "inputDataChange": { # Details about the input data change insight. # Output only. Input data change insight of the query stage. + "recordsReadDiffPercentage": 3.14, # Output only. Records read difference percentage compared to a previous run. + }, + "stageId": "A String", # Output only. The stage id that the insight mapped to. + }, + ], + "stagePerformanceStandaloneInsights": [ # Output only. Standalone query stage performance insights, for exploring potential improvements. + { # Standalone performance insights for a specific stage. + "biEngineReasons": [ # Output only. If present, the stage had the following reasons for being disqualified from BI Engine execution. + { # Reason why BI Engine didn't accelerate the query (or sub-query). + "code": "A String", # Output only. High-level BI Engine reason for partial or disabled acceleration + "message": "A String", # Output only. Free form human-readable reason for partial or disabled acceleration. + }, + ], + "highCardinalityJoins": [ # Output only. High cardinality joins in the stage. + { # High cardinality join detailed information. + "leftRows": "A String", # Output only. Count of left input rows. + "outputRows": "A String", # Output only. Count of the output rows. + "rightRows": "A String", # Output only. Count of right input rows. + "stepIndex": 42, # Output only. The index of the join operator in the ExplainQueryStep lists. + }, + ], + "insufficientShuffleQuota": True or False, # Output only. True if the stage has insufficient shuffle quota. + "slotContention": True or False, # Output only. True if the stage has a slot contention issue. + "stageId": "A String", # Output only. The stage id that the insight mapped to. + }, + ], }, - "modelTraining": { # [Output only, Beta] Information about create model query job progress. - "currentIteration": 42, # [Output-only, Beta] Index of current ML training iteration. Updated during create model query job to show job progress. - "expectedTotalIterations": "A String", # [Output-only, Beta] Expected number of iterations for the create model query job specified as num_iterations in the input query. The actual total number of iterations may be less than this number due to early stop. + "queryInfo": { # Query optimization information for a QUERY job. # Output only. Query optimization information for a QUERY job. + "optimizationDetails": { # Output only. Information about query optimizations. + "a_key": "", # Properties of the object. + }, }, - "modelTrainingCurrentIteration": 42, # [Output only, Beta] Deprecated; do not use. - "modelTrainingExpectedTotalIteration": "A String", # [Output only, Beta] Deprecated; do not use. - "numDmlAffectedRows": "A String", # [Output only] The number of rows affected by a DML statement. Present only for DML statements INSERT, UPDATE or DELETE. - "queryPlan": [ # [Output only] Describes execution plan for the query. - { + "queryPlan": [ # Output only. Describes execution plan for the query. + { # A single stage of query execution. "completedParallelInputs": "A String", # Number of parallel input segments completed. + "computeMode": "A String", # Output only. Compute mode for this stage. "computeMsAvg": "A String", # Milliseconds the average shard spent on CPU-bound tasks. "computeMsMax": "A String", # Milliseconds the slowest shard spent on CPU-bound tasks. "computeRatioAvg": 3.14, # Relative amount of time the average shard spent on CPU-bound tasks. "computeRatioMax": 3.14, # Relative amount of time the slowest shard spent on CPU-bound tasks. - "endMs": "A String", # Stage end time represented as milliseconds since epoch. - "id": "A String", # Unique ID for stage within plan. + "endMs": "A String", # Stage end time represented as milliseconds since the epoch. + "id": "A String", # Unique ID for the stage within the plan. "inputStages": [ # IDs for stages that are inputs to this stage. "A String", ], - "name": "A String", # Human-readable name for stage. - "parallelInputs": "A String", # Number of parallel input segments to be processed. + "name": "A String", # Human-readable name for the stage. + "parallelInputs": "A String", # Number of parallel input segments to be processed "readMsAvg": "A String", # Milliseconds the average shard spent reading input. "readMsMax": "A String", # Milliseconds the slowest shard spent reading input. "readRatioAvg": 3.14, # Relative amount of time the average shard spent reading input. @@ -2859,12 +5403,12 @@Method Details
"shuffleOutputBytes": "A String", # Total number of bytes written to shuffle. "shuffleOutputBytesSpilled": "A String", # Total number of bytes written to shuffle and spilled to disk. "slotMs": "A String", # Slot-milliseconds used by the stage. - "startMs": "A String", # Stage start time represented as milliseconds since epoch. - "status": "A String", # Current status for the stage. + "startMs": "A String", # Stage start time represented as milliseconds since the epoch. + "status": "A String", # Current status for this stage. "steps": [ # List of operations within the stage in dependency order (approximately chronological). - { + { # An operation within a stage. "kind": "A String", # Machine-readable operation type. - "substeps": [ # Human-readable stage descriptions. + "substeps": [ # Human-readable description of the step(s). "A String", ], }, @@ -2879,201 +5423,218 @@Method Details
"writeRatioMax": 3.14, # Relative amount of time the slowest shard spent on writing output. }, ], - "referencedRoutines": [ # [Output only] Referenced routines (persistent user-defined functions and stored procedures) for the job. - { + "referencedRoutines": [ # Output only. Referenced routines for the job. + { # Id path of a routine. "datasetId": "A String", # Required. The ID of the dataset containing this routine. "projectId": "A String", # Required. The ID of the project containing this routine. "routineId": "A String", # Required. The ID of the routine. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 256 characters. }, ], - "referencedTables": [ # [Output only] Referenced tables for the job. Queries that reference more than 50 tables will not have a complete list. + "referencedTables": [ # Output only. Referenced tables for the job. Queries that reference more than 50 tables will not have a complete list. { - "datasetId": "A String", # [Required] The ID of the dataset containing this table. - "projectId": "A String", # [Required] The ID of the project containing this table. - "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. + "datasetId": "A String", # Required. The ID of the dataset containing this table. + "projectId": "A String", # Required. The ID of the project containing this table. + "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`. }, ], - "reservationUsage": [ # [Output only] Job resource usage breakdown by reservation. - { - "name": "A String", # [Output only] Reservation name or "unreserved" for on-demand resources usage. - "slotMs": "A String", # [Output only] Slot-milliseconds the job spent in the given reservation. + "reservationUsage": [ # Output only. Job resource usage breakdown by reservation. This field reported misleading information and will no longer be populated. + { # Job resource usage breakdown by reservation. + "name": "A String", # Reservation name or "unreserved" for on-demand resources usage. + "slotMs": "A String", # Total slot milliseconds used by the reservation for a particular job. }, ], - "schema": { # [Output only] The schema of the results. Present only for successful dry run of non-legacy SQL queries. + "schema": { # Schema of a table # Output only. The schema of the results. Present only for successful dry run of non-legacy SQL queries. "fields": [ # Describes the fields in a table. - { - "categories": { # [Optional] The categories attached to this field, used for field-level access control. - "names": [ # A list of category resource names. For example, "projects/1/taxonomies/2/categories/3". At most 5 categories are allowed. + { # A field in TableSchema + "categories": { # Deprecated. + "names": [ # Deprecated. "A String", ], }, - "collation": "A String", # Optional. Collation specification of the field. It only can be set on string type field. - "defaultValueExpression": "A String", # Optional. A SQL expression to specify the default value for this field. It can only be set for top level fields (columns). You can use struct or array expression to specify default value for the entire struct or array. The valid SQL expressions are: - Literals for all data types, including STRUCT and ARRAY. - Following functions: - CURRENT_TIMESTAMP - CURRENT_TIME - CURRENT_DATE - CURRENT_DATETIME - GENERATE_UUID - RAND - SESSION_USER - ST_GEOGPOINT - Struct or array composed with the above allowed functions, for example, [CURRENT_DATE(), DATE '2020-01-01'] - "description": "A String", # [Optional] The field description. The maximum length is 1,024 characters. - "fields": [ # [Optional] Describes the nested schema fields if the type property is set to RECORD. + "collation": "A String", # Optional. Field collation can be set only when the type of field is STRING. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior. + "defaultValueExpression": "A String", # Optional. A SQL expression to specify the [default value] (https://cloud.google.com/bigquery/docs/default-values) for this field. + "description": "A String", # Optional. The field description. The maximum length is 1,024 characters. + "fields": [ # Optional. Describes the nested schema fields if the type property is set to RECORD. # Object with schema name: TableFieldSchema ], - "maxLength": "A String", # [Optional] Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES". - "mode": "A String", # [Optional] The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE. - "name": "A String", # [Required] The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters. - "policyTags": { - "names": [ # A list of category resource names. For example, "projects/1/location/eu/taxonomies/2/policyTags/3". At most 1 policy tag is allowed. + "maxLength": "A String", # Optional. Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES". + "mode": "A String", # Optional. The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE. + "name": "A String", # Required. The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters. + "policyTags": { # Optional. The policy tags attached to this field, used for field-level access control. If not set, defaults to empty policy_tags. + "names": [ # A list of policy tag resource names. For example, "projects/1/locations/eu/taxonomies/2/policyTags/3". At most 1 policy tag is currently allowed. "A String", ], }, - "precision": "A String", # [Optional] Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: - Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] - Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: - If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. - If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): - If type = "NUMERIC": 1 ≤ precision ≤ 29. - If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid. - "rangeElementType": { # Optional. The subtype of the RANGE, if the type of this field is RANGE. If the type is RANGE, this field is required. Possible values for the field element type of a RANGE include: - DATE - DATETIME - TIMESTAMP - "type": "A String", # The field element type of a RANGE + "precision": "A String", # Optional. Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: * Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] * Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: * If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. * If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): * If type = "NUMERIC": 1 ≤ precision ≤ 29. * If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid. + "rangeElementType": { # Represents the type of a field element. + "type": "A String", # Required. The type of a field element. See TableFieldSchema.type. }, - "roundingMode": "A String", # Optional. Rounding Mode specification of the field. It only can be set on NUMERIC or BIGNUMERIC type fields. - "scale": "A String", # [Optional] See documentation for precision. - "type": "A String", # [Required] The field data type. Possible values include STRING, BYTES, INTEGER, INT64 (same as INTEGER), FLOAT, FLOAT64 (same as FLOAT), NUMERIC, BIGNUMERIC, BOOLEAN, BOOL (same as BOOLEAN), TIMESTAMP, DATE, TIME, DATETIME, INTERVAL, RECORD (where RECORD indicates that the field contains a nested schema) or STRUCT (same as RECORD). + "roundingMode": "A String", # Optional. Specifies the rounding mode to be used when storing values of NUMERIC and BIGNUMERIC type. + "scale": "A String", # Optional. See documentation for precision. + "type": "A String", # Required. The field data type. Possible values include: * STRING * BYTES * INTEGER (or INT64) * FLOAT (or FLOAT64) * BOOLEAN (or BOOL) * TIMESTAMP * DATE * TIME * DATETIME * GEOGRAPHY * NUMERIC * BIGNUMERIC * JSON * RECORD (or STRUCT) Use of RECORD/STRUCT indicates that the field contains a nested schema. }, ], }, - "searchStatistics": { # [Output only] Search query specific statistics. - "indexUnusedReasons": [ # When index_usage_mode is UNUSED or PARTIALLY_USED, this field explains why index was not used in all or part of the search query. If index_usage_mode is FULLLY_USED, this field is not populated. - { - "baseTable": { # [Output-only] Specifies the base table involved in the reason that no search index was used. - "datasetId": "A String", # [Required] The ID of the dataset containing this table. - "projectId": "A String", # [Required] The ID of the project containing this table. - "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters. + "searchStatistics": { # Statistics for a search query. Populated as part of JobStatistics2. # Output only. Search query specific statistics. + "indexUnusedReasons": [ # When `indexUsageMode` is `UNUSED` or `PARTIALLY_USED`, this field explains why indexes were not used in all or part of the search query. If `indexUsageMode` is `FULLY_USED`, this field is not populated. + { # Reason about why no search index was used in the search query (or sub-query). + "baseTable": { # Specifies the base table involved in the reason that no search index was used. + "datasetId": "A String", # Required. The ID of the dataset containing this table. + "projectId": "A String", # Required. The ID of the project containing this table. + "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`. }, - "code": "$(reason.code)", # [Output-only] Specifies the high-level reason for the scenario when no search index was used. - "indexName": "$(reason.index_name)", # [Output-only] Specifies the name of the unused search index, if available. - "message": "$(reason.message)", # [Output-only] Free form human-readable reason for the scenario when no search index was used. + "code": "A String", # Specifies the high-level reason for the scenario when no search index was used. + "indexName": "A String", # Specifies the name of the unused search index, if available. + "message": "A String", # Free form human-readable reason for the scenario when no search index was used. }, ], - "indexUsageMode": "A String", # Specifies index usage mode for the query. + "indexUsageMode": "A String", # Specifies the index usage mode for the query. }, - "sparkStatistics": { # [Output only] Statistics of a Spark procedure job. - "endpoints": { # [Output-only] Endpoints generated for the Spark job. + "sparkStatistics": { # Statistics for a BigSpark query. Populated as part of JobStatistics2 # Output only. Statistics of a Spark procedure job. + "endpoints": { # Output only. Endpoints returned from Dataproc. Key list: - history_server_endpoint: A link to Spark job UI. "a_key": "A String", }, - "loggingInfo": { # [Output-only] Logging info is used to generate a link to Cloud Logging. - "projectId": "A String", # [Output-only] Project ID used for logging - "resourceType": "A String", # [Output-only] Resource type used for logging + "gcsStagingBucket": "A String", # Output only. The Google Cloud Storage bucket that is used as the default filesystem by the Spark application. This fields is only filled when the Spark procedure uses the INVOKER security mode. It is inferred from the system variable @@spark_proc_properties.staging_bucket if it is provided. Otherwise, BigQuery creates a default staging bucket for the job and returns the bucket name in this field. Example: * `gs://[bucket_name]` + "kmsKeyName": "A String", # Output only. The Cloud KMS encryption key that is used to protect the resources created by the Spark job. If the Spark procedure uses DEFINER security mode, the Cloud KMS key is inferred from the Spark connection associated with the procedure if it is provided. Otherwise the key is inferred from the default key of the Spark connection's project if the CMEK organization policy is enforced. If the Spark procedure uses INVOKER security mode, the Cloud KMS encryption key is inferred from the system variable @@spark_proc_properties.kms_key_name if it is provided. Otherwise, the key is inferred fromt he default key of the BigQuery job's project if the CMEK organization policy is enforced. Example: * `projects/[kms_project_id]/locations/[region]/keyRings/[key_region]/cryptoKeys/[key]` + "loggingInfo": { # Spark job logs can be filtered by these fields in Cloud Logging. # Output only. Logging info is used to generate a link to Cloud Logging. + "projectId": "A String", # Output only. Project ID where the Spark logs were written. + "resourceType": "A String", # Output only. Resource type used for logging. }, - "sparkJobId": "A String", # [Output-only] Spark job id if a Spark job is created successfully. - "sparkJobLocation": "A String", # [Output-only] Location where the Spark job is executed. + "sparkJobId": "A String", # Output only. Spark job ID if a Spark job is created successfully. + "sparkJobLocation": "A String", # Output only. Location where the Spark job is executed. A location is selected by BigQueury for jobs configured to run in a multi-region. }, - "statementType": "A String", # The type of query statement, if valid. Possible values (new values might be added in the future): "SELECT": SELECT query. "INSERT": INSERT query; see https://cloud.google.com/bigquery/docs/reference/standard-sql/data-manipulation-language. "UPDATE": UPDATE query; see https://cloud.google.com/bigquery/docs/reference/standard-sql/data-manipulation-language. "DELETE": DELETE query; see https://cloud.google.com/bigquery/docs/reference/standard-sql/data-manipulation-language. "MERGE": MERGE query; see https://cloud.google.com/bigquery/docs/reference/standard-sql/data-manipulation-language. "ALTER_TABLE": ALTER TABLE query. "ALTER_VIEW": ALTER VIEW query. "ASSERT": ASSERT condition AS 'description'. "CREATE_FUNCTION": CREATE FUNCTION query. "CREATE_MODEL": CREATE [OR REPLACE] MODEL ... AS SELECT ... . "CREATE_PROCEDURE": CREATE PROCEDURE query. "CREATE_TABLE": CREATE [OR REPLACE] TABLE without AS SELECT. "CREATE_TABLE_AS_SELECT": CREATE [OR REPLACE] TABLE ... AS SELECT ... . "CREATE_VIEW": CREATE [OR REPLACE] VIEW ... AS SELECT ... . "DROP_FUNCTION" : DROP FUNCTION query. "DROP_PROCEDURE": DROP PROCEDURE query. "DROP_TABLE": DROP TABLE query. "DROP_VIEW": DROP VIEW query. - "timeline": [ # [Output only] [Beta] Describes a timeline of job execution. - { - "activeUnits": "A String", # Total number of units currently being processed by workers. This does not correspond directly to slot usage. This is the largest value observed since the last sample. + "statementType": "A String", # Output only. The type of query statement, if valid. Possible values: * `SELECT`: [`SELECT`](/bigquery/docs/reference/standard-sql/query-syntax#select_list) statement. * `ASSERT`: [`ASSERT`](/bigquery/docs/reference/standard-sql/debugging-statements#assert) statement. * `INSERT`: [`INSERT`](/bigquery/docs/reference/standard-sql/dml-syntax#insert_statement) statement. * `UPDATE`: [`UPDATE`](/bigquery/docs/reference/standard-sql/query-syntax#update_statement) statement. * `DELETE`: [`DELETE`](/bigquery/docs/reference/standard-sql/data-manipulation-language) statement. * `MERGE`: [`MERGE`](/bigquery/docs/reference/standard-sql/data-manipulation-language) statement. * `CREATE_TABLE`: [`CREATE TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#create_table_statement) statement, without `AS SELECT`. * `CREATE_TABLE_AS_SELECT`: [`CREATE TABLE AS SELECT`](/bigquery/docs/reference/standard-sql/data-definition-language#query_statement) statement. * `CREATE_VIEW`: [`CREATE VIEW`](/bigquery/docs/reference/standard-sql/data-definition-language#create_view_statement) statement. * `CREATE_MODEL`: [`CREATE MODEL`](/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-create#create_model_statement) statement. * `CREATE_MATERIALIZED_VIEW`: [`CREATE MATERIALIZED VIEW`](/bigquery/docs/reference/standard-sql/data-definition-language#create_materialized_view_statement) statement. * `CREATE_FUNCTION`: [`CREATE FUNCTION`](/bigquery/docs/reference/standard-sql/data-definition-language#create_function_statement) statement. * `CREATE_TABLE_FUNCTION`: [`CREATE TABLE FUNCTION`](/bigquery/docs/reference/standard-sql/data-definition-language#create_table_function_statement) statement. * `CREATE_PROCEDURE`: [`CREATE PROCEDURE`](/bigquery/docs/reference/standard-sql/data-definition-language#create_procedure) statement. * `CREATE_ROW_ACCESS_POLICY`: [`CREATE ROW ACCESS POLICY`](/bigquery/docs/reference/standard-sql/data-definition-language#create_row_access_policy_statement) statement. * `CREATE_SCHEMA`: [`CREATE SCHEMA`](/bigquery/docs/reference/standard-sql/data-definition-language#create_schema_statement) statement. * `CREATE_SNAPSHOT_TABLE`: [`CREATE SNAPSHOT TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#create_snapshot_table_statement) statement. * `CREATE_SEARCH_INDEX`: [`CREATE SEARCH INDEX`](/bigquery/docs/reference/standard-sql/data-definition-language#create_search_index_statement) statement. * `DROP_TABLE`: [`DROP TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_table_statement) statement. * `DROP_EXTERNAL_TABLE`: [`DROP EXTERNAL TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_external_table_statement) statement. * `DROP_VIEW`: [`DROP VIEW`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_view_statement) statement. * `DROP_MODEL`: [`DROP MODEL`](/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-drop-model) statement. * `DROP_MATERIALIZED_VIEW`: [`DROP MATERIALIZED VIEW`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_materialized_view_statement) statement. * `DROP_FUNCTION` : [`DROP FUNCTION`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_function_statement) statement. * `DROP_TABLE_FUNCTION` : [`DROP TABLE FUNCTION`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_table_function) statement. * `DROP_PROCEDURE`: [`DROP PROCEDURE`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_procedure_statement) statement. * `DROP_SEARCH_INDEX`: [`DROP SEARCH INDEX`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_search_index) statement. * `DROP_SCHEMA`: [`DROP SCHEMA`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_schema_statement) statement. * `DROP_SNAPSHOT_TABLE`: [`DROP SNAPSHOT TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_snapshot_table_statement) statement. * `DROP_ROW_ACCESS_POLICY`: [`DROP [ALL] ROW ACCESS POLICY|POLICIES`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_row_access_policy_statement) statement. * `ALTER_TABLE`: [`ALTER TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#alter_table_set_options_statement) statement. * `ALTER_VIEW`: [`ALTER VIEW`](/bigquery/docs/reference/standard-sql/data-definition-language#alter_view_set_options_statement) statement. * `ALTER_MATERIALIZED_VIEW`: [`ALTER MATERIALIZED VIEW`](/bigquery/docs/reference/standard-sql/data-definition-language#alter_materialized_view_set_options_statement) statement. * `ALTER_SCHEMA`: [`ALTER SCHEMA`](/bigquery/docs/reference/standard-sql/data-definition-language#aalter_schema_set_options_statement) statement. * `SCRIPT`: [`SCRIPT`](/bigquery/docs/reference/standard-sql/procedural-language). * `TRUNCATE_TABLE`: [`TRUNCATE TABLE`](/bigquery/docs/reference/standard-sql/dml-syntax#truncate_table_statement) statement. * `CREATE_EXTERNAL_TABLE`: [`CREATE EXTERNAL TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#create_external_table_statement) statement. * `EXPORT_DATA`: [`EXPORT DATA`](/bigquery/docs/reference/standard-sql/other-statements#export_data_statement) statement. * `EXPORT_MODEL`: [`EXPORT MODEL`](/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-export-model) statement. * `LOAD_DATA`: [`LOAD DATA`](/bigquery/docs/reference/standard-sql/other-statements#load_data_statement) statement. * `CALL`: [`CALL`](/bigquery/docs/reference/standard-sql/procedural-language#call) statement. + "timeline": [ # Output only. Describes a timeline of job execution. + { # Summary of the state of query execution at a given time. + "activeUnits": "A String", # Total number of active workers. This does not correspond directly to slot usage. This is the largest value observed since the last sample. "completedUnits": "A String", # Total parallel units of work completed by this query. "elapsedMs": "A String", # Milliseconds elapsed since the start of query execution. - "estimatedRunnableUnits": "A String", # Units of work that can be scheduled immediately. Providing additional slots for these units of work will speed up the query, provided no other query in the reservation needs additional slots. + "estimatedRunnableUnits": "A String", # Units of work that can be scheduled immediately. Providing additional slots for these units of work will accelerate the query, if no other query in the reservation needs additional slots. "pendingUnits": "A String", # Total units of work remaining for the query. This number can be revised (increased or decreased) while the query is running. "totalSlotMs": "A String", # Cumulative slot-ms consumed by the query. }, ], - "totalBytesBilled": "A String", # [Output only] Total bytes billed for the job. - "totalBytesProcessed": "A String", # [Output only] Total bytes processed for the job. - "totalBytesProcessedAccuracy": "A String", # [Output only] For dry-run jobs, totalBytesProcessed is an estimate and this field specifies the accuracy of the estimate. Possible values can be: UNKNOWN: accuracy of the estimate is unknown. PRECISE: estimate is precise. LOWER_BOUND: estimate is lower bound of what the query would cost. UPPER_BOUND: estimate is upper bound of what the query would cost. - "totalPartitionsProcessed": "A String", # [Output only] Total number of partitions processed from all partitioned tables referenced in the job. - "totalSlotMs": "A String", # [Output only] Slot-milliseconds for the job. - "transferredBytes": "A String", # [Output-only] Total bytes transferred for cross-cloud queries such as Cross Cloud Transfer and CREATE TABLE AS SELECT (CTAS). - "undeclaredQueryParameters": [ # Standard SQL only: list of undeclared query parameters detected during a dry run validation. - { - "name": "A String", # [Optional] If unset, this is a positional parameter. Otherwise, should be unique within a query. - "parameterType": { # [Required] The type of this parameter. - "arrayType": # Object with schema name: QueryParameterType # [Optional] The type of the array's elements, if this is an array. - "rangeElementType": # Object with schema name: QueryParameterType # [Optional] The element type of the range, if this is a range. - "structTypes": [ # [Optional] The types of the fields of this struct, in order, if this is a struct. - { - "description": "A String", # [Optional] Human-oriented description of the field. - "name": "A String", # [Optional] The name of this field. - "type": # Object with schema name: QueryParameterType # [Required] The type of this field. + "totalBytesBilled": "A String", # Output only. If the project is configured to use on-demand pricing, then this field contains the total bytes billed for the job. If the project is configured to use flat-rate pricing, then you are not billed for bytes and this field is informational only. + "totalBytesProcessed": "A String", # Output only. Total bytes processed for the job. + "totalBytesProcessedAccuracy": "A String", # Output only. For dry-run jobs, totalBytesProcessed is an estimate and this field specifies the accuracy of the estimate. Possible values can be: UNKNOWN: accuracy of the estimate is unknown. PRECISE: estimate is precise. LOWER_BOUND: estimate is lower bound of what the query would cost. UPPER_BOUND: estimate is upper bound of what the query would cost. + "totalPartitionsProcessed": "A String", # Output only. Total number of partitions processed from all partitioned tables referenced in the job. + "totalSlotMs": "A String", # Output only. Slot-milliseconds for the job. + "transferredBytes": "A String", # Output only. Total bytes transferred for cross-cloud queries such as Cross Cloud Transfer and CREATE TABLE AS SELECT (CTAS). + "undeclaredQueryParameters": [ # Output only. GoogleSQL only: list of undeclared query parameters detected during a dry run validation. + { # A parameter given to a query. + "name": "A String", # Optional. If unset, this is a positional parameter. Otherwise, should be unique within a query. + "parameterType": { # The type of a query parameter. # Required. The type of this parameter. + "arrayType": # Object with schema name: QueryParameterType # Optional. The type of the array's elements, if this is an array. + "rangeElementType": # Object with schema name: QueryParameterType # Optional. The element type of the range, if this is a range. + "structTypes": [ # Optional. The types of the fields of this struct, in order, if this is a struct. + { # The type of a struct parameter. + "description": "A String", # Optional. Human-oriented description of the field. + "name": "A String", # Optional. The name of this field. + "type": # Object with schema name: QueryParameterType # Required. The type of this field. }, ], - "type": "A String", # [Required] The top level type of this field. + "type": "A String", # Required. The top level type of this field. }, - "parameterValue": { # [Required] The value of this parameter. - "arrayValues": [ # [Optional] The array values, if this is an array type. + "parameterValue": { # The value of a query parameter. # Required. The value of this parameter. + "arrayValues": [ # Optional. The array values, if this is an array type. # Object with schema name: QueryParameterValue ], - "rangeValue": { # [Optional] The range value, if this is a range type. - "end": # Object with schema name: QueryParameterValue - "start": # Object with schema name: QueryParameterValue + "rangeValue": { # Represents the value of a range. # Optional. The range value, if this is a range type. + "end": # Object with schema name: QueryParameterValue # Optional. The end value of the range. A missing value represents an unbounded end. + "start": # Object with schema name: QueryParameterValue # Optional. The start value of the range. A missing value represents an unbounded start. }, - "structValues": { # [Optional] The struct field values, in order of the struct type's declaration. + "structValues": { # The struct field values. "a_key": # Object with schema name: QueryParameterValue }, - "value": "A String", # [Optional] The value of this value, if a simple scalar type. + "value": "A String", # Optional. The value of this value, if a simple scalar type. }, }, ], + "vectorSearchStatistics": { # Statistics for a vector search query. Populated as part of JobStatistics2. # Output only. Search query specific statistics. + "indexUnusedReasons": [ # When `indexUsageMode` is `UNUSED` or `PARTIALLY_USED`, this field explains why indexes were not used in all or part of the vector search query. If `indexUsageMode` is `FULLY_USED`, this field is not populated. + { # Reason about why no search index was used in the search query (or sub-query). + "baseTable": { # Specifies the base table involved in the reason that no search index was used. + "datasetId": "A String", # Required. The ID of the dataset containing this table. + "projectId": "A String", # Required. The ID of the project containing this table. + "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`. + }, + "code": "A String", # Specifies the high-level reason for the scenario when no search index was used. + "indexName": "A String", # Specifies the name of the unused search index, if available. + "message": "A String", # Free form human-readable reason for the scenario when no search index was used. + }, + ], + "indexUsageMode": "A String", # Specifies the index usage mode for the query. + }, }, - "quotaDeferments": [ # [Output-only] Quotas which delayed this job's start time. + "quotaDeferments": [ # Output only. Quotas which delayed this job's start time. "A String", ], - "reservationUsage": [ # [Output-only] Job resource usage breakdown by reservation. - { - "name": "A String", # [Output-only] Reservation name or "unreserved" for on-demand resources usage. - "slotMs": "A String", # [Output-only] Slot-milliseconds the job spent in the given reservation. + "reservationUsage": [ # Output only. Job resource usage breakdown by reservation. This field reported misleading information and will no longer be populated. + { # Job resource usage breakdown by reservation. + "name": "A String", # Reservation name or "unreserved" for on-demand resources usage. + "slotMs": "A String", # Total slot milliseconds used by the reservation for a particular job. }, ], - "reservation_id": "A String", # [Output-only] Name of the primary reservation assigned to this job. Note that this could be different than reservations reported in the reservation usage field if parent reservations were used to execute this job. - "rowLevelSecurityStatistics": { # [Output-only] [Preview] Statistics for row-level security. Present only for query and extract jobs. - "rowLevelSecurityApplied": True or False, # [Output-only] [Preview] Whether any accessed data was protected by row access policies. + "reservation_id": "A String", # Output only. Name of the primary reservation assigned to this job. Note that this could be different than reservations reported in the reservation usage field if parent reservations were used to execute this job. + "rowLevelSecurityStatistics": { # Statistics for row-level security. # Output only. Statistics for row-level security. Present only for query and extract jobs. + "rowLevelSecurityApplied": True or False, # Whether any accessed data was protected by row access policies. }, - "scriptStatistics": { # [Output-only] Statistics for a child job of a script. - "evaluationKind": "A String", # [Output-only] Whether this child job was a statement or expression. + "scriptStatistics": { # Job statistics specific to the child job of a script. # Output only. If this a child job of a script, specifies information about the context of this job within the script. + "evaluationKind": "A String", # Whether this child job was a statement or expression. "stackFrames": [ # Stack trace showing the line/column/procedure name of each frame on the stack at the point where the current evaluation happened. The leaf frame is first, the primary script is last. Never empty. - { - "endColumn": 42, # [Output-only] One-based end column. - "endLine": 42, # [Output-only] One-based end line. - "procedureId": "A String", # [Output-only] Name of the active procedure, empty if in a top-level script. - "startColumn": 42, # [Output-only] One-based start column. - "startLine": 42, # [Output-only] One-based start line. - "text": "A String", # [Output-only] Text of the current statement/expression. + { # Represents the location of the statement/expression being evaluated. Line and column numbers are defined as follows: - Line and column numbers start with one. That is, line 1 column 1 denotes the start of the script. - When inside a stored procedure, all line/column numbers are relative to the procedure body, not the script in which the procedure was defined. - Start/end positions exclude leading/trailing comments and whitespace. The end position always ends with a ";", when present. - Multi-byte Unicode characters are treated as just one column. - If the original script (or procedure definition) contains TAB characters, a tab "snaps" the indentation forward to the nearest multiple of 8 characters, plus 1. For example, a TAB on column 1, 2, 3, 4, 5, 6 , or 8 will advance the next character to column 9. A TAB on column 9, 10, 11, 12, 13, 14, 15, or 16 will advance the next character to column 17. + "endColumn": 42, # Output only. One-based end column. + "endLine": 42, # Output only. One-based end line. + "procedureId": "A String", # Output only. Name of the active procedure, empty if in a top-level script. + "startColumn": 42, # Output only. One-based start column. + "startLine": 42, # Output only. One-based start line. + "text": "A String", # Output only. Text of the current statement/expression. }, ], }, - "sessionInfo": { # [Output-only] [Preview] Information of the session if this job is part of one. - "sessionId": "A String", # [Output-only] // [Preview] Id of the session. + "sessionInfo": { # [Preview] Information related to sessions. # Output only. Information of the session if this job is part of one. + "sessionId": "A String", # Output only. The id of the session. }, - "startTime": "A String", # [Output-only] Start time of this job, in milliseconds since the epoch. This field will be present when the job transitions from the PENDING state to either RUNNING or DONE. - "totalBytesProcessed": "A String", # [Output-only] [Deprecated] Use the bytes processed in the query statistics instead. - "totalSlotMs": "A String", # [Output-only] Slot-milliseconds for the job. - "transactionInfo": { # [Output-only] [Alpha] Information of the multi-statement transaction if this job is part of one. - "transactionId": "A String", # [Output-only] // [Alpha] Id of the transaction. + "startTime": "A String", # Output only. Start time of this job, in milliseconds since the epoch. This field will be present when the job transitions from the PENDING state to either RUNNING or DONE. + "totalBytesProcessed": "A String", # Output only. Total bytes processed for the job. + "totalSlotMs": "A String", # Output only. Slot-milliseconds for the job. + "transactionInfo": { # [Alpha] Information of a multi-statement transaction. # Output only. [Alpha] Information of the multi-statement transaction if this job is part of one. This property is only expected on a child job or a job that is in a session. A script parent job is not part of the transaction started in the script. + "transactionId": "A String", # Output only. [Alpha] Id of the transaction. }, }, - "status": { # [Output-only] The status of this job. Examine this value when polling an asynchronous job to see if the job is complete. - "errorResult": { # [Output-only] Final error result of the job. If present, indicates that the job has completed and was unsuccessful. + "status": { # Output only. The status of this job. Examine this value when polling an asynchronous job to see if the job is complete. + "errorResult": { # Error details. # Output only. Final error result of the job. If present, indicates that the job has completed and was unsuccessful. "debugInfo": "A String", # Debugging information. This property is internal to Google and should not be used. "location": "A String", # Specifies where the error occurred, if present. "message": "A String", # A human-readable description of the error. "reason": "A String", # A short error code that summarizes the error. }, - "errors": [ # [Output-only] The first errors encountered during the running of the job. The final message includes the number of errors that caused the process to stop. Errors here do not necessarily mean that the job has completed or was unsuccessful. - { + "errors": [ # Output only. The first errors encountered during the running of the job. The final message includes the number of errors that caused the process to stop. Errors here do not necessarily mean that the job has not completed or was unsuccessful. + { # Error details. "debugInfo": "A String", # Debugging information. This property is internal to Google and should not be used. "location": "A String", # Specifies where the error occurred, if present. "message": "A String", # A human-readable description of the error. "reason": "A String", # A short error code that summarizes the error. }, ], - "state": "A String", # [Output-only] Running state of the job. + "state": "A String", # Output only. Running state of the job. Valid states include 'PENDING', 'RUNNING', and 'DONE'. }, - "user_email": "A String", # [Output-only] Email address of the user who ran the job. + "user_email": "A String", # Output only. Email address of the user who ran the job. }
list(projectId, allUsers=None, maxCreationTime=None, maxResults=None, minCreationTime=None, pageToken=None, parentJobId=None, projection=None, stateFilter=None)
+ list(projectId, allUsers=None, maxCreationTime=None, maxResults=None, minCreationTime=None, pageToken=None, parentJobId=None, projection=None, stateFilter=None, x__xgafv=None)
Lists all jobs that you started in the specified project. Job information is available for a six month period after creation. The job list is sorted in reverse chronological order, by job creation time. Requires the Can View project role, or the Is Owner project role if you set the allUsers property.
Args:
- projectId: string, Project ID of the jobs to list (required)
- allUsers: boolean, Whether to display jobs owned by all users in the project. Default false
- maxCreationTime: string, Max value for job creation time, in milliseconds since the POSIX epoch. If set, only jobs created before or at this timestamp are returned
- maxResults: integer, Maximum number of results to return
- minCreationTime: string, Min value for job creation time, in milliseconds since the POSIX epoch. If set, only jobs created after or at this timestamp are returned
- pageToken: string, Page token, returned by a previous call, to request the next page of results
- parentJobId: string, If set, retrieves only jobs whose parent is this job. Otherwise, retrieves only jobs which have no parent
+ projectId: string, Project ID of the jobs to list. (required)
+ allUsers: boolean, Whether to display jobs owned by all users in the project. Default False.
+ maxCreationTime: string, Max value for job creation time, in milliseconds since the POSIX epoch. If set, only jobs created before or at this timestamp are returned.
+ maxResults: integer, The maximum number of results to return in a single response page. Leverage the page tokens to iterate through the entire collection.
+ minCreationTime: string, Min value for job creation time, in milliseconds since the POSIX epoch. If set, only jobs created after or at this timestamp are returned.
+ pageToken: string, Page token, returned by a previous call, to request the next page of results.
+ parentJobId: string, If set, show only child jobs of the specified parent. Otherwise, show all top-level jobs.
projection: string, Restrict information returned to a set of selected fields
Allowed values
full - Includes all job data
@@ -3083,506 +5644,1126 @@ Method Details
done - Finished jobs
pending - Pending jobs
running - Running jobs
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
Returns:
An object of the form:
- {
+ { # JobList is the response format for a jobs.list call.
"etag": "A String", # A hash of this page of results.
"jobs": [ # List of jobs that were requested.
- {
- "configuration": { # [Full-projection-only] Specifies the job configuration.
- "copy": { # [Pick one] Copies a table.
- "createDisposition": "A String", # [Optional] Specifies whether the job is allowed to create new tables. The following values are supported: CREATE_IF_NEEDED: If the table does not exist, BigQuery creates the table. CREATE_NEVER: The table must already exist. If it does not, a 'notFound' error is returned in the job result. The default value is CREATE_IF_NEEDED. Creation, truncation and append actions occur as one atomic update upon job completion.
+ { # ListFormatJob is a partial projection of job information returned as part of a jobs.list response.
+ "configuration": { # Required. Describes the job configuration.
+ "copy": { # JobConfigurationTableCopy configures a job that copies data from one table to another. For more information on copying tables, see [Copy a table](https://cloud.google.com/bigquery/docs/managing-tables#copy-table). # [Pick one] Copies a table.
+ "createDisposition": "A String", # Optional. Specifies whether the job is allowed to create new tables. The following values are supported: * CREATE_IF_NEEDED: If the table does not exist, BigQuery creates the table. * CREATE_NEVER: The table must already exist. If it does not, a 'notFound' error is returned in the job result. The default value is CREATE_IF_NEEDED. Creation, truncation and append actions occur as one atomic update upon job completion.
"destinationEncryptionConfiguration": { # Custom encryption configuration (e.g., Cloud KMS keys).
"kmsKeyName": "A String", # Optional. Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key.
},
- "destinationExpirationTime": "", # [Optional] The time when the destination table expires. Expired tables will be deleted and their storage reclaimed.
- "destinationTable": { # [Required] The destination table
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "destinationExpirationTime": "A String", # Optional. The time when the destination table expires. Expired tables will be deleted and their storage reclaimed.
+ "destinationTable": { # [Required] The destination table.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
- "operationType": "A String", # [Optional] Supported operation types in table copy job.
+ "operationType": "A String", # Optional. Supported operation types in table copy job.
"sourceTable": { # [Pick one] Source table to copy.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
"sourceTables": [ # [Pick one] Source tables to copy.
{
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
],
- "writeDisposition": "A String", # [Optional] Specifies the action that occurs if the destination table already exists. The following values are supported: WRITE_TRUNCATE: If the table already exists, BigQuery overwrites the table data. WRITE_APPEND: If the table already exists, BigQuery appends the data to the table. WRITE_EMPTY: If the table already exists and contains data, a 'duplicate' error is returned in the job result. The default value is WRITE_EMPTY. Each action is atomic and only occurs if BigQuery is able to complete the job successfully. Creation, truncation and append actions occur as one atomic update upon job completion.
+ "writeDisposition": "A String", # Optional. Specifies the action that occurs if the destination table already exists. The following values are supported: * WRITE_TRUNCATE: If the table already exists, BigQuery overwrites the table data and uses the schema and table constraints from the source table. * WRITE_APPEND: If the table already exists, BigQuery appends the data to the table. * WRITE_EMPTY: If the table already exists and contains data, a 'duplicate' error is returned in the job result. The default value is WRITE_EMPTY. Each action is atomic and only occurs if BigQuery is able to complete the job successfully. Creation, truncation and append actions occur as one atomic update upon job completion.
},
- "dryRun": True or False, # [Optional] If set, don't actually run this job. A valid query will return a mostly empty response with some processing statistics, while an invalid query will return the same error it would if it wasn't a dry run. Behavior of non-query jobs is undefined.
- "extract": { # [Pick one] Configures an extract job.
- "compression": "A String", # [Optional] The compression type to use for exported files. Possible values include GZIP, DEFLATE, SNAPPY, and NONE. The default value is NONE. DEFLATE and SNAPPY are only supported for Avro. Not applicable when extracting models.
- "destinationFormat": "A String", # [Optional] The exported file format. Possible values include CSV, NEWLINE_DELIMITED_JSON, PARQUET or AVRO for tables and ML_TF_SAVED_MODEL or ML_XGBOOST_BOOSTER for models. The default value for tables is CSV. Tables with nested or repeated fields cannot be exported as CSV. The default value for models is ML_TF_SAVED_MODEL.
+ "dryRun": True or False, # Optional. If set, don't actually run this job. A valid query will return a mostly empty response with some processing statistics, while an invalid query will return the same error it would if it wasn't a dry run. Behavior of non-query jobs is undefined.
+ "extract": { # JobConfigurationExtract configures a job that exports data from a BigQuery table into Google Cloud Storage. # [Pick one] Configures an extract job.
+ "compression": "A String", # Optional. The compression type to use for exported files. Possible values include DEFLATE, GZIP, NONE, SNAPPY, and ZSTD. The default value is NONE. Not all compression formats are support for all file formats. DEFLATE is only supported for Avro. ZSTD is only supported for Parquet. Not applicable when extracting models.
+ "destinationFormat": "A String", # Optional. The exported file format. Possible values include CSV, NEWLINE_DELIMITED_JSON, PARQUET, or AVRO for tables and ML_TF_SAVED_MODEL or ML_XGBOOST_BOOSTER for models. The default value for tables is CSV. Tables with nested or repeated fields cannot be exported as CSV. The default value for models is ML_TF_SAVED_MODEL.
"destinationUri": "A String", # [Pick one] DEPRECATED: Use destinationUris instead, passing only one URI as necessary. The fully-qualified Google Cloud Storage URI where the extracted table should be written.
"destinationUris": [ # [Pick one] A list of fully-qualified Google Cloud Storage URIs where the extracted table should be written.
"A String",
],
- "fieldDelimiter": "A String", # [Optional] Delimiter to use between fields in the exported data. Default is ','. Not applicable when extracting models.
- "printHeader": true, # [Optional] Whether to print out a header row in the results. Default is true. Not applicable when extracting models.
- "sourceModel": { # A reference to the model being exported.
+ "fieldDelimiter": "A String", # Optional. When extracting data in CSV format, this defines the delimiter to use between fields in the exported data. Default is ','. Not applicable when extracting models.
+ "modelExtractOptions": { # Options related to model extraction. # Optional. Model extract options only applicable when extracting models.
+ "trialId": "A String", # The 1-based ID of the trial to be exported from a hyperparameter tuning model. If not specified, the trial with id = [Model](/bigquery/docs/reference/rest/v2/models#resource:-model).defaultTrialId is exported. This field is ignored for models not trained with hyperparameter tuning.
+ },
+ "printHeader": true, # Optional. Whether to print out a header row in the results. Default is true. Not applicable when extracting models.
+ "sourceModel": { # Id path of a model. # A reference to the model being exported.
"datasetId": "A String", # Required. The ID of the dataset containing this model.
"modelId": "A String", # Required. The ID of the model. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
"projectId": "A String", # Required. The ID of the project containing this model.
},
"sourceTable": { # A reference to the table being exported.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
- "useAvroLogicalTypes": True or False, # [Optional] If destinationFormat is set to "AVRO", this flag indicates whether to enable extracting applicable column types (such as TIMESTAMP) to their corresponding AVRO logical types (timestamp-micros), instead of only using their raw types (avro-long). Not applicable when extracting models.
+ "useAvroLogicalTypes": True or False, # Whether to use logical types when extracting to AVRO format. Not applicable when extracting models.
},
- "jobTimeoutMs": "A String", # [Optional] Job timeout in milliseconds. If this time limit is exceeded, BigQuery may attempt to terminate the job.
- "jobType": "A String", # [Output-only] The type of the job. Can be QUERY, LOAD, EXTRACT, COPY or UNKNOWN.
+ "jobTimeoutMs": "A String", # Optional. Job timeout in milliseconds. If this time limit is exceeded, BigQuery might attempt to stop the job.
+ "jobType": "A String", # Output only. The type of the job. Can be QUERY, LOAD, EXTRACT, COPY or UNKNOWN.
"labels": { # The labels associated with this job. You can use these to organize and group your jobs. Label keys and values can be no longer than 63 characters, can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. Label values are optional. Label keys must start with a letter and each label in the list must have a different key.
"a_key": "A String",
},
- "load": { # [Pick one] Configures a load job.
- "allowJaggedRows": True or False, # [Optional] Accept rows that are missing trailing optional columns. The missing values are treated as nulls. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. Only applicable to CSV, ignored for other formats.
+ "load": { # JobConfigurationLoad contains the configuration properties for loading data into a destination table. # [Pick one] Configures a load job.
+ "allowJaggedRows": True or False, # Optional. Accept rows that are missing trailing optional columns. The missing values are treated as nulls. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. Only applicable to CSV, ignored for other formats.
"allowQuotedNewlines": True or False, # Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false.
- "autodetect": True or False, # [Optional] Indicates if we should automatically infer the options and schema for CSV and JSON sources.
- "clustering": { # [Beta] Clustering specification for the destination table. Must be specified with time-based partitioning, data in the table will be first partitioned and subsequently clustered.
- "fields": [ # [Repeated] One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. When you cluster a table using multiple columns, the order of columns you specify is important. The order of the specified columns determines the sort order of the data.
+ "autodetect": True or False, # Optional. Indicates if we should automatically infer the options and schema for CSV and JSON sources.
+ "clustering": { # Configures table clustering. # Clustering specification for the destination table.
+ "fields": [ # One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. The ordering of the clustering fields should be prioritized from most to least important for filtering purposes. Additional information on limitations can be found here: https://cloud.google.com/bigquery/docs/creating-clustered-tables#limitations
"A String",
],
},
- "connectionProperties": [ # Connection properties.
- {
- "key": "A String", # [Required] Name of the connection property to set.
- "value": "A String", # [Required] Value of the connection property.
+ "connectionProperties": [ # Optional. Connection properties which can modify the load job behavior. Currently, only the 'session_id' connection property is supported, and is used to resolve _SESSION appearing as the dataset id.
+ { # A connection-level property to customize query behavior. Under JDBC, these correspond directly to connection properties passed to the DriverManager. Under ODBC, these correspond to properties in the connection string. Currently supported connection properties: * **dataset_project_id**: represents the default project for datasets that are used in the query. Setting the system variable `@@dataset_project_id` achieves the same behavior. For more information about system variables, see: https://cloud.google.com/bigquery/docs/reference/system-variables * **time_zone**: represents the default timezone used to run the query. * **session_id**: associates the query with a given session. * **query_label**: associates the query with a given job label. If set, all subsequent queries in a script or session will have this label. For the format in which a you can specify a query label, see labels in the JobConfiguration resource type: https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#jobconfiguration Additional properties are allowed, but ignored. Specifying multiple connection properties with the same key returns an error.
+ "key": "A String", # The key of the property to set.
+ "value": "A String", # The value of the property to set.
},
],
- "createDisposition": "A String", # [Optional] Specifies whether the job is allowed to create new tables. The following values are supported: CREATE_IF_NEEDED: If the table does not exist, BigQuery creates the table. CREATE_NEVER: The table must already exist. If it does not, a 'notFound' error is returned in the job result. The default value is CREATE_IF_NEEDED. Creation, truncation and append actions occur as one atomic update upon job completion.
- "createSession": True or False, # If true, creates a new session, where session id will be a server generated random id. If false, runs query with an existing session_id passed in ConnectionProperty, otherwise runs the load job in non-session mode.
- "decimalTargetTypes": [ # [Optional] Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown. Example: Suppose the value of this field is ["NUMERIC", "BIGNUMERIC"]. If (precision,scale) is: (38,9) -> NUMERIC; (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits); (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits); (76,38) -> BIGNUMERIC; (77,38) -> BIGNUMERIC (error if value exeeds supported range). This field cannot contain duplicate types. The order of the types in this field is ignored. For example, ["BIGNUMERIC", "NUMERIC"] is the same as ["NUMERIC", "BIGNUMERIC"] and NUMERIC always takes precedence over BIGNUMERIC. Defaults to ["NUMERIC", "STRING"] for ORC and ["NUMERIC"] for the other file formats.
+ "createDisposition": "A String", # Optional. Specifies whether the job is allowed to create new tables. The following values are supported: * CREATE_IF_NEEDED: If the table does not exist, BigQuery creates the table. * CREATE_NEVER: The table must already exist. If it does not, a 'notFound' error is returned in the job result. The default value is CREATE_IF_NEEDED. Creation, truncation and append actions occur as one atomic update upon job completion.
+ "createSession": True or False, # Optional. If this property is true, the job creates a new session using a randomly generated session_id. To continue using a created session with subsequent queries, pass the existing session identifier as a `ConnectionProperty` value. The session identifier is returned as part of the `SessionInfo` message within the query statistics. The new session's location will be set to `Job.JobReference.location` if it is present, otherwise it's set to the default location based on existing routing logic.
+ "decimalTargetTypes": [ # Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown. Example: Suppose the value of this field is ["NUMERIC", "BIGNUMERIC"]. If (precision,scale) is: * (38,9) -> NUMERIC; * (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits); * (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits); * (76,38) -> BIGNUMERIC; * (77,38) -> BIGNUMERIC (error if value exeeds supported range). This field cannot contain duplicate types. The order of the types in this field is ignored. For example, ["BIGNUMERIC", "NUMERIC"] is the same as ["NUMERIC", "BIGNUMERIC"] and NUMERIC always takes precedence over BIGNUMERIC. Defaults to ["NUMERIC", "STRING"] for ORC and ["NUMERIC"] for the other file formats.
"A String",
],
- "destinationEncryptionConfiguration": { # Custom encryption configuration (e.g., Cloud KMS keys).
+ "destinationEncryptionConfiguration": { # Custom encryption configuration (e.g., Cloud KMS keys)
"kmsKeyName": "A String", # Optional. Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key.
},
"destinationTable": { # [Required] The destination table to load the data into.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- },
- "destinationTableProperties": { # [Beta] [Optional] Properties with which to create the destination table if it is new.
- "description": "A String", # [Optional] The description for the destination table. This will only be used if the destination table is newly created. If the table already exists and a value different than the current description is provided, the job will fail.
- "expirationTime": "A String", # [Internal] This field is for Google internal use only.
- "friendlyName": "A String", # [Optional] The friendly name for the destination table. This will only be used if the destination table is newly created. If the table already exists and a value different than the current friendly name is provided, the job will fail.
- "labels": { # [Optional] The labels associated with this table. You can use these to organize and group your tables. This will only be used if the destination table is newly created. If the table already exists and labels are different than the current labels are provided, the job will fail.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ "destinationTableProperties": { # Properties for the destination table. # Optional. [Experimental] Properties with which to create the destination table if it is new.
+ "description": "A String", # Optional. The description for the destination table. This will only be used if the destination table is newly created. If the table already exists and a value different than the current description is provided, the job will fail.
+ "expirationTime": "A String", # Internal use only.
+ "friendlyName": "A String", # Optional. Friendly name for the destination table. If the table already exists, it should be same as the existing friendly name.
+ "labels": { # Optional. The labels associated with this table. You can use these to organize and group your tables. This will only be used if the destination table is newly created. If the table already exists and labels are different than the current labels are provided, the job will fail.
"a_key": "A String",
},
},
- "encoding": "A String", # [Optional] The character encoding of the data. The supported values are UTF-8 or ISO-8859-1. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the quote and fieldDelimiter properties.
- "fieldDelimiter": "A String", # [Optional] The separator for fields in a CSV file. The separator can be any ISO-8859-1 single-byte character. To use a character in the range 128-255, you must encode the character as UTF8. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. BigQuery also supports the escape sequence "\t" to specify a tab separator. The default value is a comma (',').
- "fileSetSpecType": "A String", # [Optional] Specifies how source URIs are interpreted for constructing the file set to load. By default source URIs are expanded against the underlying storage. Other options include specifying manifest files. Only applicable to object storage systems.
- "hivePartitioningOptions": { # [Optional] Options to configure hive partitioning support.
- "fields": [ # [Output-only] For permanent external tables, this field is populated with the hive partition keys in the order they were inferred. The types of the partition keys can be deduced by checking the table schema (which will include the partition keys). Not every API will populate this field in the output. For example, Tables.Get will populate it, but Tables.List will not contain this field.
+ "encoding": "A String", # Optional. The character encoding of the data. The supported values are UTF-8, ISO-8859-1, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the `quote` and `fieldDelimiter` properties. If you don't specify an encoding, or if you specify a UTF-8 encoding when the CSV file is not UTF-8 encoded, BigQuery attempts to convert the data to UTF-8. Generally, your data loads successfully, but it may not match byte-for-byte what you expect. To avoid this, specify the correct encoding by using the `--encoding` flag. If BigQuery can't convert a character other than the ASCII `0` character, BigQuery converts the character to the standard Unicode replacement character: �.
+ "fieldDelimiter": "A String", # Optional. The separator character for fields in a CSV file. The separator is interpreted as a single byte. For files encoded in ISO-8859-1, any single character can be used as a separator. For files encoded in UTF-8, characters represented in decimal range 1-127 (U+0001-U+007F) can be used without any modification. UTF-8 characters encoded with multiple bytes (i.e. U+0080 and above) will have only the first byte used for separating fields. The remaining bytes will be treated as a part of the field. BigQuery also supports the escape sequence "\t" (U+0009) to specify a tab separator. The default value is comma (",", U+002C).
+ "fileSetSpecType": "A String", # Optional. Specifies how source URIs are interpreted for constructing the file set to load. By default, source URIs are expanded against the underlying storage. You can also specify manifest files to control how the file set is constructed. This option is only applicable to object storage systems.
+ "hivePartitioningOptions": { # Options for configuring hive partitioning detect. # Optional. When set, configures hive partitioning support. Not all storage formats support hive partitioning -- requesting hive partitioning on an unsupported format will lead to an error, as will providing an invalid specification.
+ "fields": [ # Output only. For permanent external tables, this field is populated with the hive partition keys in the order they were inferred. The types of the partition keys can be deduced by checking the table schema (which will include the partition keys). Not every API will populate this field in the output. For example, Tables.Get will populate it, but Tables.List will not contain this field.
"A String",
],
- "mode": "A String", # [Optional] When set, what mode of hive partitioning to use when reading data. The following modes are supported. (1) AUTO: automatically infer partition key name(s) and type(s). (2) STRINGS: automatically infer partition key name(s). All types are interpreted as strings. (3) CUSTOM: partition key schema is encoded in the source URI prefix. Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported types include: AVRO, CSV, JSON, ORC and Parquet.
- "requirePartitionFilter": True or False, # [Optional] If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. Note that this field should only be true when creating a permanent external table or querying a temporary external table. Hive-partitioned loads with requirePartitionFilter explicitly set to true will fail.
- "sourceUriPrefix": "A String", # [Optional] When hive partition detection is requested, a common prefix for all source uris should be supplied. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout. gs://bucket/path_to_table/dt=2019-01-01/country=BR/id=7/file.avro gs://bucket/path_to_table/dt=2018-12-31/country=CA/id=3/file.avro When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/ (trailing slash does not matter).
- },
- "ignoreUnknownValues": True or False, # [Optional] Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names
- "jsonExtension": "A String", # [Optional] If sourceFormat is set to newline-delimited JSON, indicates whether it should be processed as a JSON variant such as GeoJSON. For a sourceFormat other than JSON, omit this field. If the sourceFormat is newline-delimited JSON: - for newline-delimited GeoJSON: set to GEOJSON.
- "maxBadRecords": 42, # [Optional] The maximum number of bad records that BigQuery can ignore when running the job. If the number of bad records exceeds this value, an invalid error is returned in the job result. This is only valid for CSV and JSON. The default value is 0, which requires that all records are valid.
- "nullMarker": "A String", # [Optional] Specifies a string that represents a null value in a CSV file. For example, if you specify "\N", BigQuery interprets "\N" as a null value when loading a CSV file. The default value is the empty string. If you set this property to a custom value, BigQuery throws an error if an empty string is present for all data types except for STRING and BYTE. For STRING and BYTE columns, BigQuery interprets the empty string as an empty value.
- "parquetOptions": { # [Optional] Options to configure parquet support.
- "enableListInference": True or False, # [Optional] Indicates whether to use schema inference specifically for Parquet LIST logical type.
- "enumAsString": True or False, # [Optional] Indicates whether to infer Parquet ENUM logical type as STRING instead of BYTES by default.
- },
- "preserveAsciiControlCharacters": True or False, # [Optional] Preserves the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\x00' to '\x1F') when loading from CSV. Only applicable to CSV, ignored for other formats.
+ "mode": "A String", # Optional. When set, what mode of hive partitioning to use when reading data. The following modes are supported: * AUTO: automatically infer partition key name(s) and type(s). * STRINGS: automatically infer partition key name(s). All types are strings. * CUSTOM: partition key schema is encoded in the source URI prefix. Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported formats are: JSON, CSV, ORC, Avro and Parquet.
+ "requirePartitionFilter": false, # Optional. If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. Note that this field should only be true when creating a permanent external table or querying a temporary external table. Hive-partitioned loads with require_partition_filter explicitly set to true will fail.
+ "sourceUriPrefix": "A String", # Optional. When hive partition detection is requested, a common prefix for all source uris must be required. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout: gs://bucket/path_to_table/dt=2019-06-01/country=USA/id=7/file.avro gs://bucket/path_to_table/dt=2019-05-31/country=CA/id=3/file.avro When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/. CUSTOM detection requires encoding the partitioning schema immediately after the common prefix. For CUSTOM, any of * gs://bucket/path_to_table/{dt:DATE}/{country:STRING}/{id:INTEGER} * gs://bucket/path_to_table/{dt:STRING}/{country:STRING}/{id:INTEGER} * gs://bucket/path_to_table/{dt:DATE}/{country:STRING}/{id:STRING} would all be valid source URI prefixes.
+ },
+ "ignoreUnknownValues": True or False, # Optional. Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names in the table schema Avro, Parquet, ORC: Fields in the file schema that don't exist in the table schema.
+ "jsonExtension": "A String", # Optional. Load option to be used together with source_format newline-delimited JSON to indicate that a variant of JSON is being loaded. To load newline-delimited GeoJSON, specify GEOJSON (and source_format must be set to NEWLINE_DELIMITED_JSON).
+ "maxBadRecords": 42, # Optional. The maximum number of bad records that BigQuery can ignore when running the job. If the number of bad records exceeds this value, an invalid error is returned in the job result. The default value is 0, which requires that all records are valid. This is only supported for CSV and NEWLINE_DELIMITED_JSON file formats.
+ "nullMarker": "A String", # Optional. Specifies a string that represents a null value in a CSV file. For example, if you specify "\N", BigQuery interprets "\N" as a null value when loading a CSV file. The default value is the empty string. If you set this property to a custom value, BigQuery throws an error if an empty string is present for all data types except for STRING and BYTE. For STRING and BYTE columns, BigQuery interprets the empty string as an empty value.
+ "parquetOptions": { # Parquet Options for load and make external tables. # Optional. Additional properties to set if sourceFormat is set to PARQUET.
+ "enableListInference": True or False, # Optional. Indicates whether to use schema inference specifically for Parquet LIST logical type.
+ "enumAsString": True or False, # Optional. Indicates whether to infer Parquet ENUM logical type as STRING instead of BYTES by default.
+ },
+ "preserveAsciiControlCharacters": True or False, # Optional. When sourceFormat is set to "CSV", this indicates whether the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\x00' to '\x1F') are preserved.
"projectionFields": [ # If sourceFormat is set to "DATASTORE_BACKUP", indicates which entity properties to load into BigQuery from a Cloud Datastore backup. Property names are case sensitive and must be top-level properties. If no properties are specified, BigQuery loads all properties. If any named property isn't found in the Cloud Datastore backup, an invalid error is returned in the job result.
"A String",
],
- "quote": """, # [Optional] The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ('"'). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true.
- "rangePartitioning": { # [TrustedTester] Range partitioning specification for this table. Only one of timePartitioning and rangePartitioning should be specified.
- "field": "A String", # [TrustedTester] [Required] The table is partitioned by this field. The field must be a top-level NULLABLE/REQUIRED field. The only supported type is INTEGER/INT64.
- "range": { # [TrustedTester] [Required] Defines the ranges for range partitioning.
- "end": "A String", # [TrustedTester] [Required] The end of range partitioning, exclusive.
- "interval": "A String", # [TrustedTester] [Required] The width of each interval.
- "start": "A String", # [TrustedTester] [Required] The start of range partitioning, inclusive.
+ "quote": """, # Optional. The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ('"'). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true. To include the specific quote character within a quoted value, precede it with an additional matching quote character. For example, if you want to escape the default character ' " ', use ' "" '. @default "
+ "rangePartitioning": { # Range partitioning specification for the destination table. Only one of timePartitioning and rangePartitioning should be specified.
+ "field": "A String", # Required. [Experimental] The table is partitioned by this field. The field must be a top-level NULLABLE/REQUIRED field. The only supported type is INTEGER/INT64.
+ "range": { # [Experimental] Defines the ranges for range partitioning.
+ "end": "A String", # [Experimental] The end of range partitioning, exclusive.
+ "interval": "A String", # [Experimental] The width of each interval.
+ "start": "A String", # [Experimental] The start of range partitioning, inclusive.
},
},
- "referenceFileSchemaUri": "A String", # User provided referencing file with the expected reader schema, Available for the format: AVRO, PARQUET, ORC.
- "schema": { # [Optional] The schema for the destination table. The schema can be omitted if the destination table already exists, or if you're loading data from Google Cloud Datastore.
+ "referenceFileSchemaUri": "A String", # Optional. The user can provide a reference file with the reader schema. This file is only loaded if it is part of source URIs, but is not loaded otherwise. It is enabled for the following formats: AVRO, PARQUET, ORC.
+ "schema": { # Schema of a table # Optional. The schema for the destination table. The schema can be omitted if the destination table already exists, or if you're loading data from Google Cloud Datastore.
"fields": [ # Describes the fields in a table.
- {
- "categories": { # [Optional] The categories attached to this field, used for field-level access control.
- "names": [ # A list of category resource names. For example, "projects/1/taxonomies/2/categories/3". At most 5 categories are allowed.
+ { # A field in TableSchema
+ "categories": { # Deprecated.
+ "names": [ # Deprecated.
"A String",
],
},
- "collation": "A String", # Optional. Collation specification of the field. It only can be set on string type field.
- "defaultValueExpression": "A String", # Optional. A SQL expression to specify the default value for this field. It can only be set for top level fields (columns). You can use struct or array expression to specify default value for the entire struct or array. The valid SQL expressions are: - Literals for all data types, including STRUCT and ARRAY. - Following functions: - CURRENT_TIMESTAMP - CURRENT_TIME - CURRENT_DATE - CURRENT_DATETIME - GENERATE_UUID - RAND - SESSION_USER - ST_GEOGPOINT - Struct or array composed with the above allowed functions, for example, [CURRENT_DATE(), DATE '2020-01-01']
- "description": "A String", # [Optional] The field description. The maximum length is 1,024 characters.
- "fields": [ # [Optional] Describes the nested schema fields if the type property is set to RECORD.
+ "collation": "A String", # Optional. Field collation can be set only when the type of field is STRING. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.
+ "defaultValueExpression": "A String", # Optional. A SQL expression to specify the [default value] (https://cloud.google.com/bigquery/docs/default-values) for this field.
+ "description": "A String", # Optional. The field description. The maximum length is 1,024 characters.
+ "fields": [ # Optional. Describes the nested schema fields if the type property is set to RECORD.
# Object with schema name: TableFieldSchema
],
- "maxLength": "A String", # [Optional] Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
- "mode": "A String", # [Optional] The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
- "name": "A String", # [Required] The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
- "policyTags": {
- "names": [ # A list of category resource names. For example, "projects/1/location/eu/taxonomies/2/policyTags/3". At most 1 policy tag is allowed.
+ "maxLength": "A String", # Optional. Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
+ "mode": "A String", # Optional. The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
+ "name": "A String", # Required. The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
+ "policyTags": { # Optional. The policy tags attached to this field, used for field-level access control. If not set, defaults to empty policy_tags.
+ "names": [ # A list of policy tag resource names. For example, "projects/1/locations/eu/taxonomies/2/policyTags/3". At most 1 policy tag is currently allowed.
"A String",
],
},
- "precision": "A String", # [Optional] Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: - Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] - Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: - If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. - If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): - If type = "NUMERIC": 1 ≤ precision ≤ 29. - If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
- "rangeElementType": { # Optional. The subtype of the RANGE, if the type of this field is RANGE. If the type is RANGE, this field is required. Possible values for the field element type of a RANGE include: - DATE - DATETIME - TIMESTAMP
- "type": "A String", # The field element type of a RANGE
+ "precision": "A String", # Optional. Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: * Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] * Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: * If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. * If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): * If type = "NUMERIC": 1 ≤ precision ≤ 29. * If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
+ "rangeElementType": { # Represents the type of a field element.
+ "type": "A String", # Required. The type of a field element. See TableFieldSchema.type.
},
- "roundingMode": "A String", # Optional. Rounding Mode specification of the field. It only can be set on NUMERIC or BIGNUMERIC type fields.
- "scale": "A String", # [Optional] See documentation for precision.
- "type": "A String", # [Required] The field data type. Possible values include STRING, BYTES, INTEGER, INT64 (same as INTEGER), FLOAT, FLOAT64 (same as FLOAT), NUMERIC, BIGNUMERIC, BOOLEAN, BOOL (same as BOOLEAN), TIMESTAMP, DATE, TIME, DATETIME, INTERVAL, RECORD (where RECORD indicates that the field contains a nested schema) or STRUCT (same as RECORD).
+ "roundingMode": "A String", # Optional. Specifies the rounding mode to be used when storing values of NUMERIC and BIGNUMERIC type.
+ "scale": "A String", # Optional. See documentation for precision.
+ "type": "A String", # Required. The field data type. Possible values include: * STRING * BYTES * INTEGER (or INT64) * FLOAT (or FLOAT64) * BOOLEAN (or BOOL) * TIMESTAMP * DATE * TIME * DATETIME * GEOGRAPHY * NUMERIC * BIGNUMERIC * JSON * RECORD (or STRUCT) Use of RECORD/STRUCT indicates that the field contains a nested schema.
},
],
},
"schemaInline": "A String", # [Deprecated] The inline schema. For CSV schemas, specify as "Field1:Type1[,Field2:Type2]*". For example, "foo:STRING, bar:INTEGER, baz:FLOAT".
"schemaInlineFormat": "A String", # [Deprecated] The format of the schemaInline property.
- "schemaUpdateOptions": [ # Allows the schema of the destination table to be updated as a side effect of the load job if a schema is autodetected or supplied in the job configuration. Schema update options are supported in two cases: when writeDisposition is WRITE_APPEND; when writeDisposition is WRITE_TRUNCATE and the destination table is a partition of a table, specified by partition decorators. For normal tables, WRITE_TRUNCATE will always overwrite the schema. One or more of the following values are specified: ALLOW_FIELD_ADDITION: allow adding a nullable field to the schema. ALLOW_FIELD_RELAXATION: allow relaxing a required field in the original schema to nullable.
+ "schemaUpdateOptions": [ # Allows the schema of the destination table to be updated as a side effect of the load job if a schema is autodetected or supplied in the job configuration. Schema update options are supported in two cases: when writeDisposition is WRITE_APPEND; when writeDisposition is WRITE_TRUNCATE and the destination table is a partition of a table, specified by partition decorators. For normal tables, WRITE_TRUNCATE will always overwrite the schema. One or more of the following values are specified: * ALLOW_FIELD_ADDITION: allow adding a nullable field to the schema. * ALLOW_FIELD_RELAXATION: allow relaxing a required field in the original schema to nullable.
"A String",
],
- "skipLeadingRows": 42, # [Optional] The number of rows at the top of a CSV file that BigQuery will skip when loading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped.
- "sourceFormat": "A String", # [Optional] The format of the data files. For CSV files, specify "CSV". For datastore backups, specify "DATASTORE_BACKUP". For newline-delimited JSON, specify "NEWLINE_DELIMITED_JSON". For Avro, specify "AVRO". For parquet, specify "PARQUET". For orc, specify "ORC". The default value is CSV.
+ "skipLeadingRows": 42, # Optional. The number of rows at the top of a CSV file that BigQuery will skip when loading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
+ "sourceFormat": "A String", # Optional. The format of the data files. For CSV files, specify "CSV". For datastore backups, specify "DATASTORE_BACKUP". For newline-delimited JSON, specify "NEWLINE_DELIMITED_JSON". For Avro, specify "AVRO". For parquet, specify "PARQUET". For orc, specify "ORC". The default value is CSV.
"sourceUris": [ # [Required] The fully-qualified URIs that point to your data in Google Cloud. For Google Cloud Storage URIs: Each URI can contain one '*' wildcard character and it must come after the 'bucket' name. Size limits related to load jobs apply to external data sources. For Google Cloud Bigtable URIs: Exactly one URI can be specified and it has be a fully specified and valid HTTPS URL for a Google Cloud Bigtable table. For Google Cloud Datastore backups: Exactly one URI can be specified. Also, the '*' wildcard character is not allowed.
"A String",
],
"timePartitioning": { # Time-based partitioning specification for the destination table. Only one of timePartitioning and rangePartitioning should be specified.
- "expirationMs": "A String", # [Optional] Number of milliseconds for which to keep the storage for partitions in the table. The storage in a partition will have an expiration time of its partition time plus this value.
- "field": "A String", # [Beta] [Optional] If not set, the table is partitioned by pseudo column, referenced via either '_PARTITIONTIME' as TIMESTAMP type, or '_PARTITIONDATE' as DATE type. If field is specified, the table is instead partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED.
- "requirePartitionFilter": True or False,
- "type": "A String", # [Required] The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively. When the type is not specified, the default behavior is DAY.
- },
- "useAvroLogicalTypes": True or False, # [Optional] If sourceFormat is set to "AVRO", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER).
- "writeDisposition": "A String", # [Optional] Specifies the action that occurs if the destination table already exists. The following values are supported: WRITE_TRUNCATE: If the table already exists, BigQuery overwrites the table data. WRITE_APPEND: If the table already exists, BigQuery appends the data to the table. WRITE_EMPTY: If the table already exists and contains data, a 'duplicate' error is returned in the job result. The default value is WRITE_APPEND. Each action is atomic and only occurs if BigQuery is able to complete the job successfully. Creation, truncation and append actions occur as one atomic update upon job completion.
- },
- "query": { # [Pick one] Configures a query job.
- "allowLargeResults": false, # [Optional] If true and query uses legacy SQL dialect, allows the query to produce arbitrarily large result tables at a slight cost in performance. Requires destinationTable to be set. For standard SQL queries, this flag is ignored and large results are always allowed. However, you must still set destinationTable when result size exceeds the allowed maximum response size.
- "clustering": { # [Beta] Clustering specification for the destination table. Must be specified with time-based partitioning, data in the table will be first partitioned and subsequently clustered.
- "fields": [ # [Repeated] One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. When you cluster a table using multiple columns, the order of columns you specify is important. The order of the specified columns determines the sort order of the data.
+ "expirationMs": "A String", # Optional. Number of milliseconds for which to keep the storage for a partition. A wrapper is used here because 0 is an invalid value.
+ "field": "A String", # Optional. If not set, the table is partitioned by pseudo column '_PARTITIONTIME'; if set, the table is partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED. A wrapper is used here because an empty string is an invalid value.
+ "requirePartitionFilter": false, # If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. This field is deprecated; please set the field with the same name on the table itself instead. This field needs a wrapper because we want to output the default value, false, if the user explicitly set it.
+ "type": "A String", # Required. The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively.
+ },
+ "useAvroLogicalTypes": True or False, # Optional. If sourceFormat is set to "AVRO", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER).
+ "writeDisposition": "A String", # Optional. Specifies the action that occurs if the destination table already exists. The following values are supported: * WRITE_TRUNCATE: If the table already exists, BigQuery overwrites the data, removes the constraints and uses the schema from the load job. * WRITE_APPEND: If the table already exists, BigQuery appends the data to the table. * WRITE_EMPTY: If the table already exists and contains data, a 'duplicate' error is returned in the job result. The default value is WRITE_APPEND. Each action is atomic and only occurs if BigQuery is able to complete the job successfully. Creation, truncation and append actions occur as one atomic update upon job completion.
+ },
+ "query": { # JobConfigurationQuery configures a BigQuery query job. # [Pick one] Configures a query job.
+ "allowLargeResults": false, # Optional. If true and query uses legacy SQL dialect, allows the query to produce arbitrarily large result tables at a slight cost in performance. Requires destinationTable to be set. For GoogleSQL queries, this flag is ignored and large results are always allowed. However, you must still set destinationTable when result size exceeds the allowed maximum response size.
+ "clustering": { # Configures table clustering. # Clustering specification for the destination table.
+ "fields": [ # One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. The ordering of the clustering fields should be prioritized from most to least important for filtering purposes. Additional information on limitations can be found here: https://cloud.google.com/bigquery/docs/creating-clustered-tables#limitations
"A String",
],
},
- "connectionProperties": [ # Connection properties.
- {
- "key": "A String", # [Required] Name of the connection property to set.
- "value": "A String", # [Required] Value of the connection property.
+ "connectionProperties": [ # Connection properties which can modify the query behavior.
+ { # A connection-level property to customize query behavior. Under JDBC, these correspond directly to connection properties passed to the DriverManager. Under ODBC, these correspond to properties in the connection string. Currently supported connection properties: * **dataset_project_id**: represents the default project for datasets that are used in the query. Setting the system variable `@@dataset_project_id` achieves the same behavior. For more information about system variables, see: https://cloud.google.com/bigquery/docs/reference/system-variables * **time_zone**: represents the default timezone used to run the query. * **session_id**: associates the query with a given session. * **query_label**: associates the query with a given job label. If set, all subsequent queries in a script or session will have this label. For the format in which a you can specify a query label, see labels in the JobConfiguration resource type: https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#jobconfiguration Additional properties are allowed, but ignored. Specifying multiple connection properties with the same key returns an error.
+ "key": "A String", # The key of the property to set.
+ "value": "A String", # The value of the property to set.
},
],
"continuous": True or False, # [Optional] Specifies whether the query should be executed as a continuous query. The default value is false.
- "createDisposition": "A String", # [Optional] Specifies whether the job is allowed to create new tables. The following values are supported: CREATE_IF_NEEDED: If the table does not exist, BigQuery creates the table. CREATE_NEVER: The table must already exist. If it does not, a 'notFound' error is returned in the job result. The default value is CREATE_IF_NEEDED. Creation, truncation and append actions occur as one atomic update upon job completion.
- "createSession": True or False, # If true, creates a new session, where session id will be a server generated random id. If false, runs query with an existing session_id passed in ConnectionProperty, otherwise runs query in non-session mode.
- "defaultDataset": { # [Optional] Specifies the default dataset to use for unqualified table names in the query. Note that this does not alter behavior of unqualified dataset names.
- "datasetId": "A String", # [Required] A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- "projectId": "A String", # [Optional] The ID of the project containing this dataset.
+ "createDisposition": "A String", # Optional. Specifies whether the job is allowed to create new tables. The following values are supported: * CREATE_IF_NEEDED: If the table does not exist, BigQuery creates the table. * CREATE_NEVER: The table must already exist. If it does not, a 'notFound' error is returned in the job result. The default value is CREATE_IF_NEEDED. Creation, truncation and append actions occur as one atomic update upon job completion.
+ "createSession": True or False, # If this property is true, the job creates a new session using a randomly generated session_id. To continue using a created session with subsequent queries, pass the existing session identifier as a `ConnectionProperty` value. The session identifier is returned as part of the `SessionInfo` message within the query statistics. The new session's location will be set to `Job.JobReference.location` if it is present, otherwise it's set to the default location based on existing routing logic.
+ "defaultDataset": { # Optional. Specifies the default dataset to use for unqualified table names in the query. This setting does not alter behavior of unqualified dataset names. Setting the system variable `@@dataset_id` achieves the same behavior. See https://cloud.google.com/bigquery/docs/reference/system-variables for more information on system variables.
+ "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "projectId": "A String", # Optional. The ID of the project containing this dataset.
},
- "destinationEncryptionConfiguration": { # Custom encryption configuration (e.g., Cloud KMS keys).
+ "destinationEncryptionConfiguration": { # Custom encryption configuration (e.g., Cloud KMS keys)
"kmsKeyName": "A String", # Optional. Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key.
},
- "destinationTable": { # [Optional] Describes the table where the query results should be stored. If not present, a new table will be created to store the results. This property must be set for large results that exceed the maximum response size.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "destinationTable": { # Optional. Describes the table where the query results should be stored. This property must be set for large results that exceed the maximum response size. For queries that produce anonymous (cached) results, this field will be populated by BigQuery.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
- "flattenResults": true, # [Optional] If true and query uses legacy SQL dialect, flattens all nested and repeated fields in the query results. allowLargeResults must be true if this is set to false. For standard SQL queries, this flag is ignored and results are never flattened.
- "maximumBillingTier": 1, # [Optional] Limits the billing tier for this job. Queries that have resource usage beyond this tier will fail (without incurring a charge). If unspecified, this will be set to your project default.
- "maximumBytesBilled": "A String", # [Optional] Limits the bytes billed for this job. Queries that will have bytes billed beyond this limit will fail (without incurring a charge). If unspecified, this will be set to your project default.
- "parameterMode": "A String", # Standard SQL only. Set to POSITIONAL to use positional (?) query parameters or to NAMED to use named (@myparam) query parameters in this query.
+ "flattenResults": true, # Optional. If true and query uses legacy SQL dialect, flattens all nested and repeated fields in the query results. allowLargeResults must be true if this is set to false. For GoogleSQL queries, this flag is ignored and results are never flattened.
+ "maximumBillingTier": 1, # Optional. [Deprecated] Maximum billing tier allowed for this query. The billing tier controls the amount of compute resources allotted to the query, and multiplies the on-demand cost of the query accordingly. A query that runs within its allotted resources will succeed and indicate its billing tier in statistics.query.billingTier, but if the query exceeds its allotted resources, it will fail with billingTierLimitExceeded. WARNING: The billed byte amount can be multiplied by an amount up to this number! Most users should not need to alter this setting, and we recommend that you avoid introducing new uses of it.
+ "maximumBytesBilled": "A String", # Limits the bytes billed for this job. Queries that will have bytes billed beyond this limit will fail (without incurring a charge). If unspecified, this will be set to your project default.
+ "parameterMode": "A String", # GoogleSQL only. Set to POSITIONAL to use positional (?) query parameters or to NAMED to use named (@myparam) query parameters in this query.
"preserveNulls": True or False, # [Deprecated] This property is deprecated.
- "priority": "A String", # [Optional] Specifies a priority for the query. Possible values include INTERACTIVE and BATCH. The default value is INTERACTIVE.
- "query": "A String", # [Required] SQL query text to execute. The useLegacySql field can be used to indicate whether the query uses legacy SQL or standard SQL.
- "queryParameters": [ # Query parameters for standard SQL queries.
- {
- "name": "A String", # [Optional] If unset, this is a positional parameter. Otherwise, should be unique within a query.
- "parameterType": { # [Required] The type of this parameter.
- "arrayType": # Object with schema name: QueryParameterType # [Optional] The type of the array's elements, if this is an array.
- "rangeElementType": # Object with schema name: QueryParameterType # [Optional] The element type of the range, if this is a range.
- "structTypes": [ # [Optional] The types of the fields of this struct, in order, if this is a struct.
- {
- "description": "A String", # [Optional] Human-oriented description of the field.
- "name": "A String", # [Optional] The name of this field.
- "type": # Object with schema name: QueryParameterType # [Required] The type of this field.
+ "priority": "A String", # Optional. Specifies a priority for the query. Possible values include INTERACTIVE and BATCH. The default value is INTERACTIVE.
+ "query": "A String", # [Required] SQL query text to execute. The useLegacySql field can be used to indicate whether the query uses legacy SQL or GoogleSQL.
+ "queryParameters": [ # Query parameters for GoogleSQL queries.
+ { # A parameter given to a query.
+ "name": "A String", # Optional. If unset, this is a positional parameter. Otherwise, should be unique within a query.
+ "parameterType": { # The type of a query parameter. # Required. The type of this parameter.
+ "arrayType": # Object with schema name: QueryParameterType # Optional. The type of the array's elements, if this is an array.
+ "rangeElementType": # Object with schema name: QueryParameterType # Optional. The element type of the range, if this is a range.
+ "structTypes": [ # Optional. The types of the fields of this struct, in order, if this is a struct.
+ { # The type of a struct parameter.
+ "description": "A String", # Optional. Human-oriented description of the field.
+ "name": "A String", # Optional. The name of this field.
+ "type": # Object with schema name: QueryParameterType # Required. The type of this field.
},
],
- "type": "A String", # [Required] The top level type of this field.
+ "type": "A String", # Required. The top level type of this field.
},
- "parameterValue": { # [Required] The value of this parameter.
- "arrayValues": [ # [Optional] The array values, if this is an array type.
+ "parameterValue": { # The value of a query parameter. # Required. The value of this parameter.
+ "arrayValues": [ # Optional. The array values, if this is an array type.
# Object with schema name: QueryParameterValue
],
- "rangeValue": { # [Optional] The range value, if this is a range type.
- "end": # Object with schema name: QueryParameterValue
- "start": # Object with schema name: QueryParameterValue
+ "rangeValue": { # Represents the value of a range. # Optional. The range value, if this is a range type.
+ "end": # Object with schema name: QueryParameterValue # Optional. The end value of the range. A missing value represents an unbounded end.
+ "start": # Object with schema name: QueryParameterValue # Optional. The start value of the range. A missing value represents an unbounded start.
},
- "structValues": { # [Optional] The struct field values, in order of the struct type's declaration.
+ "structValues": { # The struct field values.
"a_key": # Object with schema name: QueryParameterValue
},
- "value": "A String", # [Optional] The value of this value, if a simple scalar type.
+ "value": "A String", # Optional. The value of this value, if a simple scalar type.
},
},
],
- "rangePartitioning": { # [TrustedTester] Range partitioning specification for this table. Only one of timePartitioning and rangePartitioning should be specified.
- "field": "A String", # [TrustedTester] [Required] The table is partitioned by this field. The field must be a top-level NULLABLE/REQUIRED field. The only supported type is INTEGER/INT64.
- "range": { # [TrustedTester] [Required] Defines the ranges for range partitioning.
- "end": "A String", # [TrustedTester] [Required] The end of range partitioning, exclusive.
- "interval": "A String", # [TrustedTester] [Required] The width of each interval.
- "start": "A String", # [TrustedTester] [Required] The start of range partitioning, inclusive.
+ "rangePartitioning": { # Range partitioning specification for the destination table. Only one of timePartitioning and rangePartitioning should be specified.
+ "field": "A String", # Required. [Experimental] The table is partitioned by this field. The field must be a top-level NULLABLE/REQUIRED field. The only supported type is INTEGER/INT64.
+ "range": { # [Experimental] Defines the ranges for range partitioning.
+ "end": "A String", # [Experimental] The end of range partitioning, exclusive.
+ "interval": "A String", # [Experimental] The width of each interval.
+ "start": "A String", # [Experimental] The start of range partitioning, inclusive.
},
},
- "schemaUpdateOptions": [ # Allows the schema of the destination table to be updated as a side effect of the query job. Schema update options are supported in two cases: when writeDisposition is WRITE_APPEND; when writeDisposition is WRITE_TRUNCATE and the destination table is a partition of a table, specified by partition decorators. For normal tables, WRITE_TRUNCATE will always overwrite the schema. One or more of the following values are specified: ALLOW_FIELD_ADDITION: allow adding a nullable field to the schema. ALLOW_FIELD_RELAXATION: allow relaxing a required field in the original schema to nullable.
+ "schemaUpdateOptions": [ # Allows the schema of the destination table to be updated as a side effect of the query job. Schema update options are supported in two cases: when writeDisposition is WRITE_APPEND; when writeDisposition is WRITE_TRUNCATE and the destination table is a partition of a table, specified by partition decorators. For normal tables, WRITE_TRUNCATE will always overwrite the schema. One or more of the following values are specified: * ALLOW_FIELD_ADDITION: allow adding a nullable field to the schema. * ALLOW_FIELD_RELAXATION: allow relaxing a required field in the original schema to nullable.
"A String",
],
- "tableDefinitions": { # [Optional] If querying an external data source outside of BigQuery, describes the data format, location and other properties of the data source. By defining these properties, the data source can then be queried as if it were a standard BigQuery table.
+ "scriptOptions": { # Options related to script execution. # Options controlling the execution of scripts.
+ "keyResultStatement": "A String", # Determines which statement in the script represents the "key result", used to populate the schema and query results of the script job. Default is LAST.
+ "statementByteBudget": "A String", # Limit on the number of bytes billed per statement. Exceeding this budget results in an error.
+ "statementTimeoutMs": "A String", # Timeout period for each statement in a script.
+ },
+ "systemVariables": { # System variables given to a query. # Output only. System variables for GoogleSQL queries. A system variable is output if the variable is settable and its value differs from the system default. "@@" prefix is not included in the name of the System variables.
+ "types": { # Output only. Data type for each system variable.
+ "a_key": { # The data type of a variable such as a function argument. Examples include: * INT64: `{"typeKind": "INT64"}` * ARRAY: { "typeKind": "ARRAY", "arrayElementType": {"typeKind": "STRING"} } * STRUCT>: { "typeKind": "STRUCT", "structType": { "fields": [ { "name": "x", "type": {"typeKind": "STRING"} }, { "name": "y", "type": { "typeKind": "ARRAY", "arrayElementType": {"typeKind": "DATE"} } } ] } }
+ "arrayElementType": # Object with schema name: StandardSqlDataType # The type of the array's elements, if type_kind = "ARRAY".
+ "rangeElementType": # Object with schema name: StandardSqlDataType # The type of the range's elements, if type_kind = "RANGE".
+ "structType": { # The representation of a SQL STRUCT type. # The fields of this struct, in order, if type_kind = "STRUCT".
+ "fields": [ # Fields within the struct.
+ { # A field or a column.
+ "name": "A String", # Optional. The name of this field. Can be absent for struct fields.
+ "type": # Object with schema name: StandardSqlDataType # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
+ },
+ ],
+ },
+ "typeKind": "A String", # Required. The top level type of this field. Can be any GoogleSQL data type (e.g., "INT64", "DATE", "ARRAY").
+ },
+ },
+ "values": { # Output only. Value for each system variable.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "tableDefinitions": { # Optional. You can specify external table definitions, which operate as ephemeral tables that can be queried. These definitions are configured using a JSON map, where the string key represents the table identifier, and the value is the corresponding external data configuration object.
"a_key": {
"autodetect": True or False, # Try to detect schema and format options automatically. Any option specified explicitly will be honored.
- "avroOptions": { # Additional properties to set if sourceFormat is set to Avro.
- "useAvroLogicalTypes": True or False, # [Optional] If sourceFormat is set to "AVRO", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER).
- },
- "bigtableOptions": { # [Optional] Additional options if sourceFormat is set to BIGTABLE.
- "columnFamilies": [ # [Optional] List of column families to expose in the table schema along with their types. This list restricts the column families that can be referenced in queries and specifies their value types. You can use this list to do type conversions - see the 'type' field for more details. If you leave this list empty, all column families are present in the table schema and their values are read as BYTES. During a query only the column families referenced in that query are read from Bigtable.
- {
- "columns": [ # [Optional] Lists of columns that should be exposed as individual fields as opposed to a list of (column name, value) pairs. All columns whose qualifier matches a qualifier in this list can be accessed as .. Other columns can be accessed as a list through .Column field.
- {
- "encoding": "A String", # [Optional] The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. 'encoding' can also be set at the column family level. However, the setting at this level takes precedence if 'encoding' is set at both levels.
- "fieldName": "A String", # [Optional] If the qualifier is not a valid BigQuery field identifier i.e. does not match [a-zA-Z][a-zA-Z0-9_]*, a valid identifier must be provided as the column field name and is used as field name in queries.
- "onlyReadLatest": True or False, # [Optional] If this is set, only the latest version of value in this column are exposed. 'onlyReadLatest' can also be set at the column family level. However, the setting at this level takes precedence if 'onlyReadLatest' is set at both levels.
- "qualifierEncoded": "A String", # [Required] Qualifier of the column. Columns in the parent column family that has this exact qualifier are exposed as . field. If the qualifier is valid UTF-8 string, it can be specified in the qualifier_string field. Otherwise, a base-64 encoded value must be set to qualifier_encoded. The column field name is the same as the column qualifier. However, if the qualifier is not a valid BigQuery field identifier i.e. does not match [a-zA-Z][a-zA-Z0-9_]*, a valid identifier must be provided as field_name.
- "qualifierString": "A String",
- "type": "A String", # [Optional] The type to convert the value in cells of this column. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive) - BYTES STRING INTEGER FLOAT BOOLEAN Default type is BYTES. 'type' can also be set at the column family level. However, the setting at this level takes precedence if 'type' is set at both levels.
+ "avroOptions": { # Options for external data sources. # Optional. Additional properties to set if sourceFormat is set to AVRO.
+ "useAvroLogicalTypes": True or False, # Optional. If sourceFormat is set to "AVRO", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER).
+ },
+ "bigtableOptions": { # Options specific to Google Cloud Bigtable data sources. # Optional. Additional options if sourceFormat is set to BIGTABLE.
+ "columnFamilies": [ # Optional. List of column families to expose in the table schema along with their types. This list restricts the column families that can be referenced in queries and specifies their value types. You can use this list to do type conversions - see the 'type' field for more details. If you leave this list empty, all column families are present in the table schema and their values are read as BYTES. During a query only the column families referenced in that query are read from Bigtable.
+ { # Information related to a Bigtable column family.
+ "columns": [ # Optional. Lists of columns that should be exposed as individual fields as opposed to a list of (column name, value) pairs. All columns whose qualifier matches a qualifier in this list can be accessed as .. Other columns can be accessed as a list through .Column field.
+ { # Information related to a Bigtable column.
+ "encoding": "A String", # Optional. The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. 'encoding' can also be set at the column family level. However, the setting at this level takes precedence if 'encoding' is set at both levels.
+ "fieldName": "A String", # Optional. If the qualifier is not a valid BigQuery field identifier i.e. does not match a-zA-Z*, a valid identifier must be provided as the column field name and is used as field name in queries.
+ "onlyReadLatest": True or False, # Optional. If this is set, only the latest version of value in this column are exposed. 'onlyReadLatest' can also be set at the column family level. However, the setting at this level takes precedence if 'onlyReadLatest' is set at both levels.
+ "qualifierEncoded": "A String", # [Required] Qualifier of the column. Columns in the parent column family that has this exact qualifier are exposed as . field. If the qualifier is valid UTF-8 string, it can be specified in the qualifier_string field. Otherwise, a base-64 encoded value must be set to qualifier_encoded. The column field name is the same as the column qualifier. However, if the qualifier is not a valid BigQuery field identifier i.e. does not match a-zA-Z*, a valid identifier must be provided as field_name.
+ "qualifierString": "A String", # Qualifier string.
+ "type": "A String", # Optional. The type to convert the value in cells of this column. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive): * BYTES * STRING * INTEGER * FLOAT * BOOLEAN * JSON Default type is BYTES. 'type' can also be set at the column family level. However, the setting at this level takes precedence if 'type' is set at both levels.
},
],
- "encoding": "A String", # [Optional] The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. This can be overridden for a specific column by listing that column in 'columns' and specifying an encoding for it.
+ "encoding": "A String", # Optional. The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. This can be overridden for a specific column by listing that column in 'columns' and specifying an encoding for it.
"familyId": "A String", # Identifier of the column family.
- "onlyReadLatest": True or False, # [Optional] If this is set only the latest version of value are exposed for all columns in this column family. This can be overridden for a specific column by listing that column in 'columns' and specifying a different setting for that column.
- "type": "A String", # [Optional] The type to convert the value in cells of this column family. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive) - BYTES STRING INTEGER FLOAT BOOLEAN Default type is BYTES. This can be overridden for a specific column by listing that column in 'columns' and specifying a type for it.
- },
- ],
- "ignoreUnspecifiedColumnFamilies": True or False, # [Optional] If field is true, then the column families that are not specified in columnFamilies list are not exposed in the table schema. Otherwise, they are read with BYTES type values. The default value is false.
- "readRowkeyAsString": True or False, # [Optional] If field is true, then the rowkey column families will be read and converted to string. Otherwise they are read with BYTES type values and users need to manually cast them with CAST if necessary. The default value is false.
- },
- "compression": "A String", # [Optional] The compression type of the data source. Possible values include GZIP and NONE. The default value is NONE. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups and Avro formats.
- "connectionId": "A String", # [Optional, Trusted Tester] Connection for external data source.
- "csvOptions": { # Additional properties to set if sourceFormat is set to CSV.
- "allowJaggedRows": True or False, # [Optional] Indicates if BigQuery should accept rows that are missing trailing optional columns. If true, BigQuery treats missing trailing columns as null values. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false.
- "allowQuotedNewlines": True or False, # [Optional] Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false.
- "encoding": "A String", # [Optional] The character encoding of the data. The supported values are UTF-8 or ISO-8859-1. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the quote and fieldDelimiter properties.
- "fieldDelimiter": "A String", # [Optional] The separator for fields in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. BigQuery also supports the escape sequence "\t" to specify a tab separator. The default value is a comma (',').
- "nullMarker": "A String", # [Optional] An custom string that will represent a NULL value in CSV import data.
- "preserveAsciiControlCharacters": True or False, # [Optional] Preserves the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\x00' to '\x1F') when loading from CSV. Only applicable to CSV, ignored for other formats.
- "quote": """, # [Optional] The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ('"'). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true.
- "skipLeadingRows": "A String", # [Optional] The number of rows at the top of a CSV file that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
- },
- "decimalTargetTypes": [ # [Optional] Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown. Example: Suppose the value of this field is ["NUMERIC", "BIGNUMERIC"]. If (precision,scale) is: (38,9) -> NUMERIC; (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits); (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits); (76,38) -> BIGNUMERIC; (77,38) -> BIGNUMERIC (error if value exeeds supported range). This field cannot contain duplicate types. The order of the types in this field is ignored. For example, ["BIGNUMERIC", "NUMERIC"] is the same as ["NUMERIC", "BIGNUMERIC"] and NUMERIC always takes precedence over BIGNUMERIC. Defaults to ["NUMERIC", "STRING"] for ORC and ["NUMERIC"] for the other file formats.
+ "onlyReadLatest": True or False, # Optional. If this is set only the latest version of value are exposed for all columns in this column family. This can be overridden for a specific column by listing that column in 'columns' and specifying a different setting for that column.
+ "type": "A String", # Optional. The type to convert the value in cells of this column family. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive): * BYTES * STRING * INTEGER * FLOAT * BOOLEAN * JSON Default type is BYTES. This can be overridden for a specific column by listing that column in 'columns' and specifying a type for it.
+ },
+ ],
+ "ignoreUnspecifiedColumnFamilies": True or False, # Optional. If field is true, then the column families that are not specified in columnFamilies list are not exposed in the table schema. Otherwise, they are read with BYTES type values. The default value is false.
+ "outputColumnFamiliesAsJson": True or False, # Optional. If field is true, then each column family will be read as a single JSON column. Otherwise they are read as a repeated cell structure containing timestamp/value tuples. The default value is false.
+ "readRowkeyAsString": True or False, # Optional. If field is true, then the rowkey column families will be read and converted to string. Otherwise they are read with BYTES type values and users need to manually cast them with CAST if necessary. The default value is false.
+ },
+ "compression": "A String", # Optional. The compression type of the data source. Possible values include GZIP and NONE. The default value is NONE. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups, Avro, ORC and Parquet formats. An empty string is an invalid value.
+ "connectionId": "A String", # Optional. The connection specifying the credentials to be used to read external storage, such as Azure Blob, Cloud Storage, or S3. The connection_id can have the form "<project\_id>.<location\_id>.<connection\_id>" or "projects/<project\_id>/locations/<location\_id>/connections/<connection\_id>".
+ "csvOptions": { # Information related to a CSV data source. # Optional. Additional properties to set if sourceFormat is set to CSV.
+ "allowJaggedRows": True or False, # Optional. Indicates if BigQuery should accept rows that are missing trailing optional columns. If true, BigQuery treats missing trailing columns as null values. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false.
+ "allowQuotedNewlines": True or False, # Optional. Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false.
+ "encoding": "A String", # Optional. The character encoding of the data. The supported values are UTF-8, ISO-8859-1, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the quote and fieldDelimiter properties.
+ "fieldDelimiter": "A String", # Optional. The separator character for fields in a CSV file. The separator is interpreted as a single byte. For files encoded in ISO-8859-1, any single character can be used as a separator. For files encoded in UTF-8, characters represented in decimal range 1-127 (U+0001-U+007F) can be used without any modification. UTF-8 characters encoded with multiple bytes (i.e. U+0080 and above) will have only the first byte used for separating fields. The remaining bytes will be treated as a part of the field. BigQuery also supports the escape sequence "\t" (U+0009) to specify a tab separator. The default value is comma (",", U+002C).
+ "nullMarker": "A String", # [Optional] A custom string that will represent a NULL value in CSV import data.
+ "preserveAsciiControlCharacters": True or False, # Optional. Indicates if the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\x00' to '\x1F') are preserved.
+ "quote": """, # Optional. The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ("). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true. To include the specific quote character within a quoted value, precede it with an additional matching quote character. For example, if you want to escape the default character ' " ', use ' "" '.
+ "skipLeadingRows": "A String", # Optional. The number of rows at the top of a CSV file that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
+ },
+ "decimalTargetTypes": [ # Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown. Example: Suppose the value of this field is ["NUMERIC", "BIGNUMERIC"]. If (precision,scale) is: * (38,9) -> NUMERIC; * (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits); * (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits); * (76,38) -> BIGNUMERIC; * (77,38) -> BIGNUMERIC (error if value exeeds supported range). This field cannot contain duplicate types. The order of the types in this field is ignored. For example, ["BIGNUMERIC", "NUMERIC"] is the same as ["NUMERIC", "BIGNUMERIC"] and NUMERIC always takes precedence over BIGNUMERIC. Defaults to ["NUMERIC", "STRING"] for ORC and ["NUMERIC"] for the other file formats.
"A String",
],
- "fileSetSpecType": "A String", # [Optional] Specifies how source URIs are interpreted for constructing the file set to load. By default source URIs are expanded against the underlying storage. Other options include specifying manifest files. Only applicable to object storage systems.
- "googleSheetsOptions": { # [Optional] Additional options if sourceFormat is set to GOOGLE_SHEETS.
- "range": "A String", # [Optional] Range of a sheet to query from. Only used when non-empty. Typical format: sheet_name!top_left_cell_id:bottom_right_cell_id For example: sheet1!A1:B20
- "skipLeadingRows": "A String", # [Optional] The number of rows at the top of a sheet that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows that should be skipped. When autodetect is on, behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
+ "fileSetSpecType": "A String", # Optional. Specifies how source URIs are interpreted for constructing the file set to load. By default source URIs are expanded against the underlying storage. Other options include specifying manifest files. Only applicable to object storage systems.
+ "googleSheetsOptions": { # Options specific to Google Sheets data sources. # Optional. Additional options if sourceFormat is set to GOOGLE_SHEETS.
+ "range": "A String", # Optional. Range of a sheet to query from. Only used when non-empty. Typical format: sheet_name!top_left_cell_id:bottom_right_cell_id For example: sheet1!A1:B20
+ "skipLeadingRows": "A String", # Optional. The number of rows at the top of a sheet that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
},
- "hivePartitioningOptions": { # [Optional] Options to configure hive partitioning support.
- "fields": [ # [Output-only] For permanent external tables, this field is populated with the hive partition keys in the order they were inferred. The types of the partition keys can be deduced by checking the table schema (which will include the partition keys). Not every API will populate this field in the output. For example, Tables.Get will populate it, but Tables.List will not contain this field.
+ "hivePartitioningOptions": { # Options for configuring hive partitioning detect. # Optional. When set, configures hive partitioning support. Not all storage formats support hive partitioning -- requesting hive partitioning on an unsupported format will lead to an error, as will providing an invalid specification.
+ "fields": [ # Output only. For permanent external tables, this field is populated with the hive partition keys in the order they were inferred. The types of the partition keys can be deduced by checking the table schema (which will include the partition keys). Not every API will populate this field in the output. For example, Tables.Get will populate it, but Tables.List will not contain this field.
"A String",
],
- "mode": "A String", # [Optional] When set, what mode of hive partitioning to use when reading data. The following modes are supported. (1) AUTO: automatically infer partition key name(s) and type(s). (2) STRINGS: automatically infer partition key name(s). All types are interpreted as strings. (3) CUSTOM: partition key schema is encoded in the source URI prefix. Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported types include: AVRO, CSV, JSON, ORC and Parquet.
- "requirePartitionFilter": True or False, # [Optional] If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. Note that this field should only be true when creating a permanent external table or querying a temporary external table. Hive-partitioned loads with requirePartitionFilter explicitly set to true will fail.
- "sourceUriPrefix": "A String", # [Optional] When hive partition detection is requested, a common prefix for all source uris should be supplied. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout. gs://bucket/path_to_table/dt=2019-01-01/country=BR/id=7/file.avro gs://bucket/path_to_table/dt=2018-12-31/country=CA/id=3/file.avro When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/ (trailing slash does not matter).
+ "mode": "A String", # Optional. When set, what mode of hive partitioning to use when reading data. The following modes are supported: * AUTO: automatically infer partition key name(s) and type(s). * STRINGS: automatically infer partition key name(s). All types are strings. * CUSTOM: partition key schema is encoded in the source URI prefix. Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported formats are: JSON, CSV, ORC, Avro and Parquet.
+ "requirePartitionFilter": false, # Optional. If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. Note that this field should only be true when creating a permanent external table or querying a temporary external table. Hive-partitioned loads with require_partition_filter explicitly set to true will fail.
+ "sourceUriPrefix": "A String", # Optional. When hive partition detection is requested, a common prefix for all source uris must be required. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout: gs://bucket/path_to_table/dt=2019-06-01/country=USA/id=7/file.avro gs://bucket/path_to_table/dt=2019-05-31/country=CA/id=3/file.avro When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/. CUSTOM detection requires encoding the partitioning schema immediately after the common prefix. For CUSTOM, any of * gs://bucket/path_to_table/{dt:DATE}/{country:STRING}/{id:INTEGER} * gs://bucket/path_to_table/{dt:STRING}/{country:STRING}/{id:INTEGER} * gs://bucket/path_to_table/{dt:DATE}/{country:STRING}/{id:STRING} would all be valid source URI prefixes.
},
- "ignoreUnknownValues": True or False, # [Optional] Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names Google Cloud Bigtable: This setting is ignored. Google Cloud Datastore backups: This setting is ignored. Avro: This setting is ignored.
- "jsonOptions": { # Additional properties to set if `sourceFormat` is set to `NEWLINE_DELIMITED_JSON`.
- "encoding": "A String", # [Optional] The character encoding of the data. The supported values are UTF-8, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8.
+ "ignoreUnknownValues": True or False, # Optional. Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names Google Cloud Bigtable: This setting is ignored. Google Cloud Datastore backups: This setting is ignored. Avro: This setting is ignored. ORC: This setting is ignored. Parquet: This setting is ignored.
+ "jsonExtension": "A String", # Optional. Load option to be used together with source_format newline-delimited JSON to indicate that a variant of JSON is being loaded. To load newline-delimited GeoJSON, specify GEOJSON (and source_format must be set to NEWLINE_DELIMITED_JSON).
+ "jsonOptions": { # Json Options for load and make external tables. # Optional. Additional properties to set if sourceFormat is set to JSON.
+ "encoding": "A String", # Optional. The character encoding of the data. The supported values are UTF-8, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8.
},
- "maxBadRecords": 42, # [Optional] The maximum number of bad records that BigQuery can ignore when reading data. If the number of bad records exceeds this value, an invalid error is returned in the job result. This is only valid for CSV, JSON, and Google Sheets. The default value is 0, which requires that all records are valid. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups and Avro formats.
- "metadataCacheMode": "A String", # [Optional] Metadata Cache Mode for the table. Set this to enable caching of metadata from external data source.
- "objectMetadata": "A String", # ObjectMetadata is used to create Object Tables. Object Tables contain a listing of objects (with their metadata) found at the source_uris. If ObjectMetadata is set, source_format should be omitted. Currently SIMPLE is the only supported Object Metadata type.
- "parquetOptions": { # Additional properties to set if sourceFormat is set to Parquet.
- "enableListInference": True or False, # [Optional] Indicates whether to use schema inference specifically for Parquet LIST logical type.
- "enumAsString": True or False, # [Optional] Indicates whether to infer Parquet ENUM logical type as STRING instead of BYTES by default.
+ "maxBadRecords": 42, # Optional. The maximum number of bad records that BigQuery can ignore when reading data. If the number of bad records exceeds this value, an invalid error is returned in the job result. The default value is 0, which requires that all records are valid. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups, Avro, ORC and Parquet formats.
+ "metadataCacheMode": "A String", # Optional. Metadata Cache Mode for the table. Set this to enable caching of metadata from external data source.
+ "objectMetadata": "A String", # Optional. ObjectMetadata is used to create Object Tables. Object Tables contain a listing of objects (with their metadata) found at the source_uris. If ObjectMetadata is set, source_format should be omitted. Currently SIMPLE is the only supported Object Metadata type.
+ "parquetOptions": { # Parquet Options for load and make external tables. # Optional. Additional properties to set if sourceFormat is set to PARQUET.
+ "enableListInference": True or False, # Optional. Indicates whether to use schema inference specifically for Parquet LIST logical type.
+ "enumAsString": True or False, # Optional. Indicates whether to infer Parquet ENUM logical type as STRING instead of BYTES by default.
},
- "referenceFileSchemaUri": "A String", # [Optional] Provide a referencing file with the expected table schema. Enabled for the format: AVRO, PARQUET, ORC.
- "schema": { # [Optional] The schema for the data. Schema is required for CSV and JSON formats. Schema is disallowed for Google Cloud Bigtable, Cloud Datastore backups, and Avro formats.
+ "referenceFileSchemaUri": "A String", # Optional. When creating an external table, the user can provide a reference file with the table schema. This is enabled for the following formats: AVRO, PARQUET, ORC.
+ "schema": { # Schema of a table # Optional. The schema for the data. Schema is required for CSV and JSON formats if autodetect is not on. Schema is disallowed for Google Cloud Bigtable, Cloud Datastore backups, Avro, ORC and Parquet formats.
"fields": [ # Describes the fields in a table.
- {
- "categories": { # [Optional] The categories attached to this field, used for field-level access control.
- "names": [ # A list of category resource names. For example, "projects/1/taxonomies/2/categories/3". At most 5 categories are allowed.
+ { # A field in TableSchema
+ "categories": { # Deprecated.
+ "names": [ # Deprecated.
"A String",
],
},
- "collation": "A String", # Optional. Collation specification of the field. It only can be set on string type field.
- "defaultValueExpression": "A String", # Optional. A SQL expression to specify the default value for this field. It can only be set for top level fields (columns). You can use struct or array expression to specify default value for the entire struct or array. The valid SQL expressions are: - Literals for all data types, including STRUCT and ARRAY. - Following functions: - CURRENT_TIMESTAMP - CURRENT_TIME - CURRENT_DATE - CURRENT_DATETIME - GENERATE_UUID - RAND - SESSION_USER - ST_GEOGPOINT - Struct or array composed with the above allowed functions, for example, [CURRENT_DATE(), DATE '2020-01-01']
- "description": "A String", # [Optional] The field description. The maximum length is 1,024 characters.
- "fields": [ # [Optional] Describes the nested schema fields if the type property is set to RECORD.
+ "collation": "A String", # Optional. Field collation can be set only when the type of field is STRING. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.
+ "defaultValueExpression": "A String", # Optional. A SQL expression to specify the [default value] (https://cloud.google.com/bigquery/docs/default-values) for this field.
+ "description": "A String", # Optional. The field description. The maximum length is 1,024 characters.
+ "fields": [ # Optional. Describes the nested schema fields if the type property is set to RECORD.
# Object with schema name: TableFieldSchema
],
- "maxLength": "A String", # [Optional] Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
- "mode": "A String", # [Optional] The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
- "name": "A String", # [Required] The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
- "policyTags": {
- "names": [ # A list of category resource names. For example, "projects/1/location/eu/taxonomies/2/policyTags/3". At most 1 policy tag is allowed.
+ "maxLength": "A String", # Optional. Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
+ "mode": "A String", # Optional. The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
+ "name": "A String", # Required. The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
+ "policyTags": { # Optional. The policy tags attached to this field, used for field-level access control. If not set, defaults to empty policy_tags.
+ "names": [ # A list of policy tag resource names. For example, "projects/1/locations/eu/taxonomies/2/policyTags/3". At most 1 policy tag is currently allowed.
"A String",
],
},
- "precision": "A String", # [Optional] Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: - Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] - Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: - If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. - If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): - If type = "NUMERIC": 1 ≤ precision ≤ 29. - If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
- "rangeElementType": { # Optional. The subtype of the RANGE, if the type of this field is RANGE. If the type is RANGE, this field is required. Possible values for the field element type of a RANGE include: - DATE - DATETIME - TIMESTAMP
- "type": "A String", # The field element type of a RANGE
+ "precision": "A String", # Optional. Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: * Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] * Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: * If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. * If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): * If type = "NUMERIC": 1 ≤ precision ≤ 29. * If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
+ "rangeElementType": { # Represents the type of a field element.
+ "type": "A String", # Required. The type of a field element. See TableFieldSchema.type.
},
- "roundingMode": "A String", # Optional. Rounding Mode specification of the field. It only can be set on NUMERIC or BIGNUMERIC type fields.
- "scale": "A String", # [Optional] See documentation for precision.
- "type": "A String", # [Required] The field data type. Possible values include STRING, BYTES, INTEGER, INT64 (same as INTEGER), FLOAT, FLOAT64 (same as FLOAT), NUMERIC, BIGNUMERIC, BOOLEAN, BOOL (same as BOOLEAN), TIMESTAMP, DATE, TIME, DATETIME, INTERVAL, RECORD (where RECORD indicates that the field contains a nested schema) or STRUCT (same as RECORD).
+ "roundingMode": "A String", # Optional. Specifies the rounding mode to be used when storing values of NUMERIC and BIGNUMERIC type.
+ "scale": "A String", # Optional. See documentation for precision.
+ "type": "A String", # Required. The field data type. Possible values include: * STRING * BYTES * INTEGER (or INT64) * FLOAT (or FLOAT64) * BOOLEAN (or BOOL) * TIMESTAMP * DATE * TIME * DATETIME * GEOGRAPHY * NUMERIC * BIGNUMERIC * JSON * RECORD (or STRUCT) Use of RECORD/STRUCT indicates that the field contains a nested schema.
},
],
},
- "sourceFormat": "A String", # [Required] The data format. For CSV files, specify "CSV". For Google sheets, specify "GOOGLE_SHEETS". For newline-delimited JSON, specify "NEWLINE_DELIMITED_JSON". For Avro files, specify "AVRO". For Google Cloud Datastore backups, specify "DATASTORE_BACKUP". [Beta] For Google Cloud Bigtable, specify "BIGTABLE".
+ "sourceFormat": "A String", # [Required] The data format. For CSV files, specify "CSV". For Google sheets, specify "GOOGLE_SHEETS". For newline-delimited JSON, specify "NEWLINE_DELIMITED_JSON". For Avro files, specify "AVRO". For Google Cloud Datastore backups, specify "DATASTORE_BACKUP". For Apache Iceberg tables, specify "ICEBERG". For ORC files, specify "ORC". For Parquet files, specify "PARQUET". [Beta] For Google Cloud Bigtable, specify "BIGTABLE".
"sourceUris": [ # [Required] The fully-qualified URIs that point to your data in Google Cloud. For Google Cloud Storage URIs: Each URI can contain one '*' wildcard character and it must come after the 'bucket' name. Size limits related to load jobs apply to external data sources. For Google Cloud Bigtable URIs: Exactly one URI can be specified and it has be a fully specified and valid HTTPS URL for a Google Cloud Bigtable table. For Google Cloud Datastore backups, exactly one URI can be specified. Also, the '*' wildcard character is not allowed.
"A String",
],
},
},
"timePartitioning": { # Time-based partitioning specification for the destination table. Only one of timePartitioning and rangePartitioning should be specified.
- "expirationMs": "A String", # [Optional] Number of milliseconds for which to keep the storage for partitions in the table. The storage in a partition will have an expiration time of its partition time plus this value.
- "field": "A String", # [Beta] [Optional] If not set, the table is partitioned by pseudo column, referenced via either '_PARTITIONTIME' as TIMESTAMP type, or '_PARTITIONDATE' as DATE type. If field is specified, the table is instead partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED.
- "requirePartitionFilter": True or False,
- "type": "A String", # [Required] The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively. When the type is not specified, the default behavior is DAY.
+ "expirationMs": "A String", # Optional. Number of milliseconds for which to keep the storage for a partition. A wrapper is used here because 0 is an invalid value.
+ "field": "A String", # Optional. If not set, the table is partitioned by pseudo column '_PARTITIONTIME'; if set, the table is partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED. A wrapper is used here because an empty string is an invalid value.
+ "requirePartitionFilter": false, # If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. This field is deprecated; please set the field with the same name on the table itself instead. This field needs a wrapper because we want to output the default value, false, if the user explicitly set it.
+ "type": "A String", # Required. The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively.
},
- "useLegacySql": true, # Specifies whether to use BigQuery's legacy SQL dialect for this query. The default value is true. If set to false, the query will use BigQuery's standard SQL: https://cloud.google.com/bigquery/sql-reference/ When useLegacySql is set to false, the value of flattenResults is ignored; query will be run as if flattenResults is false.
- "useQueryCache": true, # [Optional] Whether to look for the result in the query cache. The query cache is a best-effort cache that will be flushed whenever tables in the query are modified. Moreover, the query cache is only available when a query does not have a destination table specified. The default value is true.
+ "useLegacySql": true, # Optional. Specifies whether to use BigQuery's legacy SQL dialect for this query. The default value is true. If set to false, the query will use BigQuery's GoogleSQL: https://cloud.google.com/bigquery/sql-reference/ When useLegacySql is set to false, the value of flattenResults is ignored; query will be run as if flattenResults is false.
+ "useQueryCache": true, # Optional. Whether to look for the result in the query cache. The query cache is a best-effort cache that will be flushed whenever tables in the query are modified. Moreover, the query cache is only available when a query does not have a destination table specified. The default value is true.
"userDefinedFunctionResources": [ # Describes user-defined function resources used in the query.
- { # This is used for defining User Defined Function (UDF) resources only when using legacy SQL. Users of Standard SQL should leverage either DDL (e.g. CREATE [TEMPORARY] FUNCTION ... ) or the Routines API to define UDF resources. For additional information on migrating, see: https://cloud.google.com/bigquery/docs/reference/standard-sql/migrating-from-legacy-sql#differences_in_user-defined_javascript_functions
+ { # This is used for defining User Defined Function (UDF) resources only when using legacy SQL. Users of GoogleSQL should leverage either DDL (e.g. CREATE [TEMPORARY] FUNCTION ... ) or the Routines API to define UDF resources. For additional information on migrating, see: https://cloud.google.com/bigquery/docs/reference/standard-sql/migrating-from-legacy-sql#differences_in_user-defined_javascript_functions
"inlineCode": "A String", # [Pick one] An inline resource that contains code for a user-defined function (UDF). Providing a inline code resource is equivalent to providing a URI for a file containing the same code.
"resourceUri": "A String", # [Pick one] A code resource to load from a Google Cloud Storage URI (gs://bucket/path).
},
],
- "writeDisposition": "A String", # [Optional] Specifies the action that occurs if the destination table already exists. The following values are supported: WRITE_TRUNCATE: If the table already exists, BigQuery overwrites the table data and uses the schema from the query result. WRITE_APPEND: If the table already exists, BigQuery appends the data to the table. WRITE_EMPTY: If the table already exists and contains data, a 'duplicate' error is returned in the job result. The default value is WRITE_EMPTY. Each action is atomic and only occurs if BigQuery is able to complete the job successfully. Creation, truncation and append actions occur as one atomic update upon job completion.
+ "writeDisposition": "A String", # Optional. Specifies the action that occurs if the destination table already exists. The following values are supported: * WRITE_TRUNCATE: If the table already exists, BigQuery overwrites the data, removes the constraints, and uses the schema from the query result. * WRITE_APPEND: If the table already exists, BigQuery appends the data to the table. * WRITE_EMPTY: If the table already exists and contains data, a 'duplicate' error is returned in the job result. The default value is WRITE_EMPTY. Each action is atomic and only occurs if BigQuery is able to complete the job successfully. Creation, truncation and append actions occur as one atomic update upon job completion.
},
},
- "errorResult": { # A result object that will be present only if the job has failed.
+ "errorResult": { # Error details. # A result object that will be present only if the job has failed.
"debugInfo": "A String", # Debugging information. This property is internal to Google and should not be used.
"location": "A String", # Specifies where the error occurred, if present.
"message": "A String", # A human-readable description of the error.
"reason": "A String", # A short error code that summarizes the error.
},
"id": "A String", # Unique opaque ID of the job.
- "jobReference": { # Job reference uniquely identifying the job.
- "jobId": "A String", # [Required] The ID of the job. The ID must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), or dashes (-). The maximum length is 1,024 characters.
- "location": "A String", # The geographic location of the job. See details at https://cloud.google.com/bigquery/docs/locations#specifying_your_location.
- "projectId": "A String", # [Required] The ID of the project containing this job.
+ "jobReference": { # A job reference is a fully qualified identifier for referring to a job. # Unique opaque ID of the job.
+ "jobId": "A String", # Required. The ID of the job. The ID must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), or dashes (-). The maximum length is 1,024 characters.
+ "location": "A String", # Optional. The geographic location of the job. The default value is US. For more information about BigQuery locations, see: https://cloud.google.com/bigquery/docs/locations
+ "projectId": "A String", # Required. The ID of the project containing this job.
},
- "kind": "bigquery#job", # The resource type.
+ "kind": "A String", # The resource type.
+ "principal_subject": "A String", # [Full-projection-only] String representation of identity of requesting party. Populated for both first- and third-party identities. Only present for APIs that support third-party identities.
"state": "A String", # Running state of the job. When the state is DONE, errorResult can be checked to determine whether the job succeeded or failed.
- "statistics": { # [Output-only] Information about the job, including starting time and ending time of the job.
- "completionRatio": 3.14, # [TrustedTester] [Output-only] Job progress (0.0 -> 1.0) for LOAD and EXTRACT jobs.
- "copy": { # [Output-only] Statistics for a copy job.
- "copiedLogicalBytes": "A String", # [Output-only] Number of logical bytes copied to the destination table.
- "copiedRows": "A String", # [Output-only] Number of rows copied to the destination table.
- },
- "creationTime": "A String", # [Output-only] Creation time of this job, in milliseconds since the epoch. This field will be present on all jobs.
- "dataMaskingStatistics": { # [Output-only] Statistics for data masking. Present only for query and extract jobs.
- "dataMaskingApplied": false, # [Output-only] [Preview] Whether any accessed data was protected by data masking. The actual evaluation is done by accessStats.masked_field_count > 0. Since this is only used for the discovery_doc generation purpose, as long as the type (boolean) matches, client library can leverage this. The actual evaluation of the variable is done else-where.
- },
- "endTime": "A String", # [Output-only] End time of this job, in milliseconds since the epoch. This field will be present whenever a job is in the DONE state.
- "extract": { # [Output-only] Statistics for an extract job.
- "destinationUriFileCounts": [ # [Output-only] Number of files per destination URI or URI pattern specified in the extract configuration. These values will be in the same order as the URIs specified in the 'destinationUris' field.
+ "statistics": { # Statistics for a single job execution. # Output only. Information about the job, including starting time and ending time of the job.
+ "completionRatio": 3.14, # Output only. [TrustedTester] Job progress (0.0 -> 1.0) for LOAD and EXTRACT jobs.
+ "copy": { # Statistics for a copy job. # Output only. Statistics for a copy job.
+ "copiedLogicalBytes": "A String", # Output only. Number of logical bytes copied to the destination table.
+ "copiedRows": "A String", # Output only. Number of rows copied to the destination table.
+ },
+ "creationTime": "A String", # Output only. Creation time of this job, in milliseconds since the epoch. This field will be present on all jobs.
+ "dataMaskingStatistics": { # Statistics for data-masking. # Output only. Statistics for data-masking. Present only for query and extract jobs.
+ "dataMaskingApplied": True or False, # Whether any accessed data was protected by the data masking.
+ },
+ "endTime": "A String", # Output only. End time of this job, in milliseconds since the epoch. This field will be present whenever a job is in the DONE state.
+ "extract": { # Statistics for an extract job. # Output only. Statistics for an extract job.
+ "destinationUriFileCounts": [ # Output only. Number of files per destination URI or URI pattern specified in the extract configuration. These values will be in the same order as the URIs specified in the 'destinationUris' field.
"A String",
],
- "inputBytes": "A String", # [Output-only] Number of user bytes extracted into the result. This is the byte count as computed by BigQuery for billing purposes.
- },
- "load": { # [Output-only] Statistics for a load job.
- "badRecords": "A String", # [Output-only] The number of bad records encountered. Note that if the job has failed because of more bad records encountered than the maximum allowed in the load job configuration, then this number can be less than the total number of bad records present in the input data.
- "inputFileBytes": "A String", # [Output-only] Number of bytes of source data in a load job.
- "inputFiles": "A String", # [Output-only] Number of source files in a load job.
- "outputBytes": "A String", # [Output-only] Size of the loaded data in bytes. Note that while a load job is in the running state, this value may change.
- "outputRows": "A String", # [Output-only] Number of rows imported in a load job. Note that while an import job is in the running state, this value may change.
- },
- "numChildJobs": "A String", # [Output-only] Number of child jobs executed.
- "parentJobId": "A String", # [Output-only] If this is a child job, the id of the parent.
- "query": { # [Output-only] Statistics for a query job.
- "biEngineStatistics": { # BI Engine specific Statistics. [Output only] BI Engine specific Statistics.
- "accelerationMode": "", # [Output-only] Specifies which mode of BI Engine acceleration was performed (if any).
- "biEngineMode": "", # [Output-only] Specifies which mode of BI Engine acceleration was performed (if any).
+ "inputBytes": "A String", # Output only. Number of user bytes extracted into the result. This is the byte count as computed by BigQuery for billing purposes and doesn't have any relationship with the number of actual result bytes extracted in the desired format.
+ "timeline": [ # Output only. Describes a timeline of job execution.
+ { # Summary of the state of query execution at a given time.
+ "activeUnits": "A String", # Total number of active workers. This does not correspond directly to slot usage. This is the largest value observed since the last sample.
+ "completedUnits": "A String", # Total parallel units of work completed by this query.
+ "elapsedMs": "A String", # Milliseconds elapsed since the start of query execution.
+ "estimatedRunnableUnits": "A String", # Units of work that can be scheduled immediately. Providing additional slots for these units of work will accelerate the query, if no other query in the reservation needs additional slots.
+ "pendingUnits": "A String", # Total units of work remaining for the query. This number can be revised (increased or decreased) while the query is running.
+ "totalSlotMs": "A String", # Cumulative slot-ms consumed by the query.
+ },
+ ],
+ },
+ "finalExecutionDurationMs": "A String", # Output only. The duration in milliseconds of the execution of the final attempt of this job, as BigQuery may internally re-attempt to execute the job.
+ "load": { # Statistics for a load job. # Output only. Statistics for a load job.
+ "badRecords": "A String", # Output only. The number of bad records encountered. Note that if the job has failed because of more bad records encountered than the maximum allowed in the load job configuration, then this number can be less than the total number of bad records present in the input data.
+ "inputFileBytes": "A String", # Output only. Number of bytes of source data in a load job.
+ "inputFiles": "A String", # Output only. Number of source files in a load job.
+ "outputBytes": "A String", # Output only. Size of the loaded data in bytes. Note that while a load job is in the running state, this value may change.
+ "outputRows": "A String", # Output only. Number of rows imported in a load job. Note that while an import job is in the running state, this value may change.
+ "timeline": [ # Output only. Describes a timeline of job execution.
+ { # Summary of the state of query execution at a given time.
+ "activeUnits": "A String", # Total number of active workers. This does not correspond directly to slot usage. This is the largest value observed since the last sample.
+ "completedUnits": "A String", # Total parallel units of work completed by this query.
+ "elapsedMs": "A String", # Milliseconds elapsed since the start of query execution.
+ "estimatedRunnableUnits": "A String", # Units of work that can be scheduled immediately. Providing additional slots for these units of work will accelerate the query, if no other query in the reservation needs additional slots.
+ "pendingUnits": "A String", # Total units of work remaining for the query. This number can be revised (increased or decreased) while the query is running.
+ "totalSlotMs": "A String", # Cumulative slot-ms consumed by the query.
+ },
+ ],
+ },
+ "numChildJobs": "A String", # Output only. Number of child jobs executed.
+ "parentJobId": "A String", # Output only. If this is a child job, specifies the job ID of the parent.
+ "query": { # Statistics for a query job. # Output only. Statistics for a query job.
+ "biEngineStatistics": { # Statistics for a BI Engine specific query. Populated as part of JobStatistics2 # Output only. BI Engine specific Statistics.
+ "accelerationMode": "A String", # Output only. Specifies which mode of BI Engine acceleration was performed (if any).
+ "biEngineMode": "A String", # Output only. Specifies which mode of BI Engine acceleration was performed (if any).
"biEngineReasons": [ # In case of DISABLED or PARTIAL bi_engine_mode, these contain the explanatory reasons as to why BI Engine could not accelerate. In case the full query was accelerated, this field is not populated.
- {
- "code": "", # [Output-only] High-level BI Engine reason for partial or disabled acceleration.
- "message": "", # [Output-only] Free form human-readable reason for partial or disabled acceleration.
+ { # Reason why BI Engine didn't accelerate the query (or sub-query).
+ "code": "A String", # Output only. High-level BI Engine reason for partial or disabled acceleration
+ "message": "A String", # Output only. Free form human-readable reason for partial or disabled acceleration.
},
],
},
- "billingTier": 42, # [Output only] Billing tier for the job.
- "cacheHit": True or False, # [Output only] Whether the query result was fetched from the query cache.
- "ddlAffectedRowAccessPolicyCount": "A String", # [Output only] [Preview] The number of row access policies affected by a DDL statement. Present only for DROP ALL ROW ACCESS POLICIES queries.
- "ddlDestinationTable": { # [Output only] The DDL destination table. Present only for ALTER TABLE RENAME TO queries. Note that ddl_target_table is used just for its type information.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "billingTier": 42, # Output only. Billing tier for the job. This is a BigQuery-specific concept which is not related to the Google Cloud notion of "free tier". The value here is a measure of the query's resource consumption relative to the amount of data scanned. For on-demand queries, the limit is 100, and all queries within this limit are billed at the standard on-demand rates. On-demand queries that exceed this limit will fail with a billingTierLimitExceeded error.
+ "cacheHit": True or False, # Output only. Whether the query result was fetched from the query cache.
+ "dclTargetDataset": { # Output only. Referenced dataset for DCL statement.
+ "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "projectId": "A String", # Optional. The ID of the project containing this dataset.
+ },
+ "dclTargetTable": { # Output only. Referenced table for DCL statement.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ "dclTargetView": { # Output only. Referenced view for DCL statement.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ "ddlAffectedRowAccessPolicyCount": "A String", # Output only. The number of row access policies affected by a DDL statement. Present only for DROP ALL ROW ACCESS POLICIES queries.
+ "ddlDestinationTable": { # Output only. The table after rename. Present only for ALTER TABLE RENAME TO query.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
- "ddlOperationPerformed": "A String", # The DDL operation performed, possibly dependent on the pre-existence of the DDL target. Possible values (new values might be added in the future): "CREATE": The query created the DDL target. "SKIP": No-op. Example cases: the query is CREATE TABLE IF NOT EXISTS while the table already exists, or the query is DROP TABLE IF EXISTS while the table does not exist. "REPLACE": The query replaced the DDL target. Example case: the query is CREATE OR REPLACE TABLE, and the table already exists. "DROP": The query deleted the DDL target.
- "ddlTargetDataset": { # [Output only] The DDL target dataset. Present only for CREATE/ALTER/DROP/UNDROP SCHEMA queries.
- "datasetId": "A String", # [Required] A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- "projectId": "A String", # [Optional] The ID of the project containing this dataset.
+ "ddlOperationPerformed": "A String", # Output only. The DDL operation performed, possibly dependent on the pre-existence of the DDL target.
+ "ddlTargetDataset": { # Output only. The DDL target dataset. Present only for CREATE/ALTER/DROP SCHEMA(dataset) queries.
+ "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "projectId": "A String", # Optional. The ID of the project containing this dataset.
},
- "ddlTargetRoutine": { # The DDL target routine. Present only for CREATE/DROP FUNCTION/PROCEDURE queries.
+ "ddlTargetRoutine": { # Id path of a routine. # Output only. [Beta] The DDL target routine. Present only for CREATE/DROP FUNCTION/PROCEDURE queries.
"datasetId": "A String", # Required. The ID of the dataset containing this routine.
"projectId": "A String", # Required. The ID of the project containing this routine.
"routineId": "A String", # Required. The ID of the routine. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 256 characters.
},
- "ddlTargetRowAccessPolicy": { # [Output only] [Preview] The DDL target row access policy. Present only for CREATE/DROP ROW ACCESS POLICY queries.
+ "ddlTargetRowAccessPolicy": { # Id path of a row access policy. # Output only. The DDL target row access policy. Present only for CREATE/DROP ROW ACCESS POLICY queries.
"datasetId": "A String", # Required. The ID of the dataset containing this row access policy.
"policyId": "A String", # Required. The ID of the row access policy. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 256 characters.
"projectId": "A String", # Required. The ID of the project containing this row access policy.
"tableId": "A String", # Required. The ID of the table containing this row access policy.
},
- "ddlTargetTable": { # [Output only] The DDL target table. Present only for CREATE/DROP TABLE/VIEW and DROP ALL ROW ACCESS POLICIES queries.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "ddlTargetTable": { # Output only. The DDL target table. Present only for CREATE/DROP TABLE/VIEW and DROP ALL ROW ACCESS POLICIES queries.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ "dmlStats": { # Detailed statistics for DML statements # Output only. Detailed statistics for DML statements INSERT, UPDATE, DELETE, MERGE or TRUNCATE.
+ "deletedRowCount": "A String", # Output only. Number of deleted Rows. populated by DML DELETE, MERGE and TRUNCATE statements.
+ "insertedRowCount": "A String", # Output only. Number of inserted Rows. Populated by DML INSERT and MERGE statements
+ "updatedRowCount": "A String", # Output only. Number of updated Rows. Populated by DML UPDATE and MERGE statements.
+ },
+ "estimatedBytesProcessed": "A String", # Output only. The original estimate of bytes processed for the job.
+ "exportDataStatistics": { # Statistics for the EXPORT DATA statement as part of Query Job. EXTRACT JOB statistics are populated in JobStatistics4. # Output only. Stats for EXPORT DATA statement.
+ "fileCount": "A String", # Number of destination files generated in case of EXPORT DATA statement only.
+ "rowCount": "A String", # [Alpha] Number of destination rows generated in case of EXPORT DATA statement only.
+ },
+ "externalServiceCosts": [ # Output only. Job cost breakdown as bigquery internal cost and external service costs.
+ { # The external service cost is a portion of the total cost, these costs are not additive with total_bytes_billed. Moreover, this field only track external service costs that will show up as BigQuery costs (e.g. training BigQuery ML job with google cloud CAIP or Automl Tables services), not other costs which may be accrued by running the query (e.g. reading from Bigtable or Cloud Storage). The external service costs with different billing sku (e.g. CAIP job is charged based on VM usage) are converted to BigQuery billed_bytes and slot_ms with equivalent amount of US dollars. Services may not directly correlate to these metrics, but these are the equivalents for billing purposes. Output only.
+ "bytesBilled": "A String", # External service cost in terms of bigquery bytes billed.
+ "bytesProcessed": "A String", # External service cost in terms of bigquery bytes processed.
+ "externalService": "A String", # External service name.
+ "reservedSlotCount": "A String", # Non-preemptable reserved slots used for external job. For example, reserved slots for Cloua AI Platform job are the VM usages converted to BigQuery slot with equivalent mount of price.
+ "slotMs": "A String", # External service cost in terms of bigquery slot milliseconds.
+ },
+ ],
+ "loadQueryStatistics": { # Statistics for a LOAD query. # Output only. Statistics for a LOAD query.
+ "badRecords": "A String", # Output only. The number of bad records encountered while processing a LOAD query. Note that if the job has failed because of more bad records encountered than the maximum allowed in the load job configuration, then this number can be less than the total number of bad records present in the input data.
+ "bytesTransferred": "A String", # Output only. This field is deprecated. The number of bytes of source data copied over the network for a `LOAD` query. `transferred_bytes` has the canonical value for physical transferred bytes, which is used for BigQuery Omni billing.
+ "inputFileBytes": "A String", # Output only. Number of bytes of source data in a LOAD query.
+ "inputFiles": "A String", # Output only. Number of source files in a LOAD query.
+ "outputBytes": "A String", # Output only. Size of the loaded data in bytes. Note that while a LOAD query is in the running state, this value may change.
+ "outputRows": "A String", # Output only. Number of rows imported in a LOAD query. Note that while a LOAD query is in the running state, this value may change.
+ },
+ "materializedViewStatistics": { # Statistics of materialized views considered in a query job. # Output only. Statistics of materialized views of a query job.
+ "materializedView": [ # Materialized views considered for the query job. Only certain materialized views are used. For a detailed list, see the child message. If many materialized views are considered, then the list might be incomplete.
+ { # A materialized view considered for a query job.
+ "chosen": True or False, # Whether the materialized view is chosen for the query. A materialized view can be chosen to rewrite multiple parts of the same query. If a materialized view is chosen to rewrite any part of the query, then this field is true, even if the materialized view was not chosen to rewrite others parts.
+ "estimatedBytesSaved": "A String", # If present, specifies a best-effort estimation of the bytes saved by using the materialized view rather than its base tables.
+ "rejectedReason": "A String", # If present, specifies the reason why the materialized view was not chosen for the query.
+ "tableReference": { # The candidate materialized view.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ },
+ ],
},
- "dmlStats": { # [Output only] Detailed statistics for DML statements Present only for DML statements INSERT, UPDATE, DELETE or TRUNCATE.
- "deletedRowCount": "A String", # Number of deleted Rows. populated by DML DELETE, MERGE and TRUNCATE statements.
- "insertedRowCount": "A String", # Number of inserted Rows. Populated by DML INSERT and MERGE statements.
- "updatedRowCount": "A String", # Number of updated Rows. Populated by DML UPDATE and MERGE statements.
+ "metadataCacheStatistics": { # Statistics for metadata caching in BigLake tables. # Output only. Statistics of metadata cache usage in a query for BigLake tables.
+ "tableMetadataCacheUsage": [ # Set for the Metadata caching eligible tables referenced in the query.
+ { # Table level detail on the usage of metadata caching. Only set for Metadata caching eligible tables referenced in the query.
+ "explanation": "A String", # Free form human-readable reason metadata caching was unused for the job.
+ "tableReference": { # Metadata caching eligible table referenced in the query.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ "tableType": "A String", # [Table type](/bigquery/docs/reference/rest/v2/tables#Table.FIELDS.type).
+ "unusedReason": "A String", # Reason for not using metadata caching for the table.
+ },
+ ],
},
- "estimatedBytesProcessed": "A String", # [Output only] The original estimate of bytes processed for the job.
- "mlStatistics": { # [Output only] Statistics of a BigQuery ML training job.
- "iterationResults": [ # Results for all completed iterations.
- {
+ "mlStatistics": { # Job statistics specific to a BigQuery ML training job. # Output only. Statistics of a BigQuery ML training job.
+ "hparamTrials": [ # Output only. Trials of a [hyperparameter tuning job](/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview) sorted by trial_id.
+ { # Training info of a trial in [hyperparameter tuning](/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview) models.
+ "endTimeMs": "A String", # Ending time of the trial.
+ "errorMessage": "A String", # Error message for FAILED and INFEASIBLE trial.
+ "evalLoss": 3.14, # Loss computed on the eval data at the end of trial.
+ "evaluationMetrics": { # Evaluation metrics of a model. These are either computed on all training data or just the eval data based on whether eval data was used during training. These are not present for imported models. # Evaluation metrics of this trial calculated on the test data. Empty in Job API.
+ "arimaForecastingMetrics": { # Model evaluation metrics for ARIMA forecasting models. # Populated for ARIMA models.
+ "arimaFittingMetrics": [ # Arima model fitting metrics.
+ { # ARIMA model fitting metrics.
+ "aic": 3.14, # AIC.
+ "logLikelihood": 3.14, # Log-likelihood.
+ "variance": 3.14, # Variance.
+ },
+ ],
+ "arimaSingleModelForecastingMetrics": [ # Repeated as there can be many metric sets (one for each model) in auto-arima and the large-scale case.
+ { # Model evaluation metrics for a single ARIMA forecasting model.
+ "arimaFittingMetrics": { # ARIMA model fitting metrics. # Arima fitting metrics.
+ "aic": 3.14, # AIC.
+ "logLikelihood": 3.14, # Log-likelihood.
+ "variance": 3.14, # Variance.
+ },
+ "hasDrift": True or False, # Is arima model fitted with drift or not. It is always false when d is not 1.
+ "hasHolidayEffect": True or False, # If true, holiday_effect is a part of time series decomposition result.
+ "hasSpikesAndDips": True or False, # If true, spikes_and_dips is a part of time series decomposition result.
+ "hasStepChanges": True or False, # If true, step_changes is a part of time series decomposition result.
+ "nonSeasonalOrder": { # Arima order, can be used for both non-seasonal and seasonal parts. # Non-seasonal order.
+ "d": "A String", # Order of the differencing part.
+ "p": "A String", # Order of the autoregressive part.
+ "q": "A String", # Order of the moving-average part.
+ },
+ "seasonalPeriods": [ # Seasonal periods. Repeated because multiple periods are supported for one time series.
+ "A String",
+ ],
+ "timeSeriesId": "A String", # The time_series_id value for this time series. It will be one of the unique values from the time_series_id_column specified during ARIMA model training. Only present when time_series_id_column training option was used.
+ "timeSeriesIds": [ # The tuple of time_series_ids identifying this time series. It will be one of the unique tuples of values present in the time_series_id_columns specified during ARIMA model training. Only present when time_series_id_columns training option was used and the order of values here are same as the order of time_series_id_columns.
+ "A String",
+ ],
+ },
+ ],
+ "hasDrift": [ # Whether Arima model fitted with drift or not. It is always false when d is not 1.
+ True or False,
+ ],
+ "nonSeasonalOrder": [ # Non-seasonal order.
+ { # Arima order, can be used for both non-seasonal and seasonal parts.
+ "d": "A String", # Order of the differencing part.
+ "p": "A String", # Order of the autoregressive part.
+ "q": "A String", # Order of the moving-average part.
+ },
+ ],
+ "seasonalPeriods": [ # Seasonal periods. Repeated because multiple periods are supported for one time series.
+ "A String",
+ ],
+ "timeSeriesId": [ # Id to differentiate different time series for the large-scale case.
+ "A String",
+ ],
+ },
+ "binaryClassificationMetrics": { # Evaluation metrics for binary classification/classifier models. # Populated for binary classification/classifier models.
+ "aggregateClassificationMetrics": { # Aggregate metrics for classification/classifier models. For multi-class models, the metrics are either macro-averaged or micro-averaged. When macro-averaged, the metrics are calculated for each label and then an unweighted average is taken of those values. When micro-averaged, the metric is calculated globally by counting the total number of correctly predicted rows. # Aggregate classification metrics.
+ "accuracy": 3.14, # Accuracy is the fraction of predictions given the correct label. For multiclass this is a micro-averaged metric.
+ "f1Score": 3.14, # The F1 score is an average of recall and precision. For multiclass this is a macro-averaged metric.
+ "logLoss": 3.14, # Logarithmic Loss. For multiclass this is a macro-averaged metric.
+ "precision": 3.14, # Precision is the fraction of actual positive predictions that had positive actual labels. For multiclass this is a macro-averaged metric treating each class as a binary classifier.
+ "recall": 3.14, # Recall is the fraction of actual positive labels that were given a positive prediction. For multiclass this is a macro-averaged metric.
+ "rocAuc": 3.14, # Area Under a ROC Curve. For multiclass this is a macro-averaged metric.
+ "threshold": 3.14, # Threshold at which the metrics are computed. For binary classification models this is the positive class threshold. For multi-class classfication models this is the confidence threshold.
+ },
+ "binaryConfusionMatrixList": [ # Binary confusion matrix at multiple thresholds.
+ { # Confusion matrix for binary classification models.
+ "accuracy": 3.14, # The fraction of predictions given the correct label.
+ "f1Score": 3.14, # The equally weighted average of recall and precision.
+ "falseNegatives": "A String", # Number of false samples predicted as false.
+ "falsePositives": "A String", # Number of false samples predicted as true.
+ "positiveClassThreshold": 3.14, # Threshold value used when computing each of the following metric.
+ "precision": 3.14, # The fraction of actual positive predictions that had positive actual labels.
+ "recall": 3.14, # The fraction of actual positive labels that were given a positive prediction.
+ "trueNegatives": "A String", # Number of true samples predicted as false.
+ "truePositives": "A String", # Number of true samples predicted as true.
+ },
+ ],
+ "negativeLabel": "A String", # Label representing the negative class.
+ "positiveLabel": "A String", # Label representing the positive class.
+ },
+ "clusteringMetrics": { # Evaluation metrics for clustering models. # Populated for clustering models.
+ "clusters": [ # Information for all clusters.
+ { # Message containing the information about one cluster.
+ "centroidId": "A String", # Centroid id.
+ "count": "A String", # Count of training data rows that were assigned to this cluster.
+ "featureValues": [ # Values of highly variant features for this cluster.
+ { # Representative value of a single feature within the cluster.
+ "categoricalValue": { # Representative value of a categorical feature. # The categorical feature value.
+ "categoryCounts": [ # Counts of all categories for the categorical feature. If there are more than ten categories, we return top ten (by count) and return one more CategoryCount with category "_OTHER_" and count as aggregate counts of remaining categories.
+ { # Represents the count of a single category within the cluster.
+ "category": "A String", # The name of category.
+ "count": "A String", # The count of training samples matching the category within the cluster.
+ },
+ ],
+ },
+ "featureColumn": "A String", # The feature column name.
+ "numericalValue": 3.14, # The numerical feature value. This is the centroid value for this feature.
+ },
+ ],
+ },
+ ],
+ "daviesBouldinIndex": 3.14, # Davies-Bouldin index.
+ "meanSquaredDistance": 3.14, # Mean of squared distances between each sample to its cluster centroid.
+ },
+ "dimensionalityReductionMetrics": { # Model evaluation metrics for dimensionality reduction models. # Evaluation metrics when the model is a dimensionality reduction model, which currently includes PCA.
+ "totalExplainedVarianceRatio": 3.14, # Total percentage of variance explained by the selected principal components.
+ },
+ "multiClassClassificationMetrics": { # Evaluation metrics for multi-class classification/classifier models. # Populated for multi-class classification/classifier models.
+ "aggregateClassificationMetrics": { # Aggregate metrics for classification/classifier models. For multi-class models, the metrics are either macro-averaged or micro-averaged. When macro-averaged, the metrics are calculated for each label and then an unweighted average is taken of those values. When micro-averaged, the metric is calculated globally by counting the total number of correctly predicted rows. # Aggregate classification metrics.
+ "accuracy": 3.14, # Accuracy is the fraction of predictions given the correct label. For multiclass this is a micro-averaged metric.
+ "f1Score": 3.14, # The F1 score is an average of recall and precision. For multiclass this is a macro-averaged metric.
+ "logLoss": 3.14, # Logarithmic Loss. For multiclass this is a macro-averaged metric.
+ "precision": 3.14, # Precision is the fraction of actual positive predictions that had positive actual labels. For multiclass this is a macro-averaged metric treating each class as a binary classifier.
+ "recall": 3.14, # Recall is the fraction of actual positive labels that were given a positive prediction. For multiclass this is a macro-averaged metric.
+ "rocAuc": 3.14, # Area Under a ROC Curve. For multiclass this is a macro-averaged metric.
+ "threshold": 3.14, # Threshold at which the metrics are computed. For binary classification models this is the positive class threshold. For multi-class classfication models this is the confidence threshold.
+ },
+ "confusionMatrixList": [ # Confusion matrix at different thresholds.
+ { # Confusion matrix for multi-class classification models.
+ "confidenceThreshold": 3.14, # Confidence threshold used when computing the entries of the confusion matrix.
+ "rows": [ # One row per actual label.
+ { # A single row in the confusion matrix.
+ "actualLabel": "A String", # The original label of this row.
+ "entries": [ # Info describing predicted label distribution.
+ { # A single entry in the confusion matrix.
+ "itemCount": "A String", # Number of items being predicted as this label.
+ "predictedLabel": "A String", # The predicted label. For confidence_threshold > 0, we will also add an entry indicating the number of items under the confidence threshold.
+ },
+ ],
+ },
+ ],
+ },
+ ],
+ },
+ "rankingMetrics": { # Evaluation metrics used by weighted-ALS models specified by feedback_type=implicit. # Populated for implicit feedback type matrix factorization models.
+ "averageRank": 3.14, # Determines the goodness of a ranking by computing the percentile rank from the predicted confidence and dividing it by the original rank.
+ "meanAveragePrecision": 3.14, # Calculates a precision per user for all the items by ranking them and then averages all the precisions across all the users.
+ "meanSquaredError": 3.14, # Similar to the mean squared error computed in regression and explicit recommendation models except instead of computing the rating directly, the output from evaluate is computed against a preference which is 1 or 0 depending on if the rating exists or not.
+ "normalizedDiscountedCumulativeGain": 3.14, # A metric to determine the goodness of a ranking calculated from the predicted confidence by comparing it to an ideal rank measured by the original ratings.
+ },
+ "regressionMetrics": { # Evaluation metrics for regression and explicit feedback type matrix factorization models. # Populated for regression models and explicit feedback type matrix factorization models.
+ "meanAbsoluteError": 3.14, # Mean absolute error.
+ "meanSquaredError": 3.14, # Mean squared error.
+ "meanSquaredLogError": 3.14, # Mean squared log error.
+ "medianAbsoluteError": 3.14, # Median absolute error.
+ "rSquared": 3.14, # R^2 score. This corresponds to r2_score in ML.EVALUATE.
+ },
+ },
+ "hparamTuningEvaluationMetrics": { # Evaluation metrics of a model. These are either computed on all training data or just the eval data based on whether eval data was used during training. These are not present for imported models. # Hyperparameter tuning evaluation metrics of this trial calculated on the eval data. Unlike evaluation_metrics, only the fields corresponding to the hparam_tuning_objectives are set.
+ "arimaForecastingMetrics": { # Model evaluation metrics for ARIMA forecasting models. # Populated for ARIMA models.
+ "arimaFittingMetrics": [ # Arima model fitting metrics.
+ { # ARIMA model fitting metrics.
+ "aic": 3.14, # AIC.
+ "logLikelihood": 3.14, # Log-likelihood.
+ "variance": 3.14, # Variance.
+ },
+ ],
+ "arimaSingleModelForecastingMetrics": [ # Repeated as there can be many metric sets (one for each model) in auto-arima and the large-scale case.
+ { # Model evaluation metrics for a single ARIMA forecasting model.
+ "arimaFittingMetrics": { # ARIMA model fitting metrics. # Arima fitting metrics.
+ "aic": 3.14, # AIC.
+ "logLikelihood": 3.14, # Log-likelihood.
+ "variance": 3.14, # Variance.
+ },
+ "hasDrift": True or False, # Is arima model fitted with drift or not. It is always false when d is not 1.
+ "hasHolidayEffect": True or False, # If true, holiday_effect is a part of time series decomposition result.
+ "hasSpikesAndDips": True or False, # If true, spikes_and_dips is a part of time series decomposition result.
+ "hasStepChanges": True or False, # If true, step_changes is a part of time series decomposition result.
+ "nonSeasonalOrder": { # Arima order, can be used for both non-seasonal and seasonal parts. # Non-seasonal order.
+ "d": "A String", # Order of the differencing part.
+ "p": "A String", # Order of the autoregressive part.
+ "q": "A String", # Order of the moving-average part.
+ },
+ "seasonalPeriods": [ # Seasonal periods. Repeated because multiple periods are supported for one time series.
+ "A String",
+ ],
+ "timeSeriesId": "A String", # The time_series_id value for this time series. It will be one of the unique values from the time_series_id_column specified during ARIMA model training. Only present when time_series_id_column training option was used.
+ "timeSeriesIds": [ # The tuple of time_series_ids identifying this time series. It will be one of the unique tuples of values present in the time_series_id_columns specified during ARIMA model training. Only present when time_series_id_columns training option was used and the order of values here are same as the order of time_series_id_columns.
+ "A String",
+ ],
+ },
+ ],
+ "hasDrift": [ # Whether Arima model fitted with drift or not. It is always false when d is not 1.
+ True or False,
+ ],
+ "nonSeasonalOrder": [ # Non-seasonal order.
+ { # Arima order, can be used for both non-seasonal and seasonal parts.
+ "d": "A String", # Order of the differencing part.
+ "p": "A String", # Order of the autoregressive part.
+ "q": "A String", # Order of the moving-average part.
+ },
+ ],
+ "seasonalPeriods": [ # Seasonal periods. Repeated because multiple periods are supported for one time series.
+ "A String",
+ ],
+ "timeSeriesId": [ # Id to differentiate different time series for the large-scale case.
+ "A String",
+ ],
+ },
+ "binaryClassificationMetrics": { # Evaluation metrics for binary classification/classifier models. # Populated for binary classification/classifier models.
+ "aggregateClassificationMetrics": { # Aggregate metrics for classification/classifier models. For multi-class models, the metrics are either macro-averaged or micro-averaged. When macro-averaged, the metrics are calculated for each label and then an unweighted average is taken of those values. When micro-averaged, the metric is calculated globally by counting the total number of correctly predicted rows. # Aggregate classification metrics.
+ "accuracy": 3.14, # Accuracy is the fraction of predictions given the correct label. For multiclass this is a micro-averaged metric.
+ "f1Score": 3.14, # The F1 score is an average of recall and precision. For multiclass this is a macro-averaged metric.
+ "logLoss": 3.14, # Logarithmic Loss. For multiclass this is a macro-averaged metric.
+ "precision": 3.14, # Precision is the fraction of actual positive predictions that had positive actual labels. For multiclass this is a macro-averaged metric treating each class as a binary classifier.
+ "recall": 3.14, # Recall is the fraction of actual positive labels that were given a positive prediction. For multiclass this is a macro-averaged metric.
+ "rocAuc": 3.14, # Area Under a ROC Curve. For multiclass this is a macro-averaged metric.
+ "threshold": 3.14, # Threshold at which the metrics are computed. For binary classification models this is the positive class threshold. For multi-class classfication models this is the confidence threshold.
+ },
+ "binaryConfusionMatrixList": [ # Binary confusion matrix at multiple thresholds.
+ { # Confusion matrix for binary classification models.
+ "accuracy": 3.14, # The fraction of predictions given the correct label.
+ "f1Score": 3.14, # The equally weighted average of recall and precision.
+ "falseNegatives": "A String", # Number of false samples predicted as false.
+ "falsePositives": "A String", # Number of false samples predicted as true.
+ "positiveClassThreshold": 3.14, # Threshold value used when computing each of the following metric.
+ "precision": 3.14, # The fraction of actual positive predictions that had positive actual labels.
+ "recall": 3.14, # The fraction of actual positive labels that were given a positive prediction.
+ "trueNegatives": "A String", # Number of true samples predicted as false.
+ "truePositives": "A String", # Number of true samples predicted as true.
+ },
+ ],
+ "negativeLabel": "A String", # Label representing the negative class.
+ "positiveLabel": "A String", # Label representing the positive class.
+ },
+ "clusteringMetrics": { # Evaluation metrics for clustering models. # Populated for clustering models.
+ "clusters": [ # Information for all clusters.
+ { # Message containing the information about one cluster.
+ "centroidId": "A String", # Centroid id.
+ "count": "A String", # Count of training data rows that were assigned to this cluster.
+ "featureValues": [ # Values of highly variant features for this cluster.
+ { # Representative value of a single feature within the cluster.
+ "categoricalValue": { # Representative value of a categorical feature. # The categorical feature value.
+ "categoryCounts": [ # Counts of all categories for the categorical feature. If there are more than ten categories, we return top ten (by count) and return one more CategoryCount with category "_OTHER_" and count as aggregate counts of remaining categories.
+ { # Represents the count of a single category within the cluster.
+ "category": "A String", # The name of category.
+ "count": "A String", # The count of training samples matching the category within the cluster.
+ },
+ ],
+ },
+ "featureColumn": "A String", # The feature column name.
+ "numericalValue": 3.14, # The numerical feature value. This is the centroid value for this feature.
+ },
+ ],
+ },
+ ],
+ "daviesBouldinIndex": 3.14, # Davies-Bouldin index.
+ "meanSquaredDistance": 3.14, # Mean of squared distances between each sample to its cluster centroid.
+ },
+ "dimensionalityReductionMetrics": { # Model evaluation metrics for dimensionality reduction models. # Evaluation metrics when the model is a dimensionality reduction model, which currently includes PCA.
+ "totalExplainedVarianceRatio": 3.14, # Total percentage of variance explained by the selected principal components.
+ },
+ "multiClassClassificationMetrics": { # Evaluation metrics for multi-class classification/classifier models. # Populated for multi-class classification/classifier models.
+ "aggregateClassificationMetrics": { # Aggregate metrics for classification/classifier models. For multi-class models, the metrics are either macro-averaged or micro-averaged. When macro-averaged, the metrics are calculated for each label and then an unweighted average is taken of those values. When micro-averaged, the metric is calculated globally by counting the total number of correctly predicted rows. # Aggregate classification metrics.
+ "accuracy": 3.14, # Accuracy is the fraction of predictions given the correct label. For multiclass this is a micro-averaged metric.
+ "f1Score": 3.14, # The F1 score is an average of recall and precision. For multiclass this is a macro-averaged metric.
+ "logLoss": 3.14, # Logarithmic Loss. For multiclass this is a macro-averaged metric.
+ "precision": 3.14, # Precision is the fraction of actual positive predictions that had positive actual labels. For multiclass this is a macro-averaged metric treating each class as a binary classifier.
+ "recall": 3.14, # Recall is the fraction of actual positive labels that were given a positive prediction. For multiclass this is a macro-averaged metric.
+ "rocAuc": 3.14, # Area Under a ROC Curve. For multiclass this is a macro-averaged metric.
+ "threshold": 3.14, # Threshold at which the metrics are computed. For binary classification models this is the positive class threshold. For multi-class classfication models this is the confidence threshold.
+ },
+ "confusionMatrixList": [ # Confusion matrix at different thresholds.
+ { # Confusion matrix for multi-class classification models.
+ "confidenceThreshold": 3.14, # Confidence threshold used when computing the entries of the confusion matrix.
+ "rows": [ # One row per actual label.
+ { # A single row in the confusion matrix.
+ "actualLabel": "A String", # The original label of this row.
+ "entries": [ # Info describing predicted label distribution.
+ { # A single entry in the confusion matrix.
+ "itemCount": "A String", # Number of items being predicted as this label.
+ "predictedLabel": "A String", # The predicted label. For confidence_threshold > 0, we will also add an entry indicating the number of items under the confidence threshold.
+ },
+ ],
+ },
+ ],
+ },
+ ],
+ },
+ "rankingMetrics": { # Evaluation metrics used by weighted-ALS models specified by feedback_type=implicit. # Populated for implicit feedback type matrix factorization models.
+ "averageRank": 3.14, # Determines the goodness of a ranking by computing the percentile rank from the predicted confidence and dividing it by the original rank.
+ "meanAveragePrecision": 3.14, # Calculates a precision per user for all the items by ranking them and then averages all the precisions across all the users.
+ "meanSquaredError": 3.14, # Similar to the mean squared error computed in regression and explicit recommendation models except instead of computing the rating directly, the output from evaluate is computed against a preference which is 1 or 0 depending on if the rating exists or not.
+ "normalizedDiscountedCumulativeGain": 3.14, # A metric to determine the goodness of a ranking calculated from the predicted confidence by comparing it to an ideal rank measured by the original ratings.
+ },
+ "regressionMetrics": { # Evaluation metrics for regression and explicit feedback type matrix factorization models. # Populated for regression models and explicit feedback type matrix factorization models.
+ "meanAbsoluteError": 3.14, # Mean absolute error.
+ "meanSquaredError": 3.14, # Mean squared error.
+ "meanSquaredLogError": 3.14, # Mean squared log error.
+ "medianAbsoluteError": 3.14, # Median absolute error.
+ "rSquared": 3.14, # R^2 score. This corresponds to r2_score in ML.EVALUATE.
+ },
+ },
+ "hparams": { # Options used in model training. # The hyperprameters selected for this trial.
+ "activationFn": "A String", # Activation function of the neural nets.
+ "adjustStepChanges": True or False, # If true, detect step changes and make data adjustment in the input time series.
+ "approxGlobalFeatureContrib": True or False, # Whether to use approximate feature contribution method in XGBoost model explanation for global explain.
+ "autoArima": True or False, # Whether to enable auto ARIMA or not.
+ "autoArimaMaxOrder": "A String", # The max value of the sum of non-seasonal p and q.
+ "autoArimaMinOrder": "A String", # The min value of the sum of non-seasonal p and q.
+ "autoClassWeights": True or False, # Whether to calculate class weights automatically based on the popularity of each label.
+ "batchSize": "A String", # Batch size for dnn models.
+ "boosterType": "A String", # Booster type for boosted tree models.
+ "budgetHours": 3.14, # Budget in hours for AutoML training.
+ "calculatePValues": True or False, # Whether or not p-value test should be computed for this model. Only available for linear and logistic regression models.
+ "categoryEncodingMethod": "A String", # Categorical feature encoding method.
+ "cleanSpikesAndDips": True or False, # If true, clean spikes and dips in the input time series.
+ "colorSpace": "A String", # Enums for color space, used for processing images in Object Table. See more details at https://www.tensorflow.org/io/tutorials/colorspace.
+ "colsampleBylevel": 3.14, # Subsample ratio of columns for each level for boosted tree models.
+ "colsampleBynode": 3.14, # Subsample ratio of columns for each node(split) for boosted tree models.
+ "colsampleBytree": 3.14, # Subsample ratio of columns when constructing each tree for boosted tree models.
+ "dartNormalizeType": "A String", # Type of normalization algorithm for boosted tree models using dart booster.
+ "dataFrequency": "A String", # The data frequency of a time series.
+ "dataSplitColumn": "A String", # The column to split data with. This column won't be used as a feature. 1. When data_split_method is CUSTOM, the corresponding column should be boolean. The rows with true value tag are eval data, and the false are training data. 2. When data_split_method is SEQ, the first DATA_SPLIT_EVAL_FRACTION rows (from smallest to largest) in the corresponding column are used as training data, and the rest are eval data. It respects the order in Orderable data types: https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types#data-type-properties
+ "dataSplitEvalFraction": 3.14, # The fraction of evaluation data over the whole input data. The rest of data will be used as training data. The format should be double. Accurate to two decimal places. Default value is 0.2.
+ "dataSplitMethod": "A String", # The data split type for training and evaluation, e.g. RANDOM.
+ "decomposeTimeSeries": True or False, # If true, perform decompose time series and save the results.
+ "distanceType": "A String", # Distance type for clustering models.
+ "dropout": 3.14, # Dropout probability for dnn models.
+ "earlyStop": True or False, # Whether to stop early when the loss doesn't improve significantly any more (compared to min_relative_progress). Used only for iterative training algorithms.
+ "enableGlobalExplain": True or False, # If true, enable global explanation during training.
+ "feedbackType": "A String", # Feedback type that specifies which algorithm to run for matrix factorization.
+ "fitIntercept": True or False, # Whether the model should include intercept during model training.
+ "hiddenUnits": [ # Hidden units for dnn models.
+ "A String",
+ ],
+ "holidayRegion": "A String", # The geographical region based on which the holidays are considered in time series modeling. If a valid value is specified, then holiday effects modeling is enabled.
+ "holidayRegions": [ # A list of geographical regions that are used for time series modeling.
+ "A String",
+ ],
+ "horizon": "A String", # The number of periods ahead that need to be forecasted.
+ "hparamTuningObjectives": [ # The target evaluation metrics to optimize the hyperparameters for.
+ "A String",
+ ],
+ "includeDrift": True or False, # Include drift when fitting an ARIMA model.
+ "initialLearnRate": 3.14, # Specifies the initial learning rate for the line search learn rate strategy.
+ "inputLabelColumns": [ # Name of input label columns in training data.
+ "A String",
+ ],
+ "instanceWeightColumn": "A String", # Name of the instance weight column for training data. This column isn't be used as a feature.
+ "integratedGradientsNumSteps": "A String", # Number of integral steps for the integrated gradients explain method.
+ "itemColumn": "A String", # Item column specified for matrix factorization models.
+ "kmeansInitializationColumn": "A String", # The column used to provide the initial centroids for kmeans algorithm when kmeans_initialization_method is CUSTOM.
+ "kmeansInitializationMethod": "A String", # The method used to initialize the centroids for kmeans algorithm.
+ "l1RegActivation": 3.14, # L1 regularization coefficient to activations.
+ "l1Regularization": 3.14, # L1 regularization coefficient.
+ "l2Regularization": 3.14, # L2 regularization coefficient.
+ "labelClassWeights": { # Weights associated with each label class, for rebalancing the training data. Only applicable for classification models.
+ "a_key": 3.14,
+ },
+ "learnRate": 3.14, # Learning rate in training. Used only for iterative training algorithms.
+ "learnRateStrategy": "A String", # The strategy to determine learn rate for the current iteration.
+ "lossType": "A String", # Type of loss function used during training run.
+ "maxIterations": "A String", # The maximum number of iterations in training. Used only for iterative training algorithms.
+ "maxParallelTrials": "A String", # Maximum number of trials to run in parallel.
+ "maxTimeSeriesLength": "A String", # The maximum number of time points in a time series that can be used in modeling the trend component of the time series. Don't use this option with the `timeSeriesLengthFraction` or `minTimeSeriesLength` options.
+ "maxTreeDepth": "A String", # Maximum depth of a tree for boosted tree models.
+ "minRelativeProgress": 3.14, # When early_stop is true, stops training when accuracy improvement is less than 'min_relative_progress'. Used only for iterative training algorithms.
+ "minSplitLoss": 3.14, # Minimum split loss for boosted tree models.
+ "minTimeSeriesLength": "A String", # The minimum number of time points in a time series that are used in modeling the trend component of the time series. If you use this option you must also set the `timeSeriesLengthFraction` option. This training option ensures that enough time points are available when you use `timeSeriesLengthFraction` in trend modeling. This is particularly important when forecasting multiple time series in a single query using `timeSeriesIdColumn`. If the total number of time points is less than the `minTimeSeriesLength` value, then the query uses all available time points.
+ "minTreeChildWeight": "A String", # Minimum sum of instance weight needed in a child for boosted tree models.
+ "modelRegistry": "A String", # The model registry.
+ "modelUri": "A String", # Google Cloud Storage URI from which the model was imported. Only applicable for imported models.
+ "nonSeasonalOrder": { # Arima order, can be used for both non-seasonal and seasonal parts. # A specification of the non-seasonal part of the ARIMA model: the three components (p, d, q) are the AR order, the degree of differencing, and the MA order.
+ "d": "A String", # Order of the differencing part.
+ "p": "A String", # Order of the autoregressive part.
+ "q": "A String", # Order of the moving-average part.
+ },
+ "numClusters": "A String", # Number of clusters for clustering models.
+ "numFactors": "A String", # Num factors specified for matrix factorization models.
+ "numParallelTree": "A String", # Number of parallel trees constructed during each iteration for boosted tree models.
+ "numPrincipalComponents": "A String", # Number of principal components to keep in the PCA model. Must be <= the number of features.
+ "numTrials": "A String", # Number of trials to run this hyperparameter tuning job.
+ "optimizationStrategy": "A String", # Optimization strategy for training linear regression models.
+ "optimizer": "A String", # Optimizer used for training the neural nets.
+ "pcaExplainedVarianceRatio": 3.14, # The minimum ratio of cumulative explained variance that needs to be given by the PCA model.
+ "pcaSolver": "A String", # The solver for PCA.
+ "sampledShapleyNumPaths": "A String", # Number of paths for the sampled Shapley explain method.
+ "scaleFeatures": True or False, # If true, scale the feature values by dividing the feature standard deviation. Currently only apply to PCA.
+ "standardizeFeatures": True or False, # Whether to standardize numerical features. Default to true.
+ "subsample": 3.14, # Subsample fraction of the training data to grow tree to prevent overfitting for boosted tree models.
+ "tfVersion": "A String", # Based on the selected TF version, the corresponding docker image is used to train external models.
+ "timeSeriesDataColumn": "A String", # Column to be designated as time series data for ARIMA model.
+ "timeSeriesIdColumn": "A String", # The time series id column that was used during ARIMA model training.
+ "timeSeriesIdColumns": [ # The time series id columns that were used during ARIMA model training.
+ "A String",
+ ],
+ "timeSeriesLengthFraction": 3.14, # The fraction of the interpolated length of the time series that's used to model the time series trend component. All of the time points of the time series are used to model the non-trend component. This training option accelerates modeling training without sacrificing much forecasting accuracy. You can use this option with `minTimeSeriesLength` but not with `maxTimeSeriesLength`.
+ "timeSeriesTimestampColumn": "A String", # Column to be designated as time series timestamp for ARIMA model.
+ "treeMethod": "A String", # Tree construction algorithm for boosted tree models.
+ "trendSmoothingWindowSize": "A String", # Smoothing window size for the trend component. When a positive value is specified, a center moving average smoothing is applied on the history trend. When the smoothing window is out of the boundary at the beginning or the end of the trend, the first element or the last element is padded to fill the smoothing window before the average is applied.
+ "userColumn": "A String", # User column specified for matrix factorization models.
+ "vertexAiModelVersionAliases": [ # The version aliases to apply in Vertex AI model registry. Always overwrite if the version aliases exists in a existing model.
+ "A String",
+ ],
+ "walsAlpha": 3.14, # Hyperparameter for matrix factoration when implicit feedback type is specified.
+ "warmStart": True or False, # Whether to train a model from the last checkpoint.
+ "xgboostVersion": "A String", # User-selected XGBoost versions for training of XGBoost models.
+ },
+ "startTimeMs": "A String", # Starting time of the trial.
+ "status": "A String", # The status of the trial.
+ "trainingLoss": 3.14, # Loss computed on the training data at the end of trial.
+ "trialId": "A String", # 1-based index of the trial.
+ },
+ ],
+ "iterationResults": [ # Results for all completed iterations. Empty for [hyperparameter tuning jobs](/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview).
+ { # Information about a single iteration of the training run.
+ "arimaResult": { # (Auto-)arima fitting result. Wrap everything in ArimaResult for easier refactoring if we want to use model-specific iteration results. # Arima result.
+ "arimaModelInfo": [ # This message is repeated because there are multiple arima models fitted in auto-arima. For non-auto-arima model, its size is one.
+ { # Arima model information.
+ "arimaCoefficients": { # Arima coefficients. # Arima coefficients.
+ "autoRegressiveCoefficients": [ # Auto-regressive coefficients, an array of double.
+ 3.14,
+ ],
+ "interceptCoefficient": 3.14, # Intercept coefficient, just a double not an array.
+ "movingAverageCoefficients": [ # Moving-average coefficients, an array of double.
+ 3.14,
+ ],
+ },
+ "arimaFittingMetrics": { # ARIMA model fitting metrics. # Arima fitting metrics.
+ "aic": 3.14, # AIC.
+ "logLikelihood": 3.14, # Log-likelihood.
+ "variance": 3.14, # Variance.
+ },
+ "hasDrift": True or False, # Whether Arima model fitted with drift or not. It is always false when d is not 1.
+ "hasHolidayEffect": True or False, # If true, holiday_effect is a part of time series decomposition result.
+ "hasSpikesAndDips": True or False, # If true, spikes_and_dips is a part of time series decomposition result.
+ "hasStepChanges": True or False, # If true, step_changes is a part of time series decomposition result.
+ "nonSeasonalOrder": { # Arima order, can be used for both non-seasonal and seasonal parts. # Non-seasonal order.
+ "d": "A String", # Order of the differencing part.
+ "p": "A String", # Order of the autoregressive part.
+ "q": "A String", # Order of the moving-average part.
+ },
+ "seasonalPeriods": [ # Seasonal periods. Repeated because multiple periods are supported for one time series.
+ "A String",
+ ],
+ "timeSeriesId": "A String", # The time_series_id value for this time series. It will be one of the unique values from the time_series_id_column specified during ARIMA model training. Only present when time_series_id_column training option was used.
+ "timeSeriesIds": [ # The tuple of time_series_ids identifying this time series. It will be one of the unique tuples of values present in the time_series_id_columns specified during ARIMA model training. Only present when time_series_id_columns training option was used and the order of values here are same as the order of time_series_id_columns.
+ "A String",
+ ],
+ },
+ ],
+ "seasonalPeriods": [ # Seasonal periods. Repeated because multiple periods are supported for one time series.
+ "A String",
+ ],
+ },
+ "clusterInfos": [ # Information about top clusters for clustering models.
+ { # Information about a single cluster for clustering model.
+ "centroidId": "A String", # Centroid id.
+ "clusterRadius": 3.14, # Cluster radius, the average distance from centroid to each point assigned to the cluster.
+ "clusterSize": "A String", # Cluster size, the total number of points assigned to the cluster.
+ },
+ ],
"durationMs": "A String", # Time taken to run the iteration in milliseconds.
"evalLoss": 3.14, # Loss computed on the eval data at the end of iteration.
"index": 42, # Index of the iteration, 0 based.
"learnRate": 3.14, # Learn rate used for this iteration.
+ "principalComponentInfos": [ # The information of the principal components.
+ { # Principal component infos, used only for eigen decomposition based models, e.g., PCA. Ordered by explained_variance in the descending order.
+ "cumulativeExplainedVarianceRatio": 3.14, # The explained_variance is pre-ordered in the descending order to compute the cumulative explained variance ratio.
+ "explainedVariance": 3.14, # Explained variance by this principal component, which is simply the eigenvalue.
+ "explainedVarianceRatio": 3.14, # Explained_variance over the total explained variance.
+ "principalComponentId": "A String", # Id of the principal component.
+ },
+ ],
"trainingLoss": 3.14, # Loss computed on the training data at the end of iteration.
},
],
- "maxIterations": "A String", # Maximum number of iterations specified as max_iterations in the 'CREATE MODEL' query. The actual number of iterations may be less than this number due to early stop.
+ "maxIterations": "A String", # Output only. Maximum number of iterations specified as max_iterations in the 'CREATE MODEL' query. The actual number of iterations may be less than this number due to early stop.
+ "modelType": "A String", # Output only. The type of the model that is being trained.
+ "trainingType": "A String", # Output only. Training type of the job.
},
- "modelTraining": { # [Output only, Beta] Information about create model query job progress.
- "currentIteration": 42, # [Output-only, Beta] Index of current ML training iteration. Updated during create model query job to show job progress.
- "expectedTotalIterations": "A String", # [Output-only, Beta] Expected number of iterations for the create model query job specified as num_iterations in the input query. The actual total number of iterations may be less than this number due to early stop.
+ "modelTraining": { # Deprecated.
+ "currentIteration": 42, # Deprecated.
+ "expectedTotalIterations": "A String", # Deprecated.
},
- "modelTrainingCurrentIteration": 42, # [Output only, Beta] Deprecated; do not use.
- "modelTrainingExpectedTotalIteration": "A String", # [Output only, Beta] Deprecated; do not use.
- "numDmlAffectedRows": "A String", # [Output only] The number of rows affected by a DML statement. Present only for DML statements INSERT, UPDATE or DELETE.
- "queryPlan": [ # [Output only] Describes execution plan for the query.
- {
+ "modelTrainingCurrentIteration": 42, # Deprecated.
+ "modelTrainingExpectedTotalIteration": "A String", # Deprecated.
+ "numDmlAffectedRows": "A String", # Output only. The number of rows affected by a DML statement. Present only for DML statements INSERT, UPDATE or DELETE.
+ "performanceInsights": { # Performance insights for the job. # Output only. Performance insights.
+ "avgPreviousExecutionMs": "A String", # Output only. Average execution ms of previous runs. Indicates the job ran slow compared to previous executions. To find previous executions, use INFORMATION_SCHEMA tables and filter jobs with same query hash.
+ "stagePerformanceChangeInsights": [ # Output only. Query stage performance insights compared to previous runs, for diagnosing performance regression.
+ { # Performance insights compared to the previous executions for a specific stage.
+ "inputDataChange": { # Details about the input data change insight. # Output only. Input data change insight of the query stage.
+ "recordsReadDiffPercentage": 3.14, # Output only. Records read difference percentage compared to a previous run.
+ },
+ "stageId": "A String", # Output only. The stage id that the insight mapped to.
+ },
+ ],
+ "stagePerformanceStandaloneInsights": [ # Output only. Standalone query stage performance insights, for exploring potential improvements.
+ { # Standalone performance insights for a specific stage.
+ "biEngineReasons": [ # Output only. If present, the stage had the following reasons for being disqualified from BI Engine execution.
+ { # Reason why BI Engine didn't accelerate the query (or sub-query).
+ "code": "A String", # Output only. High-level BI Engine reason for partial or disabled acceleration
+ "message": "A String", # Output only. Free form human-readable reason for partial or disabled acceleration.
+ },
+ ],
+ "highCardinalityJoins": [ # Output only. High cardinality joins in the stage.
+ { # High cardinality join detailed information.
+ "leftRows": "A String", # Output only. Count of left input rows.
+ "outputRows": "A String", # Output only. Count of the output rows.
+ "rightRows": "A String", # Output only. Count of right input rows.
+ "stepIndex": 42, # Output only. The index of the join operator in the ExplainQueryStep lists.
+ },
+ ],
+ "insufficientShuffleQuota": True or False, # Output only. True if the stage has insufficient shuffle quota.
+ "slotContention": True or False, # Output only. True if the stage has a slot contention issue.
+ "stageId": "A String", # Output only. The stage id that the insight mapped to.
+ },
+ ],
+ },
+ "queryInfo": { # Query optimization information for a QUERY job. # Output only. Query optimization information for a QUERY job.
+ "optimizationDetails": { # Output only. Information about query optimizations.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "queryPlan": [ # Output only. Describes execution plan for the query.
+ { # A single stage of query execution.
"completedParallelInputs": "A String", # Number of parallel input segments completed.
+ "computeMode": "A String", # Output only. Compute mode for this stage.
"computeMsAvg": "A String", # Milliseconds the average shard spent on CPU-bound tasks.
"computeMsMax": "A String", # Milliseconds the slowest shard spent on CPU-bound tasks.
"computeRatioAvg": 3.14, # Relative amount of time the average shard spent on CPU-bound tasks.
"computeRatioMax": 3.14, # Relative amount of time the slowest shard spent on CPU-bound tasks.
- "endMs": "A String", # Stage end time represented as milliseconds since epoch.
- "id": "A String", # Unique ID for stage within plan.
+ "endMs": "A String", # Stage end time represented as milliseconds since the epoch.
+ "id": "A String", # Unique ID for the stage within the plan.
"inputStages": [ # IDs for stages that are inputs to this stage.
"A String",
],
- "name": "A String", # Human-readable name for stage.
- "parallelInputs": "A String", # Number of parallel input segments to be processed.
+ "name": "A String", # Human-readable name for the stage.
+ "parallelInputs": "A String", # Number of parallel input segments to be processed
"readMsAvg": "A String", # Milliseconds the average shard spent reading input.
"readMsMax": "A String", # Milliseconds the slowest shard spent reading input.
"readRatioAvg": 3.14, # Relative amount of time the average shard spent reading input.
@@ -3592,12 +6773,12 @@ Method Details
"shuffleOutputBytes": "A String", # Total number of bytes written to shuffle.
"shuffleOutputBytesSpilled": "A String", # Total number of bytes written to shuffle and spilled to disk.
"slotMs": "A String", # Slot-milliseconds used by the stage.
- "startMs": "A String", # Stage start time represented as milliseconds since epoch.
- "status": "A String", # Current status for the stage.
+ "startMs": "A String", # Stage start time represented as milliseconds since the epoch.
+ "status": "A String", # Current status for this stage.
"steps": [ # List of operations within the stage in dependency order (approximately chronological).
- {
+ { # An operation within a stage.
"kind": "A String", # Machine-readable operation type.
- "substeps": [ # Human-readable stage descriptions.
+ "substeps": [ # Human-readable description of the step(s).
"A String",
],
},
@@ -3612,190 +6793,210 @@ Method Details
"writeRatioMax": 3.14, # Relative amount of time the slowest shard spent on writing output.
},
],
- "referencedRoutines": [ # [Output only] Referenced routines (persistent user-defined functions and stored procedures) for the job.
- {
+ "referencedRoutines": [ # Output only. Referenced routines for the job.
+ { # Id path of a routine.
"datasetId": "A String", # Required. The ID of the dataset containing this routine.
"projectId": "A String", # Required. The ID of the project containing this routine.
"routineId": "A String", # Required. The ID of the routine. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 256 characters.
},
],
- "referencedTables": [ # [Output only] Referenced tables for the job. Queries that reference more than 50 tables will not have a complete list.
+ "referencedTables": [ # Output only. Referenced tables for the job. Queries that reference more than 50 tables will not have a complete list.
{
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
],
- "reservationUsage": [ # [Output only] Job resource usage breakdown by reservation.
- {
- "name": "A String", # [Output only] Reservation name or "unreserved" for on-demand resources usage.
- "slotMs": "A String", # [Output only] Slot-milliseconds the job spent in the given reservation.
+ "reservationUsage": [ # Output only. Job resource usage breakdown by reservation. This field reported misleading information and will no longer be populated.
+ { # Job resource usage breakdown by reservation.
+ "name": "A String", # Reservation name or "unreserved" for on-demand resources usage.
+ "slotMs": "A String", # Total slot milliseconds used by the reservation for a particular job.
},
],
- "schema": { # [Output only] The schema of the results. Present only for successful dry run of non-legacy SQL queries.
+ "schema": { # Schema of a table # Output only. The schema of the results. Present only for successful dry run of non-legacy SQL queries.
"fields": [ # Describes the fields in a table.
- {
- "categories": { # [Optional] The categories attached to this field, used for field-level access control.
- "names": [ # A list of category resource names. For example, "projects/1/taxonomies/2/categories/3". At most 5 categories are allowed.
+ { # A field in TableSchema
+ "categories": { # Deprecated.
+ "names": [ # Deprecated.
"A String",
],
},
- "collation": "A String", # Optional. Collation specification of the field. It only can be set on string type field.
- "defaultValueExpression": "A String", # Optional. A SQL expression to specify the default value for this field. It can only be set for top level fields (columns). You can use struct or array expression to specify default value for the entire struct or array. The valid SQL expressions are: - Literals for all data types, including STRUCT and ARRAY. - Following functions: - CURRENT_TIMESTAMP - CURRENT_TIME - CURRENT_DATE - CURRENT_DATETIME - GENERATE_UUID - RAND - SESSION_USER - ST_GEOGPOINT - Struct or array composed with the above allowed functions, for example, [CURRENT_DATE(), DATE '2020-01-01']
- "description": "A String", # [Optional] The field description. The maximum length is 1,024 characters.
- "fields": [ # [Optional] Describes the nested schema fields if the type property is set to RECORD.
+ "collation": "A String", # Optional. Field collation can be set only when the type of field is STRING. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.
+ "defaultValueExpression": "A String", # Optional. A SQL expression to specify the [default value] (https://cloud.google.com/bigquery/docs/default-values) for this field.
+ "description": "A String", # Optional. The field description. The maximum length is 1,024 characters.
+ "fields": [ # Optional. Describes the nested schema fields if the type property is set to RECORD.
# Object with schema name: TableFieldSchema
],
- "maxLength": "A String", # [Optional] Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
- "mode": "A String", # [Optional] The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
- "name": "A String", # [Required] The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
- "policyTags": {
- "names": [ # A list of category resource names. For example, "projects/1/location/eu/taxonomies/2/policyTags/3". At most 1 policy tag is allowed.
+ "maxLength": "A String", # Optional. Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
+ "mode": "A String", # Optional. The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
+ "name": "A String", # Required. The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
+ "policyTags": { # Optional. The policy tags attached to this field, used for field-level access control. If not set, defaults to empty policy_tags.
+ "names": [ # A list of policy tag resource names. For example, "projects/1/locations/eu/taxonomies/2/policyTags/3". At most 1 policy tag is currently allowed.
"A String",
],
},
- "precision": "A String", # [Optional] Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: - Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] - Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: - If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. - If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): - If type = "NUMERIC": 1 ≤ precision ≤ 29. - If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
- "rangeElementType": { # Optional. The subtype of the RANGE, if the type of this field is RANGE. If the type is RANGE, this field is required. Possible values for the field element type of a RANGE include: - DATE - DATETIME - TIMESTAMP
- "type": "A String", # The field element type of a RANGE
+ "precision": "A String", # Optional. Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: * Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] * Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: * If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. * If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): * If type = "NUMERIC": 1 ≤ precision ≤ 29. * If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
+ "rangeElementType": { # Represents the type of a field element.
+ "type": "A String", # Required. The type of a field element. See TableFieldSchema.type.
},
- "roundingMode": "A String", # Optional. Rounding Mode specification of the field. It only can be set on NUMERIC or BIGNUMERIC type fields.
- "scale": "A String", # [Optional] See documentation for precision.
- "type": "A String", # [Required] The field data type. Possible values include STRING, BYTES, INTEGER, INT64 (same as INTEGER), FLOAT, FLOAT64 (same as FLOAT), NUMERIC, BIGNUMERIC, BOOLEAN, BOOL (same as BOOLEAN), TIMESTAMP, DATE, TIME, DATETIME, INTERVAL, RECORD (where RECORD indicates that the field contains a nested schema) or STRUCT (same as RECORD).
+ "roundingMode": "A String", # Optional. Specifies the rounding mode to be used when storing values of NUMERIC and BIGNUMERIC type.
+ "scale": "A String", # Optional. See documentation for precision.
+ "type": "A String", # Required. The field data type. Possible values include: * STRING * BYTES * INTEGER (or INT64) * FLOAT (or FLOAT64) * BOOLEAN (or BOOL) * TIMESTAMP * DATE * TIME * DATETIME * GEOGRAPHY * NUMERIC * BIGNUMERIC * JSON * RECORD (or STRUCT) Use of RECORD/STRUCT indicates that the field contains a nested schema.
},
],
},
- "searchStatistics": { # [Output only] Search query specific statistics.
- "indexUnusedReasons": [ # When index_usage_mode is UNUSED or PARTIALLY_USED, this field explains why index was not used in all or part of the search query. If index_usage_mode is FULLLY_USED, this field is not populated.
- {
- "baseTable": { # [Output-only] Specifies the base table involved in the reason that no search index was used.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "searchStatistics": { # Statistics for a search query. Populated as part of JobStatistics2. # Output only. Search query specific statistics.
+ "indexUnusedReasons": [ # When `indexUsageMode` is `UNUSED` or `PARTIALLY_USED`, this field explains why indexes were not used in all or part of the search query. If `indexUsageMode` is `FULLY_USED`, this field is not populated.
+ { # Reason about why no search index was used in the search query (or sub-query).
+ "baseTable": { # Specifies the base table involved in the reason that no search index was used.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
- "code": "$(reason.code)", # [Output-only] Specifies the high-level reason for the scenario when no search index was used.
- "indexName": "$(reason.index_name)", # [Output-only] Specifies the name of the unused search index, if available.
- "message": "$(reason.message)", # [Output-only] Free form human-readable reason for the scenario when no search index was used.
+ "code": "A String", # Specifies the high-level reason for the scenario when no search index was used.
+ "indexName": "A String", # Specifies the name of the unused search index, if available.
+ "message": "A String", # Free form human-readable reason for the scenario when no search index was used.
},
],
- "indexUsageMode": "A String", # Specifies index usage mode for the query.
+ "indexUsageMode": "A String", # Specifies the index usage mode for the query.
},
- "sparkStatistics": { # [Output only] Statistics of a Spark procedure job.
- "endpoints": { # [Output-only] Endpoints generated for the Spark job.
+ "sparkStatistics": { # Statistics for a BigSpark query. Populated as part of JobStatistics2 # Output only. Statistics of a Spark procedure job.
+ "endpoints": { # Output only. Endpoints returned from Dataproc. Key list: - history_server_endpoint: A link to Spark job UI.
"a_key": "A String",
},
- "loggingInfo": { # [Output-only] Logging info is used to generate a link to Cloud Logging.
- "projectId": "A String", # [Output-only] Project ID used for logging
- "resourceType": "A String", # [Output-only] Resource type used for logging
+ "gcsStagingBucket": "A String", # Output only. The Google Cloud Storage bucket that is used as the default filesystem by the Spark application. This fields is only filled when the Spark procedure uses the INVOKER security mode. It is inferred from the system variable @@spark_proc_properties.staging_bucket if it is provided. Otherwise, BigQuery creates a default staging bucket for the job and returns the bucket name in this field. Example: * `gs://[bucket_name]`
+ "kmsKeyName": "A String", # Output only. The Cloud KMS encryption key that is used to protect the resources created by the Spark job. If the Spark procedure uses DEFINER security mode, the Cloud KMS key is inferred from the Spark connection associated with the procedure if it is provided. Otherwise the key is inferred from the default key of the Spark connection's project if the CMEK organization policy is enforced. If the Spark procedure uses INVOKER security mode, the Cloud KMS encryption key is inferred from the system variable @@spark_proc_properties.kms_key_name if it is provided. Otherwise, the key is inferred fromt he default key of the BigQuery job's project if the CMEK organization policy is enforced. Example: * `projects/[kms_project_id]/locations/[region]/keyRings/[key_region]/cryptoKeys/[key]`
+ "loggingInfo": { # Spark job logs can be filtered by these fields in Cloud Logging. # Output only. Logging info is used to generate a link to Cloud Logging.
+ "projectId": "A String", # Output only. Project ID where the Spark logs were written.
+ "resourceType": "A String", # Output only. Resource type used for logging.
},
- "sparkJobId": "A String", # [Output-only] Spark job id if a Spark job is created successfully.
- "sparkJobLocation": "A String", # [Output-only] Location where the Spark job is executed.
+ "sparkJobId": "A String", # Output only. Spark job ID if a Spark job is created successfully.
+ "sparkJobLocation": "A String", # Output only. Location where the Spark job is executed. A location is selected by BigQueury for jobs configured to run in a multi-region.
},
- "statementType": "A String", # The type of query statement, if valid. Possible values (new values might be added in the future): "SELECT": SELECT query. "INSERT": INSERT query; see https://cloud.google.com/bigquery/docs/reference/standard-sql/data-manipulation-language. "UPDATE": UPDATE query; see https://cloud.google.com/bigquery/docs/reference/standard-sql/data-manipulation-language. "DELETE": DELETE query; see https://cloud.google.com/bigquery/docs/reference/standard-sql/data-manipulation-language. "MERGE": MERGE query; see https://cloud.google.com/bigquery/docs/reference/standard-sql/data-manipulation-language. "ALTER_TABLE": ALTER TABLE query. "ALTER_VIEW": ALTER VIEW query. "ASSERT": ASSERT condition AS 'description'. "CREATE_FUNCTION": CREATE FUNCTION query. "CREATE_MODEL": CREATE [OR REPLACE] MODEL ... AS SELECT ... . "CREATE_PROCEDURE": CREATE PROCEDURE query. "CREATE_TABLE": CREATE [OR REPLACE] TABLE without AS SELECT. "CREATE_TABLE_AS_SELECT": CREATE [OR REPLACE] TABLE ... AS SELECT ... . "CREATE_VIEW": CREATE [OR REPLACE] VIEW ... AS SELECT ... . "DROP_FUNCTION" : DROP FUNCTION query. "DROP_PROCEDURE": DROP PROCEDURE query. "DROP_TABLE": DROP TABLE query. "DROP_VIEW": DROP VIEW query.
- "timeline": [ # [Output only] [Beta] Describes a timeline of job execution.
- {
- "activeUnits": "A String", # Total number of units currently being processed by workers. This does not correspond directly to slot usage. This is the largest value observed since the last sample.
+ "statementType": "A String", # Output only. The type of query statement, if valid. Possible values: * `SELECT`: [`SELECT`](/bigquery/docs/reference/standard-sql/query-syntax#select_list) statement. * `ASSERT`: [`ASSERT`](/bigquery/docs/reference/standard-sql/debugging-statements#assert) statement. * `INSERT`: [`INSERT`](/bigquery/docs/reference/standard-sql/dml-syntax#insert_statement) statement. * `UPDATE`: [`UPDATE`](/bigquery/docs/reference/standard-sql/query-syntax#update_statement) statement. * `DELETE`: [`DELETE`](/bigquery/docs/reference/standard-sql/data-manipulation-language) statement. * `MERGE`: [`MERGE`](/bigquery/docs/reference/standard-sql/data-manipulation-language) statement. * `CREATE_TABLE`: [`CREATE TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#create_table_statement) statement, without `AS SELECT`. * `CREATE_TABLE_AS_SELECT`: [`CREATE TABLE AS SELECT`](/bigquery/docs/reference/standard-sql/data-definition-language#query_statement) statement. * `CREATE_VIEW`: [`CREATE VIEW`](/bigquery/docs/reference/standard-sql/data-definition-language#create_view_statement) statement. * `CREATE_MODEL`: [`CREATE MODEL`](/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-create#create_model_statement) statement. * `CREATE_MATERIALIZED_VIEW`: [`CREATE MATERIALIZED VIEW`](/bigquery/docs/reference/standard-sql/data-definition-language#create_materialized_view_statement) statement. * `CREATE_FUNCTION`: [`CREATE FUNCTION`](/bigquery/docs/reference/standard-sql/data-definition-language#create_function_statement) statement. * `CREATE_TABLE_FUNCTION`: [`CREATE TABLE FUNCTION`](/bigquery/docs/reference/standard-sql/data-definition-language#create_table_function_statement) statement. * `CREATE_PROCEDURE`: [`CREATE PROCEDURE`](/bigquery/docs/reference/standard-sql/data-definition-language#create_procedure) statement. * `CREATE_ROW_ACCESS_POLICY`: [`CREATE ROW ACCESS POLICY`](/bigquery/docs/reference/standard-sql/data-definition-language#create_row_access_policy_statement) statement. * `CREATE_SCHEMA`: [`CREATE SCHEMA`](/bigquery/docs/reference/standard-sql/data-definition-language#create_schema_statement) statement. * `CREATE_SNAPSHOT_TABLE`: [`CREATE SNAPSHOT TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#create_snapshot_table_statement) statement. * `CREATE_SEARCH_INDEX`: [`CREATE SEARCH INDEX`](/bigquery/docs/reference/standard-sql/data-definition-language#create_search_index_statement) statement. * `DROP_TABLE`: [`DROP TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_table_statement) statement. * `DROP_EXTERNAL_TABLE`: [`DROP EXTERNAL TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_external_table_statement) statement. * `DROP_VIEW`: [`DROP VIEW`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_view_statement) statement. * `DROP_MODEL`: [`DROP MODEL`](/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-drop-model) statement. * `DROP_MATERIALIZED_VIEW`: [`DROP MATERIALIZED VIEW`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_materialized_view_statement) statement. * `DROP_FUNCTION` : [`DROP FUNCTION`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_function_statement) statement. * `DROP_TABLE_FUNCTION` : [`DROP TABLE FUNCTION`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_table_function) statement. * `DROP_PROCEDURE`: [`DROP PROCEDURE`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_procedure_statement) statement. * `DROP_SEARCH_INDEX`: [`DROP SEARCH INDEX`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_search_index) statement. * `DROP_SCHEMA`: [`DROP SCHEMA`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_schema_statement) statement. * `DROP_SNAPSHOT_TABLE`: [`DROP SNAPSHOT TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_snapshot_table_statement) statement. * `DROP_ROW_ACCESS_POLICY`: [`DROP [ALL] ROW ACCESS POLICY|POLICIES`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_row_access_policy_statement) statement. * `ALTER_TABLE`: [`ALTER TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#alter_table_set_options_statement) statement. * `ALTER_VIEW`: [`ALTER VIEW`](/bigquery/docs/reference/standard-sql/data-definition-language#alter_view_set_options_statement) statement. * `ALTER_MATERIALIZED_VIEW`: [`ALTER MATERIALIZED VIEW`](/bigquery/docs/reference/standard-sql/data-definition-language#alter_materialized_view_set_options_statement) statement. * `ALTER_SCHEMA`: [`ALTER SCHEMA`](/bigquery/docs/reference/standard-sql/data-definition-language#aalter_schema_set_options_statement) statement. * `SCRIPT`: [`SCRIPT`](/bigquery/docs/reference/standard-sql/procedural-language). * `TRUNCATE_TABLE`: [`TRUNCATE TABLE`](/bigquery/docs/reference/standard-sql/dml-syntax#truncate_table_statement) statement. * `CREATE_EXTERNAL_TABLE`: [`CREATE EXTERNAL TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#create_external_table_statement) statement. * `EXPORT_DATA`: [`EXPORT DATA`](/bigquery/docs/reference/standard-sql/other-statements#export_data_statement) statement. * `EXPORT_MODEL`: [`EXPORT MODEL`](/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-export-model) statement. * `LOAD_DATA`: [`LOAD DATA`](/bigquery/docs/reference/standard-sql/other-statements#load_data_statement) statement. * `CALL`: [`CALL`](/bigquery/docs/reference/standard-sql/procedural-language#call) statement.
+ "timeline": [ # Output only. Describes a timeline of job execution.
+ { # Summary of the state of query execution at a given time.
+ "activeUnits": "A String", # Total number of active workers. This does not correspond directly to slot usage. This is the largest value observed since the last sample.
"completedUnits": "A String", # Total parallel units of work completed by this query.
"elapsedMs": "A String", # Milliseconds elapsed since the start of query execution.
- "estimatedRunnableUnits": "A String", # Units of work that can be scheduled immediately. Providing additional slots for these units of work will speed up the query, provided no other query in the reservation needs additional slots.
+ "estimatedRunnableUnits": "A String", # Units of work that can be scheduled immediately. Providing additional slots for these units of work will accelerate the query, if no other query in the reservation needs additional slots.
"pendingUnits": "A String", # Total units of work remaining for the query. This number can be revised (increased or decreased) while the query is running.
"totalSlotMs": "A String", # Cumulative slot-ms consumed by the query.
},
],
- "totalBytesBilled": "A String", # [Output only] Total bytes billed for the job.
- "totalBytesProcessed": "A String", # [Output only] Total bytes processed for the job.
- "totalBytesProcessedAccuracy": "A String", # [Output only] For dry-run jobs, totalBytesProcessed is an estimate and this field specifies the accuracy of the estimate. Possible values can be: UNKNOWN: accuracy of the estimate is unknown. PRECISE: estimate is precise. LOWER_BOUND: estimate is lower bound of what the query would cost. UPPER_BOUND: estimate is upper bound of what the query would cost.
- "totalPartitionsProcessed": "A String", # [Output only] Total number of partitions processed from all partitioned tables referenced in the job.
- "totalSlotMs": "A String", # [Output only] Slot-milliseconds for the job.
- "transferredBytes": "A String", # [Output-only] Total bytes transferred for cross-cloud queries such as Cross Cloud Transfer and CREATE TABLE AS SELECT (CTAS).
- "undeclaredQueryParameters": [ # Standard SQL only: list of undeclared query parameters detected during a dry run validation.
- {
- "name": "A String", # [Optional] If unset, this is a positional parameter. Otherwise, should be unique within a query.
- "parameterType": { # [Required] The type of this parameter.
- "arrayType": # Object with schema name: QueryParameterType # [Optional] The type of the array's elements, if this is an array.
- "rangeElementType": # Object with schema name: QueryParameterType # [Optional] The element type of the range, if this is a range.
- "structTypes": [ # [Optional] The types of the fields of this struct, in order, if this is a struct.
- {
- "description": "A String", # [Optional] Human-oriented description of the field.
- "name": "A String", # [Optional] The name of this field.
- "type": # Object with schema name: QueryParameterType # [Required] The type of this field.
+ "totalBytesBilled": "A String", # Output only. If the project is configured to use on-demand pricing, then this field contains the total bytes billed for the job. If the project is configured to use flat-rate pricing, then you are not billed for bytes and this field is informational only.
+ "totalBytesProcessed": "A String", # Output only. Total bytes processed for the job.
+ "totalBytesProcessedAccuracy": "A String", # Output only. For dry-run jobs, totalBytesProcessed is an estimate and this field specifies the accuracy of the estimate. Possible values can be: UNKNOWN: accuracy of the estimate is unknown. PRECISE: estimate is precise. LOWER_BOUND: estimate is lower bound of what the query would cost. UPPER_BOUND: estimate is upper bound of what the query would cost.
+ "totalPartitionsProcessed": "A String", # Output only. Total number of partitions processed from all partitioned tables referenced in the job.
+ "totalSlotMs": "A String", # Output only. Slot-milliseconds for the job.
+ "transferredBytes": "A String", # Output only. Total bytes transferred for cross-cloud queries such as Cross Cloud Transfer and CREATE TABLE AS SELECT (CTAS).
+ "undeclaredQueryParameters": [ # Output only. GoogleSQL only: list of undeclared query parameters detected during a dry run validation.
+ { # A parameter given to a query.
+ "name": "A String", # Optional. If unset, this is a positional parameter. Otherwise, should be unique within a query.
+ "parameterType": { # The type of a query parameter. # Required. The type of this parameter.
+ "arrayType": # Object with schema name: QueryParameterType # Optional. The type of the array's elements, if this is an array.
+ "rangeElementType": # Object with schema name: QueryParameterType # Optional. The element type of the range, if this is a range.
+ "structTypes": [ # Optional. The types of the fields of this struct, in order, if this is a struct.
+ { # The type of a struct parameter.
+ "description": "A String", # Optional. Human-oriented description of the field.
+ "name": "A String", # Optional. The name of this field.
+ "type": # Object with schema name: QueryParameterType # Required. The type of this field.
},
],
- "type": "A String", # [Required] The top level type of this field.
+ "type": "A String", # Required. The top level type of this field.
},
- "parameterValue": { # [Required] The value of this parameter.
- "arrayValues": [ # [Optional] The array values, if this is an array type.
+ "parameterValue": { # The value of a query parameter. # Required. The value of this parameter.
+ "arrayValues": [ # Optional. The array values, if this is an array type.
# Object with schema name: QueryParameterValue
],
- "rangeValue": { # [Optional] The range value, if this is a range type.
- "end": # Object with schema name: QueryParameterValue
- "start": # Object with schema name: QueryParameterValue
+ "rangeValue": { # Represents the value of a range. # Optional. The range value, if this is a range type.
+ "end": # Object with schema name: QueryParameterValue # Optional. The end value of the range. A missing value represents an unbounded end.
+ "start": # Object with schema name: QueryParameterValue # Optional. The start value of the range. A missing value represents an unbounded start.
},
- "structValues": { # [Optional] The struct field values, in order of the struct type's declaration.
+ "structValues": { # The struct field values.
"a_key": # Object with schema name: QueryParameterValue
},
- "value": "A String", # [Optional] The value of this value, if a simple scalar type.
+ "value": "A String", # Optional. The value of this value, if a simple scalar type.
},
},
],
+ "vectorSearchStatistics": { # Statistics for a vector search query. Populated as part of JobStatistics2. # Output only. Search query specific statistics.
+ "indexUnusedReasons": [ # When `indexUsageMode` is `UNUSED` or `PARTIALLY_USED`, this field explains why indexes were not used in all or part of the vector search query. If `indexUsageMode` is `FULLY_USED`, this field is not populated.
+ { # Reason about why no search index was used in the search query (or sub-query).
+ "baseTable": { # Specifies the base table involved in the reason that no search index was used.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ "code": "A String", # Specifies the high-level reason for the scenario when no search index was used.
+ "indexName": "A String", # Specifies the name of the unused search index, if available.
+ "message": "A String", # Free form human-readable reason for the scenario when no search index was used.
+ },
+ ],
+ "indexUsageMode": "A String", # Specifies the index usage mode for the query.
+ },
},
- "quotaDeferments": [ # [Output-only] Quotas which delayed this job's start time.
+ "quotaDeferments": [ # Output only. Quotas which delayed this job's start time.
"A String",
],
- "reservationUsage": [ # [Output-only] Job resource usage breakdown by reservation.
- {
- "name": "A String", # [Output-only] Reservation name or "unreserved" for on-demand resources usage.
- "slotMs": "A String", # [Output-only] Slot-milliseconds the job spent in the given reservation.
+ "reservationUsage": [ # Output only. Job resource usage breakdown by reservation. This field reported misleading information and will no longer be populated.
+ { # Job resource usage breakdown by reservation.
+ "name": "A String", # Reservation name or "unreserved" for on-demand resources usage.
+ "slotMs": "A String", # Total slot milliseconds used by the reservation for a particular job.
},
],
- "reservation_id": "A String", # [Output-only] Name of the primary reservation assigned to this job. Note that this could be different than reservations reported in the reservation usage field if parent reservations were used to execute this job.
- "rowLevelSecurityStatistics": { # [Output-only] [Preview] Statistics for row-level security. Present only for query and extract jobs.
- "rowLevelSecurityApplied": True or False, # [Output-only] [Preview] Whether any accessed data was protected by row access policies.
+ "reservation_id": "A String", # Output only. Name of the primary reservation assigned to this job. Note that this could be different than reservations reported in the reservation usage field if parent reservations were used to execute this job.
+ "rowLevelSecurityStatistics": { # Statistics for row-level security. # Output only. Statistics for row-level security. Present only for query and extract jobs.
+ "rowLevelSecurityApplied": True or False, # Whether any accessed data was protected by row access policies.
},
- "scriptStatistics": { # [Output-only] Statistics for a child job of a script.
- "evaluationKind": "A String", # [Output-only] Whether this child job was a statement or expression.
+ "scriptStatistics": { # Job statistics specific to the child job of a script. # Output only. If this a child job of a script, specifies information about the context of this job within the script.
+ "evaluationKind": "A String", # Whether this child job was a statement or expression.
"stackFrames": [ # Stack trace showing the line/column/procedure name of each frame on the stack at the point where the current evaluation happened. The leaf frame is first, the primary script is last. Never empty.
- {
- "endColumn": 42, # [Output-only] One-based end column.
- "endLine": 42, # [Output-only] One-based end line.
- "procedureId": "A String", # [Output-only] Name of the active procedure, empty if in a top-level script.
- "startColumn": 42, # [Output-only] One-based start column.
- "startLine": 42, # [Output-only] One-based start line.
- "text": "A String", # [Output-only] Text of the current statement/expression.
+ { # Represents the location of the statement/expression being evaluated. Line and column numbers are defined as follows: - Line and column numbers start with one. That is, line 1 column 1 denotes the start of the script. - When inside a stored procedure, all line/column numbers are relative to the procedure body, not the script in which the procedure was defined. - Start/end positions exclude leading/trailing comments and whitespace. The end position always ends with a ";", when present. - Multi-byte Unicode characters are treated as just one column. - If the original script (or procedure definition) contains TAB characters, a tab "snaps" the indentation forward to the nearest multiple of 8 characters, plus 1. For example, a TAB on column 1, 2, 3, 4, 5, 6 , or 8 will advance the next character to column 9. A TAB on column 9, 10, 11, 12, 13, 14, 15, or 16 will advance the next character to column 17.
+ "endColumn": 42, # Output only. One-based end column.
+ "endLine": 42, # Output only. One-based end line.
+ "procedureId": "A String", # Output only. Name of the active procedure, empty if in a top-level script.
+ "startColumn": 42, # Output only. One-based start column.
+ "startLine": 42, # Output only. One-based start line.
+ "text": "A String", # Output only. Text of the current statement/expression.
},
],
},
- "sessionInfo": { # [Output-only] [Preview] Information of the session if this job is part of one.
- "sessionId": "A String", # [Output-only] // [Preview] Id of the session.
+ "sessionInfo": { # [Preview] Information related to sessions. # Output only. Information of the session if this job is part of one.
+ "sessionId": "A String", # Output only. The id of the session.
},
- "startTime": "A String", # [Output-only] Start time of this job, in milliseconds since the epoch. This field will be present when the job transitions from the PENDING state to either RUNNING or DONE.
- "totalBytesProcessed": "A String", # [Output-only] [Deprecated] Use the bytes processed in the query statistics instead.
- "totalSlotMs": "A String", # [Output-only] Slot-milliseconds for the job.
- "transactionInfo": { # [Output-only] [Alpha] Information of the multi-statement transaction if this job is part of one.
- "transactionId": "A String", # [Output-only] // [Alpha] Id of the transaction.
+ "startTime": "A String", # Output only. Start time of this job, in milliseconds since the epoch. This field will be present when the job transitions from the PENDING state to either RUNNING or DONE.
+ "totalBytesProcessed": "A String", # Output only. Total bytes processed for the job.
+ "totalSlotMs": "A String", # Output only. Slot-milliseconds for the job.
+ "transactionInfo": { # [Alpha] Information of a multi-statement transaction. # Output only. [Alpha] Information of the multi-statement transaction if this job is part of one. This property is only expected on a child job or a job that is in a session. A script parent job is not part of the transaction started in the script.
+ "transactionId": "A String", # Output only. [Alpha] Id of the transaction.
},
},
- "status": { # [Full-projection-only] Describes the state of the job.
- "errorResult": { # [Output-only] Final error result of the job. If present, indicates that the job has completed and was unsuccessful.
+ "status": { # [Full-projection-only] Describes the status of this job.
+ "errorResult": { # Error details. # Output only. Final error result of the job. If present, indicates that the job has completed and was unsuccessful.
"debugInfo": "A String", # Debugging information. This property is internal to Google and should not be used.
"location": "A String", # Specifies where the error occurred, if present.
"message": "A String", # A human-readable description of the error.
"reason": "A String", # A short error code that summarizes the error.
},
- "errors": [ # [Output-only] The first errors encountered during the running of the job. The final message includes the number of errors that caused the process to stop. Errors here do not necessarily mean that the job has completed or was unsuccessful.
- {
+ "errors": [ # Output only. The first errors encountered during the running of the job. The final message includes the number of errors that caused the process to stop. Errors here do not necessarily mean that the job has not completed or was unsuccessful.
+ { # Error details.
"debugInfo": "A String", # Debugging information. This property is internal to Google and should not be used.
"location": "A String", # Specifies where the error occurred, if present.
"message": "A String", # A human-readable description of the error.
"reason": "A String", # A short error code that summarizes the error.
},
],
- "state": "A String", # [Output-only] Running state of the job.
+ "state": "A String", # Output only. Running state of the job. Valid states include 'PENDING', 'RUNNING', and 'DONE'.
},
"user_email": "A String", # [Full-projection-only] Email address of the user who ran the job.
},
],
"kind": "bigquery#jobList", # The resource type of the response.
"nextPageToken": "A String", # A token to request the next page of results.
+ "unreachable": [ # A list of skipped locations that were unreachable. For more information about BigQuery locations, see: https://cloud.google.com/bigquery/docs/locations. Example: "europe-west5"
+ "A String",
+ ],
}
query(projectId, body=None)
+ query(projectId, body=None, x__xgafv=None)
Runs a BigQuery SQL query synchronously and returns query results if the query completes within a specified timeout.
Args:
- projectId: string, Project ID of the project billed for the query (required)
+ projectId: string, Required. Project ID of the query request. (required)
body: object, The request body.
The object takes the form of:
-{
- "connectionProperties": [ # Connection properties.
- {
- "key": "A String", # [Required] Name of the connection property to set.
- "value": "A String", # [Required] Value of the connection property.
+{ # Describes the format of the jobs.query request.
+ "connectionProperties": [ # Optional. Connection properties which can modify the query behavior.
+ { # A connection-level property to customize query behavior. Under JDBC, these correspond directly to connection properties passed to the DriverManager. Under ODBC, these correspond to properties in the connection string. Currently supported connection properties: * **dataset_project_id**: represents the default project for datasets that are used in the query. Setting the system variable `@@dataset_project_id` achieves the same behavior. For more information about system variables, see: https://cloud.google.com/bigquery/docs/reference/system-variables * **time_zone**: represents the default timezone used to run the query. * **session_id**: associates the query with a given session. * **query_label**: associates the query with a given job label. If set, all subsequent queries in a script or session will have this label. For the format in which a you can specify a query label, see labels in the JobConfiguration resource type: https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#jobconfiguration Additional properties are allowed, but ignored. Specifying multiple connection properties with the same key returns an error.
+ "key": "A String", # The key of the property to set.
+ "value": "A String", # The value of the property to set.
},
],
"continuous": True or False, # [Optional] Specifies whether the query should be executed as a continuous query. The default value is false.
- "createSession": True or False, # If true, creates a new session, where session id will be a server generated random id. If false, runs query with an existing session_id passed in ConnectionProperty, otherwise runs query in non-session mode.
- "defaultDataset": { # [Optional] Specifies the default datasetId and projectId to assume for any unqualified table names in the query. If not set, all table names in the query string must be qualified in the format 'datasetId.tableId'.
- "datasetId": "A String", # [Required] A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- "projectId": "A String", # [Optional] The ID of the project containing this dataset.
+ "createSession": True or False, # Optional. If true, creates a new session using a randomly generated session_id. If false, runs query with an existing session_id passed in ConnectionProperty, otherwise runs query in non-session mode. The session location will be set to QueryRequest.location if it is present, otherwise it's set to the default location based on existing routing logic.
+ "defaultDataset": { # Optional. Specifies the default datasetId and projectId to assume for any unqualified table names in the query. If not set, all table names in the query string must be qualified in the format 'datasetId.tableId'.
+ "datasetId": "A String", # Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "projectId": "A String", # Optional. The ID of the project containing this dataset.
+ },
+ "dryRun": True or False, # Optional. If set to true, BigQuery doesn't run the job. Instead, if the query is valid, BigQuery returns statistics about the job such as how many bytes would be processed. If the query is invalid, an error returns. The default value is false.
+ "formatOptions": { # Options for data format adjustments. # Optional. Output format adjustments.
+ "useInt64Timestamp": True or False, # Optional. Output timestamp as usec int64. Default is false.
},
- "dryRun": True or False, # [Optional] If set to true, BigQuery doesn't run the job. Instead, if the query is valid, BigQuery returns statistics about the job such as how many bytes would be processed. If the query is invalid, an error returns. The default value is false.
"jobCreationMode": "A String", # Optional. If not set, jobs are always required. If set, the query request will follow the behavior described JobCreationMode. This feature is not yet available. Jobs will always be created.
"kind": "bigquery#queryRequest", # The resource type of the request.
- "labels": { # The labels associated with this job. You can use these to organize and group your jobs. Label keys and values can be no longer than 63 characters, can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. Label values are optional. Label keys must start with a letter and each label in the list must have a different key.
+ "labels": { # Optional. The labels associated with this query. Labels can be used to organize and group query jobs. Label keys and values can be no longer than 63 characters, can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. Label keys must start with a letter and each label in the list must have a different key.
"a_key": "A String",
},
"location": "A String", # The geographic location where the job should run. See details at https://cloud.google.com/bigquery/docs/locations#specifying_your_location.
- "maxResults": 42, # [Optional] The maximum number of rows of data to return per page of results. Setting this flag to a small value such as 1000 and then paging through results might improve reliability when the query result set is large. In addition to this limit, responses are also limited to 10 MB. By default, there is no maximum row count, and only the byte limit applies.
- "maximumBytesBilled": "A String", # [Optional] Limits the bytes billed for this job. Queries that will have bytes billed beyond this limit will fail (without incurring a charge). If unspecified, this will be set to your project default.
- "parameterMode": "A String", # Standard SQL only. Set to POSITIONAL to use positional (?) query parameters or to NAMED to use named (@myparam) query parameters in this query.
- "preserveNulls": True or False, # [Deprecated] This property is deprecated.
- "query": "A String", # [Required] A query string, following the BigQuery query syntax, of the query to execute. Example: "SELECT count(f1) FROM [myProjectId:myDatasetId.myTableId]".
- "queryParameters": [ # Query parameters for Standard SQL queries.
- {
- "name": "A String", # [Optional] If unset, this is a positional parameter. Otherwise, should be unique within a query.
- "parameterType": { # [Required] The type of this parameter.
- "arrayType": # Object with schema name: QueryParameterType # [Optional] The type of the array's elements, if this is an array.
- "rangeElementType": # Object with schema name: QueryParameterType # [Optional] The element type of the range, if this is a range.
- "structTypes": [ # [Optional] The types of the fields of this struct, in order, if this is a struct.
- {
- "description": "A String", # [Optional] Human-oriented description of the field.
- "name": "A String", # [Optional] The name of this field.
- "type": # Object with schema name: QueryParameterType # [Required] The type of this field.
+ "maxResults": 42, # Optional. The maximum number of rows of data to return per page of results. Setting this flag to a small value such as 1000 and then paging through results might improve reliability when the query result set is large. In addition to this limit, responses are also limited to 10 MB. By default, there is no maximum row count, and only the byte limit applies.
+ "maximumBytesBilled": "A String", # Optional. Limits the bytes billed for this query. Queries with bytes billed above this limit will fail (without incurring a charge). If unspecified, the project default is used.
+ "parameterMode": "A String", # GoogleSQL only. Set to POSITIONAL to use positional (?) query parameters or to NAMED to use named (@myparam) query parameters in this query.
+ "preserveNulls": True or False, # This property is deprecated.
+ "query": "A String", # Required. A query string to execute, using Google Standard SQL or legacy SQL syntax. Example: "SELECT COUNT(f1) FROM myProjectId.myDatasetId.myTableId".
+ "queryParameters": [ # Query parameters for GoogleSQL queries.
+ { # A parameter given to a query.
+ "name": "A String", # Optional. If unset, this is a positional parameter. Otherwise, should be unique within a query.
+ "parameterType": { # The type of a query parameter. # Required. The type of this parameter.
+ "arrayType": # Object with schema name: QueryParameterType # Optional. The type of the array's elements, if this is an array.
+ "rangeElementType": # Object with schema name: QueryParameterType # Optional. The element type of the range, if this is a range.
+ "structTypes": [ # Optional. The types of the fields of this struct, in order, if this is a struct.
+ { # The type of a struct parameter.
+ "description": "A String", # Optional. Human-oriented description of the field.
+ "name": "A String", # Optional. The name of this field.
+ "type": # Object with schema name: QueryParameterType # Required. The type of this field.
},
],
- "type": "A String", # [Required] The top level type of this field.
+ "type": "A String", # Required. The top level type of this field.
},
- "parameterValue": { # [Required] The value of this parameter.
- "arrayValues": [ # [Optional] The array values, if this is an array type.
+ "parameterValue": { # The value of a query parameter. # Required. The value of this parameter.
+ "arrayValues": [ # Optional. The array values, if this is an array type.
# Object with schema name: QueryParameterValue
],
- "rangeValue": { # [Optional] The range value, if this is a range type.
- "end": # Object with schema name: QueryParameterValue
- "start": # Object with schema name: QueryParameterValue
+ "rangeValue": { # Represents the value of a range. # Optional. The range value, if this is a range type.
+ "end": # Object with schema name: QueryParameterValue # Optional. The end value of the range. A missing value represents an unbounded end.
+ "start": # Object with schema name: QueryParameterValue # Optional. The start value of the range. A missing value represents an unbounded start.
},
- "structValues": { # [Optional] The struct field values, in order of the struct type's declaration.
+ "structValues": { # The struct field values.
"a_key": # Object with schema name: QueryParameterValue
},
- "value": "A String", # [Optional] The value of this value, if a simple scalar type.
+ "value": "A String", # Optional. The value of this value, if a simple scalar type.
},
},
],
- "requestId": "A String", # A unique user provided identifier to ensure idempotent behavior for queries. Note that this is different from the job_id. It has the following properties: 1. It is case-sensitive, limited to up to 36 ASCII characters. A UUID is recommended. 2. Read only queries can ignore this token since they are nullipotent by definition. 3. For the purposes of idempotency ensured by the request_id, a request is considered duplicate of another only if they have the same request_id and are actually duplicates. When determining whether a request is a duplicate of the previous request, all parameters in the request that may affect the behavior are considered. For example, query, connection_properties, query_parameters, use_legacy_sql are parameters that affect the result and are considered when determining whether a request is a duplicate, but properties like timeout_ms don't affect the result and are thus not considered. Dry run query requests are never considered duplicate of another request. 4. When a duplicate mutating query request is detected, it returns: a. the results of the mutation if it completes successfully within the timeout. b. the running operation if it is still in progress at the end of the timeout. 5. Its lifetime is limited to 15 minutes. In other words, if two requests are sent with the same request_id, but more than 15 minutes apart, idempotency is not guaranteed.
- "timeoutMs": 42, # [Optional] How long to wait for the query to complete, in milliseconds, before the request times out and returns. Note that this is only a timeout for the request, not the query. If the query takes longer to run than the timeout value, the call returns without any results and with the 'jobComplete' flag set to false. You can call GetQueryResults() to wait for the query to complete and read the results. The default value is 10000 milliseconds (10 seconds).
- "useLegacySql": true, # Specifies whether to use BigQuery's legacy SQL dialect for this query. The default value is true. If set to false, the query will use BigQuery's standard SQL: https://cloud.google.com/bigquery/sql-reference/ When useLegacySql is set to false, the value of flattenResults is ignored; query will be run as if flattenResults is false.
- "useQueryCache": true, # [Optional] Whether to look for the result in the query cache. The query cache is a best-effort cache that will be flushed whenever tables in the query are modified. The default value is true.
+ "requestId": "A String", # Optional. A unique user provided identifier to ensure idempotent behavior for queries. Note that this is different from the job_id. It has the following properties: 1. It is case-sensitive, limited to up to 36 ASCII characters. A UUID is recommended. 2. Read only queries can ignore this token since they are nullipotent by definition. 3. For the purposes of idempotency ensured by the request_id, a request is considered duplicate of another only if they have the same request_id and are actually duplicates. When determining whether a request is a duplicate of another request, all parameters in the request that may affect the result are considered. For example, query, connection_properties, query_parameters, use_legacy_sql are parameters that affect the result and are considered when determining whether a request is a duplicate, but properties like timeout_ms don't affect the result and are thus not considered. Dry run query requests are never considered duplicate of another request. 4. When a duplicate mutating query request is detected, it returns: a. the results of the mutation if it completes successfully within the timeout. b. the running operation if it is still in progress at the end of the timeout. 5. Its lifetime is limited to 15 minutes. In other words, if two requests are sent with the same request_id, but more than 15 minutes apart, idempotency is not guaranteed.
+ "timeoutMs": 42, # Optional. Optional: Specifies the maximum amount of time, in milliseconds, that the client is willing to wait for the query to complete. By default, this limit is 10 seconds (10,000 milliseconds). If the query is complete, the jobComplete field in the response is true. If the query has not yet completed, jobComplete is false. You can request a longer timeout period in the timeoutMs field. However, the call is not guaranteed to wait for the specified timeout; it typically returns after around 200 seconds (200,000 milliseconds), even if the query is not complete. If jobComplete is false, you can continue to wait for the query to complete by calling the getQueryResults method until the jobComplete field in the getQueryResults response is true.
+ "useLegacySql": true, # Specifies whether to use BigQuery's legacy SQL dialect for this query. The default value is true. If set to false, the query will use BigQuery's GoogleSQL: https://cloud.google.com/bigquery/sql-reference/ When useLegacySql is set to false, the value of flattenResults is ignored; query will be run as if flattenResults is false.
+ "useQueryCache": true, # Optional. Whether to look for the result in the query cache. The query cache is a best-effort cache that will be flushed whenever tables in the query are modified. The default value is true.
}
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
Returns:
An object of the form:
{
"cacheHit": True or False, # Whether the query result was fetched from the query cache.
- "dmlStats": { # [Output-only] Detailed statistics for DML statements Present only for DML statements INSERT, UPDATE, DELETE or TRUNCATE.
- "deletedRowCount": "A String", # Number of deleted Rows. populated by DML DELETE, MERGE and TRUNCATE statements.
- "insertedRowCount": "A String", # Number of inserted Rows. Populated by DML INSERT and MERGE statements.
- "updatedRowCount": "A String", # Number of updated Rows. Populated by DML UPDATE and MERGE statements.
+ "dmlStats": { # Detailed statistics for DML statements # Output only. Detailed statistics for DML statements INSERT, UPDATE, DELETE, MERGE or TRUNCATE.
+ "deletedRowCount": "A String", # Output only. Number of deleted Rows. populated by DML DELETE, MERGE and TRUNCATE statements.
+ "insertedRowCount": "A String", # Output only. Number of inserted Rows. Populated by DML INSERT and MERGE statements
+ "updatedRowCount": "A String", # Output only. Number of updated Rows. Populated by DML UPDATE and MERGE statements.
},
- "errors": [ # [Output-only] The first errors or warnings encountered during the running of the job. The final message includes the number of errors that caused the process to stop. Errors here do not necessarily mean that the job has completed or was unsuccessful.
- {
+ "errors": [ # Output only. The first errors or warnings encountered during the running of the job. The final message includes the number of errors that caused the process to stop. Errors here do not necessarily mean that the job has completed or was unsuccessful. For more information about error messages, see [Error messages](https://cloud.google.com/bigquery/docs/error-messages).
+ { # Error details.
"debugInfo": "A String", # Debugging information. This property is internal to Google and should not be used.
"location": "A String", # Specifies where the error occurred, if present.
"message": "A String", # A human-readable description of the error.
@@ -3903,15 +7111,17 @@ Method Details
},
],
"jobComplete": True or False, # Whether the query has completed or not. If rows or totalRows are present, this will always be true. If this is false, totalRows will not be available.
- "jobCreationReason": "", # Optional. Only relevant when a job_reference is present in the response. If job_reference is not present it will always be unset. When job_reference is present, this field should be interpreted as follows: If set, it will provide the reason of why a Job was created. If not set, it should be treated as the default: REQUESTED. This feature is not yet available. Jobs will always be created.
- "jobReference": { # Reference to the Job that was created to run the query. This field will be present even if the original request timed out, in which case GetQueryResults can be used to read the results once the query has completed. Since this API only returns the first page of results, subsequent pages can be fetched via the same mechanism (GetQueryResults).
- "jobId": "A String", # [Required] The ID of the job. The ID must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), or dashes (-). The maximum length is 1,024 characters.
- "location": "A String", # The geographic location of the job. See details at https://cloud.google.com/bigquery/docs/locations#specifying_your_location.
- "projectId": "A String", # [Required] The ID of the project containing this job.
+ "jobCreationReason": { # Reason about why a Job was created from a [`jobs.query`](https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs/query) method when used with `JOB_CREATION_OPTIONAL` Job creation mode. For [`jobs.insert`](https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs/insert) method calls it will always be `REQUESTED`. This feature is not yet available. Jobs will always be created. # Optional. Only relevant when a job_reference is present in the response. If job_reference is not present it will always be unset. When job_reference is present, this field should be interpreted as follows: If set, it will provide the reason of why a Job was created. If not set, it should be treated as the default: REQUESTED. This feature is not yet available. Jobs will always be created.
+ "code": "A String", # Output only. Specifies the high level reason why a Job was created.
+ },
+ "jobReference": { # A job reference is a fully qualified identifier for referring to a job. # Reference to the Job that was created to run the query. This field will be present even if the original request timed out, in which case GetQueryResults can be used to read the results once the query has completed. Since this API only returns the first page of results, subsequent pages can be fetched via the same mechanism (GetQueryResults).
+ "jobId": "A String", # Required. The ID of the job. The ID must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), or dashes (-). The maximum length is 1,024 characters.
+ "location": "A String", # Optional. The geographic location of the job. The default value is US. For more information about BigQuery locations, see: https://cloud.google.com/bigquery/docs/locations
+ "projectId": "A String", # Required. The ID of the project containing this job.
},
"kind": "bigquery#queryResponse", # The resource type.
- "numDmlAffectedRows": "A String", # [Output-only] The number of rows affected by a DML statement. Present only for DML statements INSERT, UPDATE or DELETE.
- "pageToken": "A String", # A token used for paging results.
+ "numDmlAffectedRows": "A String", # Output only. The number of rows affected by a DML statement. Present only for DML statements INSERT, UPDATE or DELETE.
+ "pageToken": "A String", # A token used for paging results. A non-empty token indicates that additional results are available. To see additional results, query the [`jobs.getQueryResults`](https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs/getQueryResults) method. For more information, see [Paging through table data](https://cloud.google.com/bigquery/docs/paging-results).
"queryId": "A String", # Query ID for the completed query. This ID will be auto-generated. This field is not yet available and it is currently not guaranteed to be populated.
"rows": [ # An object with as many results as can be contained within the maximum permitted reply size. To get any additional rows, you can call GetQueryResults and specify the jobReference returned above.
{
@@ -3922,40 +7132,40 @@ Method Details
],
},
],
- "schema": { # The schema of the results. Present only when the query completes successfully.
+ "schema": { # Schema of a table # The schema of the results. Present only when the query completes successfully.
"fields": [ # Describes the fields in a table.
- {
- "categories": { # [Optional] The categories attached to this field, used for field-level access control.
- "names": [ # A list of category resource names. For example, "projects/1/taxonomies/2/categories/3". At most 5 categories are allowed.
+ { # A field in TableSchema
+ "categories": { # Deprecated.
+ "names": [ # Deprecated.
"A String",
],
},
- "collation": "A String", # Optional. Collation specification of the field. It only can be set on string type field.
- "defaultValueExpression": "A String", # Optional. A SQL expression to specify the default value for this field. It can only be set for top level fields (columns). You can use struct or array expression to specify default value for the entire struct or array. The valid SQL expressions are: - Literals for all data types, including STRUCT and ARRAY. - Following functions: - CURRENT_TIMESTAMP - CURRENT_TIME - CURRENT_DATE - CURRENT_DATETIME - GENERATE_UUID - RAND - SESSION_USER - ST_GEOGPOINT - Struct or array composed with the above allowed functions, for example, [CURRENT_DATE(), DATE '2020-01-01']
- "description": "A String", # [Optional] The field description. The maximum length is 1,024 characters.
- "fields": [ # [Optional] Describes the nested schema fields if the type property is set to RECORD.
+ "collation": "A String", # Optional. Field collation can be set only when the type of field is STRING. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.
+ "defaultValueExpression": "A String", # Optional. A SQL expression to specify the [default value] (https://cloud.google.com/bigquery/docs/default-values) for this field.
+ "description": "A String", # Optional. The field description. The maximum length is 1,024 characters.
+ "fields": [ # Optional. Describes the nested schema fields if the type property is set to RECORD.
# Object with schema name: TableFieldSchema
],
- "maxLength": "A String", # [Optional] Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
- "mode": "A String", # [Optional] The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
- "name": "A String", # [Required] The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
- "policyTags": {
- "names": [ # A list of category resource names. For example, "projects/1/location/eu/taxonomies/2/policyTags/3". At most 1 policy tag is allowed.
+ "maxLength": "A String", # Optional. Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
+ "mode": "A String", # Optional. The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
+ "name": "A String", # Required. The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
+ "policyTags": { # Optional. The policy tags attached to this field, used for field-level access control. If not set, defaults to empty policy_tags.
+ "names": [ # A list of policy tag resource names. For example, "projects/1/locations/eu/taxonomies/2/policyTags/3". At most 1 policy tag is currently allowed.
"A String",
],
},
- "precision": "A String", # [Optional] Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: - Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] - Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: - If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. - If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): - If type = "NUMERIC": 1 ≤ precision ≤ 29. - If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
- "rangeElementType": { # Optional. The subtype of the RANGE, if the type of this field is RANGE. If the type is RANGE, this field is required. Possible values for the field element type of a RANGE include: - DATE - DATETIME - TIMESTAMP
- "type": "A String", # The field element type of a RANGE
+ "precision": "A String", # Optional. Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: * Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] * Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: * If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. * If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): * If type = "NUMERIC": 1 ≤ precision ≤ 29. * If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
+ "rangeElementType": { # Represents the type of a field element.
+ "type": "A String", # Required. The type of a field element. See TableFieldSchema.type.
},
- "roundingMode": "A String", # Optional. Rounding Mode specification of the field. It only can be set on NUMERIC or BIGNUMERIC type fields.
- "scale": "A String", # [Optional] See documentation for precision.
- "type": "A String", # [Required] The field data type. Possible values include STRING, BYTES, INTEGER, INT64 (same as INTEGER), FLOAT, FLOAT64 (same as FLOAT), NUMERIC, BIGNUMERIC, BOOLEAN, BOOL (same as BOOLEAN), TIMESTAMP, DATE, TIME, DATETIME, INTERVAL, RECORD (where RECORD indicates that the field contains a nested schema) or STRUCT (same as RECORD).
+ "roundingMode": "A String", # Optional. Specifies the rounding mode to be used when storing values of NUMERIC and BIGNUMERIC type.
+ "scale": "A String", # Optional. See documentation for precision.
+ "type": "A String", # Required. The field data type. Possible values include: * STRING * BYTES * INTEGER (or INT64) * FLOAT (or FLOAT64) * BOOLEAN (or BOOL) * TIMESTAMP * DATE * TIME * DATETIME * GEOGRAPHY * NUMERIC * BIGNUMERIC * JSON * RECORD (or STRUCT) Use of RECORD/STRUCT indicates that the field contains a nested schema.
},
],
},
- "sessionInfo": { # [Output-only] [Preview] Information of the session if this job is part of one.
- "sessionId": "A String", # [Output-only] // [Preview] Id of the session.
+ "sessionInfo": { # [Preview] Information related to sessions. # Output only. Information of the session if this job is part of one.
+ "sessionId": "A String", # Output only. The id of the session.
},
"totalBytesProcessed": "A String", # The total number of bytes processed for this query. If this query was a dry run, this is the number of bytes that would be processed if the query were run.
"totalRows": "A String", # The total number of rows in the complete query result set, which can be more than the number of rows in this single page of results.
diff --git a/docs/dyn/bigquery_v2.models.html b/docs/dyn/bigquery_v2.models.html
index e9dbd9bf7ea..ad44c8ac45f 100644
--- a/docs/dyn/bigquery_v2.models.html
+++ b/docs/dyn/bigquery_v2.models.html
@@ -78,19 +78,19 @@ Instance Methods
close()
Close httplib2 connections.
- delete(projectId, datasetId, modelId)
+ delete(projectId, datasetId, modelId, x__xgafv=None)
Deletes the model specified by modelId from the dataset.
- get(projectId, datasetId, modelId)
+ get(projectId, datasetId, modelId, x__xgafv=None)
Gets the specified model resource by model ID.
- list(projectId, datasetId, maxResults=None, pageToken=None)
+ list(projectId, datasetId, maxResults=None, pageToken=None, x__xgafv=None)
Lists all models in the specified dataset. Requires the READER dataset role. After retrieving the list of models, you can get information about a particular model by calling the models.get method.
Retrieves the next page of results.
- patch(projectId, datasetId, modelId, body=None)
+ patch(projectId, datasetId, modelId, body=None, x__xgafv=None)
Patch specific fields in the specified model.
Method Details
@@ -99,24 +99,32 @@ Method Details
- delete(projectId, datasetId, modelId)
+ delete(projectId, datasetId, modelId, x__xgafv=None)
Deletes the model specified by modelId from the dataset.
Args:
projectId: string, Required. Project ID of the model to delete. (required)
datasetId: string, Required. Dataset ID of the model to delete. (required)
modelId: string, Required. Model ID of the model to delete. (required)
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
- get(projectId, datasetId, modelId)
+ get(projectId, datasetId, modelId, x__xgafv=None)
Gets the specified model resource by model ID.
Args:
projectId: string, Required. Project ID of the requested model. (required)
datasetId: string, Required. Dataset ID of the requested model. (required)
modelId: string, Required. Model ID of the requested model. (required)
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
Returns:
An object of the form:
@@ -134,16 +142,7 @@ Method Details
"featureColumns": [ # Output only. Input feature columns for the model inference. If the model is trained with TRANSFORM clause, these are the input of the TRANSFORM clause.
{ # A field or a column.
"name": "A String", # Optional. The name of this field. Can be absent for struct fields.
- "type": { # The data type of a variable such as a function argument. Examples include: * INT64: `{"typeKind": "INT64"}` * ARRAY: { "typeKind": "ARRAY", "arrayElementType": {"typeKind": "STRING"} } * STRUCT>: { "typeKind": "STRUCT", "structType": { "fields": [ { "name": "x", "type": {"typeKind": "STRING"} }, { "name": "y", "type": { "typeKind": "ARRAY", "arrayElementType": {"typeKind": "DATE"} } } ] } } # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
- "arrayElementType": # Object with schema name: StandardSqlDataType # The type of the array's elements, if type_kind = "ARRAY".
- "rangeElementType": # Object with schema name: StandardSqlDataType # The type of the range's elements, if type_kind = "RANGE".
- "structType": { # The representation of a SQL STRUCT type. # The fields of this struct, in order, if type_kind = "STRUCT".
- "fields": [ # Fields within the struct.
- # Object with schema name: StandardSqlField
- ],
- },
- "typeKind": "A String", # Required. The top level type of this field. Can be any GoogleSQL data type (e.g., "INT64", "DATE", "ARRAY").
- },
+ "type": # Object with schema name: StandardSqlDataType # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
},
],
"friendlyName": "A String", # Optional. A descriptive name for this model.
@@ -769,16 +768,7 @@ Method Details
"labelColumns": [ # Output only. Label columns that were used to train this model. The output of the model will have a "predicted_" prefix to these columns.
{ # A field or a column.
"name": "A String", # Optional. The name of this field. Can be absent for struct fields.
- "type": { # The data type of a variable such as a function argument. Examples include: * INT64: `{"typeKind": "INT64"}` * ARRAY: { "typeKind": "ARRAY", "arrayElementType": {"typeKind": "STRING"} } * STRUCT>: { "typeKind": "STRUCT", "structType": { "fields": [ { "name": "x", "type": {"typeKind": "STRING"} }, { "name": "y", "type": { "typeKind": "ARRAY", "arrayElementType": {"typeKind": "DATE"} } } ] } } # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
- "arrayElementType": # Object with schema name: StandardSqlDataType # The type of the array's elements, if type_kind = "ARRAY".
- "rangeElementType": # Object with schema name: StandardSqlDataType # The type of the range's elements, if type_kind = "RANGE".
- "structType": { # The representation of a SQL STRUCT type. # The fields of this struct, in order, if type_kind = "STRUCT".
- "fields": [ # Fields within the struct.
- # Object with schema name: StandardSqlField
- ],
- },
- "typeKind": "A String", # Required. The top level type of this field. Can be any GoogleSQL data type (e.g., "INT64", "DATE", "ARRAY").
- },
+ "type": # Object with schema name: StandardSqlDataType # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
},
],
"labels": { # The labels associated with this model. You can use these to organize and group your models. Label keys and values can be no longer than 63 characters, can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. Label values are optional. Label keys must start with a letter and each label in the list must have a different key.
@@ -786,7 +776,7 @@ Method Details
},
"lastModifiedTime": "A String", # Output only. The time when this model was last modified, in millisecs since the epoch.
"location": "A String", # Output only. The geographic location where the model resides. This value is inherited from the dataset.
- "modelReference": { # Required. Unique identifier for this model.
+ "modelReference": { # Id path of a model. # Required. Unique identifier for this model.
"datasetId": "A String", # Required. The ID of the dataset containing this model.
"modelId": "A String", # Required. The ID of the model. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
"projectId": "A String", # Required. The ID of the project containing this model.
@@ -818,19 +808,19 @@ Method Details
],
"dataSplitResult": { # Data split result. This contains references to the training and evaluation data tables that were used to train the model. # Output only. Data split result of the training run. Only set when the input data is actually split.
"evaluationTable": { # Table reference of the evaluation data after split.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
"testTable": { # Table reference of the test data after split.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
"trainingTable": { # Table reference of the training data after split.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
},
"evaluationMetrics": { # Evaluation metrics of a model. These are either computed on all training data or just the eval data based on whether eval data was used during training. These are not present for imported models. # Output only. The evaluation metrics over training/eval data that were computed at the end of training.
@@ -988,11 +978,65 @@ Method Details
],
},
"results": [ # Output only. Output of each iteration run, results.size() <= max_iterations.
- {
+ { # Information about a single iteration of the training run.
+ "arimaResult": { # (Auto-)arima fitting result. Wrap everything in ArimaResult for easier refactoring if we want to use model-specific iteration results. # Arima result.
+ "arimaModelInfo": [ # This message is repeated because there are multiple arima models fitted in auto-arima. For non-auto-arima model, its size is one.
+ { # Arima model information.
+ "arimaCoefficients": { # Arima coefficients. # Arima coefficients.
+ "autoRegressiveCoefficients": [ # Auto-regressive coefficients, an array of double.
+ 3.14,
+ ],
+ "interceptCoefficient": 3.14, # Intercept coefficient, just a double not an array.
+ "movingAverageCoefficients": [ # Moving-average coefficients, an array of double.
+ 3.14,
+ ],
+ },
+ "arimaFittingMetrics": { # ARIMA model fitting metrics. # Arima fitting metrics.
+ "aic": 3.14, # AIC.
+ "logLikelihood": 3.14, # Log-likelihood.
+ "variance": 3.14, # Variance.
+ },
+ "hasDrift": True or False, # Whether Arima model fitted with drift or not. It is always false when d is not 1.
+ "hasHolidayEffect": True or False, # If true, holiday_effect is a part of time series decomposition result.
+ "hasSpikesAndDips": True or False, # If true, spikes_and_dips is a part of time series decomposition result.
+ "hasStepChanges": True or False, # If true, step_changes is a part of time series decomposition result.
+ "nonSeasonalOrder": { # Arima order, can be used for both non-seasonal and seasonal parts. # Non-seasonal order.
+ "d": "A String", # Order of the differencing part.
+ "p": "A String", # Order of the autoregressive part.
+ "q": "A String", # Order of the moving-average part.
+ },
+ "seasonalPeriods": [ # Seasonal periods. Repeated because multiple periods are supported for one time series.
+ "A String",
+ ],
+ "timeSeriesId": "A String", # The time_series_id value for this time series. It will be one of the unique values from the time_series_id_column specified during ARIMA model training. Only present when time_series_id_column training option was used.
+ "timeSeriesIds": [ # The tuple of time_series_ids identifying this time series. It will be one of the unique tuples of values present in the time_series_id_columns specified during ARIMA model training. Only present when time_series_id_columns training option was used and the order of values here are same as the order of time_series_id_columns.
+ "A String",
+ ],
+ },
+ ],
+ "seasonalPeriods": [ # Seasonal periods. Repeated because multiple periods are supported for one time series.
+ "A String",
+ ],
+ },
+ "clusterInfos": [ # Information about top clusters for clustering models.
+ { # Information about a single cluster for clustering model.
+ "centroidId": "A String", # Centroid id.
+ "clusterRadius": 3.14, # Cluster radius, the average distance from centroid to each point assigned to the cluster.
+ "clusterSize": "A String", # Cluster size, the total number of points assigned to the cluster.
+ },
+ ],
"durationMs": "A String", # Time taken to run the iteration in milliseconds.
"evalLoss": 3.14, # Loss computed on the eval data at the end of iteration.
"index": 42, # Index of the iteration, 0 based.
"learnRate": 3.14, # Learn rate used for this iteration.
+ "principalComponentInfos": [ # The information of the principal components.
+ { # Principal component infos, used only for eigen decomposition based models, e.g., PCA. Ordered by explained_variance in the descending order.
+ "cumulativeExplainedVarianceRatio": 3.14, # The explained_variance is pre-ordered in the descending order to compute the cumulative explained variance ratio.
+ "explainedVariance": 3.14, # Explained variance by this principal component, which is simply the eigenvalue.
+ "explainedVarianceRatio": 3.14, # Explained_variance over the total explained variance.
+ "principalComponentId": "A String", # Id of the principal component.
+ },
+ ],
"trainingLoss": 3.14, # Loss computed on the training data at the end of iteration.
},
],
@@ -1117,7 +1161,10 @@ Method Details
"rangeElementType": # Object with schema name: StandardSqlDataType # The type of the range's elements, if type_kind = "RANGE".
"structType": { # The representation of a SQL STRUCT type. # The fields of this struct, in order, if type_kind = "STRUCT".
"fields": [ # Fields within the struct.
- # Object with schema name: StandardSqlField
+ { # A field or a column.
+ "name": "A String", # Optional. The name of this field. Can be absent for struct fields.
+ "type": # Object with schema name: StandardSqlDataType # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
+ },
],
},
"typeKind": "A String", # Required. The top level type of this field. Can be any GoogleSQL data type (e.g., "INT64", "DATE", "ARRAY").
@@ -1128,7 +1175,7 @@ Method Details
- list(projectId, datasetId, maxResults=None, pageToken=None)
+ list(projectId, datasetId, maxResults=None, pageToken=None, x__xgafv=None)
Lists all models in the specified dataset. Requires the READER dataset role. After retrieving the list of models, you can get information about a particular model by calling the models.get method.
Args:
@@ -1136,6 +1183,10 @@ Method Details
datasetId: string, Required. Dataset ID of the models to list. (required)
maxResults: integer, The maximum number of results to return in a single response page. Leverage the page tokens to iterate through the entire collection.
pageToken: string, Page token, returned by a previous call to request the next page of results
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
Returns:
An object of the form:
@@ -1155,16 +1206,7 @@ Method Details
"featureColumns": [ # Output only. Input feature columns for the model inference. If the model is trained with TRANSFORM clause, these are the input of the TRANSFORM clause.
{ # A field or a column.
"name": "A String", # Optional. The name of this field. Can be absent for struct fields.
- "type": { # The data type of a variable such as a function argument. Examples include: * INT64: `{"typeKind": "INT64"}` * ARRAY: { "typeKind": "ARRAY", "arrayElementType": {"typeKind": "STRING"} } * STRUCT>: { "typeKind": "STRUCT", "structType": { "fields": [ { "name": "x", "type": {"typeKind": "STRING"} }, { "name": "y", "type": { "typeKind": "ARRAY", "arrayElementType": {"typeKind": "DATE"} } } ] } } # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
- "arrayElementType": # Object with schema name: StandardSqlDataType # The type of the array's elements, if type_kind = "ARRAY".
- "rangeElementType": # Object with schema name: StandardSqlDataType # The type of the range's elements, if type_kind = "RANGE".
- "structType": { # The representation of a SQL STRUCT type. # The fields of this struct, in order, if type_kind = "STRUCT".
- "fields": [ # Fields within the struct.
- # Object with schema name: StandardSqlField
- ],
- },
- "typeKind": "A String", # Required. The top level type of this field. Can be any GoogleSQL data type (e.g., "INT64", "DATE", "ARRAY").
- },
+ "type": # Object with schema name: StandardSqlDataType # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
},
],
"friendlyName": "A String", # Optional. A descriptive name for this model.
@@ -1790,16 +1832,7 @@ Method Details
"labelColumns": [ # Output only. Label columns that were used to train this model. The output of the model will have a "predicted_" prefix to these columns.
{ # A field or a column.
"name": "A String", # Optional. The name of this field. Can be absent for struct fields.
- "type": { # The data type of a variable such as a function argument. Examples include: * INT64: `{"typeKind": "INT64"}` * ARRAY: { "typeKind": "ARRAY", "arrayElementType": {"typeKind": "STRING"} } * STRUCT>: { "typeKind": "STRUCT", "structType": { "fields": [ { "name": "x", "type": {"typeKind": "STRING"} }, { "name": "y", "type": { "typeKind": "ARRAY", "arrayElementType": {"typeKind": "DATE"} } } ] } } # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
- "arrayElementType": # Object with schema name: StandardSqlDataType # The type of the array's elements, if type_kind = "ARRAY".
- "rangeElementType": # Object with schema name: StandardSqlDataType # The type of the range's elements, if type_kind = "RANGE".
- "structType": { # The representation of a SQL STRUCT type. # The fields of this struct, in order, if type_kind = "STRUCT".
- "fields": [ # Fields within the struct.
- # Object with schema name: StandardSqlField
- ],
- },
- "typeKind": "A String", # Required. The top level type of this field. Can be any GoogleSQL data type (e.g., "INT64", "DATE", "ARRAY").
- },
+ "type": # Object with schema name: StandardSqlDataType # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
},
],
"labels": { # The labels associated with this model. You can use these to organize and group your models. Label keys and values can be no longer than 63 characters, can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. Label values are optional. Label keys must start with a letter and each label in the list must have a different key.
@@ -1807,7 +1840,7 @@ Method Details
},
"lastModifiedTime": "A String", # Output only. The time when this model was last modified, in millisecs since the epoch.
"location": "A String", # Output only. The geographic location where the model resides. This value is inherited from the dataset.
- "modelReference": { # Required. Unique identifier for this model.
+ "modelReference": { # Id path of a model. # Required. Unique identifier for this model.
"datasetId": "A String", # Required. The ID of the dataset containing this model.
"modelId": "A String", # Required. The ID of the model. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
"projectId": "A String", # Required. The ID of the project containing this model.
@@ -1839,19 +1872,19 @@ Method Details
],
"dataSplitResult": { # Data split result. This contains references to the training and evaluation data tables that were used to train the model. # Output only. Data split result of the training run. Only set when the input data is actually split.
"evaluationTable": { # Table reference of the evaluation data after split.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
"testTable": { # Table reference of the test data after split.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
"trainingTable": { # Table reference of the training data after split.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
},
"evaluationMetrics": { # Evaluation metrics of a model. These are either computed on all training data or just the eval data based on whether eval data was used during training. These are not present for imported models. # Output only. The evaluation metrics over training/eval data that were computed at the end of training.
@@ -2009,11 +2042,65 @@ Method Details
],
},
"results": [ # Output only. Output of each iteration run, results.size() <= max_iterations.
- {
+ { # Information about a single iteration of the training run.
+ "arimaResult": { # (Auto-)arima fitting result. Wrap everything in ArimaResult for easier refactoring if we want to use model-specific iteration results. # Arima result.
+ "arimaModelInfo": [ # This message is repeated because there are multiple arima models fitted in auto-arima. For non-auto-arima model, its size is one.
+ { # Arima model information.
+ "arimaCoefficients": { # Arima coefficients. # Arima coefficients.
+ "autoRegressiveCoefficients": [ # Auto-regressive coefficients, an array of double.
+ 3.14,
+ ],
+ "interceptCoefficient": 3.14, # Intercept coefficient, just a double not an array.
+ "movingAverageCoefficients": [ # Moving-average coefficients, an array of double.
+ 3.14,
+ ],
+ },
+ "arimaFittingMetrics": { # ARIMA model fitting metrics. # Arima fitting metrics.
+ "aic": 3.14, # AIC.
+ "logLikelihood": 3.14, # Log-likelihood.
+ "variance": 3.14, # Variance.
+ },
+ "hasDrift": True or False, # Whether Arima model fitted with drift or not. It is always false when d is not 1.
+ "hasHolidayEffect": True or False, # If true, holiday_effect is a part of time series decomposition result.
+ "hasSpikesAndDips": True or False, # If true, spikes_and_dips is a part of time series decomposition result.
+ "hasStepChanges": True or False, # If true, step_changes is a part of time series decomposition result.
+ "nonSeasonalOrder": { # Arima order, can be used for both non-seasonal and seasonal parts. # Non-seasonal order.
+ "d": "A String", # Order of the differencing part.
+ "p": "A String", # Order of the autoregressive part.
+ "q": "A String", # Order of the moving-average part.
+ },
+ "seasonalPeriods": [ # Seasonal periods. Repeated because multiple periods are supported for one time series.
+ "A String",
+ ],
+ "timeSeriesId": "A String", # The time_series_id value for this time series. It will be one of the unique values from the time_series_id_column specified during ARIMA model training. Only present when time_series_id_column training option was used.
+ "timeSeriesIds": [ # The tuple of time_series_ids identifying this time series. It will be one of the unique tuples of values present in the time_series_id_columns specified during ARIMA model training. Only present when time_series_id_columns training option was used and the order of values here are same as the order of time_series_id_columns.
+ "A String",
+ ],
+ },
+ ],
+ "seasonalPeriods": [ # Seasonal periods. Repeated because multiple periods are supported for one time series.
+ "A String",
+ ],
+ },
+ "clusterInfos": [ # Information about top clusters for clustering models.
+ { # Information about a single cluster for clustering model.
+ "centroidId": "A String", # Centroid id.
+ "clusterRadius": 3.14, # Cluster radius, the average distance from centroid to each point assigned to the cluster.
+ "clusterSize": "A String", # Cluster size, the total number of points assigned to the cluster.
+ },
+ ],
"durationMs": "A String", # Time taken to run the iteration in milliseconds.
"evalLoss": 3.14, # Loss computed on the eval data at the end of iteration.
"index": 42, # Index of the iteration, 0 based.
"learnRate": 3.14, # Learn rate used for this iteration.
+ "principalComponentInfos": [ # The information of the principal components.
+ { # Principal component infos, used only for eigen decomposition based models, e.g., PCA. Ordered by explained_variance in the descending order.
+ "cumulativeExplainedVarianceRatio": 3.14, # The explained_variance is pre-ordered in the descending order to compute the cumulative explained variance ratio.
+ "explainedVariance": 3.14, # Explained variance by this principal component, which is simply the eigenvalue.
+ "explainedVarianceRatio": 3.14, # Explained_variance over the total explained variance.
+ "principalComponentId": "A String", # Id of the principal component.
+ },
+ ],
"trainingLoss": 3.14, # Loss computed on the training data at the end of iteration.
},
],
@@ -2138,7 +2225,10 @@ Method Details
"rangeElementType": # Object with schema name: StandardSqlDataType # The type of the range's elements, if type_kind = "RANGE".
"structType": { # The representation of a SQL STRUCT type. # The fields of this struct, in order, if type_kind = "STRUCT".
"fields": [ # Fields within the struct.
- # Object with schema name: StandardSqlField
+ { # A field or a column.
+ "name": "A String", # Optional. The name of this field. Can be absent for struct fields.
+ "type": # Object with schema name: StandardSqlDataType # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
+ },
],
},
"typeKind": "A String", # Required. The top level type of this field. Can be any GoogleSQL data type (e.g., "INT64", "DATE", "ARRAY").
@@ -2166,7 +2256,7 @@ Method Details
- patch(projectId, datasetId, modelId, body=None)
+ patch(projectId, datasetId, modelId, body=None, x__xgafv=None)
Patch specific fields in the specified model.
Args:
@@ -2189,16 +2279,7 @@ Method Details
"featureColumns": [ # Output only. Input feature columns for the model inference. If the model is trained with TRANSFORM clause, these are the input of the TRANSFORM clause.
{ # A field or a column.
"name": "A String", # Optional. The name of this field. Can be absent for struct fields.
- "type": { # The data type of a variable such as a function argument. Examples include: * INT64: `{"typeKind": "INT64"}` * ARRAY: { "typeKind": "ARRAY", "arrayElementType": {"typeKind": "STRING"} } * STRUCT>: { "typeKind": "STRUCT", "structType": { "fields": [ { "name": "x", "type": {"typeKind": "STRING"} }, { "name": "y", "type": { "typeKind": "ARRAY", "arrayElementType": {"typeKind": "DATE"} } } ] } } # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
- "arrayElementType": # Object with schema name: StandardSqlDataType # The type of the array's elements, if type_kind = "ARRAY".
- "rangeElementType": # Object with schema name: StandardSqlDataType # The type of the range's elements, if type_kind = "RANGE".
- "structType": { # The representation of a SQL STRUCT type. # The fields of this struct, in order, if type_kind = "STRUCT".
- "fields": [ # Fields within the struct.
- # Object with schema name: StandardSqlField
- ],
- },
- "typeKind": "A String", # Required. The top level type of this field. Can be any GoogleSQL data type (e.g., "INT64", "DATE", "ARRAY").
- },
+ "type": # Object with schema name: StandardSqlDataType # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
},
],
"friendlyName": "A String", # Optional. A descriptive name for this model.
@@ -2824,16 +2905,7 @@ Method Details
"labelColumns": [ # Output only. Label columns that were used to train this model. The output of the model will have a "predicted_" prefix to these columns.
{ # A field or a column.
"name": "A String", # Optional. The name of this field. Can be absent for struct fields.
- "type": { # The data type of a variable such as a function argument. Examples include: * INT64: `{"typeKind": "INT64"}` * ARRAY: { "typeKind": "ARRAY", "arrayElementType": {"typeKind": "STRING"} } * STRUCT>: { "typeKind": "STRUCT", "structType": { "fields": [ { "name": "x", "type": {"typeKind": "STRING"} }, { "name": "y", "type": { "typeKind": "ARRAY", "arrayElementType": {"typeKind": "DATE"} } } ] } } # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
- "arrayElementType": # Object with schema name: StandardSqlDataType # The type of the array's elements, if type_kind = "ARRAY".
- "rangeElementType": # Object with schema name: StandardSqlDataType # The type of the range's elements, if type_kind = "RANGE".
- "structType": { # The representation of a SQL STRUCT type. # The fields of this struct, in order, if type_kind = "STRUCT".
- "fields": [ # Fields within the struct.
- # Object with schema name: StandardSqlField
- ],
- },
- "typeKind": "A String", # Required. The top level type of this field. Can be any GoogleSQL data type (e.g., "INT64", "DATE", "ARRAY").
- },
+ "type": # Object with schema name: StandardSqlDataType # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
},
],
"labels": { # The labels associated with this model. You can use these to organize and group your models. Label keys and values can be no longer than 63 characters, can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. Label values are optional. Label keys must start with a letter and each label in the list must have a different key.
@@ -2841,7 +2913,7 @@ Method Details
},
"lastModifiedTime": "A String", # Output only. The time when this model was last modified, in millisecs since the epoch.
"location": "A String", # Output only. The geographic location where the model resides. This value is inherited from the dataset.
- "modelReference": { # Required. Unique identifier for this model.
+ "modelReference": { # Id path of a model. # Required. Unique identifier for this model.
"datasetId": "A String", # Required. The ID of the dataset containing this model.
"modelId": "A String", # Required. The ID of the model. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
"projectId": "A String", # Required. The ID of the project containing this model.
@@ -2873,19 +2945,19 @@ Method Details
],
"dataSplitResult": { # Data split result. This contains references to the training and evaluation data tables that were used to train the model. # Output only. Data split result of the training run. Only set when the input data is actually split.
"evaluationTable": { # Table reference of the evaluation data after split.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
"testTable": { # Table reference of the test data after split.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
"trainingTable": { # Table reference of the training data after split.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
},
"evaluationMetrics": { # Evaluation metrics of a model. These are either computed on all training data or just the eval data based on whether eval data was used during training. These are not present for imported models. # Output only. The evaluation metrics over training/eval data that were computed at the end of training.
@@ -3043,11 +3115,65 @@ Method Details
],
},
"results": [ # Output only. Output of each iteration run, results.size() <= max_iterations.
- {
+ { # Information about a single iteration of the training run.
+ "arimaResult": { # (Auto-)arima fitting result. Wrap everything in ArimaResult for easier refactoring if we want to use model-specific iteration results. # Arima result.
+ "arimaModelInfo": [ # This message is repeated because there are multiple arima models fitted in auto-arima. For non-auto-arima model, its size is one.
+ { # Arima model information.
+ "arimaCoefficients": { # Arima coefficients. # Arima coefficients.
+ "autoRegressiveCoefficients": [ # Auto-regressive coefficients, an array of double.
+ 3.14,
+ ],
+ "interceptCoefficient": 3.14, # Intercept coefficient, just a double not an array.
+ "movingAverageCoefficients": [ # Moving-average coefficients, an array of double.
+ 3.14,
+ ],
+ },
+ "arimaFittingMetrics": { # ARIMA model fitting metrics. # Arima fitting metrics.
+ "aic": 3.14, # AIC.
+ "logLikelihood": 3.14, # Log-likelihood.
+ "variance": 3.14, # Variance.
+ },
+ "hasDrift": True or False, # Whether Arima model fitted with drift or not. It is always false when d is not 1.
+ "hasHolidayEffect": True or False, # If true, holiday_effect is a part of time series decomposition result.
+ "hasSpikesAndDips": True or False, # If true, spikes_and_dips is a part of time series decomposition result.
+ "hasStepChanges": True or False, # If true, step_changes is a part of time series decomposition result.
+ "nonSeasonalOrder": { # Arima order, can be used for both non-seasonal and seasonal parts. # Non-seasonal order.
+ "d": "A String", # Order of the differencing part.
+ "p": "A String", # Order of the autoregressive part.
+ "q": "A String", # Order of the moving-average part.
+ },
+ "seasonalPeriods": [ # Seasonal periods. Repeated because multiple periods are supported for one time series.
+ "A String",
+ ],
+ "timeSeriesId": "A String", # The time_series_id value for this time series. It will be one of the unique values from the time_series_id_column specified during ARIMA model training. Only present when time_series_id_column training option was used.
+ "timeSeriesIds": [ # The tuple of time_series_ids identifying this time series. It will be one of the unique tuples of values present in the time_series_id_columns specified during ARIMA model training. Only present when time_series_id_columns training option was used and the order of values here are same as the order of time_series_id_columns.
+ "A String",
+ ],
+ },
+ ],
+ "seasonalPeriods": [ # Seasonal periods. Repeated because multiple periods are supported for one time series.
+ "A String",
+ ],
+ },
+ "clusterInfos": [ # Information about top clusters for clustering models.
+ { # Information about a single cluster for clustering model.
+ "centroidId": "A String", # Centroid id.
+ "clusterRadius": 3.14, # Cluster radius, the average distance from centroid to each point assigned to the cluster.
+ "clusterSize": "A String", # Cluster size, the total number of points assigned to the cluster.
+ },
+ ],
"durationMs": "A String", # Time taken to run the iteration in milliseconds.
"evalLoss": 3.14, # Loss computed on the eval data at the end of iteration.
"index": 42, # Index of the iteration, 0 based.
"learnRate": 3.14, # Learn rate used for this iteration.
+ "principalComponentInfos": [ # The information of the principal components.
+ { # Principal component infos, used only for eigen decomposition based models, e.g., PCA. Ordered by explained_variance in the descending order.
+ "cumulativeExplainedVarianceRatio": 3.14, # The explained_variance is pre-ordered in the descending order to compute the cumulative explained variance ratio.
+ "explainedVariance": 3.14, # Explained variance by this principal component, which is simply the eigenvalue.
+ "explainedVarianceRatio": 3.14, # Explained_variance over the total explained variance.
+ "principalComponentId": "A String", # Id of the principal component.
+ },
+ ],
"trainingLoss": 3.14, # Loss computed on the training data at the end of iteration.
},
],
@@ -3172,7 +3298,10 @@ Method Details
"rangeElementType": # Object with schema name: StandardSqlDataType # The type of the range's elements, if type_kind = "RANGE".
"structType": { # The representation of a SQL STRUCT type. # The fields of this struct, in order, if type_kind = "STRUCT".
"fields": [ # Fields within the struct.
- # Object with schema name: StandardSqlField
+ { # A field or a column.
+ "name": "A String", # Optional. The name of this field. Can be absent for struct fields.
+ "type": # Object with schema name: StandardSqlDataType # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
+ },
],
},
"typeKind": "A String", # Required. The top level type of this field. Can be any GoogleSQL data type (e.g., "INT64", "DATE", "ARRAY").
@@ -3181,6 +3310,10 @@ Method Details
],
}
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
Returns:
An object of the form:
@@ -3198,16 +3331,7 @@ Method Details
"featureColumns": [ # Output only. Input feature columns for the model inference. If the model is trained with TRANSFORM clause, these are the input of the TRANSFORM clause.
{ # A field or a column.
"name": "A String", # Optional. The name of this field. Can be absent for struct fields.
- "type": { # The data type of a variable such as a function argument. Examples include: * INT64: `{"typeKind": "INT64"}` * ARRAY: { "typeKind": "ARRAY", "arrayElementType": {"typeKind": "STRING"} } * STRUCT>: { "typeKind": "STRUCT", "structType": { "fields": [ { "name": "x", "type": {"typeKind": "STRING"} }, { "name": "y", "type": { "typeKind": "ARRAY", "arrayElementType": {"typeKind": "DATE"} } } ] } } # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
- "arrayElementType": # Object with schema name: StandardSqlDataType # The type of the array's elements, if type_kind = "ARRAY".
- "rangeElementType": # Object with schema name: StandardSqlDataType # The type of the range's elements, if type_kind = "RANGE".
- "structType": { # The representation of a SQL STRUCT type. # The fields of this struct, in order, if type_kind = "STRUCT".
- "fields": [ # Fields within the struct.
- # Object with schema name: StandardSqlField
- ],
- },
- "typeKind": "A String", # Required. The top level type of this field. Can be any GoogleSQL data type (e.g., "INT64", "DATE", "ARRAY").
- },
+ "type": # Object with schema name: StandardSqlDataType # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
},
],
"friendlyName": "A String", # Optional. A descriptive name for this model.
@@ -3833,16 +3957,7 @@ Method Details
"labelColumns": [ # Output only. Label columns that were used to train this model. The output of the model will have a "predicted_" prefix to these columns.
{ # A field or a column.
"name": "A String", # Optional. The name of this field. Can be absent for struct fields.
- "type": { # The data type of a variable such as a function argument. Examples include: * INT64: `{"typeKind": "INT64"}` * ARRAY: { "typeKind": "ARRAY", "arrayElementType": {"typeKind": "STRING"} } * STRUCT>: { "typeKind": "STRUCT", "structType": { "fields": [ { "name": "x", "type": {"typeKind": "STRING"} }, { "name": "y", "type": { "typeKind": "ARRAY", "arrayElementType": {"typeKind": "DATE"} } } ] } } # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
- "arrayElementType": # Object with schema name: StandardSqlDataType # The type of the array's elements, if type_kind = "ARRAY".
- "rangeElementType": # Object with schema name: StandardSqlDataType # The type of the range's elements, if type_kind = "RANGE".
- "structType": { # The representation of a SQL STRUCT type. # The fields of this struct, in order, if type_kind = "STRUCT".
- "fields": [ # Fields within the struct.
- # Object with schema name: StandardSqlField
- ],
- },
- "typeKind": "A String", # Required. The top level type of this field. Can be any GoogleSQL data type (e.g., "INT64", "DATE", "ARRAY").
- },
+ "type": # Object with schema name: StandardSqlDataType # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
},
],
"labels": { # The labels associated with this model. You can use these to organize and group your models. Label keys and values can be no longer than 63 characters, can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. Label values are optional. Label keys must start with a letter and each label in the list must have a different key.
@@ -3850,7 +3965,7 @@ Method Details
},
"lastModifiedTime": "A String", # Output only. The time when this model was last modified, in millisecs since the epoch.
"location": "A String", # Output only. The geographic location where the model resides. This value is inherited from the dataset.
- "modelReference": { # Required. Unique identifier for this model.
+ "modelReference": { # Id path of a model. # Required. Unique identifier for this model.
"datasetId": "A String", # Required. The ID of the dataset containing this model.
"modelId": "A String", # Required. The ID of the model. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
"projectId": "A String", # Required. The ID of the project containing this model.
@@ -3882,19 +3997,19 @@ Method Details
],
"dataSplitResult": { # Data split result. This contains references to the training and evaluation data tables that were used to train the model. # Output only. Data split result of the training run. Only set when the input data is actually split.
"evaluationTable": { # Table reference of the evaluation data after split.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
"testTable": { # Table reference of the test data after split.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
"trainingTable": { # Table reference of the training data after split.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
},
"evaluationMetrics": { # Evaluation metrics of a model. These are either computed on all training data or just the eval data based on whether eval data was used during training. These are not present for imported models. # Output only. The evaluation metrics over training/eval data that were computed at the end of training.
@@ -4052,11 +4167,65 @@ Method Details
],
},
"results": [ # Output only. Output of each iteration run, results.size() <= max_iterations.
- {
+ { # Information about a single iteration of the training run.
+ "arimaResult": { # (Auto-)arima fitting result. Wrap everything in ArimaResult for easier refactoring if we want to use model-specific iteration results. # Arima result.
+ "arimaModelInfo": [ # This message is repeated because there are multiple arima models fitted in auto-arima. For non-auto-arima model, its size is one.
+ { # Arima model information.
+ "arimaCoefficients": { # Arima coefficients. # Arima coefficients.
+ "autoRegressiveCoefficients": [ # Auto-regressive coefficients, an array of double.
+ 3.14,
+ ],
+ "interceptCoefficient": 3.14, # Intercept coefficient, just a double not an array.
+ "movingAverageCoefficients": [ # Moving-average coefficients, an array of double.
+ 3.14,
+ ],
+ },
+ "arimaFittingMetrics": { # ARIMA model fitting metrics. # Arima fitting metrics.
+ "aic": 3.14, # AIC.
+ "logLikelihood": 3.14, # Log-likelihood.
+ "variance": 3.14, # Variance.
+ },
+ "hasDrift": True or False, # Whether Arima model fitted with drift or not. It is always false when d is not 1.
+ "hasHolidayEffect": True or False, # If true, holiday_effect is a part of time series decomposition result.
+ "hasSpikesAndDips": True or False, # If true, spikes_and_dips is a part of time series decomposition result.
+ "hasStepChanges": True or False, # If true, step_changes is a part of time series decomposition result.
+ "nonSeasonalOrder": { # Arima order, can be used for both non-seasonal and seasonal parts. # Non-seasonal order.
+ "d": "A String", # Order of the differencing part.
+ "p": "A String", # Order of the autoregressive part.
+ "q": "A String", # Order of the moving-average part.
+ },
+ "seasonalPeriods": [ # Seasonal periods. Repeated because multiple periods are supported for one time series.
+ "A String",
+ ],
+ "timeSeriesId": "A String", # The time_series_id value for this time series. It will be one of the unique values from the time_series_id_column specified during ARIMA model training. Only present when time_series_id_column training option was used.
+ "timeSeriesIds": [ # The tuple of time_series_ids identifying this time series. It will be one of the unique tuples of values present in the time_series_id_columns specified during ARIMA model training. Only present when time_series_id_columns training option was used and the order of values here are same as the order of time_series_id_columns.
+ "A String",
+ ],
+ },
+ ],
+ "seasonalPeriods": [ # Seasonal periods. Repeated because multiple periods are supported for one time series.
+ "A String",
+ ],
+ },
+ "clusterInfos": [ # Information about top clusters for clustering models.
+ { # Information about a single cluster for clustering model.
+ "centroidId": "A String", # Centroid id.
+ "clusterRadius": 3.14, # Cluster radius, the average distance from centroid to each point assigned to the cluster.
+ "clusterSize": "A String", # Cluster size, the total number of points assigned to the cluster.
+ },
+ ],
"durationMs": "A String", # Time taken to run the iteration in milliseconds.
"evalLoss": 3.14, # Loss computed on the eval data at the end of iteration.
"index": 42, # Index of the iteration, 0 based.
"learnRate": 3.14, # Learn rate used for this iteration.
+ "principalComponentInfos": [ # The information of the principal components.
+ { # Principal component infos, used only for eigen decomposition based models, e.g., PCA. Ordered by explained_variance in the descending order.
+ "cumulativeExplainedVarianceRatio": 3.14, # The explained_variance is pre-ordered in the descending order to compute the cumulative explained variance ratio.
+ "explainedVariance": 3.14, # Explained variance by this principal component, which is simply the eigenvalue.
+ "explainedVarianceRatio": 3.14, # Explained_variance over the total explained variance.
+ "principalComponentId": "A String", # Id of the principal component.
+ },
+ ],
"trainingLoss": 3.14, # Loss computed on the training data at the end of iteration.
},
],
@@ -4181,7 +4350,10 @@ Method Details
"rangeElementType": # Object with schema name: StandardSqlDataType # The type of the range's elements, if type_kind = "RANGE".
"structType": { # The representation of a SQL STRUCT type. # The fields of this struct, in order, if type_kind = "STRUCT".
"fields": [ # Fields within the struct.
- # Object with schema name: StandardSqlField
+ { # A field or a column.
+ "name": "A String", # Optional. The name of this field. Can be absent for struct fields.
+ "type": # Object with schema name: StandardSqlDataType # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
+ },
],
},
"typeKind": "A String", # Required. The top level type of this field. Can be any GoogleSQL data type (e.g., "INT64", "DATE", "ARRAY").
diff --git a/docs/dyn/bigquery_v2.projects.html b/docs/dyn/bigquery_v2.projects.html
index b4459c7ce7d..222e30c0488 100644
--- a/docs/dyn/bigquery_v2.projects.html
+++ b/docs/dyn/bigquery_v2.projects.html
@@ -78,11 +78,11 @@ Instance Methods
close()
Close httplib2 connections.
- getServiceAccount(projectId)
-Returns the email address of the service account for your project used for interactions with Google Cloud KMS.
+ getServiceAccount(projectId, x__xgafv=None)
+RPC to get the service account for a project used for interactions with Google Cloud KMS
- list(maxResults=None, pageToken=None)
-Lists all projects to which you have been granted any project role.
+ list(maxResults=None, pageToken=None, x__xgafv=None)
+RPC to list projects to which the user has been granted any project role. Users of this method are encouraged to consider the [Resource Manager](https://cloud.google.com/resource-manager/docs/) API, which provides the underlying data for this method and has more capabilities.
Retrieves the next page of results.
@@ -93,48 +93,56 @@ Method Details
- getServiceAccount(projectId)
- Returns the email address of the service account for your project used for interactions with Google Cloud KMS.
+ getServiceAccount(projectId, x__xgafv=None)
+ RPC to get the service account for a project used for interactions with Google Cloud KMS
Args:
- projectId: string, Project ID for which the service account is requested. (required)
+ projectId: string, Required. ID of the project. (required)
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
Returns:
An object of the form:
- {
+ { # Response object of GetServiceAccount
"email": "A String", # The service account email address.
"kind": "bigquery#getServiceAccountResponse", # The resource type of the response.
}
- list(maxResults=None, pageToken=None)
- Lists all projects to which you have been granted any project role.
+ list(maxResults=None, pageToken=None, x__xgafv=None)
+ RPC to list projects to which the user has been granted any project role. Users of this method are encouraged to consider the [Resource Manager](https://cloud.google.com/resource-manager/docs/) API, which provides the underlying data for this method and has more capabilities.
Args:
- maxResults: integer, Maximum number of results to return
- pageToken: string, Page token, returned by a previous call, to request the next page of results
+ maxResults: integer, `maxResults` unset returns all results, up to 50 per page. Additionally, the number of projects in a page may be fewer than `maxResults` because projects are retrieved and then filtered to only projects with the BigQuery API enabled.
+ pageToken: string, Page token, returned by a previous call, to request the next page of results. If not present, no further pages are present.
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
Returns:
An object of the form:
- {
- "etag": "A String", # A hash of the page of results
- "kind": "bigquery#projectList", # The type of list.
- "nextPageToken": "A String", # A token to request the next page of results.
- "projects": [ # Projects to which you have at least READ access.
- {
- "friendlyName": "A String", # A descriptive name for this project.
+ { # Response object of ListProjects
+ "etag": "A String", # A hash of the page of results.
+ "kind": "bigquery#projectList", # The resource type of the response.
+ "nextPageToken": "A String", # Use this token to request the next page of results.
+ "projects": [ # Projects to which the user has at least READ access.
+ { # Information about a single project.
+ "friendlyName": "A String", # A descriptive name for this project. A wrapper is used here because friendlyName can be set to the empty string.
"id": "A String", # An opaque ID of this project.
- "kind": "bigquery#project", # The resource type.
+ "kind": "A String", # The resource type.
"numericId": "A String", # The numeric ID of this project.
- "projectReference": { # A unique reference to this project.
- "projectId": "A String", # [Required] ID of the project. Can be either the numeric ID or the assigned ID of the project.
+ "projectReference": { # A unique reference to a project. # A unique reference to this project.
+ "projectId": "A String", # Required. ID of the project. Can be either the numeric ID or the assigned ID of the project.
},
},
],
- "totalItems": 42, # The total number of projects in the list.
+ "totalItems": 42, # The total number of projects in the page. A wrapper is used here because the field should still be in the response when the value is 0.
}
diff --git a/docs/dyn/bigquery_v2.routines.html b/docs/dyn/bigquery_v2.routines.html
index fe28a9ad3c2..1f973f248d1 100644
--- a/docs/dyn/bigquery_v2.routines.html
+++ b/docs/dyn/bigquery_v2.routines.html
@@ -78,22 +78,22 @@ Instance Methods
close()
Close httplib2 connections.
- delete(projectId, datasetId, routineId)
+ delete(projectId, datasetId, routineId, x__xgafv=None)
Deletes the routine specified by routineId from the dataset.
- get(projectId, datasetId, routineId, readMask=None)
+ get(projectId, datasetId, routineId, readMask=None, x__xgafv=None)
Gets the specified routine resource by routine ID.
- insert(projectId, datasetId, body=None)
+ insert(projectId, datasetId, body=None, x__xgafv=None)
Creates a new routine in the dataset.
- list(projectId, datasetId, filter=None, maxResults=None, pageToken=None, readMask=None)
+ list(projectId, datasetId, filter=None, maxResults=None, pageToken=None, readMask=None, x__xgafv=None)
Lists all routines in the specified dataset. Requires the READER dataset role.
Retrieves the next page of results.
- update(projectId, datasetId, routineId, body=None)
+ update(projectId, datasetId, routineId, body=None, x__xgafv=None)
Updates information in an existing routine. The update method replaces the entire Routine resource.
Method Details
@@ -102,18 +102,22 @@ Method Details
- delete(projectId, datasetId, routineId)
+ delete(projectId, datasetId, routineId, x__xgafv=None)
Deletes the routine specified by routineId from the dataset.
Args:
projectId: string, Required. Project ID of the routine to delete (required)
datasetId: string, Required. Dataset ID of the routine to delete (required)
routineId: string, Required. Routine ID of the routine to delete (required)
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
- get(projectId, datasetId, routineId, readMask=None)
+ get(projectId, datasetId, routineId, readMask=None, x__xgafv=None)
Gets the specified routine resource by routine ID.
Args:
@@ -121,6 +125,10 @@ Method Details
datasetId: string, Required. Dataset ID of the requested routine (required)
routineId: string, Required. Routine ID of the requested routine (required)
readMask: string, If set, only the Routine fields in the field mask are returned in the response. If unset, all Routine fields are returned.
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
Returns:
An object of the form:
@@ -134,7 +142,10 @@ Method Details
"rangeElementType": # Object with schema name: StandardSqlDataType # The type of the range's elements, if type_kind = "RANGE".
"structType": { # The representation of a SQL STRUCT type. # The fields of this struct, in order, if type_kind = "STRUCT".
"fields": [ # Fields within the struct.
- # Object with schema name: StandardSqlField
+ { # A field or a column.
+ "name": "A String", # Optional. The name of this field. Can be absent for struct fields.
+ "type": # Object with schema name: StandardSqlDataType # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
+ },
],
},
"typeKind": "A String", # Required. The top level type of this field. Can be any GoogleSQL data type (e.g., "INT64", "DATE", "ARRAY").
@@ -167,16 +178,7 @@ Method Details
"columns": [ # The columns in this table type
{ # A field or a column.
"name": "A String", # Optional. The name of this field. Can be absent for struct fields.
- "type": { # The data type of a variable such as a function argument. Examples include: * INT64: `{"typeKind": "INT64"}` * ARRAY: { "typeKind": "ARRAY", "arrayElementType": {"typeKind": "STRING"} } * STRUCT>: { "typeKind": "STRUCT", "structType": { "fields": [ { "name": "x", "type": {"typeKind": "STRING"} }, { "name": "y", "type": { "typeKind": "ARRAY", "arrayElementType": {"typeKind": "DATE"} } } ] } } # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
- "arrayElementType": # Object with schema name: StandardSqlDataType # The type of the array's elements, if type_kind = "ARRAY".
- "rangeElementType": # Object with schema name: StandardSqlDataType # The type of the range's elements, if type_kind = "RANGE".
- "structType": { # The representation of a SQL STRUCT type. # The fields of this struct, in order, if type_kind = "STRUCT".
- "fields": [ # Fields within the struct.
- # Object with schema name: StandardSqlField
- ],
- },
- "typeKind": "A String", # Required. The top level type of this field. Can be any GoogleSQL data type (e.g., "INT64", "DATE", "ARRAY").
- },
+ "type": # Object with schema name: StandardSqlDataType # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
},
],
},
@@ -185,12 +187,15 @@ Method Details
"rangeElementType": # Object with schema name: StandardSqlDataType # The type of the range's elements, if type_kind = "RANGE".
"structType": { # The representation of a SQL STRUCT type. # The fields of this struct, in order, if type_kind = "STRUCT".
"fields": [ # Fields within the struct.
- # Object with schema name: StandardSqlField
+ { # A field or a column.
+ "name": "A String", # Optional. The name of this field. Can be absent for struct fields.
+ "type": # Object with schema name: StandardSqlDataType # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
+ },
],
},
"typeKind": "A String", # Required. The top level type of this field. Can be any GoogleSQL data type (e.g., "INT64", "DATE", "ARRAY").
},
- "routineReference": { # Required. Reference describing the ID of this routine.
+ "routineReference": { # Id path of a routine. # Required. Reference describing the ID of this routine.
"datasetId": "A String", # Required. The ID of the dataset containing this routine.
"projectId": "A String", # Required. The ID of the project containing this routine.
"routineId": "A String", # Required. The ID of the routine. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 256 characters.
@@ -224,7 +229,7 @@ Method Details
- insert(projectId, datasetId, body=None)
+ insert(projectId, datasetId, body=None, x__xgafv=None)
Creates a new routine in the dataset.
Args:
@@ -242,7 +247,10 @@ Method Details
"rangeElementType": # Object with schema name: StandardSqlDataType # The type of the range's elements, if type_kind = "RANGE".
"structType": { # The representation of a SQL STRUCT type. # The fields of this struct, in order, if type_kind = "STRUCT".
"fields": [ # Fields within the struct.
- # Object with schema name: StandardSqlField
+ { # A field or a column.
+ "name": "A String", # Optional. The name of this field. Can be absent for struct fields.
+ "type": # Object with schema name: StandardSqlDataType # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
+ },
],
},
"typeKind": "A String", # Required. The top level type of this field. Can be any GoogleSQL data type (e.g., "INT64", "DATE", "ARRAY").
@@ -275,16 +283,7 @@ Method Details
"columns": [ # The columns in this table type
{ # A field or a column.
"name": "A String", # Optional. The name of this field. Can be absent for struct fields.
- "type": { # The data type of a variable such as a function argument. Examples include: * INT64: `{"typeKind": "INT64"}` * ARRAY: { "typeKind": "ARRAY", "arrayElementType": {"typeKind": "STRING"} } * STRUCT>: { "typeKind": "STRUCT", "structType": { "fields": [ { "name": "x", "type": {"typeKind": "STRING"} }, { "name": "y", "type": { "typeKind": "ARRAY", "arrayElementType": {"typeKind": "DATE"} } } ] } } # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
- "arrayElementType": # Object with schema name: StandardSqlDataType # The type of the array's elements, if type_kind = "ARRAY".
- "rangeElementType": # Object with schema name: StandardSqlDataType # The type of the range's elements, if type_kind = "RANGE".
- "structType": { # The representation of a SQL STRUCT type. # The fields of this struct, in order, if type_kind = "STRUCT".
- "fields": [ # Fields within the struct.
- # Object with schema name: StandardSqlField
- ],
- },
- "typeKind": "A String", # Required. The top level type of this field. Can be any GoogleSQL data type (e.g., "INT64", "DATE", "ARRAY").
- },
+ "type": # Object with schema name: StandardSqlDataType # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
},
],
},
@@ -293,12 +292,15 @@ Method Details
"rangeElementType": # Object with schema name: StandardSqlDataType # The type of the range's elements, if type_kind = "RANGE".
"structType": { # The representation of a SQL STRUCT type. # The fields of this struct, in order, if type_kind = "STRUCT".
"fields": [ # Fields within the struct.
- # Object with schema name: StandardSqlField
+ { # A field or a column.
+ "name": "A String", # Optional. The name of this field. Can be absent for struct fields.
+ "type": # Object with schema name: StandardSqlDataType # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
+ },
],
},
"typeKind": "A String", # Required. The top level type of this field. Can be any GoogleSQL data type (e.g., "INT64", "DATE", "ARRAY").
},
- "routineReference": { # Required. Reference describing the ID of this routine.
+ "routineReference": { # Id path of a routine. # Required. Reference describing the ID of this routine.
"datasetId": "A String", # Required. The ID of the dataset containing this routine.
"projectId": "A String", # Required. The ID of the project containing this routine.
"routineId": "A String", # Required. The ID of the routine. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 256 characters.
@@ -330,6 +332,10 @@ Method Details
"strictMode": True or False, # Optional. Use this option to catch many common errors. Error checking is not exhaustive, and successfully creating a procedure doesn't guarantee that the procedure will successfully execute at runtime. If `strictMode` is set to `TRUE`, the procedure body is further checked for errors such as non-existent tables or columns. The `CREATE PROCEDURE` statement fails if the body fails any of these checks. If `strictMode` is set to `FALSE`, the procedure body is checked only for syntax. For procedures that invoke themselves recursively, specify `strictMode=FALSE` to avoid non-existent procedure errors during validation. Default value is `TRUE`.
}
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
Returns:
An object of the form:
@@ -343,7 +349,10 @@ Method Details
"rangeElementType": # Object with schema name: StandardSqlDataType # The type of the range's elements, if type_kind = "RANGE".
"structType": { # The representation of a SQL STRUCT type. # The fields of this struct, in order, if type_kind = "STRUCT".
"fields": [ # Fields within the struct.
- # Object with schema name: StandardSqlField
+ { # A field or a column.
+ "name": "A String", # Optional. The name of this field. Can be absent for struct fields.
+ "type": # Object with schema name: StandardSqlDataType # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
+ },
],
},
"typeKind": "A String", # Required. The top level type of this field. Can be any GoogleSQL data type (e.g., "INT64", "DATE", "ARRAY").
@@ -376,16 +385,7 @@ Method Details
"columns": [ # The columns in this table type
{ # A field or a column.
"name": "A String", # Optional. The name of this field. Can be absent for struct fields.
- "type": { # The data type of a variable such as a function argument. Examples include: * INT64: `{"typeKind": "INT64"}` * ARRAY: { "typeKind": "ARRAY", "arrayElementType": {"typeKind": "STRING"} } * STRUCT>: { "typeKind": "STRUCT", "structType": { "fields": [ { "name": "x", "type": {"typeKind": "STRING"} }, { "name": "y", "type": { "typeKind": "ARRAY", "arrayElementType": {"typeKind": "DATE"} } } ] } } # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
- "arrayElementType": # Object with schema name: StandardSqlDataType # The type of the array's elements, if type_kind = "ARRAY".
- "rangeElementType": # Object with schema name: StandardSqlDataType # The type of the range's elements, if type_kind = "RANGE".
- "structType": { # The representation of a SQL STRUCT type. # The fields of this struct, in order, if type_kind = "STRUCT".
- "fields": [ # Fields within the struct.
- # Object with schema name: StandardSqlField
- ],
- },
- "typeKind": "A String", # Required. The top level type of this field. Can be any GoogleSQL data type (e.g., "INT64", "DATE", "ARRAY").
- },
+ "type": # Object with schema name: StandardSqlDataType # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
},
],
},
@@ -394,12 +394,15 @@ Method Details
"rangeElementType": # Object with schema name: StandardSqlDataType # The type of the range's elements, if type_kind = "RANGE".
"structType": { # The representation of a SQL STRUCT type. # The fields of this struct, in order, if type_kind = "STRUCT".
"fields": [ # Fields within the struct.
- # Object with schema name: StandardSqlField
+ { # A field or a column.
+ "name": "A String", # Optional. The name of this field. Can be absent for struct fields.
+ "type": # Object with schema name: StandardSqlDataType # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
+ },
],
},
"typeKind": "A String", # Required. The top level type of this field. Can be any GoogleSQL data type (e.g., "INT64", "DATE", "ARRAY").
},
- "routineReference": { # Required. Reference describing the ID of this routine.
+ "routineReference": { # Id path of a routine. # Required. Reference describing the ID of this routine.
"datasetId": "A String", # Required. The ID of the dataset containing this routine.
"projectId": "A String", # Required. The ID of the project containing this routine.
"routineId": "A String", # Required. The ID of the routine. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 256 characters.
@@ -433,7 +436,7 @@ Method Details
- list(projectId, datasetId, filter=None, maxResults=None, pageToken=None, readMask=None)
+ list(projectId, datasetId, filter=None, maxResults=None, pageToken=None, readMask=None, x__xgafv=None)
Lists all routines in the specified dataset. Requires the READER dataset role.
Args:
@@ -443,6 +446,10 @@ Method Details
maxResults: integer, The maximum number of results to return in a single response page. Leverage the page tokens to iterate through the entire collection.
pageToken: string, Page token, returned by a previous call, to request the next page of results
readMask: string, If set, then only the Routine fields in the field mask, as well as project_id, dataset_id and routine_id, are returned in the response. If unset, then the following Routine fields are returned: etag, project_id, dataset_id, routine_id, routine_type, creation_time, last_modified_time, and language.
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
Returns:
An object of the form:
@@ -459,7 +466,10 @@ Method Details
"rangeElementType": # Object with schema name: StandardSqlDataType # The type of the range's elements, if type_kind = "RANGE".
"structType": { # The representation of a SQL STRUCT type. # The fields of this struct, in order, if type_kind = "STRUCT".
"fields": [ # Fields within the struct.
- # Object with schema name: StandardSqlField
+ { # A field or a column.
+ "name": "A String", # Optional. The name of this field. Can be absent for struct fields.
+ "type": # Object with schema name: StandardSqlDataType # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
+ },
],
},
"typeKind": "A String", # Required. The top level type of this field. Can be any GoogleSQL data type (e.g., "INT64", "DATE", "ARRAY").
@@ -492,16 +502,7 @@ Method Details
"columns": [ # The columns in this table type
{ # A field or a column.
"name": "A String", # Optional. The name of this field. Can be absent for struct fields.
- "type": { # The data type of a variable such as a function argument. Examples include: * INT64: `{"typeKind": "INT64"}` * ARRAY: { "typeKind": "ARRAY", "arrayElementType": {"typeKind": "STRING"} } * STRUCT>: { "typeKind": "STRUCT", "structType": { "fields": [ { "name": "x", "type": {"typeKind": "STRING"} }, { "name": "y", "type": { "typeKind": "ARRAY", "arrayElementType": {"typeKind": "DATE"} } } ] } } # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
- "arrayElementType": # Object with schema name: StandardSqlDataType # The type of the array's elements, if type_kind = "ARRAY".
- "rangeElementType": # Object with schema name: StandardSqlDataType # The type of the range's elements, if type_kind = "RANGE".
- "structType": { # The representation of a SQL STRUCT type. # The fields of this struct, in order, if type_kind = "STRUCT".
- "fields": [ # Fields within the struct.
- # Object with schema name: StandardSqlField
- ],
- },
- "typeKind": "A String", # Required. The top level type of this field. Can be any GoogleSQL data type (e.g., "INT64", "DATE", "ARRAY").
- },
+ "type": # Object with schema name: StandardSqlDataType # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
},
],
},
@@ -510,12 +511,15 @@ Method Details
"rangeElementType": # Object with schema name: StandardSqlDataType # The type of the range's elements, if type_kind = "RANGE".
"structType": { # The representation of a SQL STRUCT type. # The fields of this struct, in order, if type_kind = "STRUCT".
"fields": [ # Fields within the struct.
- # Object with schema name: StandardSqlField
+ { # A field or a column.
+ "name": "A String", # Optional. The name of this field. Can be absent for struct fields.
+ "type": # Object with schema name: StandardSqlDataType # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
+ },
],
},
"typeKind": "A String", # Required. The top level type of this field. Can be any GoogleSQL data type (e.g., "INT64", "DATE", "ARRAY").
},
- "routineReference": { # Required. Reference describing the ID of this routine.
+ "routineReference": { # Id path of a routine. # Required. Reference describing the ID of this routine.
"datasetId": "A String", # Required. The ID of the dataset containing this routine.
"projectId": "A String", # Required. The ID of the project containing this routine.
"routineId": "A String", # Required. The ID of the routine. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 256 characters.
@@ -565,7 +569,7 @@ Method Details
- update(projectId, datasetId, routineId, body=None)
+ update(projectId, datasetId, routineId, body=None, x__xgafv=None)
Updates information in an existing routine. The update method replaces the entire Routine resource.
Args:
@@ -584,7 +588,10 @@ Method Details
"rangeElementType": # Object with schema name: StandardSqlDataType # The type of the range's elements, if type_kind = "RANGE".
"structType": { # The representation of a SQL STRUCT type. # The fields of this struct, in order, if type_kind = "STRUCT".
"fields": [ # Fields within the struct.
- # Object with schema name: StandardSqlField
+ { # A field or a column.
+ "name": "A String", # Optional. The name of this field. Can be absent for struct fields.
+ "type": # Object with schema name: StandardSqlDataType # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
+ },
],
},
"typeKind": "A String", # Required. The top level type of this field. Can be any GoogleSQL data type (e.g., "INT64", "DATE", "ARRAY").
@@ -617,16 +624,7 @@ Method Details
"columns": [ # The columns in this table type
{ # A field or a column.
"name": "A String", # Optional. The name of this field. Can be absent for struct fields.
- "type": { # The data type of a variable such as a function argument. Examples include: * INT64: `{"typeKind": "INT64"}` * ARRAY: { "typeKind": "ARRAY", "arrayElementType": {"typeKind": "STRING"} } * STRUCT>: { "typeKind": "STRUCT", "structType": { "fields": [ { "name": "x", "type": {"typeKind": "STRING"} }, { "name": "y", "type": { "typeKind": "ARRAY", "arrayElementType": {"typeKind": "DATE"} } } ] } } # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
- "arrayElementType": # Object with schema name: StandardSqlDataType # The type of the array's elements, if type_kind = "ARRAY".
- "rangeElementType": # Object with schema name: StandardSqlDataType # The type of the range's elements, if type_kind = "RANGE".
- "structType": { # The representation of a SQL STRUCT type. # The fields of this struct, in order, if type_kind = "STRUCT".
- "fields": [ # Fields within the struct.
- # Object with schema name: StandardSqlField
- ],
- },
- "typeKind": "A String", # Required. The top level type of this field. Can be any GoogleSQL data type (e.g., "INT64", "DATE", "ARRAY").
- },
+ "type": # Object with schema name: StandardSqlDataType # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
},
],
},
@@ -635,12 +633,15 @@ Method Details
"rangeElementType": # Object with schema name: StandardSqlDataType # The type of the range's elements, if type_kind = "RANGE".
"structType": { # The representation of a SQL STRUCT type. # The fields of this struct, in order, if type_kind = "STRUCT".
"fields": [ # Fields within the struct.
- # Object with schema name: StandardSqlField
+ { # A field or a column.
+ "name": "A String", # Optional. The name of this field. Can be absent for struct fields.
+ "type": # Object with schema name: StandardSqlDataType # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
+ },
],
},
"typeKind": "A String", # Required. The top level type of this field. Can be any GoogleSQL data type (e.g., "INT64", "DATE", "ARRAY").
},
- "routineReference": { # Required. Reference describing the ID of this routine.
+ "routineReference": { # Id path of a routine. # Required. Reference describing the ID of this routine.
"datasetId": "A String", # Required. The ID of the dataset containing this routine.
"projectId": "A String", # Required. The ID of the project containing this routine.
"routineId": "A String", # Required. The ID of the routine. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 256 characters.
@@ -672,6 +673,10 @@ Method Details
"strictMode": True or False, # Optional. Use this option to catch many common errors. Error checking is not exhaustive, and successfully creating a procedure doesn't guarantee that the procedure will successfully execute at runtime. If `strictMode` is set to `TRUE`, the procedure body is further checked for errors such as non-existent tables or columns. The `CREATE PROCEDURE` statement fails if the body fails any of these checks. If `strictMode` is set to `FALSE`, the procedure body is checked only for syntax. For procedures that invoke themselves recursively, specify `strictMode=FALSE` to avoid non-existent procedure errors during validation. Default value is `TRUE`.
}
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
Returns:
An object of the form:
@@ -685,7 +690,10 @@ Method Details
"rangeElementType": # Object with schema name: StandardSqlDataType # The type of the range's elements, if type_kind = "RANGE".
"structType": { # The representation of a SQL STRUCT type. # The fields of this struct, in order, if type_kind = "STRUCT".
"fields": [ # Fields within the struct.
- # Object with schema name: StandardSqlField
+ { # A field or a column.
+ "name": "A String", # Optional. The name of this field. Can be absent for struct fields.
+ "type": # Object with schema name: StandardSqlDataType # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
+ },
],
},
"typeKind": "A String", # Required. The top level type of this field. Can be any GoogleSQL data type (e.g., "INT64", "DATE", "ARRAY").
@@ -718,16 +726,7 @@ Method Details
"columns": [ # The columns in this table type
{ # A field or a column.
"name": "A String", # Optional. The name of this field. Can be absent for struct fields.
- "type": { # The data type of a variable such as a function argument. Examples include: * INT64: `{"typeKind": "INT64"}` * ARRAY: { "typeKind": "ARRAY", "arrayElementType": {"typeKind": "STRING"} } * STRUCT>: { "typeKind": "STRUCT", "structType": { "fields": [ { "name": "x", "type": {"typeKind": "STRING"} }, { "name": "y", "type": { "typeKind": "ARRAY", "arrayElementType": {"typeKind": "DATE"} } } ] } } # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
- "arrayElementType": # Object with schema name: StandardSqlDataType # The type of the array's elements, if type_kind = "ARRAY".
- "rangeElementType": # Object with schema name: StandardSqlDataType # The type of the range's elements, if type_kind = "RANGE".
- "structType": { # The representation of a SQL STRUCT type. # The fields of this struct, in order, if type_kind = "STRUCT".
- "fields": [ # Fields within the struct.
- # Object with schema name: StandardSqlField
- ],
- },
- "typeKind": "A String", # Required. The top level type of this field. Can be any GoogleSQL data type (e.g., "INT64", "DATE", "ARRAY").
- },
+ "type": # Object with schema name: StandardSqlDataType # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
},
],
},
@@ -736,12 +735,15 @@ Method Details
"rangeElementType": # Object with schema name: StandardSqlDataType # The type of the range's elements, if type_kind = "RANGE".
"structType": { # The representation of a SQL STRUCT type. # The fields of this struct, in order, if type_kind = "STRUCT".
"fields": [ # Fields within the struct.
- # Object with schema name: StandardSqlField
+ { # A field or a column.
+ "name": "A String", # Optional. The name of this field. Can be absent for struct fields.
+ "type": # Object with schema name: StandardSqlDataType # Optional. The type of this parameter. Absent if not explicitly specified (e.g., CREATE FUNCTION statement can omit the return type; in this case the output parameter does not have this "type" field).
+ },
],
},
"typeKind": "A String", # Required. The top level type of this field. Can be any GoogleSQL data type (e.g., "INT64", "DATE", "ARRAY").
},
- "routineReference": { # Required. Reference describing the ID of this routine.
+ "routineReference": { # Id path of a routine. # Required. Reference describing the ID of this routine.
"datasetId": "A String", # Required. The ID of the dataset containing this routine.
"projectId": "A String", # Required. The ID of the project containing this routine.
"routineId": "A String", # Required. The ID of the routine. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 256 characters.
diff --git a/docs/dyn/bigquery_v2.rowAccessPolicies.html b/docs/dyn/bigquery_v2.rowAccessPolicies.html
index 2f5ded257aa..c2bbb393a1f 100644
--- a/docs/dyn/bigquery_v2.rowAccessPolicies.html
+++ b/docs/dyn/bigquery_v2.rowAccessPolicies.html
@@ -78,16 +78,16 @@ Instance Methods
close()
Close httplib2 connections.
- getIamPolicy(resource, body=None)
+ getIamPolicy(resource, body=None, x__xgafv=None)
Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.
- list(projectId, datasetId, tableId, pageSize=None, pageToken=None)
+ list(projectId, datasetId, tableId, pageSize=None, pageToken=None, x__xgafv=None)
Lists all row access policies on the specified table.
Retrieves the next page of results.
- testIamPermissions(resource, body=None)
+ testIamPermissions(resource, body=None, x__xgafv=None)
Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a `NOT_FOUND` error. Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may "fail open" without warning.
Method Details
@@ -96,7 +96,7 @@ Method Details
- getIamPolicy(resource, body=None)
+ getIamPolicy(resource, body=None, x__xgafv=None)
Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.
Args:
@@ -110,6 +110,10 @@ Method Details
},
}
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
Returns:
An object of the form:
@@ -139,7 +143,7 @@ Method Details
"members": [ # Specifies the principals requesting access for a Google Cloud resource. `members` can have the following values: * `allUsers`: A special identifier that represents anyone who is on the internet; with or without a Google account. * `allAuthenticatedUsers`: A special identifier that represents anyone who is authenticated with a Google account or a service account. Does not include identities that come from external identity providers (IdPs) through identity federation. * `user:{emailid}`: An email address that represents a specific Google account. For example, `alice@example.com` . * `serviceAccount:{emailid}`: An email address that represents a Google service account. For example, `my-other-app@appspot.gserviceaccount.com`. * `serviceAccount:{projectid}.svc.id.goog[{namespace}/{kubernetes-sa}]`: An identifier for a [Kubernetes service account](https://cloud.google.com/kubernetes-engine/docs/how-to/kubernetes-service-accounts). For example, `my-project.svc.id.goog[my-namespace/my-kubernetes-sa]`. * `group:{emailid}`: An email address that represents a Google group. For example, `admins@example.com`. * `domain:{domain}`: The G Suite domain (primary) that represents all the users of that domain. For example, `google.com` or `example.com`. * `principal://iam.googleapis.com/locations/global/workforcePools/{pool_id}/subject/{subject_attribute_value}`: A single identity in a workforce identity pool. * `principalSet://iam.googleapis.com/locations/global/workforcePools/{pool_id}/group/{group_id}`: All workforce identities in a group. * `principalSet://iam.googleapis.com/locations/global/workforcePools/{pool_id}/attribute.{attribute_name}/{attribute_value}`: All workforce identities with a specific attribute value. * `principalSet://iam.googleapis.com/locations/global/workforcePools/{pool_id}/*`: All identities in a workforce identity pool. * `principal://iam.googleapis.com/projects/{project_number}/locations/global/workloadIdentityPools/{pool_id}/subject/{subject_attribute_value}`: A single identity in a workload identity pool. * `principalSet://iam.googleapis.com/projects/{project_number}/locations/global/workloadIdentityPools/{pool_id}/group/{group_id}`: A workload identity pool group. * `principalSet://iam.googleapis.com/projects/{project_number}/locations/global/workloadIdentityPools/{pool_id}/attribute.{attribute_name}/{attribute_value}`: All identities in a workload identity pool with a certain attribute. * `principalSet://iam.googleapis.com/projects/{project_number}/locations/global/workloadIdentityPools/{pool_id}/*`: All identities in a workload identity pool. * `deleted:user:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a user that has been recently deleted. For example, `alice@example.com?uid=123456789012345678901`. If the user is recovered, this value reverts to `user:{emailid}` and the recovered user retains the role in the binding. * `deleted:serviceAccount:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a service account that has been recently deleted. For example, `my-other-app@appspot.gserviceaccount.com?uid=123456789012345678901`. If the service account is undeleted, this value reverts to `serviceAccount:{emailid}` and the undeleted service account retains the role in the binding. * `deleted:group:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a Google group that has been recently deleted. For example, `admins@example.com?uid=123456789012345678901`. If the group is recovered, this value reverts to `group:{emailid}` and the recovered group retains the role in the binding. * `deleted:principal://iam.googleapis.com/locations/global/workforcePools/{pool_id}/subject/{subject_attribute_value}`: Deleted single identity in a workforce identity pool. For example, `deleted:principal://iam.googleapis.com/locations/global/workforcePools/my-pool-id/subject/my-subject-attribute-value`.
"A String",
],
- "role": "A String", # Role that is assigned to the list of `members`, or principals. For example, `roles/viewer`, `roles/editor`, or `roles/owner`.
+ "role": "A String", # Role that is assigned to the list of `members`, or principals. For example, `roles/viewer`, `roles/editor`, or `roles/owner`. For an overview of the IAM roles and permissions, see the [IAM documentation](https://cloud.google.com/iam/docs/roles-overview). For a list of the available pre-defined roles, see [here](https://cloud.google.com/iam/docs/understanding-roles).
},
],
"etag": "A String", # `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform policy updates in order to avoid race conditions: An `etag` is returned in the response to `getIamPolicy`, and systems are expected to put that etag in the request to `setIamPolicy` to ensure that their change will be applied to the same version of the policy. **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost.
@@ -148,7 +152,7 @@ Method Details
- list(projectId, datasetId, tableId, pageSize=None, pageToken=None)
+ list(projectId, datasetId, tableId, pageSize=None, pageToken=None, x__xgafv=None)
Lists all row access policies on the specified table.
Args:
@@ -157,6 +161,10 @@ Method Details
tableId: string, Required. Table ID of the table to list row access policies. (required)
pageSize: integer, The maximum number of results to return in a single response page. Leverage the page tokens to iterate through the entire collection.
pageToken: string, Page token, returned by a previous call, to request the next page of results.
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
Returns:
An object of the form:
@@ -169,7 +177,7 @@ Method Details
"etag": "A String", # Output only. A hash of this resource.
"filterPredicate": "A String", # Required. A SQL boolean expression that represents the rows defined by this row access policy, similar to the boolean expression in a WHERE clause of a SELECT query on a table. References to other tables, routines, and temporary functions are not supported. Examples: region="EU" date_field = CAST('2019-9-27' as DATE) nullable_field is not NULL numeric_field BETWEEN 1.0 AND 5.0
"lastModifiedTime": "A String", # Output only. The time when this row access policy was last modified, in milliseconds since the epoch.
- "rowAccessPolicyReference": { # Required. Reference describing the ID of this row access policy.
+ "rowAccessPolicyReference": { # Id path of a row access policy. # Required. Reference describing the ID of this row access policy.
"datasetId": "A String", # Required. The ID of the dataset containing this row access policy.
"policyId": "A String", # Required. The ID of the row access policy. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 256 characters.
"projectId": "A String", # Required. The ID of the project containing this row access policy.
@@ -195,7 +203,7 @@ Method Details
- testIamPermissions(resource, body=None)
+ testIamPermissions(resource, body=None, x__xgafv=None)
Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a `NOT_FOUND` error. Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may "fail open" without warning.
Args:
@@ -209,6 +217,10 @@ Method Details
],
}
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
Returns:
An object of the form:
diff --git a/docs/dyn/bigquery_v2.tabledata.html b/docs/dyn/bigquery_v2.tabledata.html
index 8cabc086c65..b3b039167e7 100644
--- a/docs/dyn/bigquery_v2.tabledata.html
+++ b/docs/dyn/bigquery_v2.tabledata.html
@@ -78,11 +78,11 @@ Instance Methods
close()
Close httplib2 connections.
- insertAll(projectId, datasetId, tableId, body=None)
-Streams data into BigQuery one record at a time without needing to run a load job. Requires the WRITER dataset role.
+ insertAll(projectId, datasetId, tableId, body=None, x__xgafv=None)
+Streams data into BigQuery one record at a time without needing to run a load job.
-Retrieves table data from a specified set of rows. Requires the READER dataset role.
+ list(projectId, datasetId, tableId, formatOptions_useInt64Timestamp=None, maxResults=None, pageToken=None, selectedFields=None, startIndex=None, x__xgafv=None)
+List the content of a table in rows.
Retrieves the next page of results.
@@ -93,40 +93,45 @@ Method Details
- insertAll(projectId, datasetId, tableId, body=None)
- Streams data into BigQuery one record at a time without needing to run a load job. Requires the WRITER dataset role.
+ insertAll(projectId, datasetId, tableId, body=None, x__xgafv=None)
+ Streams data into BigQuery one record at a time without needing to run a load job.
Args:
- projectId: string, Project ID of the destination table. (required)
- datasetId: string, Dataset ID of the destination table. (required)
- tableId: string, Table ID of the destination table. (required)
+ projectId: string, Required. Project ID of the destination. (required)
+ datasetId: string, Required. Dataset ID of the destination. (required)
+ tableId: string, Required. Table ID of the destination. (required)
body: object, The request body.
The object takes the form of:
-{
- "ignoreUnknownValues": True or False, # [Optional] Accept rows that contain values that do not match the schema. The unknown values are ignored. Default is false, which treats unknown values as errors.
- "kind": "bigquery#tableDataInsertAllRequest", # The resource type of the response.
- "rows": [ # The rows to insert.
- {
- "insertId": "A String", # [Optional] A unique ID for each row. BigQuery uses this property to detect duplicate insertion requests on a best-effort basis.
- "json": { # Represents a single JSON object. # [Required] A JSON object that contains a row of data. The object's properties and values must match the destination table's schema.
+{ # Request for sending a single streaming insert.
+ "ignoreUnknownValues": True or False, # Optional. Accept rows that contain values that do not match the schema. The unknown values are ignored. Default is false, which treats unknown values as errors.
+ "kind": "bigquery#tableDataInsertAllRequest", # Optional. The resource type of the response. The value is not checked at the backend. Historically, it has been set to "bigquery#tableDataInsertAllRequest" but you are not required to set it.
+ "rows": [
+ { # Data for a single insertion row.
+ "insertId": "A String", # Insertion ID for best-effort deduplication. This feature is not recommended, and users seeking stronger insertion semantics are encouraged to use other mechanisms such as the BigQuery Write API.
+ "json": { # Represents a single JSON object. # Data for a single row.
"a_key": "",
},
},
],
- "skipInvalidRows": True or False, # [Optional] Insert all valid rows of a request, even if invalid rows exist. The default value is false, which causes the entire request to fail if any invalid rows exist.
- "templateSuffix": "A String", # If specified, treats the destination table as a base template, and inserts the rows into an instance table named "{destination}{templateSuffix}". BigQuery will manage creation of the instance table, using the schema of the base template table. See https://cloud.google.com/bigquery/streaming-data-into-bigquery#template-tables for considerations when working with templates tables.
+ "skipInvalidRows": True or False, # Optional. Insert all valid rows of a request, even if invalid rows exist. The default value is false, which causes the entire request to fail if any invalid rows exist.
+ "templateSuffix": "A String", # Optional. If specified, treats the destination table as a base template, and inserts the rows into an instance table named "{destination}{templateSuffix}". BigQuery will manage creation of the instance table, using the schema of the base template table. See https://cloud.google.com/bigquery/streaming-data-into-bigquery#template-tables for considerations when working with templates tables.
+ "traceId": "A String", # Optional. Unique request trace id. Used for debugging purposes only. It is case-sensitive, limited to up to 36 ASCII characters. A UUID is recommended.
}
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
Returns:
An object of the form:
- {
- "insertErrors": [ # An array of errors for rows that were not inserted.
- {
+ { # Describes the format of a streaming insert response.
+ "insertErrors": [ # Describes specific errors encountered while processing the request.
+ { # Error details about a single row's insertion.
"errors": [ # Error information for the row indicated by the index property.
- {
+ { # Error details.
"debugInfo": "A String", # Debugging information. This property is internal to Google and should not be used.
"location": "A String", # Specifies where the error occurred, if present.
"message": "A String", # A human-readable description of the error.
@@ -136,22 +141,27 @@ Method Details
"index": 42, # The index of the row that error applies to.
},
],
- "kind": "bigquery#tableDataInsertAllResponse", # The resource type of the response.
+ "kind": "bigquery#tableDataInsertAllResponse", # Returns "bigquery#tableDataInsertAllResponse".
}
- list(projectId, datasetId, tableId, maxResults=None, pageToken=None, selectedFields=None, startIndex=None)
- Retrieves table data from a specified set of rows. Requires the READER dataset role.
+ list(projectId, datasetId, tableId, formatOptions_useInt64Timestamp=None, maxResults=None, pageToken=None, selectedFields=None, startIndex=None, x__xgafv=None)
+ List the content of a table in rows.
Args:
- projectId: string, Project ID of the table to read (required)
- datasetId: string, Dataset ID of the table to read (required)
- tableId: string, Table ID of the table to read (required)
- maxResults: integer, Maximum number of results to return
- pageToken: string, Page token, returned by a previous call, identifying the result set
- selectedFields: string, List of fields to return (comma-separated). If unspecified, all fields are returned
- startIndex: string, Zero-based index of the starting row to read
+ projectId: string, Required. Project id of the table to list. (required)
+ datasetId: string, Required. Dataset id of the table to list. (required)
+ tableId: string, Required. Table id of the table to list. (required)
+ formatOptions_useInt64Timestamp: boolean, Optional. Output timestamp as usec int64. Default is false.
+ maxResults: integer, Row limit of the table.
+ pageToken: string, To retrieve the next page of table data, set this field to the string provided in the pageToken field of the response body from your previous call to tabledata.list.
+ selectedFields: string, Subset of fields to return, supports select into sub fields. Example: selected_fields = "a,e.d.f";
+ startIndex: string, Start row index of the table.
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
Returns:
An object of the form:
@@ -169,7 +179,7 @@ Method Details
],
},
],
- "totalRows": "A String", # The total number of rows in the complete table.
+ "totalRows": "A String", # Total rows of the entire table. In order to show default value 0 we have to present it as string.
}
diff --git a/docs/dyn/bigquery_v2.tables.html b/docs/dyn/bigquery_v2.tables.html
index 7f6eaf18e56..11b306b1130 100644
--- a/docs/dyn/bigquery_v2.tables.html
+++ b/docs/dyn/bigquery_v2.tables.html
@@ -78,35 +78,35 @@ Instance Methods
close()
Close httplib2 connections.
- delete(projectId, datasetId, tableId)
+ delete(projectId, datasetId, tableId, x__xgafv=None)
Deletes the table specified by tableId from the dataset. If the table contains data, all the data will be deleted.
- get(projectId, datasetId, tableId, selectedFields=None, view=None)
+ get(projectId, datasetId, tableId, selectedFields=None, view=None, x__xgafv=None)
Gets the specified table resource by table ID. This method does not return the data in the table, it only returns the table resource, which describes the structure of this table.
- getIamPolicy(resource, body=None)
+ getIamPolicy(resource, body=None, x__xgafv=None)
Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.
- insert(projectId, datasetId, body=None)
+ insert(projectId, datasetId, body=None, x__xgafv=None)
Creates a new, empty table in the dataset.
- list(projectId, datasetId, maxResults=None, pageToken=None)
+ list(projectId, datasetId, maxResults=None, pageToken=None, x__xgafv=None)
Lists all tables in the specified dataset. Requires the READER dataset role.
Retrieves the next page of results.
- patch(projectId, datasetId, tableId, autodetect_schema=None, body=None)
-Updates information in an existing table. The update method replaces the entire table resource, whereas the patch method only replaces fields that are provided in the submitted table resource. This method supports patch semantics.
+ patch(projectId, datasetId, tableId, autodetect_schema=None, body=None, x__xgafv=None)
+Updates information in an existing table. The update method replaces the entire table resource, whereas the patch method only replaces fields that are provided in the submitted table resource. This method supports RFC5789 patch semantics.
- setIamPolicy(resource, body=None)
+ setIamPolicy(resource, body=None, x__xgafv=None)
Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.
- testIamPermissions(resource, body=None)
+ testIamPermissions(resource, body=None, x__xgafv=None)
Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a `NOT_FOUND` error. Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may "fail open" without warning.
- update(projectId, datasetId, tableId, autodetect_schema=None, body=None)
-Updates information in an existing table. The update method replaces the entire table resource, whereas the patch method only replaces fields that are provided in the submitted table resource.
+ update(projectId, datasetId, tableId, autodetect_schema=None, body=None, x__xgafv=None)
+Updates information in an existing table. The update method replaces the entire Table resource, whereas the patch method only replaces fields that are provided in the submitted Table resource.
Method Details
close()
@@ -114,207 +114,226 @@ Method Details
- delete(projectId, datasetId, tableId)
+ delete(projectId, datasetId, tableId, x__xgafv=None)
Deletes the table specified by tableId from the dataset. If the table contains data, all the data will be deleted.
Args:
- projectId: string, Project ID of the table to delete (required)
- datasetId: string, Dataset ID of the table to delete (required)
- tableId: string, Table ID of the table to delete (required)
+ projectId: string, Required. Project ID of the table to delete (required)
+ datasetId: string, Required. Dataset ID of the table to delete (required)
+ tableId: string, Required. Table ID of the table to delete (required)
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
- get(projectId, datasetId, tableId, selectedFields=None, view=None)
+ get(projectId, datasetId, tableId, selectedFields=None, view=None, x__xgafv=None)
Gets the specified table resource by table ID. This method does not return the data in the table, it only returns the table resource, which describes the structure of this table.
Args:
- projectId: string, Project ID of the requested table (required)
- datasetId: string, Dataset ID of the requested table (required)
- tableId: string, Table ID of the requested table (required)
- selectedFields: string, List of fields to return (comma-separated). If unspecified, all fields are returned
- view: string, Specifies the view that determines which table information is returned. By default, basic table information and storage statistics (STORAGE_STATS) are returned.
+ projectId: string, Required. Project ID of the requested table (required)
+ datasetId: string, Required. Dataset ID of the requested table (required)
+ tableId: string, Required. Table ID of the requested table (required)
+ selectedFields: string, List of table schema fields to return (comma-separated). If unspecified, all fields are returned. A fieldMask cannot be used here because the fields will automatically be converted from camelCase to snake_case and the conversion will fail if there are underscores. Since these are fields in BigQuery table schemas, underscores are allowed.
+ view: string, Optional. Specifies the view that determines which table information is returned. By default, basic table information and storage statistics (STORAGE_STATS) are returned.
Allowed values
+ TABLE_METADATA_VIEW_UNSPECIFIED - The default value. Default to the STORAGE_STATS view.
BASIC - Includes basic table information including schema and partitioning specification. This view does not include storage statistics such as numRows or numBytes. This view is significantly more efficient and should be used to support high query rates.
- FULL - Includes all table information, including storage statistics. It returns same information as STORAGE_STATS view, but may contain additional information in the future.
STORAGE_STATS - Includes all information in the BASIC view as well as storage statistics (numBytes, numLongTermBytes, numRows and lastModifiedTime).
- TABLE_METADATA_VIEW_UNSPECIFIED - The default value. Default to the STORAGE_STATS view.
+ FULL - Includes all table information, including storage statistics. It returns same information as STORAGE_STATS view, but may contain additional information in the future.
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
Returns:
An object of the form:
{
- "biglakeConfiguration": { # [Optional] Specifies the configuration of a BigLake managed table.
- "connectionId": "A String", # [Required] Required and immutable. Credential reference for accessing external storage system. Normalized as project_id.location_id.connection_id.
- "fileFormat": "A String", # [Required] Required and immutable. Open source file format that the table data is stored in. Currently only PARQUET is supported.
- "storageUri": "A String", # [Required] Required and immutable. Fully qualified location prefix of the external folder where data is stored. Normalized to standard format: "gs:////". Starts with "gs://" rather than "/bigstore/". Ends with "/". Does not contain "*". See also BigLakeStorageMetadata on how it is used.
- "tableFormat": "A String", # [Required] Required and immutable. Open source file format that the table data is stored in. Currently only PARQUET is supported.
- },
- "cloneDefinition": { # [Output-only] Clone definition.
- "baseTableReference": { # [Required] Reference describing the ID of the table that was cloned.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- },
- "cloneTime": "A String", # [Required] The time at which the base table was cloned. This value is reported in the JSON response using RFC3339 format.
- },
- "clustering": { # [Beta] Clustering specification for the table. Must be specified with partitioning, data in the table will be first partitioned and subsequently clustered.
- "fields": [ # [Repeated] One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. When you cluster a table using multiple columns, the order of columns you specify is important. The order of the specified columns determines the sort order of the data.
+ "biglakeConfiguration": { # Configuration for BigLake managed tables. # Optional. Specifies the configuration of a BigLake managed table.
+ "connectionId": "A String", # Required. The connection specifying the credentials to be used to read and write to external storage, such as Cloud Storage. The connection_id can have the form "<project\_id>.<location\_id>.<connection\_id>" or "projects/<project\_id>/locations/<location\_id>/connections/<connection\_id>".
+ "fileFormat": "A String", # Required. The file format the table data is stored in.
+ "storageUri": "A String", # Required. The fully qualified location prefix of the external folder where table data is stored. The '*' wildcard character is not allowed. The URI should be in the format "gs://bucket/path_to_table/"
+ "tableFormat": "A String", # Required. The table format the metadata only snapshots are stored in.
+ },
+ "cloneDefinition": { # Information about base table and clone time of a table clone. # Output only. Contains information about the clone. This value is set via the clone operation.
+ "baseTableReference": { # Required. Reference describing the ID of the table that was cloned.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ "cloneTime": "A String", # Required. The time at which the base table was cloned. This value is reported in the JSON response using RFC3339 format.
+ },
+ "clustering": { # Configures table clustering. # Clustering specification for the table. Must be specified with time-based partitioning, data in the table will be first partitioned and subsequently clustered.
+ "fields": [ # One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. The ordering of the clustering fields should be prioritized from most to least important for filtering purposes. Additional information on limitations can be found here: https://cloud.google.com/bigquery/docs/creating-clustered-tables#limitations
"A String",
],
},
- "creationTime": "A String", # [Output-only] The time when this table was created, in milliseconds since the epoch.
- "defaultCollation": "A String", # [Output-only] The default collation of the table.
- "defaultRoundingMode": "A String", # [Output-only] The default rounding mode of the table.
- "description": "A String", # [Optional] A user-friendly description of this table.
+ "creationTime": "A String", # Output only. The time when this table was created, in milliseconds since the epoch.
+ "defaultCollation": "A String", # Optional. Defines the default collation specification of new STRING fields in the table. During table creation or update, if a STRING field is added to this table without explicit collation specified, then the table inherits the table default collation. A change to this field affects only fields added afterwards, and does not alter the existing fields. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.
+ "defaultRoundingMode": "A String", # Optional. Defines the default rounding mode specification of new decimal fields (NUMERIC OR BIGNUMERIC) in the table. During table creation or update, if a decimal field is added to this table without an explicit rounding mode specified, then the field inherits the table default rounding mode. Changing this field doesn't affect existing fields.
+ "description": "A String", # Optional. A user-friendly description of this table.
"encryptionConfiguration": { # Custom encryption configuration (e.g., Cloud KMS keys).
"kmsKeyName": "A String", # Optional. Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key.
},
- "etag": "A String", # [Output-only] A hash of the table metadata. Used to ensure there were no concurrent modifications to the resource when attempting an update. Not guaranteed to change when the table contents or the fields numRows, numBytes, numLongTermBytes or lastModifiedTime change.
- "expirationTime": "A String", # [Optional] The time when this table expires, in milliseconds since the epoch. If not present, the table will persist indefinitely. Expired tables will be deleted and their storage reclaimed. The defaultTableExpirationMs property of the encapsulating dataset can be used to set a default expirationTime on newly created tables.
- "externalDataConfiguration": { # [Optional] Describes the data format, location, and other properties of a table stored outside of BigQuery. By defining these properties, the data source can then be queried as if it were a standard BigQuery table.
+ "etag": "A String", # Output only. A hash of this resource.
+ "expirationTime": "A String", # Optional. The time when this table expires, in milliseconds since the epoch. If not present, the table will persist indefinitely. Expired tables will be deleted and their storage reclaimed. The defaultTableExpirationMs property of the encapsulating dataset can be used to set a default expirationTime on newly created tables.
+ "externalDataConfiguration": { # Optional. Describes the data format, location, and other properties of a table stored outside of BigQuery. By defining these properties, the data source can then be queried as if it were a standard BigQuery table.
"autodetect": True or False, # Try to detect schema and format options automatically. Any option specified explicitly will be honored.
- "avroOptions": { # Additional properties to set if sourceFormat is set to Avro.
- "useAvroLogicalTypes": True or False, # [Optional] If sourceFormat is set to "AVRO", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER).
- },
- "bigtableOptions": { # [Optional] Additional options if sourceFormat is set to BIGTABLE.
- "columnFamilies": [ # [Optional] List of column families to expose in the table schema along with their types. This list restricts the column families that can be referenced in queries and specifies their value types. You can use this list to do type conversions - see the 'type' field for more details. If you leave this list empty, all column families are present in the table schema and their values are read as BYTES. During a query only the column families referenced in that query are read from Bigtable.
- {
- "columns": [ # [Optional] Lists of columns that should be exposed as individual fields as opposed to a list of (column name, value) pairs. All columns whose qualifier matches a qualifier in this list can be accessed as .. Other columns can be accessed as a list through .Column field.
- {
- "encoding": "A String", # [Optional] The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. 'encoding' can also be set at the column family level. However, the setting at this level takes precedence if 'encoding' is set at both levels.
- "fieldName": "A String", # [Optional] If the qualifier is not a valid BigQuery field identifier i.e. does not match [a-zA-Z][a-zA-Z0-9_]*, a valid identifier must be provided as the column field name and is used as field name in queries.
- "onlyReadLatest": True or False, # [Optional] If this is set, only the latest version of value in this column are exposed. 'onlyReadLatest' can also be set at the column family level. However, the setting at this level takes precedence if 'onlyReadLatest' is set at both levels.
- "qualifierEncoded": "A String", # [Required] Qualifier of the column. Columns in the parent column family that has this exact qualifier are exposed as . field. If the qualifier is valid UTF-8 string, it can be specified in the qualifier_string field. Otherwise, a base-64 encoded value must be set to qualifier_encoded. The column field name is the same as the column qualifier. However, if the qualifier is not a valid BigQuery field identifier i.e. does not match [a-zA-Z][a-zA-Z0-9_]*, a valid identifier must be provided as field_name.
- "qualifierString": "A String",
- "type": "A String", # [Optional] The type to convert the value in cells of this column. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive) - BYTES STRING INTEGER FLOAT BOOLEAN Default type is BYTES. 'type' can also be set at the column family level. However, the setting at this level takes precedence if 'type' is set at both levels.
+ "avroOptions": { # Options for external data sources. # Optional. Additional properties to set if sourceFormat is set to AVRO.
+ "useAvroLogicalTypes": True or False, # Optional. If sourceFormat is set to "AVRO", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER).
+ },
+ "bigtableOptions": { # Options specific to Google Cloud Bigtable data sources. # Optional. Additional options if sourceFormat is set to BIGTABLE.
+ "columnFamilies": [ # Optional. List of column families to expose in the table schema along with their types. This list restricts the column families that can be referenced in queries and specifies their value types. You can use this list to do type conversions - see the 'type' field for more details. If you leave this list empty, all column families are present in the table schema and their values are read as BYTES. During a query only the column families referenced in that query are read from Bigtable.
+ { # Information related to a Bigtable column family.
+ "columns": [ # Optional. Lists of columns that should be exposed as individual fields as opposed to a list of (column name, value) pairs. All columns whose qualifier matches a qualifier in this list can be accessed as .. Other columns can be accessed as a list through .Column field.
+ { # Information related to a Bigtable column.
+ "encoding": "A String", # Optional. The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. 'encoding' can also be set at the column family level. However, the setting at this level takes precedence if 'encoding' is set at both levels.
+ "fieldName": "A String", # Optional. If the qualifier is not a valid BigQuery field identifier i.e. does not match a-zA-Z*, a valid identifier must be provided as the column field name and is used as field name in queries.
+ "onlyReadLatest": True or False, # Optional. If this is set, only the latest version of value in this column are exposed. 'onlyReadLatest' can also be set at the column family level. However, the setting at this level takes precedence if 'onlyReadLatest' is set at both levels.
+ "qualifierEncoded": "A String", # [Required] Qualifier of the column. Columns in the parent column family that has this exact qualifier are exposed as . field. If the qualifier is valid UTF-8 string, it can be specified in the qualifier_string field. Otherwise, a base-64 encoded value must be set to qualifier_encoded. The column field name is the same as the column qualifier. However, if the qualifier is not a valid BigQuery field identifier i.e. does not match a-zA-Z*, a valid identifier must be provided as field_name.
+ "qualifierString": "A String", # Qualifier string.
+ "type": "A String", # Optional. The type to convert the value in cells of this column. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive): * BYTES * STRING * INTEGER * FLOAT * BOOLEAN * JSON Default type is BYTES. 'type' can also be set at the column family level. However, the setting at this level takes precedence if 'type' is set at both levels.
},
],
- "encoding": "A String", # [Optional] The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. This can be overridden for a specific column by listing that column in 'columns' and specifying an encoding for it.
+ "encoding": "A String", # Optional. The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. This can be overridden for a specific column by listing that column in 'columns' and specifying an encoding for it.
"familyId": "A String", # Identifier of the column family.
- "onlyReadLatest": True or False, # [Optional] If this is set only the latest version of value are exposed for all columns in this column family. This can be overridden for a specific column by listing that column in 'columns' and specifying a different setting for that column.
- "type": "A String", # [Optional] The type to convert the value in cells of this column family. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive) - BYTES STRING INTEGER FLOAT BOOLEAN Default type is BYTES. This can be overridden for a specific column by listing that column in 'columns' and specifying a type for it.
+ "onlyReadLatest": True or False, # Optional. If this is set only the latest version of value are exposed for all columns in this column family. This can be overridden for a specific column by listing that column in 'columns' and specifying a different setting for that column.
+ "type": "A String", # Optional. The type to convert the value in cells of this column family. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive): * BYTES * STRING * INTEGER * FLOAT * BOOLEAN * JSON Default type is BYTES. This can be overridden for a specific column by listing that column in 'columns' and specifying a type for it.
},
],
- "ignoreUnspecifiedColumnFamilies": True or False, # [Optional] If field is true, then the column families that are not specified in columnFamilies list are not exposed in the table schema. Otherwise, they are read with BYTES type values. The default value is false.
- "readRowkeyAsString": True or False, # [Optional] If field is true, then the rowkey column families will be read and converted to string. Otherwise they are read with BYTES type values and users need to manually cast them with CAST if necessary. The default value is false.
- },
- "compression": "A String", # [Optional] The compression type of the data source. Possible values include GZIP and NONE. The default value is NONE. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups and Avro formats.
- "connectionId": "A String", # [Optional, Trusted Tester] Connection for external data source.
- "csvOptions": { # Additional properties to set if sourceFormat is set to CSV.
- "allowJaggedRows": True or False, # [Optional] Indicates if BigQuery should accept rows that are missing trailing optional columns. If true, BigQuery treats missing trailing columns as null values. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false.
- "allowQuotedNewlines": True or False, # [Optional] Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false.
- "encoding": "A String", # [Optional] The character encoding of the data. The supported values are UTF-8 or ISO-8859-1. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the quote and fieldDelimiter properties.
- "fieldDelimiter": "A String", # [Optional] The separator for fields in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. BigQuery also supports the escape sequence "\t" to specify a tab separator. The default value is a comma (',').
- "nullMarker": "A String", # [Optional] An custom string that will represent a NULL value in CSV import data.
- "preserveAsciiControlCharacters": True or False, # [Optional] Preserves the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\x00' to '\x1F') when loading from CSV. Only applicable to CSV, ignored for other formats.
- "quote": """, # [Optional] The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ('"'). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true.
- "skipLeadingRows": "A String", # [Optional] The number of rows at the top of a CSV file that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
- },
- "decimalTargetTypes": [ # [Optional] Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown. Example: Suppose the value of this field is ["NUMERIC", "BIGNUMERIC"]. If (precision,scale) is: (38,9) -> NUMERIC; (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits); (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits); (76,38) -> BIGNUMERIC; (77,38) -> BIGNUMERIC (error if value exeeds supported range). This field cannot contain duplicate types. The order of the types in this field is ignored. For example, ["BIGNUMERIC", "NUMERIC"] is the same as ["NUMERIC", "BIGNUMERIC"] and NUMERIC always takes precedence over BIGNUMERIC. Defaults to ["NUMERIC", "STRING"] for ORC and ["NUMERIC"] for the other file formats.
+ "ignoreUnspecifiedColumnFamilies": True or False, # Optional. If field is true, then the column families that are not specified in columnFamilies list are not exposed in the table schema. Otherwise, they are read with BYTES type values. The default value is false.
+ "outputColumnFamiliesAsJson": True or False, # Optional. If field is true, then each column family will be read as a single JSON column. Otherwise they are read as a repeated cell structure containing timestamp/value tuples. The default value is false.
+ "readRowkeyAsString": True or False, # Optional. If field is true, then the rowkey column families will be read and converted to string. Otherwise they are read with BYTES type values and users need to manually cast them with CAST if necessary. The default value is false.
+ },
+ "compression": "A String", # Optional. The compression type of the data source. Possible values include GZIP and NONE. The default value is NONE. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups, Avro, ORC and Parquet formats. An empty string is an invalid value.
+ "connectionId": "A String", # Optional. The connection specifying the credentials to be used to read external storage, such as Azure Blob, Cloud Storage, or S3. The connection_id can have the form "<project\_id>.<location\_id>.<connection\_id>" or "projects/<project\_id>/locations/<location\_id>/connections/<connection\_id>".
+ "csvOptions": { # Information related to a CSV data source. # Optional. Additional properties to set if sourceFormat is set to CSV.
+ "allowJaggedRows": True or False, # Optional. Indicates if BigQuery should accept rows that are missing trailing optional columns. If true, BigQuery treats missing trailing columns as null values. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false.
+ "allowQuotedNewlines": True or False, # Optional. Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false.
+ "encoding": "A String", # Optional. The character encoding of the data. The supported values are UTF-8, ISO-8859-1, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the quote and fieldDelimiter properties.
+ "fieldDelimiter": "A String", # Optional. The separator character for fields in a CSV file. The separator is interpreted as a single byte. For files encoded in ISO-8859-1, any single character can be used as a separator. For files encoded in UTF-8, characters represented in decimal range 1-127 (U+0001-U+007F) can be used without any modification. UTF-8 characters encoded with multiple bytes (i.e. U+0080 and above) will have only the first byte used for separating fields. The remaining bytes will be treated as a part of the field. BigQuery also supports the escape sequence "\t" (U+0009) to specify a tab separator. The default value is comma (",", U+002C).
+ "nullMarker": "A String", # [Optional] A custom string that will represent a NULL value in CSV import data.
+ "preserveAsciiControlCharacters": True or False, # Optional. Indicates if the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\x00' to '\x1F') are preserved.
+ "quote": """, # Optional. The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ("). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true. To include the specific quote character within a quoted value, precede it with an additional matching quote character. For example, if you want to escape the default character ' " ', use ' "" '.
+ "skipLeadingRows": "A String", # Optional. The number of rows at the top of a CSV file that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
+ },
+ "decimalTargetTypes": [ # Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown. Example: Suppose the value of this field is ["NUMERIC", "BIGNUMERIC"]. If (precision,scale) is: * (38,9) -> NUMERIC; * (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits); * (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits); * (76,38) -> BIGNUMERIC; * (77,38) -> BIGNUMERIC (error if value exeeds supported range). This field cannot contain duplicate types. The order of the types in this field is ignored. For example, ["BIGNUMERIC", "NUMERIC"] is the same as ["NUMERIC", "BIGNUMERIC"] and NUMERIC always takes precedence over BIGNUMERIC. Defaults to ["NUMERIC", "STRING"] for ORC and ["NUMERIC"] for the other file formats.
"A String",
],
- "fileSetSpecType": "A String", # [Optional] Specifies how source URIs are interpreted for constructing the file set to load. By default source URIs are expanded against the underlying storage. Other options include specifying manifest files. Only applicable to object storage systems.
- "googleSheetsOptions": { # [Optional] Additional options if sourceFormat is set to GOOGLE_SHEETS.
- "range": "A String", # [Optional] Range of a sheet to query from. Only used when non-empty. Typical format: sheet_name!top_left_cell_id:bottom_right_cell_id For example: sheet1!A1:B20
- "skipLeadingRows": "A String", # [Optional] The number of rows at the top of a sheet that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows that should be skipped. When autodetect is on, behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
+ "fileSetSpecType": "A String", # Optional. Specifies how source URIs are interpreted for constructing the file set to load. By default source URIs are expanded against the underlying storage. Other options include specifying manifest files. Only applicable to object storage systems.
+ "googleSheetsOptions": { # Options specific to Google Sheets data sources. # Optional. Additional options if sourceFormat is set to GOOGLE_SHEETS.
+ "range": "A String", # Optional. Range of a sheet to query from. Only used when non-empty. Typical format: sheet_name!top_left_cell_id:bottom_right_cell_id For example: sheet1!A1:B20
+ "skipLeadingRows": "A String", # Optional. The number of rows at the top of a sheet that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
},
- "hivePartitioningOptions": { # [Optional] Options to configure hive partitioning support.
- "fields": [ # [Output-only] For permanent external tables, this field is populated with the hive partition keys in the order they were inferred. The types of the partition keys can be deduced by checking the table schema (which will include the partition keys). Not every API will populate this field in the output. For example, Tables.Get will populate it, but Tables.List will not contain this field.
+ "hivePartitioningOptions": { # Options for configuring hive partitioning detect. # Optional. When set, configures hive partitioning support. Not all storage formats support hive partitioning -- requesting hive partitioning on an unsupported format will lead to an error, as will providing an invalid specification.
+ "fields": [ # Output only. For permanent external tables, this field is populated with the hive partition keys in the order they were inferred. The types of the partition keys can be deduced by checking the table schema (which will include the partition keys). Not every API will populate this field in the output. For example, Tables.Get will populate it, but Tables.List will not contain this field.
"A String",
],
- "mode": "A String", # [Optional] When set, what mode of hive partitioning to use when reading data. The following modes are supported. (1) AUTO: automatically infer partition key name(s) and type(s). (2) STRINGS: automatically infer partition key name(s). All types are interpreted as strings. (3) CUSTOM: partition key schema is encoded in the source URI prefix. Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported types include: AVRO, CSV, JSON, ORC and Parquet.
- "requirePartitionFilter": True or False, # [Optional] If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. Note that this field should only be true when creating a permanent external table or querying a temporary external table. Hive-partitioned loads with requirePartitionFilter explicitly set to true will fail.
- "sourceUriPrefix": "A String", # [Optional] When hive partition detection is requested, a common prefix for all source uris should be supplied. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout. gs://bucket/path_to_table/dt=2019-01-01/country=BR/id=7/file.avro gs://bucket/path_to_table/dt=2018-12-31/country=CA/id=3/file.avro When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/ (trailing slash does not matter).
- },
- "ignoreUnknownValues": True or False, # [Optional] Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names Google Cloud Bigtable: This setting is ignored. Google Cloud Datastore backups: This setting is ignored. Avro: This setting is ignored.
- "jsonOptions": { # Additional properties to set if `sourceFormat` is set to `NEWLINE_DELIMITED_JSON`.
- "encoding": "A String", # [Optional] The character encoding of the data. The supported values are UTF-8, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8.
- },
- "maxBadRecords": 42, # [Optional] The maximum number of bad records that BigQuery can ignore when reading data. If the number of bad records exceeds this value, an invalid error is returned in the job result. This is only valid for CSV, JSON, and Google Sheets. The default value is 0, which requires that all records are valid. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups and Avro formats.
- "metadataCacheMode": "A String", # [Optional] Metadata Cache Mode for the table. Set this to enable caching of metadata from external data source.
- "objectMetadata": "A String", # ObjectMetadata is used to create Object Tables. Object Tables contain a listing of objects (with their metadata) found at the source_uris. If ObjectMetadata is set, source_format should be omitted. Currently SIMPLE is the only supported Object Metadata type.
- "parquetOptions": { # Additional properties to set if sourceFormat is set to Parquet.
- "enableListInference": True or False, # [Optional] Indicates whether to use schema inference specifically for Parquet LIST logical type.
- "enumAsString": True or False, # [Optional] Indicates whether to infer Parquet ENUM logical type as STRING instead of BYTES by default.
- },
- "referenceFileSchemaUri": "A String", # [Optional] Provide a referencing file with the expected table schema. Enabled for the format: AVRO, PARQUET, ORC.
- "schema": { # [Optional] The schema for the data. Schema is required for CSV and JSON formats. Schema is disallowed for Google Cloud Bigtable, Cloud Datastore backups, and Avro formats.
+ "mode": "A String", # Optional. When set, what mode of hive partitioning to use when reading data. The following modes are supported: * AUTO: automatically infer partition key name(s) and type(s). * STRINGS: automatically infer partition key name(s). All types are strings. * CUSTOM: partition key schema is encoded in the source URI prefix. Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported formats are: JSON, CSV, ORC, Avro and Parquet.
+ "requirePartitionFilter": false, # Optional. If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. Note that this field should only be true when creating a permanent external table or querying a temporary external table. Hive-partitioned loads with require_partition_filter explicitly set to true will fail.
+ "sourceUriPrefix": "A String", # Optional. When hive partition detection is requested, a common prefix for all source uris must be required. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout: gs://bucket/path_to_table/dt=2019-06-01/country=USA/id=7/file.avro gs://bucket/path_to_table/dt=2019-05-31/country=CA/id=3/file.avro When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/. CUSTOM detection requires encoding the partitioning schema immediately after the common prefix. For CUSTOM, any of * gs://bucket/path_to_table/{dt:DATE}/{country:STRING}/{id:INTEGER} * gs://bucket/path_to_table/{dt:STRING}/{country:STRING}/{id:INTEGER} * gs://bucket/path_to_table/{dt:DATE}/{country:STRING}/{id:STRING} would all be valid source URI prefixes.
+ },
+ "ignoreUnknownValues": True or False, # Optional. Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names Google Cloud Bigtable: This setting is ignored. Google Cloud Datastore backups: This setting is ignored. Avro: This setting is ignored. ORC: This setting is ignored. Parquet: This setting is ignored.
+ "jsonExtension": "A String", # Optional. Load option to be used together with source_format newline-delimited JSON to indicate that a variant of JSON is being loaded. To load newline-delimited GeoJSON, specify GEOJSON (and source_format must be set to NEWLINE_DELIMITED_JSON).
+ "jsonOptions": { # Json Options for load and make external tables. # Optional. Additional properties to set if sourceFormat is set to JSON.
+ "encoding": "A String", # Optional. The character encoding of the data. The supported values are UTF-8, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8.
+ },
+ "maxBadRecords": 42, # Optional. The maximum number of bad records that BigQuery can ignore when reading data. If the number of bad records exceeds this value, an invalid error is returned in the job result. The default value is 0, which requires that all records are valid. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups, Avro, ORC and Parquet formats.
+ "metadataCacheMode": "A String", # Optional. Metadata Cache Mode for the table. Set this to enable caching of metadata from external data source.
+ "objectMetadata": "A String", # Optional. ObjectMetadata is used to create Object Tables. Object Tables contain a listing of objects (with their metadata) found at the source_uris. If ObjectMetadata is set, source_format should be omitted. Currently SIMPLE is the only supported Object Metadata type.
+ "parquetOptions": { # Parquet Options for load and make external tables. # Optional. Additional properties to set if sourceFormat is set to PARQUET.
+ "enableListInference": True or False, # Optional. Indicates whether to use schema inference specifically for Parquet LIST logical type.
+ "enumAsString": True or False, # Optional. Indicates whether to infer Parquet ENUM logical type as STRING instead of BYTES by default.
+ },
+ "referenceFileSchemaUri": "A String", # Optional. When creating an external table, the user can provide a reference file with the table schema. This is enabled for the following formats: AVRO, PARQUET, ORC.
+ "schema": { # Schema of a table # Optional. The schema for the data. Schema is required for CSV and JSON formats if autodetect is not on. Schema is disallowed for Google Cloud Bigtable, Cloud Datastore backups, Avro, ORC and Parquet formats.
"fields": [ # Describes the fields in a table.
- {
- "categories": { # [Optional] The categories attached to this field, used for field-level access control.
- "names": [ # A list of category resource names. For example, "projects/1/taxonomies/2/categories/3". At most 5 categories are allowed.
+ { # A field in TableSchema
+ "categories": { # Deprecated.
+ "names": [ # Deprecated.
"A String",
],
},
- "collation": "A String", # Optional. Collation specification of the field. It only can be set on string type field.
- "defaultValueExpression": "A String", # Optional. A SQL expression to specify the default value for this field. It can only be set for top level fields (columns). You can use struct or array expression to specify default value for the entire struct or array. The valid SQL expressions are: - Literals for all data types, including STRUCT and ARRAY. - Following functions: - CURRENT_TIMESTAMP - CURRENT_TIME - CURRENT_DATE - CURRENT_DATETIME - GENERATE_UUID - RAND - SESSION_USER - ST_GEOGPOINT - Struct or array composed with the above allowed functions, for example, [CURRENT_DATE(), DATE '2020-01-01']
- "description": "A String", # [Optional] The field description. The maximum length is 1,024 characters.
- "fields": [ # [Optional] Describes the nested schema fields if the type property is set to RECORD.
+ "collation": "A String", # Optional. Field collation can be set only when the type of field is STRING. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.
+ "defaultValueExpression": "A String", # Optional. A SQL expression to specify the [default value] (https://cloud.google.com/bigquery/docs/default-values) for this field.
+ "description": "A String", # Optional. The field description. The maximum length is 1,024 characters.
+ "fields": [ # Optional. Describes the nested schema fields if the type property is set to RECORD.
# Object with schema name: TableFieldSchema
],
- "maxLength": "A String", # [Optional] Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
- "mode": "A String", # [Optional] The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
- "name": "A String", # [Required] The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
- "policyTags": {
- "names": [ # A list of category resource names. For example, "projects/1/location/eu/taxonomies/2/policyTags/3". At most 1 policy tag is allowed.
+ "maxLength": "A String", # Optional. Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
+ "mode": "A String", # Optional. The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
+ "name": "A String", # Required. The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
+ "policyTags": { # Optional. The policy tags attached to this field, used for field-level access control. If not set, defaults to empty policy_tags.
+ "names": [ # A list of policy tag resource names. For example, "projects/1/locations/eu/taxonomies/2/policyTags/3". At most 1 policy tag is currently allowed.
"A String",
],
},
- "precision": "A String", # [Optional] Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: - Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] - Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: - If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. - If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): - If type = "NUMERIC": 1 ≤ precision ≤ 29. - If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
- "rangeElementType": { # Optional. The subtype of the RANGE, if the type of this field is RANGE. If the type is RANGE, this field is required. Possible values for the field element type of a RANGE include: - DATE - DATETIME - TIMESTAMP
- "type": "A String", # The field element type of a RANGE
+ "precision": "A String", # Optional. Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: * Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] * Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: * If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. * If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): * If type = "NUMERIC": 1 ≤ precision ≤ 29. * If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
+ "rangeElementType": { # Represents the type of a field element.
+ "type": "A String", # Required. The type of a field element. See TableFieldSchema.type.
},
- "roundingMode": "A String", # Optional. Rounding Mode specification of the field. It only can be set on NUMERIC or BIGNUMERIC type fields.
- "scale": "A String", # [Optional] See documentation for precision.
- "type": "A String", # [Required] The field data type. Possible values include STRING, BYTES, INTEGER, INT64 (same as INTEGER), FLOAT, FLOAT64 (same as FLOAT), NUMERIC, BIGNUMERIC, BOOLEAN, BOOL (same as BOOLEAN), TIMESTAMP, DATE, TIME, DATETIME, INTERVAL, RECORD (where RECORD indicates that the field contains a nested schema) or STRUCT (same as RECORD).
+ "roundingMode": "A String", # Optional. Specifies the rounding mode to be used when storing values of NUMERIC and BIGNUMERIC type.
+ "scale": "A String", # Optional. See documentation for precision.
+ "type": "A String", # Required. The field data type. Possible values include: * STRING * BYTES * INTEGER (or INT64) * FLOAT (or FLOAT64) * BOOLEAN (or BOOL) * TIMESTAMP * DATE * TIME * DATETIME * GEOGRAPHY * NUMERIC * BIGNUMERIC * JSON * RECORD (or STRUCT) Use of RECORD/STRUCT indicates that the field contains a nested schema.
},
],
},
- "sourceFormat": "A String", # [Required] The data format. For CSV files, specify "CSV". For Google sheets, specify "GOOGLE_SHEETS". For newline-delimited JSON, specify "NEWLINE_DELIMITED_JSON". For Avro files, specify "AVRO". For Google Cloud Datastore backups, specify "DATASTORE_BACKUP". [Beta] For Google Cloud Bigtable, specify "BIGTABLE".
+ "sourceFormat": "A String", # [Required] The data format. For CSV files, specify "CSV". For Google sheets, specify "GOOGLE_SHEETS". For newline-delimited JSON, specify "NEWLINE_DELIMITED_JSON". For Avro files, specify "AVRO". For Google Cloud Datastore backups, specify "DATASTORE_BACKUP". For Apache Iceberg tables, specify "ICEBERG". For ORC files, specify "ORC". For Parquet files, specify "PARQUET". [Beta] For Google Cloud Bigtable, specify "BIGTABLE".
"sourceUris": [ # [Required] The fully-qualified URIs that point to your data in Google Cloud. For Google Cloud Storage URIs: Each URI can contain one '*' wildcard character and it must come after the 'bucket' name. Size limits related to load jobs apply to external data sources. For Google Cloud Bigtable URIs: Exactly one URI can be specified and it has be a fully specified and valid HTTPS URL for a Google Cloud Bigtable table. For Google Cloud Datastore backups, exactly one URI can be specified. Also, the '*' wildcard character is not allowed.
"A String",
],
},
- "friendlyName": "A String", # [Optional] A descriptive name for this table.
- "id": "A String", # [Output-only] An opaque ID uniquely identifying the table.
- "kind": "bigquery#table", # [Output-only] The type of the resource.
+ "friendlyName": "A String", # Optional. A descriptive name for this table.
+ "id": "A String", # Output only. An opaque ID uniquely identifying the table.
+ "kind": "bigquery#table", # The type of resource ID.
"labels": { # The labels associated with this table. You can use these to organize and group your tables. Label keys and values can be no longer than 63 characters, can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. Label values are optional. Label keys must start with a letter and each label in the list must have a different key.
"a_key": "A String",
},
- "lastModifiedTime": "A String", # [Output-only] The time when this table was last modified, in milliseconds since the epoch.
- "location": "A String", # [Output-only] The geographic location where the table resides. This value is inherited from the dataset.
- "materializedView": { # [Optional] Materialized view definition.
- "allowNonIncrementalDefinition": True or False, # [Optional] Allow non incremental materialized view definition. The default value is "false".
- "enableRefresh": True or False, # [Optional] [TrustedTester] Enable automatic refresh of the materialized view when the base table is updated. The default value is "true".
- "lastRefreshTime": "A String", # [Output-only] [TrustedTester] The time when this materialized view was last modified, in milliseconds since the epoch.
+ "lastModifiedTime": "A String", # Output only. The time when this table was last modified, in milliseconds since the epoch.
+ "location": "A String", # Output only. The geographic location where the table resides. This value is inherited from the dataset.
+ "materializedView": { # Definition and configuration of a materialized view. # Optional. The materialized view definition.
+ "allowNonIncrementalDefinition": True or False, # Optional. This option declares authors intention to construct a materialized view that will not be refreshed incrementally.
+ "enableRefresh": True or False, # Optional. Enable automatic refresh of the materialized view when the base table is updated. The default value is "true".
+ "lastRefreshTime": "A String", # Output only. The time when this materialized view was last refreshed, in milliseconds since the epoch.
"maxStaleness": "A String", # [Optional] Max staleness of data that could be returned when materizlized view is queried (formatted as Google SQL Interval type).
- "query": "A String", # [Required] A query whose result is persisted.
- "refreshIntervalMs": "A String", # [Optional] [TrustedTester] The maximum frequency at which this materialized view will be refreshed. The default value is "1800000" (30 minutes).
+ "query": "A String", # Required. A query whose results are persisted.
+ "refreshIntervalMs": "A String", # Optional. The maximum frequency at which this materialized view will be refreshed. The default value is "1800000" (30 minutes).
+ },
+ "materializedViewStatus": { # Status of a materialized view. The last refresh timestamp status is omitted here, but is present in the MaterializedViewDefinition message. # Output only. The materialized view status.
+ "lastRefreshStatus": { # Error details. # Output only. Error result of the last automatic refresh. If present, indicates that the last automatic refresh was unsuccessful.
+ "debugInfo": "A String", # Debugging information. This property is internal to Google and should not be used.
+ "location": "A String", # Specifies where the error occurred, if present.
+ "message": "A String", # A human-readable description of the error.
+ "reason": "A String", # A short error code that summarizes the error.
+ },
+ "refreshWatermark": "A String", # Output only. Refresh watermark of materialized view. The base tables' data were collected into the materialized view cache until this time.
},
- "maxStaleness": "A String", # [Optional] Max staleness of data that could be returned when table or materialized view is queried (formatted as Google SQL Interval type).
- "model": { # [Output-only, Beta] Present iff this table represents a ML model. Describes the training information for the model, and it is required to run 'PREDICT' queries.
- "modelOptions": { # [Output-only, Beta] Model options used for the first training run. These options are immutable for subsequent training runs. Default values are used for any options not specified in the input query.
+ "maxStaleness": "A String", # Optional. The maximum staleness of data that could be returned when the table (or stale MV) is queried. Staleness encoded as a string encoding of sql IntervalValue type.
+ "model": { # Deprecated.
+ "modelOptions": { # Deprecated.
"labels": [
"A String",
],
"lossType": "A String",
"modelType": "A String",
},
- "trainingRuns": [ # [Output-only, Beta] Information about ml training runs, each training run comprises of multiple iterations and there may be multiple training runs for the model if warm start is used or if a user decides to continue a previously cancelled query.
+ "trainingRuns": [ # Deprecated.
{
- "iterationResults": [ # [Output-only, Beta] List of each iteration results.
+ "iterationResults": [ # Deprecated.
{
- "durationMs": "A String", # [Output-only, Beta] Time taken to run the training iteration in milliseconds.
- "evalLoss": 3.14, # [Output-only, Beta] Eval loss computed on the eval data at the end of the iteration. The eval loss is used for early stopping to avoid overfitting. No eval loss if eval_split_method option is specified as no_split or auto_split with input data size less than 500 rows.
- "index": 42, # [Output-only, Beta] Index of the ML training iteration, starting from zero for each training run.
- "learnRate": 3.14, # [Output-only, Beta] Learning rate used for this iteration, it varies for different training iterations if learn_rate_strategy option is not constant.
- "trainingLoss": 3.14, # [Output-only, Beta] Training loss computed on the training data at the end of the iteration. The training loss function is defined by model type.
+ "durationMs": "A String", # Deprecated.
+ "evalLoss": 3.14, # Deprecated.
+ "index": 42, # Deprecated.
+ "learnRate": 3.14, # Deprecated.
+ "trainingLoss": 3.14, # Deprecated.
},
],
- "startTime": "A String", # [Output-only, Beta] Training run start time in milliseconds since the epoch.
- "state": "A String", # [Output-only, Beta] Different state applicable for a training run. IN PROGRESS: Training run is in progress. FAILED: Training run ended due to a non-retryable failure. SUCCEEDED: Training run successfully completed. CANCELLED: Training run cancelled by the user.
- "trainingOptions": { # [Output-only, Beta] Training options used by this training run. These options are mutable for subsequent training runs. Default values are explicitly stored for options not specified in the input query of the first training run. For subsequent training runs, any option not explicitly specified in the input query will be copied from the previous training run.
+ "startTime": "A String", # Deprecated.
+ "state": "A String", # Deprecated.
+ "trainingOptions": { # Deprecated.
"earlyStop": True or False,
"l1Reg": 3.14,
"l2Reg": 3.14,
@@ -328,86 +347,93 @@ Method Details
},
],
},
- "numActiveLogicalBytes": "A String", # [Output-only] Number of logical bytes that are less than 90 days old.
- "numActivePhysicalBytes": "A String", # [Output-only] Number of physical bytes less than 90 days old. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
- "numBytes": "A String", # [Output-only] The size of this table in bytes, excluding any data in the streaming buffer.
- "numLongTermBytes": "A String", # [Output-only] The number of bytes in the table that are considered "long-term storage".
- "numLongTermLogicalBytes": "A String", # [Output-only] Number of logical bytes that are more than 90 days old.
- "numLongTermPhysicalBytes": "A String", # [Output-only] Number of physical bytes more than 90 days old. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
- "numPartitions": "A String", # [Output-only] The number of partitions present in the table or materialized view. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
- "numPhysicalBytes": "A String", # [Output-only] [TrustedTester] The physical size of this table in bytes, excluding any data in the streaming buffer. This includes compression and storage used for time travel.
- "numRows": "A String", # [Output-only] The number of rows of data in this table, excluding any data in the streaming buffer.
- "numTimeTravelPhysicalBytes": "A String", # [Output-only] Number of physical bytes used by time travel storage (deleted or changed data). This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
- "numTotalLogicalBytes": "A String", # [Output-only] Total number of logical bytes in the table or materialized view.
- "numTotalPhysicalBytes": "A String", # [Output-only] The physical size of this table in bytes. This also includes storage used for time travel. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
- "rangePartitioning": { # [TrustedTester] Range partitioning specification for this table. Only one of timePartitioning and rangePartitioning should be specified.
- "field": "A String", # [TrustedTester] [Required] The table is partitioned by this field. The field must be a top-level NULLABLE/REQUIRED field. The only supported type is INTEGER/INT64.
- "range": { # [TrustedTester] [Required] Defines the ranges for range partitioning.
- "end": "A String", # [TrustedTester] [Required] The end of range partitioning, exclusive.
- "interval": "A String", # [TrustedTester] [Required] The width of each interval.
- "start": "A String", # [TrustedTester] [Required] The start of range partitioning, inclusive.
- },
- },
- "requirePartitionFilter": false, # [Optional] If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified.
+ "numActiveLogicalBytes": "A String", # Output only. Number of logical bytes that are less than 90 days old.
+ "numActivePhysicalBytes": "A String", # Output only. Number of physical bytes less than 90 days old. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
+ "numBytes": "A String", # Output only. The size of this table in logical bytes, excluding any data in the streaming buffer.
+ "numLongTermBytes": "A String", # Output only. The number of logical bytes in the table that are considered "long-term storage".
+ "numLongTermLogicalBytes": "A String", # Output only. Number of logical bytes that are more than 90 days old.
+ "numLongTermPhysicalBytes": "A String", # Output only. Number of physical bytes more than 90 days old. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
+ "numPartitions": "A String", # Output only. The number of partitions present in the table or materialized view. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
+ "numPhysicalBytes": "A String", # Output only. The physical size of this table in bytes. This includes storage used for time travel.
+ "numRows": "A String", # Output only. The number of rows of data in this table, excluding any data in the streaming buffer.
+ "numTimeTravelPhysicalBytes": "A String", # Output only. Number of physical bytes used by time travel storage (deleted or changed data). This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
+ "numTotalLogicalBytes": "A String", # Output only. Total number of logical bytes in the table or materialized view.
+ "numTotalPhysicalBytes": "A String", # Output only. The physical size of this table in bytes. This also includes storage used for time travel. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
+ "rangePartitioning": { # If specified, configures range partitioning for this table.
+ "field": "A String", # Required. [Experimental] The table is partitioned by this field. The field must be a top-level NULLABLE/REQUIRED field. The only supported type is INTEGER/INT64.
+ "range": { # [Experimental] Defines the ranges for range partitioning.
+ "end": "A String", # [Experimental] The end of range partitioning, exclusive.
+ "interval": "A String", # [Experimental] The width of each interval.
+ "start": "A String", # [Experimental] The start of range partitioning, inclusive.
+ },
+ },
+ "replicas": [ # Optional. Output only. Table references of all replicas currently active on the table.
+ {
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ ],
+ "requirePartitionFilter": false, # Optional. If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified.
"resourceTags": { # [Optional] The tags associated with this table. Tag keys are globally unique. See additional information on [tags](https://cloud.google.com/iam/docs/tags-access-control#definitions). An object containing a list of "key": value pairs. The key is the namespaced friendly name of the tag key, e.g. "12345/environment" where 12345 is parent id. The value is the friendly short name of the tag value, e.g. "production".
"a_key": "A String",
},
- "schema": { # [Optional] Describes the schema of this table.
+ "schema": { # Schema of a table # Optional. Describes the schema of this table.
"fields": [ # Describes the fields in a table.
- {
- "categories": { # [Optional] The categories attached to this field, used for field-level access control.
- "names": [ # A list of category resource names. For example, "projects/1/taxonomies/2/categories/3". At most 5 categories are allowed.
+ { # A field in TableSchema
+ "categories": { # Deprecated.
+ "names": [ # Deprecated.
"A String",
],
},
- "collation": "A String", # Optional. Collation specification of the field. It only can be set on string type field.
- "defaultValueExpression": "A String", # Optional. A SQL expression to specify the default value for this field. It can only be set for top level fields (columns). You can use struct or array expression to specify default value for the entire struct or array. The valid SQL expressions are: - Literals for all data types, including STRUCT and ARRAY. - Following functions: - CURRENT_TIMESTAMP - CURRENT_TIME - CURRENT_DATE - CURRENT_DATETIME - GENERATE_UUID - RAND - SESSION_USER - ST_GEOGPOINT - Struct or array composed with the above allowed functions, for example, [CURRENT_DATE(), DATE '2020-01-01']
- "description": "A String", # [Optional] The field description. The maximum length is 1,024 characters.
- "fields": [ # [Optional] Describes the nested schema fields if the type property is set to RECORD.
+ "collation": "A String", # Optional. Field collation can be set only when the type of field is STRING. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.
+ "defaultValueExpression": "A String", # Optional. A SQL expression to specify the [default value] (https://cloud.google.com/bigquery/docs/default-values) for this field.
+ "description": "A String", # Optional. The field description. The maximum length is 1,024 characters.
+ "fields": [ # Optional. Describes the nested schema fields if the type property is set to RECORD.
# Object with schema name: TableFieldSchema
],
- "maxLength": "A String", # [Optional] Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
- "mode": "A String", # [Optional] The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
- "name": "A String", # [Required] The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
- "policyTags": {
- "names": [ # A list of category resource names. For example, "projects/1/location/eu/taxonomies/2/policyTags/3". At most 1 policy tag is allowed.
+ "maxLength": "A String", # Optional. Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
+ "mode": "A String", # Optional. The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
+ "name": "A String", # Required. The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
+ "policyTags": { # Optional. The policy tags attached to this field, used for field-level access control. If not set, defaults to empty policy_tags.
+ "names": [ # A list of policy tag resource names. For example, "projects/1/locations/eu/taxonomies/2/policyTags/3". At most 1 policy tag is currently allowed.
"A String",
],
},
- "precision": "A String", # [Optional] Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: - Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] - Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: - If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. - If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): - If type = "NUMERIC": 1 ≤ precision ≤ 29. - If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
- "rangeElementType": { # Optional. The subtype of the RANGE, if the type of this field is RANGE. If the type is RANGE, this field is required. Possible values for the field element type of a RANGE include: - DATE - DATETIME - TIMESTAMP
- "type": "A String", # The field element type of a RANGE
+ "precision": "A String", # Optional. Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: * Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] * Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: * If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. * If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): * If type = "NUMERIC": 1 ≤ precision ≤ 29. * If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
+ "rangeElementType": { # Represents the type of a field element.
+ "type": "A String", # Required. The type of a field element. See TableFieldSchema.type.
},
- "roundingMode": "A String", # Optional. Rounding Mode specification of the field. It only can be set on NUMERIC or BIGNUMERIC type fields.
- "scale": "A String", # [Optional] See documentation for precision.
- "type": "A String", # [Required] The field data type. Possible values include STRING, BYTES, INTEGER, INT64 (same as INTEGER), FLOAT, FLOAT64 (same as FLOAT), NUMERIC, BIGNUMERIC, BOOLEAN, BOOL (same as BOOLEAN), TIMESTAMP, DATE, TIME, DATETIME, INTERVAL, RECORD (where RECORD indicates that the field contains a nested schema) or STRUCT (same as RECORD).
+ "roundingMode": "A String", # Optional. Specifies the rounding mode to be used when storing values of NUMERIC and BIGNUMERIC type.
+ "scale": "A String", # Optional. See documentation for precision.
+ "type": "A String", # Required. The field data type. Possible values include: * STRING * BYTES * INTEGER (or INT64) * FLOAT (or FLOAT64) * BOOLEAN (or BOOL) * TIMESTAMP * DATE * TIME * DATETIME * GEOGRAPHY * NUMERIC * BIGNUMERIC * JSON * RECORD (or STRUCT) Use of RECORD/STRUCT indicates that the field contains a nested schema.
},
],
},
- "selfLink": "A String", # [Output-only] A URL that can be used to access this resource again.
- "snapshotDefinition": { # [Output-only] Snapshot definition.
- "baseTableReference": { # [Required] Reference describing the ID of the table that was snapshot.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- },
- "snapshotTime": "A String", # [Required] The time at which the base table was snapshot. This value is reported in the JSON response using RFC3339 format.
- },
- "streamingBuffer": { # [Output-only] Contains information regarding this table's streaming buffer, if one is present. This field will be absent if the table is not being streamed to or if there is no data in the streaming buffer.
- "estimatedBytes": "A String", # [Output-only] A lower-bound estimate of the number of bytes currently in the streaming buffer.
- "estimatedRows": "A String", # [Output-only] A lower-bound estimate of the number of rows currently in the streaming buffer.
- "oldestEntryTime": "A String", # [Output-only] Contains the timestamp of the oldest entry in the streaming buffer, in milliseconds since the epoch, if the streaming buffer is available.
- },
- "tableConstraints": { # [Optional] The table constraints on the table.
- "foreignKeys": [ # [Optional] The foreign keys of the tables.
- {
- "columnReferences": [
- {
- "referencedColumn": "A String",
- "referencingColumn": "A String",
+ "selfLink": "A String", # Output only. A URL that can be used to access this resource again.
+ "snapshotDefinition": { # Information about base table and snapshot time of the snapshot. # Output only. Contains information about the snapshot. This value is set via snapshot creation.
+ "baseTableReference": { # Required. Reference describing the ID of the table that was snapshot.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ "snapshotTime": "A String", # Required. The time at which the base table was snapshot. This value is reported in the JSON response using RFC3339 format.
+ },
+ "streamingBuffer": { # Output only. Contains information regarding this table's streaming buffer, if one is present. This field will be absent if the table is not being streamed to or if there is no data in the streaming buffer.
+ "estimatedBytes": "A String", # Output only. A lower-bound estimate of the number of bytes currently in the streaming buffer.
+ "estimatedRows": "A String", # Output only. A lower-bound estimate of the number of rows currently in the streaming buffer.
+ "oldestEntryTime": "A String", # Output only. Contains the timestamp of the oldest entry in the streaming buffer, in milliseconds since the epoch, if the streaming buffer is available.
+ },
+ "tableConstraints": { # The TableConstraints defines the primary key and foreign key. # Optional. Tables Primary Key and Foreign Key information
+ "foreignKeys": [ # Optional. Present only if the table has a foreign key. The foreign key is not enforced.
+ { # Represents a foreign key constraint on a table's columns.
+ "columnReferences": [ # Required. The columns that compose the foreign key.
+ { # The pair of the foreign key column and primary key column.
+ "referencedColumn": "A String", # Required. The column in the primary key that are referenced by the referencing_column.
+ "referencingColumn": "A String", # Required. The column that composes the foreign key.
},
],
- "name": "A String",
+ "name": "A String", # Optional. Set only if the foreign key constraint is named.
"referencedTable": {
"datasetId": "A String",
"projectId": "A String",
@@ -415,30 +441,54 @@ Method Details
},
},
],
- "primaryKey": { # [Optional] The primary key of the table.
- "columns": [
+ "primaryKey": { # Represents the primary key constraint on a table's columns.
+ "columns": [ # Required. The columns that are composed of the primary key constraint.
"A String",
],
},
},
- "tableReference": { # [Required] Reference describing the ID of this table.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- },
- "timePartitioning": { # Time-based partitioning specification for this table. Only one of timePartitioning and rangePartitioning should be specified.
- "expirationMs": "A String", # [Optional] Number of milliseconds for which to keep the storage for partitions in the table. The storage in a partition will have an expiration time of its partition time plus this value.
- "field": "A String", # [Beta] [Optional] If not set, the table is partitioned by pseudo column, referenced via either '_PARTITIONTIME' as TIMESTAMP type, or '_PARTITIONDATE' as DATE type. If field is specified, the table is instead partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED.
- "requirePartitionFilter": True or False,
- "type": "A String", # [Required] The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively. When the type is not specified, the default behavior is DAY.
- },
- "type": "A String", # [Output-only] Describes the table type. The following values are supported: TABLE: A normal BigQuery table. VIEW: A virtual table defined by a SQL query. SNAPSHOT: An immutable, read-only table that is a copy of another table. [TrustedTester] MATERIALIZED_VIEW: SQL query whose result is persisted. EXTERNAL: A table that references data stored in an external storage system, such as Google Cloud Storage. The default value is TABLE.
- "view": { # [Optional] The view definition.
- "query": "A String", # [Required] A query that BigQuery executes when the view is referenced.
- "useExplicitColumnNames": True or False, # True if the column names are explicitly specified. For example by using the 'CREATE VIEW v(c1, c2) AS ...' syntax. Can only be set using BigQuery's standard SQL: https://cloud.google.com/bigquery/sql-reference/
- "useLegacySql": True or False, # Specifies whether to use BigQuery's legacy SQL for this view. The default value is true. If set to false, the view will use BigQuery's standard SQL: https://cloud.google.com/bigquery/sql-reference/ Queries and views that reference this view must use the same flag value.
+ "tableReference": { # Required. Reference describing the ID of this table.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ "tableReplicationInfo": { # Replication info of a table created using `AS REPLICA` DDL like: `CREATE MATERIALIZED VIEW mv1 AS REPLICA OF src_mv` # Optional. Table replication info for table created `AS REPLICA` DDL like: `CREATE MATERIALIZED VIEW mv1 AS REPLICA OF src_mv`
+ "replicatedSourceLastRefreshTime": "A String", # Optional. Output only. If source is a materialized view, this field signifies the last refresh time of the source.
+ "replicationError": { # Error details. # Optional. Output only. Replication error that will permanently stopped table replication.
+ "debugInfo": "A String", # Debugging information. This property is internal to Google and should not be used.
+ "location": "A String", # Specifies where the error occurred, if present.
+ "message": "A String", # A human-readable description of the error.
+ "reason": "A String", # A short error code that summarizes the error.
+ },
+ "replicationIntervalMs": "A String", # Required. Specifies the interval at which the source table is polled for updates.
+ "replicationStatus": "A String", # Optional. Output only. Replication status of configured replication.
+ "sourceTable": { # Required. Source table reference that is replicated.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ },
+ "timePartitioning": { # If specified, configures time-based partitioning for this table.
+ "expirationMs": "A String", # Optional. Number of milliseconds for which to keep the storage for a partition. A wrapper is used here because 0 is an invalid value.
+ "field": "A String", # Optional. If not set, the table is partitioned by pseudo column '_PARTITIONTIME'; if set, the table is partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED. A wrapper is used here because an empty string is an invalid value.
+ "requirePartitionFilter": false, # If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. This field is deprecated; please set the field with the same name on the table itself instead. This field needs a wrapper because we want to output the default value, false, if the user explicitly set it.
+ "type": "A String", # Required. The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively.
+ },
+ "type": "A String", # Output only. Describes the table type. The following values are supported: * `TABLE`: A normal BigQuery table. * `VIEW`: A virtual table defined by a SQL query. * `EXTERNAL`: A table that references data stored in an external storage system, such as Google Cloud Storage. * `MATERIALIZED_VIEW`: A precomputed view defined by a SQL query. * `SNAPSHOT`: An immutable BigQuery table that preserves the contents of a base table at a particular time. See additional information on [table snapshots](/bigquery/docs/table-snapshots-intro). The default value is `TABLE`.
+ "view": { # Describes the definition of a logical view. # Optional. The view definition.
+ "privacyPolicy": { # Represents privacy policy that contains the privacy requirements specified by the data owner. Currently, this is only supported on views. # Optional. Specifices the privacy policy for the view.
+ "aggregationThresholdPolicy": { # Represents privacy policy associated with "aggregation threshold" method. # Optional. Policy used for aggregation thresholds.
+ "privacyUnitColumns": [ # Optional. The privacy unit column(s) associated with this policy. For now, only one column per data source object (table, view) is allowed as a privacy unit column. Representing as a repeated field in metadata for extensibility to multiple columns in future. Duplicates and Repeated struct fields are not allowed. For nested fields, use dot notation ("outer.inner")
+ "A String",
+ ],
+ "threshold": "A String", # Optional. The threshold for the "aggregation threshold" policy.
+ },
+ },
+ "query": "A String", # Required. A query that BigQuery executes when the view is referenced.
+ "useExplicitColumnNames": True or False, # True if the column names are explicitly specified. For example by using the 'CREATE VIEW v(c1, c2) AS ...' syntax. Can only be set for GoogleSQL views.
+ "useLegacySql": True or False, # Specifies whether to use BigQuery's legacy SQL for this view. The default value is true. If set to false, the view will use BigQuery's GoogleSQL: https://cloud.google.com/bigquery/sql-reference/ Queries and views that reference this view must use the same flag value. A wrapper is used here because the default value is True.
"userDefinedFunctionResources": [ # Describes user-defined function resources used in the query.
- { # This is used for defining User Defined Function (UDF) resources only when using legacy SQL. Users of Standard SQL should leverage either DDL (e.g. CREATE [TEMPORARY] FUNCTION ... ) or the Routines API to define UDF resources. For additional information on migrating, see: https://cloud.google.com/bigquery/docs/reference/standard-sql/migrating-from-legacy-sql#differences_in_user-defined_javascript_functions
+ { # This is used for defining User Defined Function (UDF) resources only when using legacy SQL. Users of GoogleSQL should leverage either DDL (e.g. CREATE [TEMPORARY] FUNCTION ... ) or the Routines API to define UDF resources. For additional information on migrating, see: https://cloud.google.com/bigquery/docs/reference/standard-sql/migrating-from-legacy-sql#differences_in_user-defined_javascript_functions
"inlineCode": "A String", # [Pick one] An inline resource that contains code for a user-defined function (UDF). Providing a inline code resource is equivalent to providing a URI for a file containing the same code.
"resourceUri": "A String", # [Pick one] A code resource to load from a Google Cloud Storage URI (gs://bucket/path).
},
@@ -448,7 +498,7 @@ Method Details
- getIamPolicy(resource, body=None)
+ getIamPolicy(resource, body=None, x__xgafv=None)
Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.
Args:
@@ -462,6 +512,10 @@ Method Details
},
}
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
Returns:
An object of the form:
@@ -491,7 +545,7 @@ Method Details
"members": [ # Specifies the principals requesting access for a Google Cloud resource. `members` can have the following values: * `allUsers`: A special identifier that represents anyone who is on the internet; with or without a Google account. * `allAuthenticatedUsers`: A special identifier that represents anyone who is authenticated with a Google account or a service account. Does not include identities that come from external identity providers (IdPs) through identity federation. * `user:{emailid}`: An email address that represents a specific Google account. For example, `alice@example.com` . * `serviceAccount:{emailid}`: An email address that represents a Google service account. For example, `my-other-app@appspot.gserviceaccount.com`. * `serviceAccount:{projectid}.svc.id.goog[{namespace}/{kubernetes-sa}]`: An identifier for a [Kubernetes service account](https://cloud.google.com/kubernetes-engine/docs/how-to/kubernetes-service-accounts). For example, `my-project.svc.id.goog[my-namespace/my-kubernetes-sa]`. * `group:{emailid}`: An email address that represents a Google group. For example, `admins@example.com`. * `domain:{domain}`: The G Suite domain (primary) that represents all the users of that domain. For example, `google.com` or `example.com`. * `principal://iam.googleapis.com/locations/global/workforcePools/{pool_id}/subject/{subject_attribute_value}`: A single identity in a workforce identity pool. * `principalSet://iam.googleapis.com/locations/global/workforcePools/{pool_id}/group/{group_id}`: All workforce identities in a group. * `principalSet://iam.googleapis.com/locations/global/workforcePools/{pool_id}/attribute.{attribute_name}/{attribute_value}`: All workforce identities with a specific attribute value. * `principalSet://iam.googleapis.com/locations/global/workforcePools/{pool_id}/*`: All identities in a workforce identity pool. * `principal://iam.googleapis.com/projects/{project_number}/locations/global/workloadIdentityPools/{pool_id}/subject/{subject_attribute_value}`: A single identity in a workload identity pool. * `principalSet://iam.googleapis.com/projects/{project_number}/locations/global/workloadIdentityPools/{pool_id}/group/{group_id}`: A workload identity pool group. * `principalSet://iam.googleapis.com/projects/{project_number}/locations/global/workloadIdentityPools/{pool_id}/attribute.{attribute_name}/{attribute_value}`: All identities in a workload identity pool with a certain attribute. * `principalSet://iam.googleapis.com/projects/{project_number}/locations/global/workloadIdentityPools/{pool_id}/*`: All identities in a workload identity pool. * `deleted:user:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a user that has been recently deleted. For example, `alice@example.com?uid=123456789012345678901`. If the user is recovered, this value reverts to `user:{emailid}` and the recovered user retains the role in the binding. * `deleted:serviceAccount:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a service account that has been recently deleted. For example, `my-other-app@appspot.gserviceaccount.com?uid=123456789012345678901`. If the service account is undeleted, this value reverts to `serviceAccount:{emailid}` and the undeleted service account retains the role in the binding. * `deleted:group:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a Google group that has been recently deleted. For example, `admins@example.com?uid=123456789012345678901`. If the group is recovered, this value reverts to `group:{emailid}` and the recovered group retains the role in the binding. * `deleted:principal://iam.googleapis.com/locations/global/workforcePools/{pool_id}/subject/{subject_attribute_value}`: Deleted single identity in a workforce identity pool. For example, `deleted:principal://iam.googleapis.com/locations/global/workforcePools/my-pool-id/subject/my-subject-attribute-value`.
"A String",
],
- "role": "A String", # Role that is assigned to the list of `members`, or principals. For example, `roles/viewer`, `roles/editor`, or `roles/owner`.
+ "role": "A String", # Role that is assigned to the list of `members`, or principals. For example, `roles/viewer`, `roles/editor`, or `roles/owner`. For an overview of the IAM roles and permissions, see the [IAM documentation](https://cloud.google.com/iam/docs/roles-overview). For a list of the available pre-defined roles, see [here](https://cloud.google.com/iam/docs/understanding-roles).
},
],
"etag": "A String", # `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform policy updates in order to avoid race conditions: An `etag` is returned in the response to `getIamPolicy`, and systems are expected to put that etag in the request to `setIamPolicy` to ensure that their change will be applied to the same version of the policy. **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost.
@@ -500,187 +554,198 @@ Method Details
- insert(projectId, datasetId, body=None)
+ insert(projectId, datasetId, body=None, x__xgafv=None)
Creates a new, empty table in the dataset.
Args:
- projectId: string, Project ID of the new table (required)
- datasetId: string, Dataset ID of the new table (required)
+ projectId: string, Required. Project ID of the new table (required)
+ datasetId: string, Required. Dataset ID of the new table (required)
body: object, The request body.
The object takes the form of:
{
- "biglakeConfiguration": { # [Optional] Specifies the configuration of a BigLake managed table.
- "connectionId": "A String", # [Required] Required and immutable. Credential reference for accessing external storage system. Normalized as project_id.location_id.connection_id.
- "fileFormat": "A String", # [Required] Required and immutable. Open source file format that the table data is stored in. Currently only PARQUET is supported.
- "storageUri": "A String", # [Required] Required and immutable. Fully qualified location prefix of the external folder where data is stored. Normalized to standard format: "gs:////". Starts with "gs://" rather than "/bigstore/". Ends with "/". Does not contain "*". See also BigLakeStorageMetadata on how it is used.
- "tableFormat": "A String", # [Required] Required and immutable. Open source file format that the table data is stored in. Currently only PARQUET is supported.
- },
- "cloneDefinition": { # [Output-only] Clone definition.
- "baseTableReference": { # [Required] Reference describing the ID of the table that was cloned.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- },
- "cloneTime": "A String", # [Required] The time at which the base table was cloned. This value is reported in the JSON response using RFC3339 format.
- },
- "clustering": { # [Beta] Clustering specification for the table. Must be specified with partitioning, data in the table will be first partitioned and subsequently clustered.
- "fields": [ # [Repeated] One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. When you cluster a table using multiple columns, the order of columns you specify is important. The order of the specified columns determines the sort order of the data.
+ "biglakeConfiguration": { # Configuration for BigLake managed tables. # Optional. Specifies the configuration of a BigLake managed table.
+ "connectionId": "A String", # Required. The connection specifying the credentials to be used to read and write to external storage, such as Cloud Storage. The connection_id can have the form "<project\_id>.<location\_id>.<connection\_id>" or "projects/<project\_id>/locations/<location\_id>/connections/<connection\_id>".
+ "fileFormat": "A String", # Required. The file format the table data is stored in.
+ "storageUri": "A String", # Required. The fully qualified location prefix of the external folder where table data is stored. The '*' wildcard character is not allowed. The URI should be in the format "gs://bucket/path_to_table/"
+ "tableFormat": "A String", # Required. The table format the metadata only snapshots are stored in.
+ },
+ "cloneDefinition": { # Information about base table and clone time of a table clone. # Output only. Contains information about the clone. This value is set via the clone operation.
+ "baseTableReference": { # Required. Reference describing the ID of the table that was cloned.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ "cloneTime": "A String", # Required. The time at which the base table was cloned. This value is reported in the JSON response using RFC3339 format.
+ },
+ "clustering": { # Configures table clustering. # Clustering specification for the table. Must be specified with time-based partitioning, data in the table will be first partitioned and subsequently clustered.
+ "fields": [ # One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. The ordering of the clustering fields should be prioritized from most to least important for filtering purposes. Additional information on limitations can be found here: https://cloud.google.com/bigquery/docs/creating-clustered-tables#limitations
"A String",
],
},
- "creationTime": "A String", # [Output-only] The time when this table was created, in milliseconds since the epoch.
- "defaultCollation": "A String", # [Output-only] The default collation of the table.
- "defaultRoundingMode": "A String", # [Output-only] The default rounding mode of the table.
- "description": "A String", # [Optional] A user-friendly description of this table.
+ "creationTime": "A String", # Output only. The time when this table was created, in milliseconds since the epoch.
+ "defaultCollation": "A String", # Optional. Defines the default collation specification of new STRING fields in the table. During table creation or update, if a STRING field is added to this table without explicit collation specified, then the table inherits the table default collation. A change to this field affects only fields added afterwards, and does not alter the existing fields. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.
+ "defaultRoundingMode": "A String", # Optional. Defines the default rounding mode specification of new decimal fields (NUMERIC OR BIGNUMERIC) in the table. During table creation or update, if a decimal field is added to this table without an explicit rounding mode specified, then the field inherits the table default rounding mode. Changing this field doesn't affect existing fields.
+ "description": "A String", # Optional. A user-friendly description of this table.
"encryptionConfiguration": { # Custom encryption configuration (e.g., Cloud KMS keys).
"kmsKeyName": "A String", # Optional. Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key.
},
- "etag": "A String", # [Output-only] A hash of the table metadata. Used to ensure there were no concurrent modifications to the resource when attempting an update. Not guaranteed to change when the table contents or the fields numRows, numBytes, numLongTermBytes or lastModifiedTime change.
- "expirationTime": "A String", # [Optional] The time when this table expires, in milliseconds since the epoch. If not present, the table will persist indefinitely. Expired tables will be deleted and their storage reclaimed. The defaultTableExpirationMs property of the encapsulating dataset can be used to set a default expirationTime on newly created tables.
- "externalDataConfiguration": { # [Optional] Describes the data format, location, and other properties of a table stored outside of BigQuery. By defining these properties, the data source can then be queried as if it were a standard BigQuery table.
+ "etag": "A String", # Output only. A hash of this resource.
+ "expirationTime": "A String", # Optional. The time when this table expires, in milliseconds since the epoch. If not present, the table will persist indefinitely. Expired tables will be deleted and their storage reclaimed. The defaultTableExpirationMs property of the encapsulating dataset can be used to set a default expirationTime on newly created tables.
+ "externalDataConfiguration": { # Optional. Describes the data format, location, and other properties of a table stored outside of BigQuery. By defining these properties, the data source can then be queried as if it were a standard BigQuery table.
"autodetect": True or False, # Try to detect schema and format options automatically. Any option specified explicitly will be honored.
- "avroOptions": { # Additional properties to set if sourceFormat is set to Avro.
- "useAvroLogicalTypes": True or False, # [Optional] If sourceFormat is set to "AVRO", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER).
- },
- "bigtableOptions": { # [Optional] Additional options if sourceFormat is set to BIGTABLE.
- "columnFamilies": [ # [Optional] List of column families to expose in the table schema along with their types. This list restricts the column families that can be referenced in queries and specifies their value types. You can use this list to do type conversions - see the 'type' field for more details. If you leave this list empty, all column families are present in the table schema and their values are read as BYTES. During a query only the column families referenced in that query are read from Bigtable.
- {
- "columns": [ # [Optional] Lists of columns that should be exposed as individual fields as opposed to a list of (column name, value) pairs. All columns whose qualifier matches a qualifier in this list can be accessed as .. Other columns can be accessed as a list through .Column field.
- {
- "encoding": "A String", # [Optional] The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. 'encoding' can also be set at the column family level. However, the setting at this level takes precedence if 'encoding' is set at both levels.
- "fieldName": "A String", # [Optional] If the qualifier is not a valid BigQuery field identifier i.e. does not match [a-zA-Z][a-zA-Z0-9_]*, a valid identifier must be provided as the column field name and is used as field name in queries.
- "onlyReadLatest": True or False, # [Optional] If this is set, only the latest version of value in this column are exposed. 'onlyReadLatest' can also be set at the column family level. However, the setting at this level takes precedence if 'onlyReadLatest' is set at both levels.
- "qualifierEncoded": "A String", # [Required] Qualifier of the column. Columns in the parent column family that has this exact qualifier are exposed as . field. If the qualifier is valid UTF-8 string, it can be specified in the qualifier_string field. Otherwise, a base-64 encoded value must be set to qualifier_encoded. The column field name is the same as the column qualifier. However, if the qualifier is not a valid BigQuery field identifier i.e. does not match [a-zA-Z][a-zA-Z0-9_]*, a valid identifier must be provided as field_name.
- "qualifierString": "A String",
- "type": "A String", # [Optional] The type to convert the value in cells of this column. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive) - BYTES STRING INTEGER FLOAT BOOLEAN Default type is BYTES. 'type' can also be set at the column family level. However, the setting at this level takes precedence if 'type' is set at both levels.
+ "avroOptions": { # Options for external data sources. # Optional. Additional properties to set if sourceFormat is set to AVRO.
+ "useAvroLogicalTypes": True or False, # Optional. If sourceFormat is set to "AVRO", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER).
+ },
+ "bigtableOptions": { # Options specific to Google Cloud Bigtable data sources. # Optional. Additional options if sourceFormat is set to BIGTABLE.
+ "columnFamilies": [ # Optional. List of column families to expose in the table schema along with their types. This list restricts the column families that can be referenced in queries and specifies their value types. You can use this list to do type conversions - see the 'type' field for more details. If you leave this list empty, all column families are present in the table schema and their values are read as BYTES. During a query only the column families referenced in that query are read from Bigtable.
+ { # Information related to a Bigtable column family.
+ "columns": [ # Optional. Lists of columns that should be exposed as individual fields as opposed to a list of (column name, value) pairs. All columns whose qualifier matches a qualifier in this list can be accessed as .. Other columns can be accessed as a list through .Column field.
+ { # Information related to a Bigtable column.
+ "encoding": "A String", # Optional. The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. 'encoding' can also be set at the column family level. However, the setting at this level takes precedence if 'encoding' is set at both levels.
+ "fieldName": "A String", # Optional. If the qualifier is not a valid BigQuery field identifier i.e. does not match a-zA-Z*, a valid identifier must be provided as the column field name and is used as field name in queries.
+ "onlyReadLatest": True or False, # Optional. If this is set, only the latest version of value in this column are exposed. 'onlyReadLatest' can also be set at the column family level. However, the setting at this level takes precedence if 'onlyReadLatest' is set at both levels.
+ "qualifierEncoded": "A String", # [Required] Qualifier of the column. Columns in the parent column family that has this exact qualifier are exposed as . field. If the qualifier is valid UTF-8 string, it can be specified in the qualifier_string field. Otherwise, a base-64 encoded value must be set to qualifier_encoded. The column field name is the same as the column qualifier. However, if the qualifier is not a valid BigQuery field identifier i.e. does not match a-zA-Z*, a valid identifier must be provided as field_name.
+ "qualifierString": "A String", # Qualifier string.
+ "type": "A String", # Optional. The type to convert the value in cells of this column. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive): * BYTES * STRING * INTEGER * FLOAT * BOOLEAN * JSON Default type is BYTES. 'type' can also be set at the column family level. However, the setting at this level takes precedence if 'type' is set at both levels.
},
],
- "encoding": "A String", # [Optional] The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. This can be overridden for a specific column by listing that column in 'columns' and specifying an encoding for it.
+ "encoding": "A String", # Optional. The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. This can be overridden for a specific column by listing that column in 'columns' and specifying an encoding for it.
"familyId": "A String", # Identifier of the column family.
- "onlyReadLatest": True or False, # [Optional] If this is set only the latest version of value are exposed for all columns in this column family. This can be overridden for a specific column by listing that column in 'columns' and specifying a different setting for that column.
- "type": "A String", # [Optional] The type to convert the value in cells of this column family. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive) - BYTES STRING INTEGER FLOAT BOOLEAN Default type is BYTES. This can be overridden for a specific column by listing that column in 'columns' and specifying a type for it.
+ "onlyReadLatest": True or False, # Optional. If this is set only the latest version of value are exposed for all columns in this column family. This can be overridden for a specific column by listing that column in 'columns' and specifying a different setting for that column.
+ "type": "A String", # Optional. The type to convert the value in cells of this column family. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive): * BYTES * STRING * INTEGER * FLOAT * BOOLEAN * JSON Default type is BYTES. This can be overridden for a specific column by listing that column in 'columns' and specifying a type for it.
},
],
- "ignoreUnspecifiedColumnFamilies": True or False, # [Optional] If field is true, then the column families that are not specified in columnFamilies list are not exposed in the table schema. Otherwise, they are read with BYTES type values. The default value is false.
- "readRowkeyAsString": True or False, # [Optional] If field is true, then the rowkey column families will be read and converted to string. Otherwise they are read with BYTES type values and users need to manually cast them with CAST if necessary. The default value is false.
- },
- "compression": "A String", # [Optional] The compression type of the data source. Possible values include GZIP and NONE. The default value is NONE. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups and Avro formats.
- "connectionId": "A String", # [Optional, Trusted Tester] Connection for external data source.
- "csvOptions": { # Additional properties to set if sourceFormat is set to CSV.
- "allowJaggedRows": True or False, # [Optional] Indicates if BigQuery should accept rows that are missing trailing optional columns. If true, BigQuery treats missing trailing columns as null values. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false.
- "allowQuotedNewlines": True or False, # [Optional] Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false.
- "encoding": "A String", # [Optional] The character encoding of the data. The supported values are UTF-8 or ISO-8859-1. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the quote and fieldDelimiter properties.
- "fieldDelimiter": "A String", # [Optional] The separator for fields in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. BigQuery also supports the escape sequence "\t" to specify a tab separator. The default value is a comma (',').
- "nullMarker": "A String", # [Optional] An custom string that will represent a NULL value in CSV import data.
- "preserveAsciiControlCharacters": True or False, # [Optional] Preserves the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\x00' to '\x1F') when loading from CSV. Only applicable to CSV, ignored for other formats.
- "quote": """, # [Optional] The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ('"'). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true.
- "skipLeadingRows": "A String", # [Optional] The number of rows at the top of a CSV file that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
- },
- "decimalTargetTypes": [ # [Optional] Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown. Example: Suppose the value of this field is ["NUMERIC", "BIGNUMERIC"]. If (precision,scale) is: (38,9) -> NUMERIC; (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits); (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits); (76,38) -> BIGNUMERIC; (77,38) -> BIGNUMERIC (error if value exeeds supported range). This field cannot contain duplicate types. The order of the types in this field is ignored. For example, ["BIGNUMERIC", "NUMERIC"] is the same as ["NUMERIC", "BIGNUMERIC"] and NUMERIC always takes precedence over BIGNUMERIC. Defaults to ["NUMERIC", "STRING"] for ORC and ["NUMERIC"] for the other file formats.
+ "ignoreUnspecifiedColumnFamilies": True or False, # Optional. If field is true, then the column families that are not specified in columnFamilies list are not exposed in the table schema. Otherwise, they are read with BYTES type values. The default value is false.
+ "outputColumnFamiliesAsJson": True or False, # Optional. If field is true, then each column family will be read as a single JSON column. Otherwise they are read as a repeated cell structure containing timestamp/value tuples. The default value is false.
+ "readRowkeyAsString": True or False, # Optional. If field is true, then the rowkey column families will be read and converted to string. Otherwise they are read with BYTES type values and users need to manually cast them with CAST if necessary. The default value is false.
+ },
+ "compression": "A String", # Optional. The compression type of the data source. Possible values include GZIP and NONE. The default value is NONE. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups, Avro, ORC and Parquet formats. An empty string is an invalid value.
+ "connectionId": "A String", # Optional. The connection specifying the credentials to be used to read external storage, such as Azure Blob, Cloud Storage, or S3. The connection_id can have the form "<project\_id>.<location\_id>.<connection\_id>" or "projects/<project\_id>/locations/<location\_id>/connections/<connection\_id>".
+ "csvOptions": { # Information related to a CSV data source. # Optional. Additional properties to set if sourceFormat is set to CSV.
+ "allowJaggedRows": True or False, # Optional. Indicates if BigQuery should accept rows that are missing trailing optional columns. If true, BigQuery treats missing trailing columns as null values. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false.
+ "allowQuotedNewlines": True or False, # Optional. Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false.
+ "encoding": "A String", # Optional. The character encoding of the data. The supported values are UTF-8, ISO-8859-1, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the quote and fieldDelimiter properties.
+ "fieldDelimiter": "A String", # Optional. The separator character for fields in a CSV file. The separator is interpreted as a single byte. For files encoded in ISO-8859-1, any single character can be used as a separator. For files encoded in UTF-8, characters represented in decimal range 1-127 (U+0001-U+007F) can be used without any modification. UTF-8 characters encoded with multiple bytes (i.e. U+0080 and above) will have only the first byte used for separating fields. The remaining bytes will be treated as a part of the field. BigQuery also supports the escape sequence "\t" (U+0009) to specify a tab separator. The default value is comma (",", U+002C).
+ "nullMarker": "A String", # [Optional] A custom string that will represent a NULL value in CSV import data.
+ "preserveAsciiControlCharacters": True or False, # Optional. Indicates if the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\x00' to '\x1F') are preserved.
+ "quote": """, # Optional. The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ("). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true. To include the specific quote character within a quoted value, precede it with an additional matching quote character. For example, if you want to escape the default character ' " ', use ' "" '.
+ "skipLeadingRows": "A String", # Optional. The number of rows at the top of a CSV file that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
+ },
+ "decimalTargetTypes": [ # Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown. Example: Suppose the value of this field is ["NUMERIC", "BIGNUMERIC"]. If (precision,scale) is: * (38,9) -> NUMERIC; * (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits); * (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits); * (76,38) -> BIGNUMERIC; * (77,38) -> BIGNUMERIC (error if value exeeds supported range). This field cannot contain duplicate types. The order of the types in this field is ignored. For example, ["BIGNUMERIC", "NUMERIC"] is the same as ["NUMERIC", "BIGNUMERIC"] and NUMERIC always takes precedence over BIGNUMERIC. Defaults to ["NUMERIC", "STRING"] for ORC and ["NUMERIC"] for the other file formats.
"A String",
],
- "fileSetSpecType": "A String", # [Optional] Specifies how source URIs are interpreted for constructing the file set to load. By default source URIs are expanded against the underlying storage. Other options include specifying manifest files. Only applicable to object storage systems.
- "googleSheetsOptions": { # [Optional] Additional options if sourceFormat is set to GOOGLE_SHEETS.
- "range": "A String", # [Optional] Range of a sheet to query from. Only used when non-empty. Typical format: sheet_name!top_left_cell_id:bottom_right_cell_id For example: sheet1!A1:B20
- "skipLeadingRows": "A String", # [Optional] The number of rows at the top of a sheet that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows that should be skipped. When autodetect is on, behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
+ "fileSetSpecType": "A String", # Optional. Specifies how source URIs are interpreted for constructing the file set to load. By default source URIs are expanded against the underlying storage. Other options include specifying manifest files. Only applicable to object storage systems.
+ "googleSheetsOptions": { # Options specific to Google Sheets data sources. # Optional. Additional options if sourceFormat is set to GOOGLE_SHEETS.
+ "range": "A String", # Optional. Range of a sheet to query from. Only used when non-empty. Typical format: sheet_name!top_left_cell_id:bottom_right_cell_id For example: sheet1!A1:B20
+ "skipLeadingRows": "A String", # Optional. The number of rows at the top of a sheet that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
},
- "hivePartitioningOptions": { # [Optional] Options to configure hive partitioning support.
- "fields": [ # [Output-only] For permanent external tables, this field is populated with the hive partition keys in the order they were inferred. The types of the partition keys can be deduced by checking the table schema (which will include the partition keys). Not every API will populate this field in the output. For example, Tables.Get will populate it, but Tables.List will not contain this field.
+ "hivePartitioningOptions": { # Options for configuring hive partitioning detect. # Optional. When set, configures hive partitioning support. Not all storage formats support hive partitioning -- requesting hive partitioning on an unsupported format will lead to an error, as will providing an invalid specification.
+ "fields": [ # Output only. For permanent external tables, this field is populated with the hive partition keys in the order they were inferred. The types of the partition keys can be deduced by checking the table schema (which will include the partition keys). Not every API will populate this field in the output. For example, Tables.Get will populate it, but Tables.List will not contain this field.
"A String",
],
- "mode": "A String", # [Optional] When set, what mode of hive partitioning to use when reading data. The following modes are supported. (1) AUTO: automatically infer partition key name(s) and type(s). (2) STRINGS: automatically infer partition key name(s). All types are interpreted as strings. (3) CUSTOM: partition key schema is encoded in the source URI prefix. Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported types include: AVRO, CSV, JSON, ORC and Parquet.
- "requirePartitionFilter": True or False, # [Optional] If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. Note that this field should only be true when creating a permanent external table or querying a temporary external table. Hive-partitioned loads with requirePartitionFilter explicitly set to true will fail.
- "sourceUriPrefix": "A String", # [Optional] When hive partition detection is requested, a common prefix for all source uris should be supplied. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout. gs://bucket/path_to_table/dt=2019-01-01/country=BR/id=7/file.avro gs://bucket/path_to_table/dt=2018-12-31/country=CA/id=3/file.avro When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/ (trailing slash does not matter).
- },
- "ignoreUnknownValues": True or False, # [Optional] Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names Google Cloud Bigtable: This setting is ignored. Google Cloud Datastore backups: This setting is ignored. Avro: This setting is ignored.
- "jsonOptions": { # Additional properties to set if `sourceFormat` is set to `NEWLINE_DELIMITED_JSON`.
- "encoding": "A String", # [Optional] The character encoding of the data. The supported values are UTF-8, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8.
- },
- "maxBadRecords": 42, # [Optional] The maximum number of bad records that BigQuery can ignore when reading data. If the number of bad records exceeds this value, an invalid error is returned in the job result. This is only valid for CSV, JSON, and Google Sheets. The default value is 0, which requires that all records are valid. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups and Avro formats.
- "metadataCacheMode": "A String", # [Optional] Metadata Cache Mode for the table. Set this to enable caching of metadata from external data source.
- "objectMetadata": "A String", # ObjectMetadata is used to create Object Tables. Object Tables contain a listing of objects (with their metadata) found at the source_uris. If ObjectMetadata is set, source_format should be omitted. Currently SIMPLE is the only supported Object Metadata type.
- "parquetOptions": { # Additional properties to set if sourceFormat is set to Parquet.
- "enableListInference": True or False, # [Optional] Indicates whether to use schema inference specifically for Parquet LIST logical type.
- "enumAsString": True or False, # [Optional] Indicates whether to infer Parquet ENUM logical type as STRING instead of BYTES by default.
- },
- "referenceFileSchemaUri": "A String", # [Optional] Provide a referencing file with the expected table schema. Enabled for the format: AVRO, PARQUET, ORC.
- "schema": { # [Optional] The schema for the data. Schema is required for CSV and JSON formats. Schema is disallowed for Google Cloud Bigtable, Cloud Datastore backups, and Avro formats.
+ "mode": "A String", # Optional. When set, what mode of hive partitioning to use when reading data. The following modes are supported: * AUTO: automatically infer partition key name(s) and type(s). * STRINGS: automatically infer partition key name(s). All types are strings. * CUSTOM: partition key schema is encoded in the source URI prefix. Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported formats are: JSON, CSV, ORC, Avro and Parquet.
+ "requirePartitionFilter": false, # Optional. If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. Note that this field should only be true when creating a permanent external table or querying a temporary external table. Hive-partitioned loads with require_partition_filter explicitly set to true will fail.
+ "sourceUriPrefix": "A String", # Optional. When hive partition detection is requested, a common prefix for all source uris must be required. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout: gs://bucket/path_to_table/dt=2019-06-01/country=USA/id=7/file.avro gs://bucket/path_to_table/dt=2019-05-31/country=CA/id=3/file.avro When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/. CUSTOM detection requires encoding the partitioning schema immediately after the common prefix. For CUSTOM, any of * gs://bucket/path_to_table/{dt:DATE}/{country:STRING}/{id:INTEGER} * gs://bucket/path_to_table/{dt:STRING}/{country:STRING}/{id:INTEGER} * gs://bucket/path_to_table/{dt:DATE}/{country:STRING}/{id:STRING} would all be valid source URI prefixes.
+ },
+ "ignoreUnknownValues": True or False, # Optional. Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names Google Cloud Bigtable: This setting is ignored. Google Cloud Datastore backups: This setting is ignored. Avro: This setting is ignored. ORC: This setting is ignored. Parquet: This setting is ignored.
+ "jsonExtension": "A String", # Optional. Load option to be used together with source_format newline-delimited JSON to indicate that a variant of JSON is being loaded. To load newline-delimited GeoJSON, specify GEOJSON (and source_format must be set to NEWLINE_DELIMITED_JSON).
+ "jsonOptions": { # Json Options for load and make external tables. # Optional. Additional properties to set if sourceFormat is set to JSON.
+ "encoding": "A String", # Optional. The character encoding of the data. The supported values are UTF-8, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8.
+ },
+ "maxBadRecords": 42, # Optional. The maximum number of bad records that BigQuery can ignore when reading data. If the number of bad records exceeds this value, an invalid error is returned in the job result. The default value is 0, which requires that all records are valid. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups, Avro, ORC and Parquet formats.
+ "metadataCacheMode": "A String", # Optional. Metadata Cache Mode for the table. Set this to enable caching of metadata from external data source.
+ "objectMetadata": "A String", # Optional. ObjectMetadata is used to create Object Tables. Object Tables contain a listing of objects (with their metadata) found at the source_uris. If ObjectMetadata is set, source_format should be omitted. Currently SIMPLE is the only supported Object Metadata type.
+ "parquetOptions": { # Parquet Options for load and make external tables. # Optional. Additional properties to set if sourceFormat is set to PARQUET.
+ "enableListInference": True or False, # Optional. Indicates whether to use schema inference specifically for Parquet LIST logical type.
+ "enumAsString": True or False, # Optional. Indicates whether to infer Parquet ENUM logical type as STRING instead of BYTES by default.
+ },
+ "referenceFileSchemaUri": "A String", # Optional. When creating an external table, the user can provide a reference file with the table schema. This is enabled for the following formats: AVRO, PARQUET, ORC.
+ "schema": { # Schema of a table # Optional. The schema for the data. Schema is required for CSV and JSON formats if autodetect is not on. Schema is disallowed for Google Cloud Bigtable, Cloud Datastore backups, Avro, ORC and Parquet formats.
"fields": [ # Describes the fields in a table.
- {
- "categories": { # [Optional] The categories attached to this field, used for field-level access control.
- "names": [ # A list of category resource names. For example, "projects/1/taxonomies/2/categories/3". At most 5 categories are allowed.
+ { # A field in TableSchema
+ "categories": { # Deprecated.
+ "names": [ # Deprecated.
"A String",
],
},
- "collation": "A String", # Optional. Collation specification of the field. It only can be set on string type field.
- "defaultValueExpression": "A String", # Optional. A SQL expression to specify the default value for this field. It can only be set for top level fields (columns). You can use struct or array expression to specify default value for the entire struct or array. The valid SQL expressions are: - Literals for all data types, including STRUCT and ARRAY. - Following functions: - CURRENT_TIMESTAMP - CURRENT_TIME - CURRENT_DATE - CURRENT_DATETIME - GENERATE_UUID - RAND - SESSION_USER - ST_GEOGPOINT - Struct or array composed with the above allowed functions, for example, [CURRENT_DATE(), DATE '2020-01-01']
- "description": "A String", # [Optional] The field description. The maximum length is 1,024 characters.
- "fields": [ # [Optional] Describes the nested schema fields if the type property is set to RECORD.
+ "collation": "A String", # Optional. Field collation can be set only when the type of field is STRING. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.
+ "defaultValueExpression": "A String", # Optional. A SQL expression to specify the [default value] (https://cloud.google.com/bigquery/docs/default-values) for this field.
+ "description": "A String", # Optional. The field description. The maximum length is 1,024 characters.
+ "fields": [ # Optional. Describes the nested schema fields if the type property is set to RECORD.
# Object with schema name: TableFieldSchema
],
- "maxLength": "A String", # [Optional] Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
- "mode": "A String", # [Optional] The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
- "name": "A String", # [Required] The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
- "policyTags": {
- "names": [ # A list of category resource names. For example, "projects/1/location/eu/taxonomies/2/policyTags/3". At most 1 policy tag is allowed.
+ "maxLength": "A String", # Optional. Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
+ "mode": "A String", # Optional. The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
+ "name": "A String", # Required. The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
+ "policyTags": { # Optional. The policy tags attached to this field, used for field-level access control. If not set, defaults to empty policy_tags.
+ "names": [ # A list of policy tag resource names. For example, "projects/1/locations/eu/taxonomies/2/policyTags/3". At most 1 policy tag is currently allowed.
"A String",
],
},
- "precision": "A String", # [Optional] Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: - Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] - Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: - If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. - If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): - If type = "NUMERIC": 1 ≤ precision ≤ 29. - If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
- "rangeElementType": { # Optional. The subtype of the RANGE, if the type of this field is RANGE. If the type is RANGE, this field is required. Possible values for the field element type of a RANGE include: - DATE - DATETIME - TIMESTAMP
- "type": "A String", # The field element type of a RANGE
+ "precision": "A String", # Optional. Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: * Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] * Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: * If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. * If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): * If type = "NUMERIC": 1 ≤ precision ≤ 29. * If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
+ "rangeElementType": { # Represents the type of a field element.
+ "type": "A String", # Required. The type of a field element. See TableFieldSchema.type.
},
- "roundingMode": "A String", # Optional. Rounding Mode specification of the field. It only can be set on NUMERIC or BIGNUMERIC type fields.
- "scale": "A String", # [Optional] See documentation for precision.
- "type": "A String", # [Required] The field data type. Possible values include STRING, BYTES, INTEGER, INT64 (same as INTEGER), FLOAT, FLOAT64 (same as FLOAT), NUMERIC, BIGNUMERIC, BOOLEAN, BOOL (same as BOOLEAN), TIMESTAMP, DATE, TIME, DATETIME, INTERVAL, RECORD (where RECORD indicates that the field contains a nested schema) or STRUCT (same as RECORD).
+ "roundingMode": "A String", # Optional. Specifies the rounding mode to be used when storing values of NUMERIC and BIGNUMERIC type.
+ "scale": "A String", # Optional. See documentation for precision.
+ "type": "A String", # Required. The field data type. Possible values include: * STRING * BYTES * INTEGER (or INT64) * FLOAT (or FLOAT64) * BOOLEAN (or BOOL) * TIMESTAMP * DATE * TIME * DATETIME * GEOGRAPHY * NUMERIC * BIGNUMERIC * JSON * RECORD (or STRUCT) Use of RECORD/STRUCT indicates that the field contains a nested schema.
},
],
},
- "sourceFormat": "A String", # [Required] The data format. For CSV files, specify "CSV". For Google sheets, specify "GOOGLE_SHEETS". For newline-delimited JSON, specify "NEWLINE_DELIMITED_JSON". For Avro files, specify "AVRO". For Google Cloud Datastore backups, specify "DATASTORE_BACKUP". [Beta] For Google Cloud Bigtable, specify "BIGTABLE".
+ "sourceFormat": "A String", # [Required] The data format. For CSV files, specify "CSV". For Google sheets, specify "GOOGLE_SHEETS". For newline-delimited JSON, specify "NEWLINE_DELIMITED_JSON". For Avro files, specify "AVRO". For Google Cloud Datastore backups, specify "DATASTORE_BACKUP". For Apache Iceberg tables, specify "ICEBERG". For ORC files, specify "ORC". For Parquet files, specify "PARQUET". [Beta] For Google Cloud Bigtable, specify "BIGTABLE".
"sourceUris": [ # [Required] The fully-qualified URIs that point to your data in Google Cloud. For Google Cloud Storage URIs: Each URI can contain one '*' wildcard character and it must come after the 'bucket' name. Size limits related to load jobs apply to external data sources. For Google Cloud Bigtable URIs: Exactly one URI can be specified and it has be a fully specified and valid HTTPS URL for a Google Cloud Bigtable table. For Google Cloud Datastore backups, exactly one URI can be specified. Also, the '*' wildcard character is not allowed.
"A String",
],
},
- "friendlyName": "A String", # [Optional] A descriptive name for this table.
- "id": "A String", # [Output-only] An opaque ID uniquely identifying the table.
- "kind": "bigquery#table", # [Output-only] The type of the resource.
+ "friendlyName": "A String", # Optional. A descriptive name for this table.
+ "id": "A String", # Output only. An opaque ID uniquely identifying the table.
+ "kind": "bigquery#table", # The type of resource ID.
"labels": { # The labels associated with this table. You can use these to organize and group your tables. Label keys and values can be no longer than 63 characters, can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. Label values are optional. Label keys must start with a letter and each label in the list must have a different key.
"a_key": "A String",
},
- "lastModifiedTime": "A String", # [Output-only] The time when this table was last modified, in milliseconds since the epoch.
- "location": "A String", # [Output-only] The geographic location where the table resides. This value is inherited from the dataset.
- "materializedView": { # [Optional] Materialized view definition.
- "allowNonIncrementalDefinition": True or False, # [Optional] Allow non incremental materialized view definition. The default value is "false".
- "enableRefresh": True or False, # [Optional] [TrustedTester] Enable automatic refresh of the materialized view when the base table is updated. The default value is "true".
- "lastRefreshTime": "A String", # [Output-only] [TrustedTester] The time when this materialized view was last modified, in milliseconds since the epoch.
+ "lastModifiedTime": "A String", # Output only. The time when this table was last modified, in milliseconds since the epoch.
+ "location": "A String", # Output only. The geographic location where the table resides. This value is inherited from the dataset.
+ "materializedView": { # Definition and configuration of a materialized view. # Optional. The materialized view definition.
+ "allowNonIncrementalDefinition": True or False, # Optional. This option declares authors intention to construct a materialized view that will not be refreshed incrementally.
+ "enableRefresh": True or False, # Optional. Enable automatic refresh of the materialized view when the base table is updated. The default value is "true".
+ "lastRefreshTime": "A String", # Output only. The time when this materialized view was last refreshed, in milliseconds since the epoch.
"maxStaleness": "A String", # [Optional] Max staleness of data that could be returned when materizlized view is queried (formatted as Google SQL Interval type).
- "query": "A String", # [Required] A query whose result is persisted.
- "refreshIntervalMs": "A String", # [Optional] [TrustedTester] The maximum frequency at which this materialized view will be refreshed. The default value is "1800000" (30 minutes).
+ "query": "A String", # Required. A query whose results are persisted.
+ "refreshIntervalMs": "A String", # Optional. The maximum frequency at which this materialized view will be refreshed. The default value is "1800000" (30 minutes).
+ },
+ "materializedViewStatus": { # Status of a materialized view. The last refresh timestamp status is omitted here, but is present in the MaterializedViewDefinition message. # Output only. The materialized view status.
+ "lastRefreshStatus": { # Error details. # Output only. Error result of the last automatic refresh. If present, indicates that the last automatic refresh was unsuccessful.
+ "debugInfo": "A String", # Debugging information. This property is internal to Google and should not be used.
+ "location": "A String", # Specifies where the error occurred, if present.
+ "message": "A String", # A human-readable description of the error.
+ "reason": "A String", # A short error code that summarizes the error.
+ },
+ "refreshWatermark": "A String", # Output only. Refresh watermark of materialized view. The base tables' data were collected into the materialized view cache until this time.
},
- "maxStaleness": "A String", # [Optional] Max staleness of data that could be returned when table or materialized view is queried (formatted as Google SQL Interval type).
- "model": { # [Output-only, Beta] Present iff this table represents a ML model. Describes the training information for the model, and it is required to run 'PREDICT' queries.
- "modelOptions": { # [Output-only, Beta] Model options used for the first training run. These options are immutable for subsequent training runs. Default values are used for any options not specified in the input query.
+ "maxStaleness": "A String", # Optional. The maximum staleness of data that could be returned when the table (or stale MV) is queried. Staleness encoded as a string encoding of sql IntervalValue type.
+ "model": { # Deprecated.
+ "modelOptions": { # Deprecated.
"labels": [
"A String",
],
"lossType": "A String",
"modelType": "A String",
},
- "trainingRuns": [ # [Output-only, Beta] Information about ml training runs, each training run comprises of multiple iterations and there may be multiple training runs for the model if warm start is used or if a user decides to continue a previously cancelled query.
+ "trainingRuns": [ # Deprecated.
{
- "iterationResults": [ # [Output-only, Beta] List of each iteration results.
+ "iterationResults": [ # Deprecated.
{
- "durationMs": "A String", # [Output-only, Beta] Time taken to run the training iteration in milliseconds.
- "evalLoss": 3.14, # [Output-only, Beta] Eval loss computed on the eval data at the end of the iteration. The eval loss is used for early stopping to avoid overfitting. No eval loss if eval_split_method option is specified as no_split or auto_split with input data size less than 500 rows.
- "index": 42, # [Output-only, Beta] Index of the ML training iteration, starting from zero for each training run.
- "learnRate": 3.14, # [Output-only, Beta] Learning rate used for this iteration, it varies for different training iterations if learn_rate_strategy option is not constant.
- "trainingLoss": 3.14, # [Output-only, Beta] Training loss computed on the training data at the end of the iteration. The training loss function is defined by model type.
+ "durationMs": "A String", # Deprecated.
+ "evalLoss": 3.14, # Deprecated.
+ "index": 42, # Deprecated.
+ "learnRate": 3.14, # Deprecated.
+ "trainingLoss": 3.14, # Deprecated.
},
],
- "startTime": "A String", # [Output-only, Beta] Training run start time in milliseconds since the epoch.
- "state": "A String", # [Output-only, Beta] Different state applicable for a training run. IN PROGRESS: Training run is in progress. FAILED: Training run ended due to a non-retryable failure. SUCCEEDED: Training run successfully completed. CANCELLED: Training run cancelled by the user.
- "trainingOptions": { # [Output-only, Beta] Training options used by this training run. These options are mutable for subsequent training runs. Default values are explicitly stored for options not specified in the input query of the first training run. For subsequent training runs, any option not explicitly specified in the input query will be copied from the previous training run.
+ "startTime": "A String", # Deprecated.
+ "state": "A String", # Deprecated.
+ "trainingOptions": { # Deprecated.
"earlyStop": True or False,
"l1Reg": 3.14,
"l2Reg": 3.14,
@@ -694,86 +759,93 @@ Method Details
},
],
},
- "numActiveLogicalBytes": "A String", # [Output-only] Number of logical bytes that are less than 90 days old.
- "numActivePhysicalBytes": "A String", # [Output-only] Number of physical bytes less than 90 days old. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
- "numBytes": "A String", # [Output-only] The size of this table in bytes, excluding any data in the streaming buffer.
- "numLongTermBytes": "A String", # [Output-only] The number of bytes in the table that are considered "long-term storage".
- "numLongTermLogicalBytes": "A String", # [Output-only] Number of logical bytes that are more than 90 days old.
- "numLongTermPhysicalBytes": "A String", # [Output-only] Number of physical bytes more than 90 days old. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
- "numPartitions": "A String", # [Output-only] The number of partitions present in the table or materialized view. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
- "numPhysicalBytes": "A String", # [Output-only] [TrustedTester] The physical size of this table in bytes, excluding any data in the streaming buffer. This includes compression and storage used for time travel.
- "numRows": "A String", # [Output-only] The number of rows of data in this table, excluding any data in the streaming buffer.
- "numTimeTravelPhysicalBytes": "A String", # [Output-only] Number of physical bytes used by time travel storage (deleted or changed data). This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
- "numTotalLogicalBytes": "A String", # [Output-only] Total number of logical bytes in the table or materialized view.
- "numTotalPhysicalBytes": "A String", # [Output-only] The physical size of this table in bytes. This also includes storage used for time travel. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
- "rangePartitioning": { # [TrustedTester] Range partitioning specification for this table. Only one of timePartitioning and rangePartitioning should be specified.
- "field": "A String", # [TrustedTester] [Required] The table is partitioned by this field. The field must be a top-level NULLABLE/REQUIRED field. The only supported type is INTEGER/INT64.
- "range": { # [TrustedTester] [Required] Defines the ranges for range partitioning.
- "end": "A String", # [TrustedTester] [Required] The end of range partitioning, exclusive.
- "interval": "A String", # [TrustedTester] [Required] The width of each interval.
- "start": "A String", # [TrustedTester] [Required] The start of range partitioning, inclusive.
- },
- },
- "requirePartitionFilter": false, # [Optional] If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified.
+ "numActiveLogicalBytes": "A String", # Output only. Number of logical bytes that are less than 90 days old.
+ "numActivePhysicalBytes": "A String", # Output only. Number of physical bytes less than 90 days old. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
+ "numBytes": "A String", # Output only. The size of this table in logical bytes, excluding any data in the streaming buffer.
+ "numLongTermBytes": "A String", # Output only. The number of logical bytes in the table that are considered "long-term storage".
+ "numLongTermLogicalBytes": "A String", # Output only. Number of logical bytes that are more than 90 days old.
+ "numLongTermPhysicalBytes": "A String", # Output only. Number of physical bytes more than 90 days old. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
+ "numPartitions": "A String", # Output only. The number of partitions present in the table or materialized view. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
+ "numPhysicalBytes": "A String", # Output only. The physical size of this table in bytes. This includes storage used for time travel.
+ "numRows": "A String", # Output only. The number of rows of data in this table, excluding any data in the streaming buffer.
+ "numTimeTravelPhysicalBytes": "A String", # Output only. Number of physical bytes used by time travel storage (deleted or changed data). This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
+ "numTotalLogicalBytes": "A String", # Output only. Total number of logical bytes in the table or materialized view.
+ "numTotalPhysicalBytes": "A String", # Output only. The physical size of this table in bytes. This also includes storage used for time travel. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
+ "rangePartitioning": { # If specified, configures range partitioning for this table.
+ "field": "A String", # Required. [Experimental] The table is partitioned by this field. The field must be a top-level NULLABLE/REQUIRED field. The only supported type is INTEGER/INT64.
+ "range": { # [Experimental] Defines the ranges for range partitioning.
+ "end": "A String", # [Experimental] The end of range partitioning, exclusive.
+ "interval": "A String", # [Experimental] The width of each interval.
+ "start": "A String", # [Experimental] The start of range partitioning, inclusive.
+ },
+ },
+ "replicas": [ # Optional. Output only. Table references of all replicas currently active on the table.
+ {
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ ],
+ "requirePartitionFilter": false, # Optional. If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified.
"resourceTags": { # [Optional] The tags associated with this table. Tag keys are globally unique. See additional information on [tags](https://cloud.google.com/iam/docs/tags-access-control#definitions). An object containing a list of "key": value pairs. The key is the namespaced friendly name of the tag key, e.g. "12345/environment" where 12345 is parent id. The value is the friendly short name of the tag value, e.g. "production".
"a_key": "A String",
},
- "schema": { # [Optional] Describes the schema of this table.
+ "schema": { # Schema of a table # Optional. Describes the schema of this table.
"fields": [ # Describes the fields in a table.
- {
- "categories": { # [Optional] The categories attached to this field, used for field-level access control.
- "names": [ # A list of category resource names. For example, "projects/1/taxonomies/2/categories/3". At most 5 categories are allowed.
+ { # A field in TableSchema
+ "categories": { # Deprecated.
+ "names": [ # Deprecated.
"A String",
],
},
- "collation": "A String", # Optional. Collation specification of the field. It only can be set on string type field.
- "defaultValueExpression": "A String", # Optional. A SQL expression to specify the default value for this field. It can only be set for top level fields (columns). You can use struct or array expression to specify default value for the entire struct or array. The valid SQL expressions are: - Literals for all data types, including STRUCT and ARRAY. - Following functions: - CURRENT_TIMESTAMP - CURRENT_TIME - CURRENT_DATE - CURRENT_DATETIME - GENERATE_UUID - RAND - SESSION_USER - ST_GEOGPOINT - Struct or array composed with the above allowed functions, for example, [CURRENT_DATE(), DATE '2020-01-01']
- "description": "A String", # [Optional] The field description. The maximum length is 1,024 characters.
- "fields": [ # [Optional] Describes the nested schema fields if the type property is set to RECORD.
+ "collation": "A String", # Optional. Field collation can be set only when the type of field is STRING. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.
+ "defaultValueExpression": "A String", # Optional. A SQL expression to specify the [default value] (https://cloud.google.com/bigquery/docs/default-values) for this field.
+ "description": "A String", # Optional. The field description. The maximum length is 1,024 characters.
+ "fields": [ # Optional. Describes the nested schema fields if the type property is set to RECORD.
# Object with schema name: TableFieldSchema
],
- "maxLength": "A String", # [Optional] Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
- "mode": "A String", # [Optional] The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
- "name": "A String", # [Required] The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
- "policyTags": {
- "names": [ # A list of category resource names. For example, "projects/1/location/eu/taxonomies/2/policyTags/3". At most 1 policy tag is allowed.
+ "maxLength": "A String", # Optional. Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
+ "mode": "A String", # Optional. The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
+ "name": "A String", # Required. The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
+ "policyTags": { # Optional. The policy tags attached to this field, used for field-level access control. If not set, defaults to empty policy_tags.
+ "names": [ # A list of policy tag resource names. For example, "projects/1/locations/eu/taxonomies/2/policyTags/3". At most 1 policy tag is currently allowed.
"A String",
],
},
- "precision": "A String", # [Optional] Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: - Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] - Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: - If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. - If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): - If type = "NUMERIC": 1 ≤ precision ≤ 29. - If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
- "rangeElementType": { # Optional. The subtype of the RANGE, if the type of this field is RANGE. If the type is RANGE, this field is required. Possible values for the field element type of a RANGE include: - DATE - DATETIME - TIMESTAMP
- "type": "A String", # The field element type of a RANGE
+ "precision": "A String", # Optional. Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: * Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] * Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: * If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. * If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): * If type = "NUMERIC": 1 ≤ precision ≤ 29. * If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
+ "rangeElementType": { # Represents the type of a field element.
+ "type": "A String", # Required. The type of a field element. See TableFieldSchema.type.
},
- "roundingMode": "A String", # Optional. Rounding Mode specification of the field. It only can be set on NUMERIC or BIGNUMERIC type fields.
- "scale": "A String", # [Optional] See documentation for precision.
- "type": "A String", # [Required] The field data type. Possible values include STRING, BYTES, INTEGER, INT64 (same as INTEGER), FLOAT, FLOAT64 (same as FLOAT), NUMERIC, BIGNUMERIC, BOOLEAN, BOOL (same as BOOLEAN), TIMESTAMP, DATE, TIME, DATETIME, INTERVAL, RECORD (where RECORD indicates that the field contains a nested schema) or STRUCT (same as RECORD).
+ "roundingMode": "A String", # Optional. Specifies the rounding mode to be used when storing values of NUMERIC and BIGNUMERIC type.
+ "scale": "A String", # Optional. See documentation for precision.
+ "type": "A String", # Required. The field data type. Possible values include: * STRING * BYTES * INTEGER (or INT64) * FLOAT (or FLOAT64) * BOOLEAN (or BOOL) * TIMESTAMP * DATE * TIME * DATETIME * GEOGRAPHY * NUMERIC * BIGNUMERIC * JSON * RECORD (or STRUCT) Use of RECORD/STRUCT indicates that the field contains a nested schema.
},
],
},
- "selfLink": "A String", # [Output-only] A URL that can be used to access this resource again.
- "snapshotDefinition": { # [Output-only] Snapshot definition.
- "baseTableReference": { # [Required] Reference describing the ID of the table that was snapshot.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- },
- "snapshotTime": "A String", # [Required] The time at which the base table was snapshot. This value is reported in the JSON response using RFC3339 format.
- },
- "streamingBuffer": { # [Output-only] Contains information regarding this table's streaming buffer, if one is present. This field will be absent if the table is not being streamed to or if there is no data in the streaming buffer.
- "estimatedBytes": "A String", # [Output-only] A lower-bound estimate of the number of bytes currently in the streaming buffer.
- "estimatedRows": "A String", # [Output-only] A lower-bound estimate of the number of rows currently in the streaming buffer.
- "oldestEntryTime": "A String", # [Output-only] Contains the timestamp of the oldest entry in the streaming buffer, in milliseconds since the epoch, if the streaming buffer is available.
- },
- "tableConstraints": { # [Optional] The table constraints on the table.
- "foreignKeys": [ # [Optional] The foreign keys of the tables.
- {
- "columnReferences": [
- {
- "referencedColumn": "A String",
- "referencingColumn": "A String",
+ "selfLink": "A String", # Output only. A URL that can be used to access this resource again.
+ "snapshotDefinition": { # Information about base table and snapshot time of the snapshot. # Output only. Contains information about the snapshot. This value is set via snapshot creation.
+ "baseTableReference": { # Required. Reference describing the ID of the table that was snapshot.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ "snapshotTime": "A String", # Required. The time at which the base table was snapshot. This value is reported in the JSON response using RFC3339 format.
+ },
+ "streamingBuffer": { # Output only. Contains information regarding this table's streaming buffer, if one is present. This field will be absent if the table is not being streamed to or if there is no data in the streaming buffer.
+ "estimatedBytes": "A String", # Output only. A lower-bound estimate of the number of bytes currently in the streaming buffer.
+ "estimatedRows": "A String", # Output only. A lower-bound estimate of the number of rows currently in the streaming buffer.
+ "oldestEntryTime": "A String", # Output only. Contains the timestamp of the oldest entry in the streaming buffer, in milliseconds since the epoch, if the streaming buffer is available.
+ },
+ "tableConstraints": { # The TableConstraints defines the primary key and foreign key. # Optional. Tables Primary Key and Foreign Key information
+ "foreignKeys": [ # Optional. Present only if the table has a foreign key. The foreign key is not enforced.
+ { # Represents a foreign key constraint on a table's columns.
+ "columnReferences": [ # Required. The columns that compose the foreign key.
+ { # The pair of the foreign key column and primary key column.
+ "referencedColumn": "A String", # Required. The column in the primary key that are referenced by the referencing_column.
+ "referencingColumn": "A String", # Required. The column that composes the foreign key.
},
],
- "name": "A String",
+ "name": "A String", # Optional. Set only if the foreign key constraint is named.
"referencedTable": {
"datasetId": "A String",
"projectId": "A String",
@@ -781,30 +853,54 @@ Method Details
},
},
],
- "primaryKey": { # [Optional] The primary key of the table.
- "columns": [
+ "primaryKey": { # Represents the primary key constraint on a table's columns.
+ "columns": [ # Required. The columns that are composed of the primary key constraint.
"A String",
],
},
},
- "tableReference": { # [Required] Reference describing the ID of this table.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- },
- "timePartitioning": { # Time-based partitioning specification for this table. Only one of timePartitioning and rangePartitioning should be specified.
- "expirationMs": "A String", # [Optional] Number of milliseconds for which to keep the storage for partitions in the table. The storage in a partition will have an expiration time of its partition time plus this value.
- "field": "A String", # [Beta] [Optional] If not set, the table is partitioned by pseudo column, referenced via either '_PARTITIONTIME' as TIMESTAMP type, or '_PARTITIONDATE' as DATE type. If field is specified, the table is instead partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED.
- "requirePartitionFilter": True or False,
- "type": "A String", # [Required] The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively. When the type is not specified, the default behavior is DAY.
- },
- "type": "A String", # [Output-only] Describes the table type. The following values are supported: TABLE: A normal BigQuery table. VIEW: A virtual table defined by a SQL query. SNAPSHOT: An immutable, read-only table that is a copy of another table. [TrustedTester] MATERIALIZED_VIEW: SQL query whose result is persisted. EXTERNAL: A table that references data stored in an external storage system, such as Google Cloud Storage. The default value is TABLE.
- "view": { # [Optional] The view definition.
- "query": "A String", # [Required] A query that BigQuery executes when the view is referenced.
- "useExplicitColumnNames": True or False, # True if the column names are explicitly specified. For example by using the 'CREATE VIEW v(c1, c2) AS ...' syntax. Can only be set using BigQuery's standard SQL: https://cloud.google.com/bigquery/sql-reference/
- "useLegacySql": True or False, # Specifies whether to use BigQuery's legacy SQL for this view. The default value is true. If set to false, the view will use BigQuery's standard SQL: https://cloud.google.com/bigquery/sql-reference/ Queries and views that reference this view must use the same flag value.
+ "tableReference": { # Required. Reference describing the ID of this table.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ "tableReplicationInfo": { # Replication info of a table created using `AS REPLICA` DDL like: `CREATE MATERIALIZED VIEW mv1 AS REPLICA OF src_mv` # Optional. Table replication info for table created `AS REPLICA` DDL like: `CREATE MATERIALIZED VIEW mv1 AS REPLICA OF src_mv`
+ "replicatedSourceLastRefreshTime": "A String", # Optional. Output only. If source is a materialized view, this field signifies the last refresh time of the source.
+ "replicationError": { # Error details. # Optional. Output only. Replication error that will permanently stopped table replication.
+ "debugInfo": "A String", # Debugging information. This property is internal to Google and should not be used.
+ "location": "A String", # Specifies where the error occurred, if present.
+ "message": "A String", # A human-readable description of the error.
+ "reason": "A String", # A short error code that summarizes the error.
+ },
+ "replicationIntervalMs": "A String", # Required. Specifies the interval at which the source table is polled for updates.
+ "replicationStatus": "A String", # Optional. Output only. Replication status of configured replication.
+ "sourceTable": { # Required. Source table reference that is replicated.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ },
+ "timePartitioning": { # If specified, configures time-based partitioning for this table.
+ "expirationMs": "A String", # Optional. Number of milliseconds for which to keep the storage for a partition. A wrapper is used here because 0 is an invalid value.
+ "field": "A String", # Optional. If not set, the table is partitioned by pseudo column '_PARTITIONTIME'; if set, the table is partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED. A wrapper is used here because an empty string is an invalid value.
+ "requirePartitionFilter": false, # If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. This field is deprecated; please set the field with the same name on the table itself instead. This field needs a wrapper because we want to output the default value, false, if the user explicitly set it.
+ "type": "A String", # Required. The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively.
+ },
+ "type": "A String", # Output only. Describes the table type. The following values are supported: * `TABLE`: A normal BigQuery table. * `VIEW`: A virtual table defined by a SQL query. * `EXTERNAL`: A table that references data stored in an external storage system, such as Google Cloud Storage. * `MATERIALIZED_VIEW`: A precomputed view defined by a SQL query. * `SNAPSHOT`: An immutable BigQuery table that preserves the contents of a base table at a particular time. See additional information on [table snapshots](/bigquery/docs/table-snapshots-intro). The default value is `TABLE`.
+ "view": { # Describes the definition of a logical view. # Optional. The view definition.
+ "privacyPolicy": { # Represents privacy policy that contains the privacy requirements specified by the data owner. Currently, this is only supported on views. # Optional. Specifices the privacy policy for the view.
+ "aggregationThresholdPolicy": { # Represents privacy policy associated with "aggregation threshold" method. # Optional. Policy used for aggregation thresholds.
+ "privacyUnitColumns": [ # Optional. The privacy unit column(s) associated with this policy. For now, only one column per data source object (table, view) is allowed as a privacy unit column. Representing as a repeated field in metadata for extensibility to multiple columns in future. Duplicates and Repeated struct fields are not allowed. For nested fields, use dot notation ("outer.inner")
+ "A String",
+ ],
+ "threshold": "A String", # Optional. The threshold for the "aggregation threshold" policy.
+ },
+ },
+ "query": "A String", # Required. A query that BigQuery executes when the view is referenced.
+ "useExplicitColumnNames": True or False, # True if the column names are explicitly specified. For example by using the 'CREATE VIEW v(c1, c2) AS ...' syntax. Can only be set for GoogleSQL views.
+ "useLegacySql": True or False, # Specifies whether to use BigQuery's legacy SQL for this view. The default value is true. If set to false, the view will use BigQuery's GoogleSQL: https://cloud.google.com/bigquery/sql-reference/ Queries and views that reference this view must use the same flag value. A wrapper is used here because the default value is True.
"userDefinedFunctionResources": [ # Describes user-defined function resources used in the query.
- { # This is used for defining User Defined Function (UDF) resources only when using legacy SQL. Users of Standard SQL should leverage either DDL (e.g. CREATE [TEMPORARY] FUNCTION ... ) or the Routines API to define UDF resources. For additional information on migrating, see: https://cloud.google.com/bigquery/docs/reference/standard-sql/migrating-from-legacy-sql#differences_in_user-defined_javascript_functions
+ { # This is used for defining User Defined Function (UDF) resources only when using legacy SQL. Users of GoogleSQL should leverage either DDL (e.g. CREATE [TEMPORARY] FUNCTION ... ) or the Routines API to define UDF resources. For additional information on migrating, see: https://cloud.google.com/bigquery/docs/reference/standard-sql/migrating-from-legacy-sql#differences_in_user-defined_javascript_functions
"inlineCode": "A String", # [Pick one] An inline resource that contains code for a user-defined function (UDF). Providing a inline code resource is equivalent to providing a URI for a file containing the same code.
"resourceUri": "A String", # [Pick one] A code resource to load from a Google Cloud Storage URI (gs://bucket/path).
},
@@ -812,182 +908,197 @@ Method Details
},
}
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
Returns:
An object of the form:
{
- "biglakeConfiguration": { # [Optional] Specifies the configuration of a BigLake managed table.
- "connectionId": "A String", # [Required] Required and immutable. Credential reference for accessing external storage system. Normalized as project_id.location_id.connection_id.
- "fileFormat": "A String", # [Required] Required and immutable. Open source file format that the table data is stored in. Currently only PARQUET is supported.
- "storageUri": "A String", # [Required] Required and immutable. Fully qualified location prefix of the external folder where data is stored. Normalized to standard format: "gs:////". Starts with "gs://" rather than "/bigstore/". Ends with "/". Does not contain "*". See also BigLakeStorageMetadata on how it is used.
- "tableFormat": "A String", # [Required] Required and immutable. Open source file format that the table data is stored in. Currently only PARQUET is supported.
- },
- "cloneDefinition": { # [Output-only] Clone definition.
- "baseTableReference": { # [Required] Reference describing the ID of the table that was cloned.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- },
- "cloneTime": "A String", # [Required] The time at which the base table was cloned. This value is reported in the JSON response using RFC3339 format.
- },
- "clustering": { # [Beta] Clustering specification for the table. Must be specified with partitioning, data in the table will be first partitioned and subsequently clustered.
- "fields": [ # [Repeated] One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. When you cluster a table using multiple columns, the order of columns you specify is important. The order of the specified columns determines the sort order of the data.
+ "biglakeConfiguration": { # Configuration for BigLake managed tables. # Optional. Specifies the configuration of a BigLake managed table.
+ "connectionId": "A String", # Required. The connection specifying the credentials to be used to read and write to external storage, such as Cloud Storage. The connection_id can have the form "<project\_id>.<location\_id>.<connection\_id>" or "projects/<project\_id>/locations/<location\_id>/connections/<connection\_id>".
+ "fileFormat": "A String", # Required. The file format the table data is stored in.
+ "storageUri": "A String", # Required. The fully qualified location prefix of the external folder where table data is stored. The '*' wildcard character is not allowed. The URI should be in the format "gs://bucket/path_to_table/"
+ "tableFormat": "A String", # Required. The table format the metadata only snapshots are stored in.
+ },
+ "cloneDefinition": { # Information about base table and clone time of a table clone. # Output only. Contains information about the clone. This value is set via the clone operation.
+ "baseTableReference": { # Required. Reference describing the ID of the table that was cloned.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ "cloneTime": "A String", # Required. The time at which the base table was cloned. This value is reported in the JSON response using RFC3339 format.
+ },
+ "clustering": { # Configures table clustering. # Clustering specification for the table. Must be specified with time-based partitioning, data in the table will be first partitioned and subsequently clustered.
+ "fields": [ # One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. The ordering of the clustering fields should be prioritized from most to least important for filtering purposes. Additional information on limitations can be found here: https://cloud.google.com/bigquery/docs/creating-clustered-tables#limitations
"A String",
],
},
- "creationTime": "A String", # [Output-only] The time when this table was created, in milliseconds since the epoch.
- "defaultCollation": "A String", # [Output-only] The default collation of the table.
- "defaultRoundingMode": "A String", # [Output-only] The default rounding mode of the table.
- "description": "A String", # [Optional] A user-friendly description of this table.
+ "creationTime": "A String", # Output only. The time when this table was created, in milliseconds since the epoch.
+ "defaultCollation": "A String", # Optional. Defines the default collation specification of new STRING fields in the table. During table creation or update, if a STRING field is added to this table without explicit collation specified, then the table inherits the table default collation. A change to this field affects only fields added afterwards, and does not alter the existing fields. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.
+ "defaultRoundingMode": "A String", # Optional. Defines the default rounding mode specification of new decimal fields (NUMERIC OR BIGNUMERIC) in the table. During table creation or update, if a decimal field is added to this table without an explicit rounding mode specified, then the field inherits the table default rounding mode. Changing this field doesn't affect existing fields.
+ "description": "A String", # Optional. A user-friendly description of this table.
"encryptionConfiguration": { # Custom encryption configuration (e.g., Cloud KMS keys).
"kmsKeyName": "A String", # Optional. Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key.
},
- "etag": "A String", # [Output-only] A hash of the table metadata. Used to ensure there were no concurrent modifications to the resource when attempting an update. Not guaranteed to change when the table contents or the fields numRows, numBytes, numLongTermBytes or lastModifiedTime change.
- "expirationTime": "A String", # [Optional] The time when this table expires, in milliseconds since the epoch. If not present, the table will persist indefinitely. Expired tables will be deleted and their storage reclaimed. The defaultTableExpirationMs property of the encapsulating dataset can be used to set a default expirationTime on newly created tables.
- "externalDataConfiguration": { # [Optional] Describes the data format, location, and other properties of a table stored outside of BigQuery. By defining these properties, the data source can then be queried as if it were a standard BigQuery table.
+ "etag": "A String", # Output only. A hash of this resource.
+ "expirationTime": "A String", # Optional. The time when this table expires, in milliseconds since the epoch. If not present, the table will persist indefinitely. Expired tables will be deleted and their storage reclaimed. The defaultTableExpirationMs property of the encapsulating dataset can be used to set a default expirationTime on newly created tables.
+ "externalDataConfiguration": { # Optional. Describes the data format, location, and other properties of a table stored outside of BigQuery. By defining these properties, the data source can then be queried as if it were a standard BigQuery table.
"autodetect": True or False, # Try to detect schema and format options automatically. Any option specified explicitly will be honored.
- "avroOptions": { # Additional properties to set if sourceFormat is set to Avro.
- "useAvroLogicalTypes": True or False, # [Optional] If sourceFormat is set to "AVRO", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER).
- },
- "bigtableOptions": { # [Optional] Additional options if sourceFormat is set to BIGTABLE.
- "columnFamilies": [ # [Optional] List of column families to expose in the table schema along with their types. This list restricts the column families that can be referenced in queries and specifies their value types. You can use this list to do type conversions - see the 'type' field for more details. If you leave this list empty, all column families are present in the table schema and their values are read as BYTES. During a query only the column families referenced in that query are read from Bigtable.
- {
- "columns": [ # [Optional] Lists of columns that should be exposed as individual fields as opposed to a list of (column name, value) pairs. All columns whose qualifier matches a qualifier in this list can be accessed as .. Other columns can be accessed as a list through .Column field.
- {
- "encoding": "A String", # [Optional] The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. 'encoding' can also be set at the column family level. However, the setting at this level takes precedence if 'encoding' is set at both levels.
- "fieldName": "A String", # [Optional] If the qualifier is not a valid BigQuery field identifier i.e. does not match [a-zA-Z][a-zA-Z0-9_]*, a valid identifier must be provided as the column field name and is used as field name in queries.
- "onlyReadLatest": True or False, # [Optional] If this is set, only the latest version of value in this column are exposed. 'onlyReadLatest' can also be set at the column family level. However, the setting at this level takes precedence if 'onlyReadLatest' is set at both levels.
- "qualifierEncoded": "A String", # [Required] Qualifier of the column. Columns in the parent column family that has this exact qualifier are exposed as . field. If the qualifier is valid UTF-8 string, it can be specified in the qualifier_string field. Otherwise, a base-64 encoded value must be set to qualifier_encoded. The column field name is the same as the column qualifier. However, if the qualifier is not a valid BigQuery field identifier i.e. does not match [a-zA-Z][a-zA-Z0-9_]*, a valid identifier must be provided as field_name.
- "qualifierString": "A String",
- "type": "A String", # [Optional] The type to convert the value in cells of this column. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive) - BYTES STRING INTEGER FLOAT BOOLEAN Default type is BYTES. 'type' can also be set at the column family level. However, the setting at this level takes precedence if 'type' is set at both levels.
+ "avroOptions": { # Options for external data sources. # Optional. Additional properties to set if sourceFormat is set to AVRO.
+ "useAvroLogicalTypes": True or False, # Optional. If sourceFormat is set to "AVRO", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER).
+ },
+ "bigtableOptions": { # Options specific to Google Cloud Bigtable data sources. # Optional. Additional options if sourceFormat is set to BIGTABLE.
+ "columnFamilies": [ # Optional. List of column families to expose in the table schema along with their types. This list restricts the column families that can be referenced in queries and specifies their value types. You can use this list to do type conversions - see the 'type' field for more details. If you leave this list empty, all column families are present in the table schema and their values are read as BYTES. During a query only the column families referenced in that query are read from Bigtable.
+ { # Information related to a Bigtable column family.
+ "columns": [ # Optional. Lists of columns that should be exposed as individual fields as opposed to a list of (column name, value) pairs. All columns whose qualifier matches a qualifier in this list can be accessed as .. Other columns can be accessed as a list through .Column field.
+ { # Information related to a Bigtable column.
+ "encoding": "A String", # Optional. The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. 'encoding' can also be set at the column family level. However, the setting at this level takes precedence if 'encoding' is set at both levels.
+ "fieldName": "A String", # Optional. If the qualifier is not a valid BigQuery field identifier i.e. does not match a-zA-Z*, a valid identifier must be provided as the column field name and is used as field name in queries.
+ "onlyReadLatest": True or False, # Optional. If this is set, only the latest version of value in this column are exposed. 'onlyReadLatest' can also be set at the column family level. However, the setting at this level takes precedence if 'onlyReadLatest' is set at both levels.
+ "qualifierEncoded": "A String", # [Required] Qualifier of the column. Columns in the parent column family that has this exact qualifier are exposed as . field. If the qualifier is valid UTF-8 string, it can be specified in the qualifier_string field. Otherwise, a base-64 encoded value must be set to qualifier_encoded. The column field name is the same as the column qualifier. However, if the qualifier is not a valid BigQuery field identifier i.e. does not match a-zA-Z*, a valid identifier must be provided as field_name.
+ "qualifierString": "A String", # Qualifier string.
+ "type": "A String", # Optional. The type to convert the value in cells of this column. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive): * BYTES * STRING * INTEGER * FLOAT * BOOLEAN * JSON Default type is BYTES. 'type' can also be set at the column family level. However, the setting at this level takes precedence if 'type' is set at both levels.
},
],
- "encoding": "A String", # [Optional] The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. This can be overridden for a specific column by listing that column in 'columns' and specifying an encoding for it.
+ "encoding": "A String", # Optional. The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. This can be overridden for a specific column by listing that column in 'columns' and specifying an encoding for it.
"familyId": "A String", # Identifier of the column family.
- "onlyReadLatest": True or False, # [Optional] If this is set only the latest version of value are exposed for all columns in this column family. This can be overridden for a specific column by listing that column in 'columns' and specifying a different setting for that column.
- "type": "A String", # [Optional] The type to convert the value in cells of this column family. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive) - BYTES STRING INTEGER FLOAT BOOLEAN Default type is BYTES. This can be overridden for a specific column by listing that column in 'columns' and specifying a type for it.
+ "onlyReadLatest": True or False, # Optional. If this is set only the latest version of value are exposed for all columns in this column family. This can be overridden for a specific column by listing that column in 'columns' and specifying a different setting for that column.
+ "type": "A String", # Optional. The type to convert the value in cells of this column family. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive): * BYTES * STRING * INTEGER * FLOAT * BOOLEAN * JSON Default type is BYTES. This can be overridden for a specific column by listing that column in 'columns' and specifying a type for it.
},
],
- "ignoreUnspecifiedColumnFamilies": True or False, # [Optional] If field is true, then the column families that are not specified in columnFamilies list are not exposed in the table schema. Otherwise, they are read with BYTES type values. The default value is false.
- "readRowkeyAsString": True or False, # [Optional] If field is true, then the rowkey column families will be read and converted to string. Otherwise they are read with BYTES type values and users need to manually cast them with CAST if necessary. The default value is false.
- },
- "compression": "A String", # [Optional] The compression type of the data source. Possible values include GZIP and NONE. The default value is NONE. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups and Avro formats.
- "connectionId": "A String", # [Optional, Trusted Tester] Connection for external data source.
- "csvOptions": { # Additional properties to set if sourceFormat is set to CSV.
- "allowJaggedRows": True or False, # [Optional] Indicates if BigQuery should accept rows that are missing trailing optional columns. If true, BigQuery treats missing trailing columns as null values. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false.
- "allowQuotedNewlines": True or False, # [Optional] Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false.
- "encoding": "A String", # [Optional] The character encoding of the data. The supported values are UTF-8 or ISO-8859-1. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the quote and fieldDelimiter properties.
- "fieldDelimiter": "A String", # [Optional] The separator for fields in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. BigQuery also supports the escape sequence "\t" to specify a tab separator. The default value is a comma (',').
- "nullMarker": "A String", # [Optional] An custom string that will represent a NULL value in CSV import data.
- "preserveAsciiControlCharacters": True or False, # [Optional] Preserves the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\x00' to '\x1F') when loading from CSV. Only applicable to CSV, ignored for other formats.
- "quote": """, # [Optional] The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ('"'). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true.
- "skipLeadingRows": "A String", # [Optional] The number of rows at the top of a CSV file that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
- },
- "decimalTargetTypes": [ # [Optional] Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown. Example: Suppose the value of this field is ["NUMERIC", "BIGNUMERIC"]. If (precision,scale) is: (38,9) -> NUMERIC; (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits); (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits); (76,38) -> BIGNUMERIC; (77,38) -> BIGNUMERIC (error if value exeeds supported range). This field cannot contain duplicate types. The order of the types in this field is ignored. For example, ["BIGNUMERIC", "NUMERIC"] is the same as ["NUMERIC", "BIGNUMERIC"] and NUMERIC always takes precedence over BIGNUMERIC. Defaults to ["NUMERIC", "STRING"] for ORC and ["NUMERIC"] for the other file formats.
+ "ignoreUnspecifiedColumnFamilies": True or False, # Optional. If field is true, then the column families that are not specified in columnFamilies list are not exposed in the table schema. Otherwise, they are read with BYTES type values. The default value is false.
+ "outputColumnFamiliesAsJson": True or False, # Optional. If field is true, then each column family will be read as a single JSON column. Otherwise they are read as a repeated cell structure containing timestamp/value tuples. The default value is false.
+ "readRowkeyAsString": True or False, # Optional. If field is true, then the rowkey column families will be read and converted to string. Otherwise they are read with BYTES type values and users need to manually cast them with CAST if necessary. The default value is false.
+ },
+ "compression": "A String", # Optional. The compression type of the data source. Possible values include GZIP and NONE. The default value is NONE. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups, Avro, ORC and Parquet formats. An empty string is an invalid value.
+ "connectionId": "A String", # Optional. The connection specifying the credentials to be used to read external storage, such as Azure Blob, Cloud Storage, or S3. The connection_id can have the form "<project\_id>.<location\_id>.<connection\_id>" or "projects/<project\_id>/locations/<location\_id>/connections/<connection\_id>".
+ "csvOptions": { # Information related to a CSV data source. # Optional. Additional properties to set if sourceFormat is set to CSV.
+ "allowJaggedRows": True or False, # Optional. Indicates if BigQuery should accept rows that are missing trailing optional columns. If true, BigQuery treats missing trailing columns as null values. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false.
+ "allowQuotedNewlines": True or False, # Optional. Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false.
+ "encoding": "A String", # Optional. The character encoding of the data. The supported values are UTF-8, ISO-8859-1, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the quote and fieldDelimiter properties.
+ "fieldDelimiter": "A String", # Optional. The separator character for fields in a CSV file. The separator is interpreted as a single byte. For files encoded in ISO-8859-1, any single character can be used as a separator. For files encoded in UTF-8, characters represented in decimal range 1-127 (U+0001-U+007F) can be used without any modification. UTF-8 characters encoded with multiple bytes (i.e. U+0080 and above) will have only the first byte used for separating fields. The remaining bytes will be treated as a part of the field. BigQuery also supports the escape sequence "\t" (U+0009) to specify a tab separator. The default value is comma (",", U+002C).
+ "nullMarker": "A String", # [Optional] A custom string that will represent a NULL value in CSV import data.
+ "preserveAsciiControlCharacters": True or False, # Optional. Indicates if the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\x00' to '\x1F') are preserved.
+ "quote": """, # Optional. The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ("). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true. To include the specific quote character within a quoted value, precede it with an additional matching quote character. For example, if you want to escape the default character ' " ', use ' "" '.
+ "skipLeadingRows": "A String", # Optional. The number of rows at the top of a CSV file that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
+ },
+ "decimalTargetTypes": [ # Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown. Example: Suppose the value of this field is ["NUMERIC", "BIGNUMERIC"]. If (precision,scale) is: * (38,9) -> NUMERIC; * (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits); * (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits); * (76,38) -> BIGNUMERIC; * (77,38) -> BIGNUMERIC (error if value exeeds supported range). This field cannot contain duplicate types. The order of the types in this field is ignored. For example, ["BIGNUMERIC", "NUMERIC"] is the same as ["NUMERIC", "BIGNUMERIC"] and NUMERIC always takes precedence over BIGNUMERIC. Defaults to ["NUMERIC", "STRING"] for ORC and ["NUMERIC"] for the other file formats.
"A String",
],
- "fileSetSpecType": "A String", # [Optional] Specifies how source URIs are interpreted for constructing the file set to load. By default source URIs are expanded against the underlying storage. Other options include specifying manifest files. Only applicable to object storage systems.
- "googleSheetsOptions": { # [Optional] Additional options if sourceFormat is set to GOOGLE_SHEETS.
- "range": "A String", # [Optional] Range of a sheet to query from. Only used when non-empty. Typical format: sheet_name!top_left_cell_id:bottom_right_cell_id For example: sheet1!A1:B20
- "skipLeadingRows": "A String", # [Optional] The number of rows at the top of a sheet that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows that should be skipped. When autodetect is on, behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
+ "fileSetSpecType": "A String", # Optional. Specifies how source URIs are interpreted for constructing the file set to load. By default source URIs are expanded against the underlying storage. Other options include specifying manifest files. Only applicable to object storage systems.
+ "googleSheetsOptions": { # Options specific to Google Sheets data sources. # Optional. Additional options if sourceFormat is set to GOOGLE_SHEETS.
+ "range": "A String", # Optional. Range of a sheet to query from. Only used when non-empty. Typical format: sheet_name!top_left_cell_id:bottom_right_cell_id For example: sheet1!A1:B20
+ "skipLeadingRows": "A String", # Optional. The number of rows at the top of a sheet that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
},
- "hivePartitioningOptions": { # [Optional] Options to configure hive partitioning support.
- "fields": [ # [Output-only] For permanent external tables, this field is populated with the hive partition keys in the order they were inferred. The types of the partition keys can be deduced by checking the table schema (which will include the partition keys). Not every API will populate this field in the output. For example, Tables.Get will populate it, but Tables.List will not contain this field.
+ "hivePartitioningOptions": { # Options for configuring hive partitioning detect. # Optional. When set, configures hive partitioning support. Not all storage formats support hive partitioning -- requesting hive partitioning on an unsupported format will lead to an error, as will providing an invalid specification.
+ "fields": [ # Output only. For permanent external tables, this field is populated with the hive partition keys in the order they were inferred. The types of the partition keys can be deduced by checking the table schema (which will include the partition keys). Not every API will populate this field in the output. For example, Tables.Get will populate it, but Tables.List will not contain this field.
"A String",
],
- "mode": "A String", # [Optional] When set, what mode of hive partitioning to use when reading data. The following modes are supported. (1) AUTO: automatically infer partition key name(s) and type(s). (2) STRINGS: automatically infer partition key name(s). All types are interpreted as strings. (3) CUSTOM: partition key schema is encoded in the source URI prefix. Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported types include: AVRO, CSV, JSON, ORC and Parquet.
- "requirePartitionFilter": True or False, # [Optional] If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. Note that this field should only be true when creating a permanent external table or querying a temporary external table. Hive-partitioned loads with requirePartitionFilter explicitly set to true will fail.
- "sourceUriPrefix": "A String", # [Optional] When hive partition detection is requested, a common prefix for all source uris should be supplied. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout. gs://bucket/path_to_table/dt=2019-01-01/country=BR/id=7/file.avro gs://bucket/path_to_table/dt=2018-12-31/country=CA/id=3/file.avro When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/ (trailing slash does not matter).
- },
- "ignoreUnknownValues": True or False, # [Optional] Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names Google Cloud Bigtable: This setting is ignored. Google Cloud Datastore backups: This setting is ignored. Avro: This setting is ignored.
- "jsonOptions": { # Additional properties to set if `sourceFormat` is set to `NEWLINE_DELIMITED_JSON`.
- "encoding": "A String", # [Optional] The character encoding of the data. The supported values are UTF-8, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8.
- },
- "maxBadRecords": 42, # [Optional] The maximum number of bad records that BigQuery can ignore when reading data. If the number of bad records exceeds this value, an invalid error is returned in the job result. This is only valid for CSV, JSON, and Google Sheets. The default value is 0, which requires that all records are valid. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups and Avro formats.
- "metadataCacheMode": "A String", # [Optional] Metadata Cache Mode for the table. Set this to enable caching of metadata from external data source.
- "objectMetadata": "A String", # ObjectMetadata is used to create Object Tables. Object Tables contain a listing of objects (with their metadata) found at the source_uris. If ObjectMetadata is set, source_format should be omitted. Currently SIMPLE is the only supported Object Metadata type.
- "parquetOptions": { # Additional properties to set if sourceFormat is set to Parquet.
- "enableListInference": True or False, # [Optional] Indicates whether to use schema inference specifically for Parquet LIST logical type.
- "enumAsString": True or False, # [Optional] Indicates whether to infer Parquet ENUM logical type as STRING instead of BYTES by default.
- },
- "referenceFileSchemaUri": "A String", # [Optional] Provide a referencing file with the expected table schema. Enabled for the format: AVRO, PARQUET, ORC.
- "schema": { # [Optional] The schema for the data. Schema is required for CSV and JSON formats. Schema is disallowed for Google Cloud Bigtable, Cloud Datastore backups, and Avro formats.
+ "mode": "A String", # Optional. When set, what mode of hive partitioning to use when reading data. The following modes are supported: * AUTO: automatically infer partition key name(s) and type(s). * STRINGS: automatically infer partition key name(s). All types are strings. * CUSTOM: partition key schema is encoded in the source URI prefix. Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported formats are: JSON, CSV, ORC, Avro and Parquet.
+ "requirePartitionFilter": false, # Optional. If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. Note that this field should only be true when creating a permanent external table or querying a temporary external table. Hive-partitioned loads with require_partition_filter explicitly set to true will fail.
+ "sourceUriPrefix": "A String", # Optional. When hive partition detection is requested, a common prefix for all source uris must be required. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout: gs://bucket/path_to_table/dt=2019-06-01/country=USA/id=7/file.avro gs://bucket/path_to_table/dt=2019-05-31/country=CA/id=3/file.avro When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/. CUSTOM detection requires encoding the partitioning schema immediately after the common prefix. For CUSTOM, any of * gs://bucket/path_to_table/{dt:DATE}/{country:STRING}/{id:INTEGER} * gs://bucket/path_to_table/{dt:STRING}/{country:STRING}/{id:INTEGER} * gs://bucket/path_to_table/{dt:DATE}/{country:STRING}/{id:STRING} would all be valid source URI prefixes.
+ },
+ "ignoreUnknownValues": True or False, # Optional. Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names Google Cloud Bigtable: This setting is ignored. Google Cloud Datastore backups: This setting is ignored. Avro: This setting is ignored. ORC: This setting is ignored. Parquet: This setting is ignored.
+ "jsonExtension": "A String", # Optional. Load option to be used together with source_format newline-delimited JSON to indicate that a variant of JSON is being loaded. To load newline-delimited GeoJSON, specify GEOJSON (and source_format must be set to NEWLINE_DELIMITED_JSON).
+ "jsonOptions": { # Json Options for load and make external tables. # Optional. Additional properties to set if sourceFormat is set to JSON.
+ "encoding": "A String", # Optional. The character encoding of the data. The supported values are UTF-8, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8.
+ },
+ "maxBadRecords": 42, # Optional. The maximum number of bad records that BigQuery can ignore when reading data. If the number of bad records exceeds this value, an invalid error is returned in the job result. The default value is 0, which requires that all records are valid. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups, Avro, ORC and Parquet formats.
+ "metadataCacheMode": "A String", # Optional. Metadata Cache Mode for the table. Set this to enable caching of metadata from external data source.
+ "objectMetadata": "A String", # Optional. ObjectMetadata is used to create Object Tables. Object Tables contain a listing of objects (with their metadata) found at the source_uris. If ObjectMetadata is set, source_format should be omitted. Currently SIMPLE is the only supported Object Metadata type.
+ "parquetOptions": { # Parquet Options for load and make external tables. # Optional. Additional properties to set if sourceFormat is set to PARQUET.
+ "enableListInference": True or False, # Optional. Indicates whether to use schema inference specifically for Parquet LIST logical type.
+ "enumAsString": True or False, # Optional. Indicates whether to infer Parquet ENUM logical type as STRING instead of BYTES by default.
+ },
+ "referenceFileSchemaUri": "A String", # Optional. When creating an external table, the user can provide a reference file with the table schema. This is enabled for the following formats: AVRO, PARQUET, ORC.
+ "schema": { # Schema of a table # Optional. The schema for the data. Schema is required for CSV and JSON formats if autodetect is not on. Schema is disallowed for Google Cloud Bigtable, Cloud Datastore backups, Avro, ORC and Parquet formats.
"fields": [ # Describes the fields in a table.
- {
- "categories": { # [Optional] The categories attached to this field, used for field-level access control.
- "names": [ # A list of category resource names. For example, "projects/1/taxonomies/2/categories/3". At most 5 categories are allowed.
+ { # A field in TableSchema
+ "categories": { # Deprecated.
+ "names": [ # Deprecated.
"A String",
],
},
- "collation": "A String", # Optional. Collation specification of the field. It only can be set on string type field.
- "defaultValueExpression": "A String", # Optional. A SQL expression to specify the default value for this field. It can only be set for top level fields (columns). You can use struct or array expression to specify default value for the entire struct or array. The valid SQL expressions are: - Literals for all data types, including STRUCT and ARRAY. - Following functions: - CURRENT_TIMESTAMP - CURRENT_TIME - CURRENT_DATE - CURRENT_DATETIME - GENERATE_UUID - RAND - SESSION_USER - ST_GEOGPOINT - Struct or array composed with the above allowed functions, for example, [CURRENT_DATE(), DATE '2020-01-01']
- "description": "A String", # [Optional] The field description. The maximum length is 1,024 characters.
- "fields": [ # [Optional] Describes the nested schema fields if the type property is set to RECORD.
+ "collation": "A String", # Optional. Field collation can be set only when the type of field is STRING. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.
+ "defaultValueExpression": "A String", # Optional. A SQL expression to specify the [default value] (https://cloud.google.com/bigquery/docs/default-values) for this field.
+ "description": "A String", # Optional. The field description. The maximum length is 1,024 characters.
+ "fields": [ # Optional. Describes the nested schema fields if the type property is set to RECORD.
# Object with schema name: TableFieldSchema
],
- "maxLength": "A String", # [Optional] Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
- "mode": "A String", # [Optional] The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
- "name": "A String", # [Required] The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
- "policyTags": {
- "names": [ # A list of category resource names. For example, "projects/1/location/eu/taxonomies/2/policyTags/3". At most 1 policy tag is allowed.
+ "maxLength": "A String", # Optional. Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
+ "mode": "A String", # Optional. The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
+ "name": "A String", # Required. The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
+ "policyTags": { # Optional. The policy tags attached to this field, used for field-level access control. If not set, defaults to empty policy_tags.
+ "names": [ # A list of policy tag resource names. For example, "projects/1/locations/eu/taxonomies/2/policyTags/3". At most 1 policy tag is currently allowed.
"A String",
],
},
- "precision": "A String", # [Optional] Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: - Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] - Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: - If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. - If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): - If type = "NUMERIC": 1 ≤ precision ≤ 29. - If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
- "rangeElementType": { # Optional. The subtype of the RANGE, if the type of this field is RANGE. If the type is RANGE, this field is required. Possible values for the field element type of a RANGE include: - DATE - DATETIME - TIMESTAMP
- "type": "A String", # The field element type of a RANGE
+ "precision": "A String", # Optional. Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: * Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] * Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: * If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. * If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): * If type = "NUMERIC": 1 ≤ precision ≤ 29. * If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
+ "rangeElementType": { # Represents the type of a field element.
+ "type": "A String", # Required. The type of a field element. See TableFieldSchema.type.
},
- "roundingMode": "A String", # Optional. Rounding Mode specification of the field. It only can be set on NUMERIC or BIGNUMERIC type fields.
- "scale": "A String", # [Optional] See documentation for precision.
- "type": "A String", # [Required] The field data type. Possible values include STRING, BYTES, INTEGER, INT64 (same as INTEGER), FLOAT, FLOAT64 (same as FLOAT), NUMERIC, BIGNUMERIC, BOOLEAN, BOOL (same as BOOLEAN), TIMESTAMP, DATE, TIME, DATETIME, INTERVAL, RECORD (where RECORD indicates that the field contains a nested schema) or STRUCT (same as RECORD).
+ "roundingMode": "A String", # Optional. Specifies the rounding mode to be used when storing values of NUMERIC and BIGNUMERIC type.
+ "scale": "A String", # Optional. See documentation for precision.
+ "type": "A String", # Required. The field data type. Possible values include: * STRING * BYTES * INTEGER (or INT64) * FLOAT (or FLOAT64) * BOOLEAN (or BOOL) * TIMESTAMP * DATE * TIME * DATETIME * GEOGRAPHY * NUMERIC * BIGNUMERIC * JSON * RECORD (or STRUCT) Use of RECORD/STRUCT indicates that the field contains a nested schema.
},
],
},
- "sourceFormat": "A String", # [Required] The data format. For CSV files, specify "CSV". For Google sheets, specify "GOOGLE_SHEETS". For newline-delimited JSON, specify "NEWLINE_DELIMITED_JSON". For Avro files, specify "AVRO". For Google Cloud Datastore backups, specify "DATASTORE_BACKUP". [Beta] For Google Cloud Bigtable, specify "BIGTABLE".
+ "sourceFormat": "A String", # [Required] The data format. For CSV files, specify "CSV". For Google sheets, specify "GOOGLE_SHEETS". For newline-delimited JSON, specify "NEWLINE_DELIMITED_JSON". For Avro files, specify "AVRO". For Google Cloud Datastore backups, specify "DATASTORE_BACKUP". For Apache Iceberg tables, specify "ICEBERG". For ORC files, specify "ORC". For Parquet files, specify "PARQUET". [Beta] For Google Cloud Bigtable, specify "BIGTABLE".
"sourceUris": [ # [Required] The fully-qualified URIs that point to your data in Google Cloud. For Google Cloud Storage URIs: Each URI can contain one '*' wildcard character and it must come after the 'bucket' name. Size limits related to load jobs apply to external data sources. For Google Cloud Bigtable URIs: Exactly one URI can be specified and it has be a fully specified and valid HTTPS URL for a Google Cloud Bigtable table. For Google Cloud Datastore backups, exactly one URI can be specified. Also, the '*' wildcard character is not allowed.
"A String",
],
},
- "friendlyName": "A String", # [Optional] A descriptive name for this table.
- "id": "A String", # [Output-only] An opaque ID uniquely identifying the table.
- "kind": "bigquery#table", # [Output-only] The type of the resource.
+ "friendlyName": "A String", # Optional. A descriptive name for this table.
+ "id": "A String", # Output only. An opaque ID uniquely identifying the table.
+ "kind": "bigquery#table", # The type of resource ID.
"labels": { # The labels associated with this table. You can use these to organize and group your tables. Label keys and values can be no longer than 63 characters, can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. Label values are optional. Label keys must start with a letter and each label in the list must have a different key.
"a_key": "A String",
},
- "lastModifiedTime": "A String", # [Output-only] The time when this table was last modified, in milliseconds since the epoch.
- "location": "A String", # [Output-only] The geographic location where the table resides. This value is inherited from the dataset.
- "materializedView": { # [Optional] Materialized view definition.
- "allowNonIncrementalDefinition": True or False, # [Optional] Allow non incremental materialized view definition. The default value is "false".
- "enableRefresh": True or False, # [Optional] [TrustedTester] Enable automatic refresh of the materialized view when the base table is updated. The default value is "true".
- "lastRefreshTime": "A String", # [Output-only] [TrustedTester] The time when this materialized view was last modified, in milliseconds since the epoch.
+ "lastModifiedTime": "A String", # Output only. The time when this table was last modified, in milliseconds since the epoch.
+ "location": "A String", # Output only. The geographic location where the table resides. This value is inherited from the dataset.
+ "materializedView": { # Definition and configuration of a materialized view. # Optional. The materialized view definition.
+ "allowNonIncrementalDefinition": True or False, # Optional. This option declares authors intention to construct a materialized view that will not be refreshed incrementally.
+ "enableRefresh": True or False, # Optional. Enable automatic refresh of the materialized view when the base table is updated. The default value is "true".
+ "lastRefreshTime": "A String", # Output only. The time when this materialized view was last refreshed, in milliseconds since the epoch.
"maxStaleness": "A String", # [Optional] Max staleness of data that could be returned when materizlized view is queried (formatted as Google SQL Interval type).
- "query": "A String", # [Required] A query whose result is persisted.
- "refreshIntervalMs": "A String", # [Optional] [TrustedTester] The maximum frequency at which this materialized view will be refreshed. The default value is "1800000" (30 minutes).
+ "query": "A String", # Required. A query whose results are persisted.
+ "refreshIntervalMs": "A String", # Optional. The maximum frequency at which this materialized view will be refreshed. The default value is "1800000" (30 minutes).
+ },
+ "materializedViewStatus": { # Status of a materialized view. The last refresh timestamp status is omitted here, but is present in the MaterializedViewDefinition message. # Output only. The materialized view status.
+ "lastRefreshStatus": { # Error details. # Output only. Error result of the last automatic refresh. If present, indicates that the last automatic refresh was unsuccessful.
+ "debugInfo": "A String", # Debugging information. This property is internal to Google and should not be used.
+ "location": "A String", # Specifies where the error occurred, if present.
+ "message": "A String", # A human-readable description of the error.
+ "reason": "A String", # A short error code that summarizes the error.
+ },
+ "refreshWatermark": "A String", # Output only. Refresh watermark of materialized view. The base tables' data were collected into the materialized view cache until this time.
},
- "maxStaleness": "A String", # [Optional] Max staleness of data that could be returned when table or materialized view is queried (formatted as Google SQL Interval type).
- "model": { # [Output-only, Beta] Present iff this table represents a ML model. Describes the training information for the model, and it is required to run 'PREDICT' queries.
- "modelOptions": { # [Output-only, Beta] Model options used for the first training run. These options are immutable for subsequent training runs. Default values are used for any options not specified in the input query.
+ "maxStaleness": "A String", # Optional. The maximum staleness of data that could be returned when the table (or stale MV) is queried. Staleness encoded as a string encoding of sql IntervalValue type.
+ "model": { # Deprecated.
+ "modelOptions": { # Deprecated.
"labels": [
"A String",
],
"lossType": "A String",
"modelType": "A String",
},
- "trainingRuns": [ # [Output-only, Beta] Information about ml training runs, each training run comprises of multiple iterations and there may be multiple training runs for the model if warm start is used or if a user decides to continue a previously cancelled query.
+ "trainingRuns": [ # Deprecated.
{
- "iterationResults": [ # [Output-only, Beta] List of each iteration results.
+ "iterationResults": [ # Deprecated.
{
- "durationMs": "A String", # [Output-only, Beta] Time taken to run the training iteration in milliseconds.
- "evalLoss": 3.14, # [Output-only, Beta] Eval loss computed on the eval data at the end of the iteration. The eval loss is used for early stopping to avoid overfitting. No eval loss if eval_split_method option is specified as no_split or auto_split with input data size less than 500 rows.
- "index": 42, # [Output-only, Beta] Index of the ML training iteration, starting from zero for each training run.
- "learnRate": 3.14, # [Output-only, Beta] Learning rate used for this iteration, it varies for different training iterations if learn_rate_strategy option is not constant.
- "trainingLoss": 3.14, # [Output-only, Beta] Training loss computed on the training data at the end of the iteration. The training loss function is defined by model type.
+ "durationMs": "A String", # Deprecated.
+ "evalLoss": 3.14, # Deprecated.
+ "index": 42, # Deprecated.
+ "learnRate": 3.14, # Deprecated.
+ "trainingLoss": 3.14, # Deprecated.
},
],
- "startTime": "A String", # [Output-only, Beta] Training run start time in milliseconds since the epoch.
- "state": "A String", # [Output-only, Beta] Different state applicable for a training run. IN PROGRESS: Training run is in progress. FAILED: Training run ended due to a non-retryable failure. SUCCEEDED: Training run successfully completed. CANCELLED: Training run cancelled by the user.
- "trainingOptions": { # [Output-only, Beta] Training options used by this training run. These options are mutable for subsequent training runs. Default values are explicitly stored for options not specified in the input query of the first training run. For subsequent training runs, any option not explicitly specified in the input query will be copied from the previous training run.
+ "startTime": "A String", # Deprecated.
+ "state": "A String", # Deprecated.
+ "trainingOptions": { # Deprecated.
"earlyStop": True or False,
"l1Reg": 3.14,
"l2Reg": 3.14,
@@ -1001,86 +1112,93 @@ Method Details
},
],
},
- "numActiveLogicalBytes": "A String", # [Output-only] Number of logical bytes that are less than 90 days old.
- "numActivePhysicalBytes": "A String", # [Output-only] Number of physical bytes less than 90 days old. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
- "numBytes": "A String", # [Output-only] The size of this table in bytes, excluding any data in the streaming buffer.
- "numLongTermBytes": "A String", # [Output-only] The number of bytes in the table that are considered "long-term storage".
- "numLongTermLogicalBytes": "A String", # [Output-only] Number of logical bytes that are more than 90 days old.
- "numLongTermPhysicalBytes": "A String", # [Output-only] Number of physical bytes more than 90 days old. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
- "numPartitions": "A String", # [Output-only] The number of partitions present in the table or materialized view. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
- "numPhysicalBytes": "A String", # [Output-only] [TrustedTester] The physical size of this table in bytes, excluding any data in the streaming buffer. This includes compression and storage used for time travel.
- "numRows": "A String", # [Output-only] The number of rows of data in this table, excluding any data in the streaming buffer.
- "numTimeTravelPhysicalBytes": "A String", # [Output-only] Number of physical bytes used by time travel storage (deleted or changed data). This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
- "numTotalLogicalBytes": "A String", # [Output-only] Total number of logical bytes in the table or materialized view.
- "numTotalPhysicalBytes": "A String", # [Output-only] The physical size of this table in bytes. This also includes storage used for time travel. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
- "rangePartitioning": { # [TrustedTester] Range partitioning specification for this table. Only one of timePartitioning and rangePartitioning should be specified.
- "field": "A String", # [TrustedTester] [Required] The table is partitioned by this field. The field must be a top-level NULLABLE/REQUIRED field. The only supported type is INTEGER/INT64.
- "range": { # [TrustedTester] [Required] Defines the ranges for range partitioning.
- "end": "A String", # [TrustedTester] [Required] The end of range partitioning, exclusive.
- "interval": "A String", # [TrustedTester] [Required] The width of each interval.
- "start": "A String", # [TrustedTester] [Required] The start of range partitioning, inclusive.
- },
- },
- "requirePartitionFilter": false, # [Optional] If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified.
+ "numActiveLogicalBytes": "A String", # Output only. Number of logical bytes that are less than 90 days old.
+ "numActivePhysicalBytes": "A String", # Output only. Number of physical bytes less than 90 days old. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
+ "numBytes": "A String", # Output only. The size of this table in logical bytes, excluding any data in the streaming buffer.
+ "numLongTermBytes": "A String", # Output only. The number of logical bytes in the table that are considered "long-term storage".
+ "numLongTermLogicalBytes": "A String", # Output only. Number of logical bytes that are more than 90 days old.
+ "numLongTermPhysicalBytes": "A String", # Output only. Number of physical bytes more than 90 days old. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
+ "numPartitions": "A String", # Output only. The number of partitions present in the table or materialized view. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
+ "numPhysicalBytes": "A String", # Output only. The physical size of this table in bytes. This includes storage used for time travel.
+ "numRows": "A String", # Output only. The number of rows of data in this table, excluding any data in the streaming buffer.
+ "numTimeTravelPhysicalBytes": "A String", # Output only. Number of physical bytes used by time travel storage (deleted or changed data). This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
+ "numTotalLogicalBytes": "A String", # Output only. Total number of logical bytes in the table or materialized view.
+ "numTotalPhysicalBytes": "A String", # Output only. The physical size of this table in bytes. This also includes storage used for time travel. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
+ "rangePartitioning": { # If specified, configures range partitioning for this table.
+ "field": "A String", # Required. [Experimental] The table is partitioned by this field. The field must be a top-level NULLABLE/REQUIRED field. The only supported type is INTEGER/INT64.
+ "range": { # [Experimental] Defines the ranges for range partitioning.
+ "end": "A String", # [Experimental] The end of range partitioning, exclusive.
+ "interval": "A String", # [Experimental] The width of each interval.
+ "start": "A String", # [Experimental] The start of range partitioning, inclusive.
+ },
+ },
+ "replicas": [ # Optional. Output only. Table references of all replicas currently active on the table.
+ {
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ ],
+ "requirePartitionFilter": false, # Optional. If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified.
"resourceTags": { # [Optional] The tags associated with this table. Tag keys are globally unique. See additional information on [tags](https://cloud.google.com/iam/docs/tags-access-control#definitions). An object containing a list of "key": value pairs. The key is the namespaced friendly name of the tag key, e.g. "12345/environment" where 12345 is parent id. The value is the friendly short name of the tag value, e.g. "production".
"a_key": "A String",
},
- "schema": { # [Optional] Describes the schema of this table.
+ "schema": { # Schema of a table # Optional. Describes the schema of this table.
"fields": [ # Describes the fields in a table.
- {
- "categories": { # [Optional] The categories attached to this field, used for field-level access control.
- "names": [ # A list of category resource names. For example, "projects/1/taxonomies/2/categories/3". At most 5 categories are allowed.
+ { # A field in TableSchema
+ "categories": { # Deprecated.
+ "names": [ # Deprecated.
"A String",
],
},
- "collation": "A String", # Optional. Collation specification of the field. It only can be set on string type field.
- "defaultValueExpression": "A String", # Optional. A SQL expression to specify the default value for this field. It can only be set for top level fields (columns). You can use struct or array expression to specify default value for the entire struct or array. The valid SQL expressions are: - Literals for all data types, including STRUCT and ARRAY. - Following functions: - CURRENT_TIMESTAMP - CURRENT_TIME - CURRENT_DATE - CURRENT_DATETIME - GENERATE_UUID - RAND - SESSION_USER - ST_GEOGPOINT - Struct or array composed with the above allowed functions, for example, [CURRENT_DATE(), DATE '2020-01-01']
- "description": "A String", # [Optional] The field description. The maximum length is 1,024 characters.
- "fields": [ # [Optional] Describes the nested schema fields if the type property is set to RECORD.
+ "collation": "A String", # Optional. Field collation can be set only when the type of field is STRING. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.
+ "defaultValueExpression": "A String", # Optional. A SQL expression to specify the [default value] (https://cloud.google.com/bigquery/docs/default-values) for this field.
+ "description": "A String", # Optional. The field description. The maximum length is 1,024 characters.
+ "fields": [ # Optional. Describes the nested schema fields if the type property is set to RECORD.
# Object with schema name: TableFieldSchema
],
- "maxLength": "A String", # [Optional] Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
- "mode": "A String", # [Optional] The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
- "name": "A String", # [Required] The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
- "policyTags": {
- "names": [ # A list of category resource names. For example, "projects/1/location/eu/taxonomies/2/policyTags/3". At most 1 policy tag is allowed.
+ "maxLength": "A String", # Optional. Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
+ "mode": "A String", # Optional. The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
+ "name": "A String", # Required. The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
+ "policyTags": { # Optional. The policy tags attached to this field, used for field-level access control. If not set, defaults to empty policy_tags.
+ "names": [ # A list of policy tag resource names. For example, "projects/1/locations/eu/taxonomies/2/policyTags/3". At most 1 policy tag is currently allowed.
"A String",
],
},
- "precision": "A String", # [Optional] Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: - Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] - Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: - If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. - If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): - If type = "NUMERIC": 1 ≤ precision ≤ 29. - If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
- "rangeElementType": { # Optional. The subtype of the RANGE, if the type of this field is RANGE. If the type is RANGE, this field is required. Possible values for the field element type of a RANGE include: - DATE - DATETIME - TIMESTAMP
- "type": "A String", # The field element type of a RANGE
+ "precision": "A String", # Optional. Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: * Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] * Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: * If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. * If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): * If type = "NUMERIC": 1 ≤ precision ≤ 29. * If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
+ "rangeElementType": { # Represents the type of a field element.
+ "type": "A String", # Required. The type of a field element. See TableFieldSchema.type.
},
- "roundingMode": "A String", # Optional. Rounding Mode specification of the field. It only can be set on NUMERIC or BIGNUMERIC type fields.
- "scale": "A String", # [Optional] See documentation for precision.
- "type": "A String", # [Required] The field data type. Possible values include STRING, BYTES, INTEGER, INT64 (same as INTEGER), FLOAT, FLOAT64 (same as FLOAT), NUMERIC, BIGNUMERIC, BOOLEAN, BOOL (same as BOOLEAN), TIMESTAMP, DATE, TIME, DATETIME, INTERVAL, RECORD (where RECORD indicates that the field contains a nested schema) or STRUCT (same as RECORD).
+ "roundingMode": "A String", # Optional. Specifies the rounding mode to be used when storing values of NUMERIC and BIGNUMERIC type.
+ "scale": "A String", # Optional. See documentation for precision.
+ "type": "A String", # Required. The field data type. Possible values include: * STRING * BYTES * INTEGER (or INT64) * FLOAT (or FLOAT64) * BOOLEAN (or BOOL) * TIMESTAMP * DATE * TIME * DATETIME * GEOGRAPHY * NUMERIC * BIGNUMERIC * JSON * RECORD (or STRUCT) Use of RECORD/STRUCT indicates that the field contains a nested schema.
},
],
},
- "selfLink": "A String", # [Output-only] A URL that can be used to access this resource again.
- "snapshotDefinition": { # [Output-only] Snapshot definition.
- "baseTableReference": { # [Required] Reference describing the ID of the table that was snapshot.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- },
- "snapshotTime": "A String", # [Required] The time at which the base table was snapshot. This value is reported in the JSON response using RFC3339 format.
- },
- "streamingBuffer": { # [Output-only] Contains information regarding this table's streaming buffer, if one is present. This field will be absent if the table is not being streamed to or if there is no data in the streaming buffer.
- "estimatedBytes": "A String", # [Output-only] A lower-bound estimate of the number of bytes currently in the streaming buffer.
- "estimatedRows": "A String", # [Output-only] A lower-bound estimate of the number of rows currently in the streaming buffer.
- "oldestEntryTime": "A String", # [Output-only] Contains the timestamp of the oldest entry in the streaming buffer, in milliseconds since the epoch, if the streaming buffer is available.
- },
- "tableConstraints": { # [Optional] The table constraints on the table.
- "foreignKeys": [ # [Optional] The foreign keys of the tables.
- {
- "columnReferences": [
- {
- "referencedColumn": "A String",
- "referencingColumn": "A String",
+ "selfLink": "A String", # Output only. A URL that can be used to access this resource again.
+ "snapshotDefinition": { # Information about base table and snapshot time of the snapshot. # Output only. Contains information about the snapshot. This value is set via snapshot creation.
+ "baseTableReference": { # Required. Reference describing the ID of the table that was snapshot.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ "snapshotTime": "A String", # Required. The time at which the base table was snapshot. This value is reported in the JSON response using RFC3339 format.
+ },
+ "streamingBuffer": { # Output only. Contains information regarding this table's streaming buffer, if one is present. This field will be absent if the table is not being streamed to or if there is no data in the streaming buffer.
+ "estimatedBytes": "A String", # Output only. A lower-bound estimate of the number of bytes currently in the streaming buffer.
+ "estimatedRows": "A String", # Output only. A lower-bound estimate of the number of rows currently in the streaming buffer.
+ "oldestEntryTime": "A String", # Output only. Contains the timestamp of the oldest entry in the streaming buffer, in milliseconds since the epoch, if the streaming buffer is available.
+ },
+ "tableConstraints": { # The TableConstraints defines the primary key and foreign key. # Optional. Tables Primary Key and Foreign Key information
+ "foreignKeys": [ # Optional. Present only if the table has a foreign key. The foreign key is not enforced.
+ { # Represents a foreign key constraint on a table's columns.
+ "columnReferences": [ # Required. The columns that compose the foreign key.
+ { # The pair of the foreign key column and primary key column.
+ "referencedColumn": "A String", # Required. The column in the primary key that are referenced by the referencing_column.
+ "referencingColumn": "A String", # Required. The column that composes the foreign key.
},
],
- "name": "A String",
+ "name": "A String", # Optional. Set only if the foreign key constraint is named.
"referencedTable": {
"datasetId": "A String",
"projectId": "A String",
@@ -1088,30 +1206,54 @@ Method Details
},
},
],
- "primaryKey": { # [Optional] The primary key of the table.
- "columns": [
+ "primaryKey": { # Represents the primary key constraint on a table's columns.
+ "columns": [ # Required. The columns that are composed of the primary key constraint.
"A String",
],
},
},
- "tableReference": { # [Required] Reference describing the ID of this table.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- },
- "timePartitioning": { # Time-based partitioning specification for this table. Only one of timePartitioning and rangePartitioning should be specified.
- "expirationMs": "A String", # [Optional] Number of milliseconds for which to keep the storage for partitions in the table. The storage in a partition will have an expiration time of its partition time plus this value.
- "field": "A String", # [Beta] [Optional] If not set, the table is partitioned by pseudo column, referenced via either '_PARTITIONTIME' as TIMESTAMP type, or '_PARTITIONDATE' as DATE type. If field is specified, the table is instead partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED.
- "requirePartitionFilter": True or False,
- "type": "A String", # [Required] The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively. When the type is not specified, the default behavior is DAY.
- },
- "type": "A String", # [Output-only] Describes the table type. The following values are supported: TABLE: A normal BigQuery table. VIEW: A virtual table defined by a SQL query. SNAPSHOT: An immutable, read-only table that is a copy of another table. [TrustedTester] MATERIALIZED_VIEW: SQL query whose result is persisted. EXTERNAL: A table that references data stored in an external storage system, such as Google Cloud Storage. The default value is TABLE.
- "view": { # [Optional] The view definition.
- "query": "A String", # [Required] A query that BigQuery executes when the view is referenced.
- "useExplicitColumnNames": True or False, # True if the column names are explicitly specified. For example by using the 'CREATE VIEW v(c1, c2) AS ...' syntax. Can only be set using BigQuery's standard SQL: https://cloud.google.com/bigquery/sql-reference/
- "useLegacySql": True or False, # Specifies whether to use BigQuery's legacy SQL for this view. The default value is true. If set to false, the view will use BigQuery's standard SQL: https://cloud.google.com/bigquery/sql-reference/ Queries and views that reference this view must use the same flag value.
+ "tableReference": { # Required. Reference describing the ID of this table.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ "tableReplicationInfo": { # Replication info of a table created using `AS REPLICA` DDL like: `CREATE MATERIALIZED VIEW mv1 AS REPLICA OF src_mv` # Optional. Table replication info for table created `AS REPLICA` DDL like: `CREATE MATERIALIZED VIEW mv1 AS REPLICA OF src_mv`
+ "replicatedSourceLastRefreshTime": "A String", # Optional. Output only. If source is a materialized view, this field signifies the last refresh time of the source.
+ "replicationError": { # Error details. # Optional. Output only. Replication error that will permanently stopped table replication.
+ "debugInfo": "A String", # Debugging information. This property is internal to Google and should not be used.
+ "location": "A String", # Specifies where the error occurred, if present.
+ "message": "A String", # A human-readable description of the error.
+ "reason": "A String", # A short error code that summarizes the error.
+ },
+ "replicationIntervalMs": "A String", # Required. Specifies the interval at which the source table is polled for updates.
+ "replicationStatus": "A String", # Optional. Output only. Replication status of configured replication.
+ "sourceTable": { # Required. Source table reference that is replicated.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ },
+ "timePartitioning": { # If specified, configures time-based partitioning for this table.
+ "expirationMs": "A String", # Optional. Number of milliseconds for which to keep the storage for a partition. A wrapper is used here because 0 is an invalid value.
+ "field": "A String", # Optional. If not set, the table is partitioned by pseudo column '_PARTITIONTIME'; if set, the table is partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED. A wrapper is used here because an empty string is an invalid value.
+ "requirePartitionFilter": false, # If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. This field is deprecated; please set the field with the same name on the table itself instead. This field needs a wrapper because we want to output the default value, false, if the user explicitly set it.
+ "type": "A String", # Required. The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively.
+ },
+ "type": "A String", # Output only. Describes the table type. The following values are supported: * `TABLE`: A normal BigQuery table. * `VIEW`: A virtual table defined by a SQL query. * `EXTERNAL`: A table that references data stored in an external storage system, such as Google Cloud Storage. * `MATERIALIZED_VIEW`: A precomputed view defined by a SQL query. * `SNAPSHOT`: An immutable BigQuery table that preserves the contents of a base table at a particular time. See additional information on [table snapshots](/bigquery/docs/table-snapshots-intro). The default value is `TABLE`.
+ "view": { # Describes the definition of a logical view. # Optional. The view definition.
+ "privacyPolicy": { # Represents privacy policy that contains the privacy requirements specified by the data owner. Currently, this is only supported on views. # Optional. Specifices the privacy policy for the view.
+ "aggregationThresholdPolicy": { # Represents privacy policy associated with "aggregation threshold" method. # Optional. Policy used for aggregation thresholds.
+ "privacyUnitColumns": [ # Optional. The privacy unit column(s) associated with this policy. For now, only one column per data source object (table, view) is allowed as a privacy unit column. Representing as a repeated field in metadata for extensibility to multiple columns in future. Duplicates and Repeated struct fields are not allowed. For nested fields, use dot notation ("outer.inner")
+ "A String",
+ ],
+ "threshold": "A String", # Optional. The threshold for the "aggregation threshold" policy.
+ },
+ },
+ "query": "A String", # Required. A query that BigQuery executes when the view is referenced.
+ "useExplicitColumnNames": True or False, # True if the column names are explicitly specified. For example by using the 'CREATE VIEW v(c1, c2) AS ...' syntax. Can only be set for GoogleSQL views.
+ "useLegacySql": True or False, # Specifies whether to use BigQuery's legacy SQL for this view. The default value is true. If set to false, the view will use BigQuery's GoogleSQL: https://cloud.google.com/bigquery/sql-reference/ Queries and views that reference this view must use the same flag value. A wrapper is used here because the default value is True.
"userDefinedFunctionResources": [ # Describes user-defined function resources used in the query.
- { # This is used for defining User Defined Function (UDF) resources only when using legacy SQL. Users of Standard SQL should leverage either DDL (e.g. CREATE [TEMPORARY] FUNCTION ... ) or the Routines API to define UDF resources. For additional information on migrating, see: https://cloud.google.com/bigquery/docs/reference/standard-sql/migrating-from-legacy-sql#differences_in_user-defined_javascript_functions
+ { # This is used for defining User Defined Function (UDF) resources only when using legacy SQL. Users of GoogleSQL should leverage either DDL (e.g. CREATE [TEMPORARY] FUNCTION ... ) or the Routines API to define UDF resources. For additional information on migrating, see: https://cloud.google.com/bigquery/docs/reference/standard-sql/migrating-from-legacy-sql#differences_in_user-defined_javascript_functions
"inlineCode": "A String", # [Pick one] An inline resource that contains code for a user-defined function (UDF). Providing a inline code resource is equivalent to providing a URI for a file containing the same code.
"resourceUri": "A String", # [Pick one] A code resource to load from a Google Cloud Storage URI (gs://bucket/path).
},
@@ -1121,59 +1263,72 @@ Method Details
- list(projectId, datasetId, maxResults=None, pageToken=None)
+ list(projectId, datasetId, maxResults=None, pageToken=None, x__xgafv=None)
Lists all tables in the specified dataset. Requires the READER dataset role.
Args:
- projectId: string, Project ID of the tables to list (required)
- datasetId: string, Dataset ID of the tables to list (required)
- maxResults: integer, Maximum number of results to return
+ projectId: string, Required. Project ID of the tables to list (required)
+ datasetId: string, Required. Dataset ID of the tables to list (required)
+ maxResults: integer, The maximum number of results to return in a single response page. Leverage the page tokens to iterate through the entire collection.
pageToken: string, Page token, returned by a previous call, to request the next page of results
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
Returns:
An object of the form:
- {
+ { # Partial projection of the metadata for a given table in a list response.
"etag": "A String", # A hash of this page of results.
"kind": "bigquery#tableList", # The type of list.
"nextPageToken": "A String", # A token to request the next page of results.
"tables": [ # Tables in the requested dataset.
{
- "clustering": { # [Beta] Clustering specification for this table, if configured.
- "fields": [ # [Repeated] One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. When you cluster a table using multiple columns, the order of columns you specify is important. The order of the specified columns determines the sort order of the data.
+ "clustering": { # Configures table clustering. # Clustering specification for this table, if configured.
+ "fields": [ # One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. The ordering of the clustering fields should be prioritized from most to least important for filtering purposes. Additional information on limitations can be found here: https://cloud.google.com/bigquery/docs/creating-clustered-tables#limitations
"A String",
],
},
- "creationTime": "A String", # The time when this table was created, in milliseconds since the epoch.
- "expirationTime": "A String", # [Optional] The time when this table expires, in milliseconds since the epoch. If not present, the table will persist indefinitely. Expired tables will be deleted and their storage reclaimed.
+ "creationTime": "A String", # Output only. The time when this table was created, in milliseconds since the epoch.
+ "expirationTime": "A String", # The time when this table expires, in milliseconds since the epoch. If not present, the table will persist indefinitely. Expired tables will be deleted and their storage reclaimed.
"friendlyName": "A String", # The user-friendly name for this table.
- "id": "A String", # An opaque ID of the table
- "kind": "bigquery#table", # The resource type.
+ "id": "A String", # An opaque ID of the table.
+ "kind": "A String", # The resource type.
"labels": { # The labels associated with this table. You can use these to organize and group your tables.
"a_key": "A String",
},
- "rangePartitioning": { # The range partitioning specification for this table, if configured.
- "field": "A String", # [TrustedTester] [Required] The table is partitioned by this field. The field must be a top-level NULLABLE/REQUIRED field. The only supported type is INTEGER/INT64.
- "range": { # [TrustedTester] [Required] Defines the ranges for range partitioning.
- "end": "A String", # [TrustedTester] [Required] The end of range partitioning, exclusive.
- "interval": "A String", # [TrustedTester] [Required] The width of each interval.
- "start": "A String", # [TrustedTester] [Required] The start of range partitioning, inclusive.
+ "rangePartitioning": { # The range partitioning for this table.
+ "field": "A String", # Required. [Experimental] The table is partitioned by this field. The field must be a top-level NULLABLE/REQUIRED field. The only supported type is INTEGER/INT64.
+ "range": { # [Experimental] Defines the ranges for range partitioning.
+ "end": "A String", # [Experimental] The end of range partitioning, exclusive.
+ "interval": "A String", # [Experimental] The width of each interval.
+ "start": "A String", # [Experimental] The start of range partitioning, inclusive.
},
},
- "tableReference": { # A reference uniquely identifying the table.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
+ "requirePartitionFilter": false, # Optional. If set to true, queries including this table must specify a partition filter. This filter is used for partition elimination.
+ "tableReference": { # A reference uniquely identifying table.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
},
- "timePartitioning": { # The time-based partitioning specification for this table, if configured.
- "expirationMs": "A String", # [Optional] Number of milliseconds for which to keep the storage for partitions in the table. The storage in a partition will have an expiration time of its partition time plus this value.
- "field": "A String", # [Beta] [Optional] If not set, the table is partitioned by pseudo column, referenced via either '_PARTITIONTIME' as TIMESTAMP type, or '_PARTITIONDATE' as DATE type. If field is specified, the table is instead partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED.
- "requirePartitionFilter": True or False,
- "type": "A String", # [Required] The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively. When the type is not specified, the default behavior is DAY.
+ "timePartitioning": { # The time-based partitioning for this table.
+ "expirationMs": "A String", # Optional. Number of milliseconds for which to keep the storage for a partition. A wrapper is used here because 0 is an invalid value.
+ "field": "A String", # Optional. If not set, the table is partitioned by pseudo column '_PARTITIONTIME'; if set, the table is partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED. A wrapper is used here because an empty string is an invalid value.
+ "requirePartitionFilter": false, # If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. This field is deprecated; please set the field with the same name on the table itself instead. This field needs a wrapper because we want to output the default value, false, if the user explicitly set it.
+ "type": "A String", # Required. The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively.
},
- "type": "A String", # The type of table. Possible values are: TABLE, VIEW.
- "view": { # Additional details for a view.
- "useLegacySql": True or False, # True if view is defined in legacy SQL dialect, false if in standard SQL.
+ "type": "A String", # The type of table.
+ "view": { # Information about a logical view.
+ "privacyPolicy": { # Represents privacy policy that contains the privacy requirements specified by the data owner. Currently, this is only supported on views. # Specifices the privacy policy for the view.
+ "aggregationThresholdPolicy": { # Represents privacy policy associated with "aggregation threshold" method. # Optional. Policy used for aggregation thresholds.
+ "privacyUnitColumns": [ # Optional. The privacy unit column(s) associated with this policy. For now, only one column per data source object (table, view) is allowed as a privacy unit column. Representing as a repeated field in metadata for extensibility to multiple columns in future. Duplicates and Repeated struct fields are not allowed. For nested fields, use dot notation ("outer.inner")
+ "A String",
+ ],
+ "threshold": "A String", # Optional. The threshold for the "aggregation threshold" policy.
+ },
+ },
+ "useLegacySql": True or False, # True if view is defined in legacy SQL dialect, false if in GoogleSQL.
},
},
],
@@ -1196,188 +1351,199 @@ Method Details
- patch(projectId, datasetId, tableId, autodetect_schema=None, body=None)
- Updates information in an existing table. The update method replaces the entire table resource, whereas the patch method only replaces fields that are provided in the submitted table resource. This method supports patch semantics.
+ patch(projectId, datasetId, tableId, autodetect_schema=None, body=None, x__xgafv=None)
+ Updates information in an existing table. The update method replaces the entire table resource, whereas the patch method only replaces fields that are provided in the submitted table resource. This method supports RFC5789 patch semantics.
Args:
- projectId: string, Project ID of the table to update (required)
- datasetId: string, Dataset ID of the table to update (required)
- tableId: string, Table ID of the table to update (required)
+ projectId: string, Required. Project ID of the table to update (required)
+ datasetId: string, Required. Dataset ID of the table to update (required)
+ tableId: string, Required. Table ID of the table to update (required)
body: object, The request body.
The object takes the form of:
{
- "biglakeConfiguration": { # [Optional] Specifies the configuration of a BigLake managed table.
- "connectionId": "A String", # [Required] Required and immutable. Credential reference for accessing external storage system. Normalized as project_id.location_id.connection_id.
- "fileFormat": "A String", # [Required] Required and immutable. Open source file format that the table data is stored in. Currently only PARQUET is supported.
- "storageUri": "A String", # [Required] Required and immutable. Fully qualified location prefix of the external folder where data is stored. Normalized to standard format: "gs:////". Starts with "gs://" rather than "/bigstore/". Ends with "/". Does not contain "*". See also BigLakeStorageMetadata on how it is used.
- "tableFormat": "A String", # [Required] Required and immutable. Open source file format that the table data is stored in. Currently only PARQUET is supported.
- },
- "cloneDefinition": { # [Output-only] Clone definition.
- "baseTableReference": { # [Required] Reference describing the ID of the table that was cloned.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- },
- "cloneTime": "A String", # [Required] The time at which the base table was cloned. This value is reported in the JSON response using RFC3339 format.
- },
- "clustering": { # [Beta] Clustering specification for the table. Must be specified with partitioning, data in the table will be first partitioned and subsequently clustered.
- "fields": [ # [Repeated] One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. When you cluster a table using multiple columns, the order of columns you specify is important. The order of the specified columns determines the sort order of the data.
+ "biglakeConfiguration": { # Configuration for BigLake managed tables. # Optional. Specifies the configuration of a BigLake managed table.
+ "connectionId": "A String", # Required. The connection specifying the credentials to be used to read and write to external storage, such as Cloud Storage. The connection_id can have the form "<project\_id>.<location\_id>.<connection\_id>" or "projects/<project\_id>/locations/<location\_id>/connections/<connection\_id>".
+ "fileFormat": "A String", # Required. The file format the table data is stored in.
+ "storageUri": "A String", # Required. The fully qualified location prefix of the external folder where table data is stored. The '*' wildcard character is not allowed. The URI should be in the format "gs://bucket/path_to_table/"
+ "tableFormat": "A String", # Required. The table format the metadata only snapshots are stored in.
+ },
+ "cloneDefinition": { # Information about base table and clone time of a table clone. # Output only. Contains information about the clone. This value is set via the clone operation.
+ "baseTableReference": { # Required. Reference describing the ID of the table that was cloned.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ "cloneTime": "A String", # Required. The time at which the base table was cloned. This value is reported in the JSON response using RFC3339 format.
+ },
+ "clustering": { # Configures table clustering. # Clustering specification for the table. Must be specified with time-based partitioning, data in the table will be first partitioned and subsequently clustered.
+ "fields": [ # One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. The ordering of the clustering fields should be prioritized from most to least important for filtering purposes. Additional information on limitations can be found here: https://cloud.google.com/bigquery/docs/creating-clustered-tables#limitations
"A String",
],
},
- "creationTime": "A String", # [Output-only] The time when this table was created, in milliseconds since the epoch.
- "defaultCollation": "A String", # [Output-only] The default collation of the table.
- "defaultRoundingMode": "A String", # [Output-only] The default rounding mode of the table.
- "description": "A String", # [Optional] A user-friendly description of this table.
+ "creationTime": "A String", # Output only. The time when this table was created, in milliseconds since the epoch.
+ "defaultCollation": "A String", # Optional. Defines the default collation specification of new STRING fields in the table. During table creation or update, if a STRING field is added to this table without explicit collation specified, then the table inherits the table default collation. A change to this field affects only fields added afterwards, and does not alter the existing fields. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.
+ "defaultRoundingMode": "A String", # Optional. Defines the default rounding mode specification of new decimal fields (NUMERIC OR BIGNUMERIC) in the table. During table creation or update, if a decimal field is added to this table without an explicit rounding mode specified, then the field inherits the table default rounding mode. Changing this field doesn't affect existing fields.
+ "description": "A String", # Optional. A user-friendly description of this table.
"encryptionConfiguration": { # Custom encryption configuration (e.g., Cloud KMS keys).
"kmsKeyName": "A String", # Optional. Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key.
},
- "etag": "A String", # [Output-only] A hash of the table metadata. Used to ensure there were no concurrent modifications to the resource when attempting an update. Not guaranteed to change when the table contents or the fields numRows, numBytes, numLongTermBytes or lastModifiedTime change.
- "expirationTime": "A String", # [Optional] The time when this table expires, in milliseconds since the epoch. If not present, the table will persist indefinitely. Expired tables will be deleted and their storage reclaimed. The defaultTableExpirationMs property of the encapsulating dataset can be used to set a default expirationTime on newly created tables.
- "externalDataConfiguration": { # [Optional] Describes the data format, location, and other properties of a table stored outside of BigQuery. By defining these properties, the data source can then be queried as if it were a standard BigQuery table.
+ "etag": "A String", # Output only. A hash of this resource.
+ "expirationTime": "A String", # Optional. The time when this table expires, in milliseconds since the epoch. If not present, the table will persist indefinitely. Expired tables will be deleted and their storage reclaimed. The defaultTableExpirationMs property of the encapsulating dataset can be used to set a default expirationTime on newly created tables.
+ "externalDataConfiguration": { # Optional. Describes the data format, location, and other properties of a table stored outside of BigQuery. By defining these properties, the data source can then be queried as if it were a standard BigQuery table.
"autodetect": True or False, # Try to detect schema and format options automatically. Any option specified explicitly will be honored.
- "avroOptions": { # Additional properties to set if sourceFormat is set to Avro.
- "useAvroLogicalTypes": True or False, # [Optional] If sourceFormat is set to "AVRO", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER).
- },
- "bigtableOptions": { # [Optional] Additional options if sourceFormat is set to BIGTABLE.
- "columnFamilies": [ # [Optional] List of column families to expose in the table schema along with their types. This list restricts the column families that can be referenced in queries and specifies their value types. You can use this list to do type conversions - see the 'type' field for more details. If you leave this list empty, all column families are present in the table schema and their values are read as BYTES. During a query only the column families referenced in that query are read from Bigtable.
- {
- "columns": [ # [Optional] Lists of columns that should be exposed as individual fields as opposed to a list of (column name, value) pairs. All columns whose qualifier matches a qualifier in this list can be accessed as .. Other columns can be accessed as a list through .Column field.
- {
- "encoding": "A String", # [Optional] The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. 'encoding' can also be set at the column family level. However, the setting at this level takes precedence if 'encoding' is set at both levels.
- "fieldName": "A String", # [Optional] If the qualifier is not a valid BigQuery field identifier i.e. does not match [a-zA-Z][a-zA-Z0-9_]*, a valid identifier must be provided as the column field name and is used as field name in queries.
- "onlyReadLatest": True or False, # [Optional] If this is set, only the latest version of value in this column are exposed. 'onlyReadLatest' can also be set at the column family level. However, the setting at this level takes precedence if 'onlyReadLatest' is set at both levels.
- "qualifierEncoded": "A String", # [Required] Qualifier of the column. Columns in the parent column family that has this exact qualifier are exposed as . field. If the qualifier is valid UTF-8 string, it can be specified in the qualifier_string field. Otherwise, a base-64 encoded value must be set to qualifier_encoded. The column field name is the same as the column qualifier. However, if the qualifier is not a valid BigQuery field identifier i.e. does not match [a-zA-Z][a-zA-Z0-9_]*, a valid identifier must be provided as field_name.
- "qualifierString": "A String",
- "type": "A String", # [Optional] The type to convert the value in cells of this column. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive) - BYTES STRING INTEGER FLOAT BOOLEAN Default type is BYTES. 'type' can also be set at the column family level. However, the setting at this level takes precedence if 'type' is set at both levels.
+ "avroOptions": { # Options for external data sources. # Optional. Additional properties to set if sourceFormat is set to AVRO.
+ "useAvroLogicalTypes": True or False, # Optional. If sourceFormat is set to "AVRO", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER).
+ },
+ "bigtableOptions": { # Options specific to Google Cloud Bigtable data sources. # Optional. Additional options if sourceFormat is set to BIGTABLE.
+ "columnFamilies": [ # Optional. List of column families to expose in the table schema along with their types. This list restricts the column families that can be referenced in queries and specifies their value types. You can use this list to do type conversions - see the 'type' field for more details. If you leave this list empty, all column families are present in the table schema and their values are read as BYTES. During a query only the column families referenced in that query are read from Bigtable.
+ { # Information related to a Bigtable column family.
+ "columns": [ # Optional. Lists of columns that should be exposed as individual fields as opposed to a list of (column name, value) pairs. All columns whose qualifier matches a qualifier in this list can be accessed as .. Other columns can be accessed as a list through .Column field.
+ { # Information related to a Bigtable column.
+ "encoding": "A String", # Optional. The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. 'encoding' can also be set at the column family level. However, the setting at this level takes precedence if 'encoding' is set at both levels.
+ "fieldName": "A String", # Optional. If the qualifier is not a valid BigQuery field identifier i.e. does not match a-zA-Z*, a valid identifier must be provided as the column field name and is used as field name in queries.
+ "onlyReadLatest": True or False, # Optional. If this is set, only the latest version of value in this column are exposed. 'onlyReadLatest' can also be set at the column family level. However, the setting at this level takes precedence if 'onlyReadLatest' is set at both levels.
+ "qualifierEncoded": "A String", # [Required] Qualifier of the column. Columns in the parent column family that has this exact qualifier are exposed as . field. If the qualifier is valid UTF-8 string, it can be specified in the qualifier_string field. Otherwise, a base-64 encoded value must be set to qualifier_encoded. The column field name is the same as the column qualifier. However, if the qualifier is not a valid BigQuery field identifier i.e. does not match a-zA-Z*, a valid identifier must be provided as field_name.
+ "qualifierString": "A String", # Qualifier string.
+ "type": "A String", # Optional. The type to convert the value in cells of this column. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive): * BYTES * STRING * INTEGER * FLOAT * BOOLEAN * JSON Default type is BYTES. 'type' can also be set at the column family level. However, the setting at this level takes precedence if 'type' is set at both levels.
},
],
- "encoding": "A String", # [Optional] The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. This can be overridden for a specific column by listing that column in 'columns' and specifying an encoding for it.
+ "encoding": "A String", # Optional. The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. This can be overridden for a specific column by listing that column in 'columns' and specifying an encoding for it.
"familyId": "A String", # Identifier of the column family.
- "onlyReadLatest": True or False, # [Optional] If this is set only the latest version of value are exposed for all columns in this column family. This can be overridden for a specific column by listing that column in 'columns' and specifying a different setting for that column.
- "type": "A String", # [Optional] The type to convert the value in cells of this column family. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive) - BYTES STRING INTEGER FLOAT BOOLEAN Default type is BYTES. This can be overridden for a specific column by listing that column in 'columns' and specifying a type for it.
+ "onlyReadLatest": True or False, # Optional. If this is set only the latest version of value are exposed for all columns in this column family. This can be overridden for a specific column by listing that column in 'columns' and specifying a different setting for that column.
+ "type": "A String", # Optional. The type to convert the value in cells of this column family. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive): * BYTES * STRING * INTEGER * FLOAT * BOOLEAN * JSON Default type is BYTES. This can be overridden for a specific column by listing that column in 'columns' and specifying a type for it.
},
],
- "ignoreUnspecifiedColumnFamilies": True or False, # [Optional] If field is true, then the column families that are not specified in columnFamilies list are not exposed in the table schema. Otherwise, they are read with BYTES type values. The default value is false.
- "readRowkeyAsString": True or False, # [Optional] If field is true, then the rowkey column families will be read and converted to string. Otherwise they are read with BYTES type values and users need to manually cast them with CAST if necessary. The default value is false.
- },
- "compression": "A String", # [Optional] The compression type of the data source. Possible values include GZIP and NONE. The default value is NONE. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups and Avro formats.
- "connectionId": "A String", # [Optional, Trusted Tester] Connection for external data source.
- "csvOptions": { # Additional properties to set if sourceFormat is set to CSV.
- "allowJaggedRows": True or False, # [Optional] Indicates if BigQuery should accept rows that are missing trailing optional columns. If true, BigQuery treats missing trailing columns as null values. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false.
- "allowQuotedNewlines": True or False, # [Optional] Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false.
- "encoding": "A String", # [Optional] The character encoding of the data. The supported values are UTF-8 or ISO-8859-1. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the quote and fieldDelimiter properties.
- "fieldDelimiter": "A String", # [Optional] The separator for fields in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. BigQuery also supports the escape sequence "\t" to specify a tab separator. The default value is a comma (',').
- "nullMarker": "A String", # [Optional] An custom string that will represent a NULL value in CSV import data.
- "preserveAsciiControlCharacters": True or False, # [Optional] Preserves the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\x00' to '\x1F') when loading from CSV. Only applicable to CSV, ignored for other formats.
- "quote": """, # [Optional] The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ('"'). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true.
- "skipLeadingRows": "A String", # [Optional] The number of rows at the top of a CSV file that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
- },
- "decimalTargetTypes": [ # [Optional] Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown. Example: Suppose the value of this field is ["NUMERIC", "BIGNUMERIC"]. If (precision,scale) is: (38,9) -> NUMERIC; (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits); (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits); (76,38) -> BIGNUMERIC; (77,38) -> BIGNUMERIC (error if value exeeds supported range). This field cannot contain duplicate types. The order of the types in this field is ignored. For example, ["BIGNUMERIC", "NUMERIC"] is the same as ["NUMERIC", "BIGNUMERIC"] and NUMERIC always takes precedence over BIGNUMERIC. Defaults to ["NUMERIC", "STRING"] for ORC and ["NUMERIC"] for the other file formats.
+ "ignoreUnspecifiedColumnFamilies": True or False, # Optional. If field is true, then the column families that are not specified in columnFamilies list are not exposed in the table schema. Otherwise, they are read with BYTES type values. The default value is false.
+ "outputColumnFamiliesAsJson": True or False, # Optional. If field is true, then each column family will be read as a single JSON column. Otherwise they are read as a repeated cell structure containing timestamp/value tuples. The default value is false.
+ "readRowkeyAsString": True or False, # Optional. If field is true, then the rowkey column families will be read and converted to string. Otherwise they are read with BYTES type values and users need to manually cast them with CAST if necessary. The default value is false.
+ },
+ "compression": "A String", # Optional. The compression type of the data source. Possible values include GZIP and NONE. The default value is NONE. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups, Avro, ORC and Parquet formats. An empty string is an invalid value.
+ "connectionId": "A String", # Optional. The connection specifying the credentials to be used to read external storage, such as Azure Blob, Cloud Storage, or S3. The connection_id can have the form "<project\_id>.<location\_id>.<connection\_id>" or "projects/<project\_id>/locations/<location\_id>/connections/<connection\_id>".
+ "csvOptions": { # Information related to a CSV data source. # Optional. Additional properties to set if sourceFormat is set to CSV.
+ "allowJaggedRows": True or False, # Optional. Indicates if BigQuery should accept rows that are missing trailing optional columns. If true, BigQuery treats missing trailing columns as null values. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false.
+ "allowQuotedNewlines": True or False, # Optional. Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false.
+ "encoding": "A String", # Optional. The character encoding of the data. The supported values are UTF-8, ISO-8859-1, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the quote and fieldDelimiter properties.
+ "fieldDelimiter": "A String", # Optional. The separator character for fields in a CSV file. The separator is interpreted as a single byte. For files encoded in ISO-8859-1, any single character can be used as a separator. For files encoded in UTF-8, characters represented in decimal range 1-127 (U+0001-U+007F) can be used without any modification. UTF-8 characters encoded with multiple bytes (i.e. U+0080 and above) will have only the first byte used for separating fields. The remaining bytes will be treated as a part of the field. BigQuery also supports the escape sequence "\t" (U+0009) to specify a tab separator. The default value is comma (",", U+002C).
+ "nullMarker": "A String", # [Optional] A custom string that will represent a NULL value in CSV import data.
+ "preserveAsciiControlCharacters": True or False, # Optional. Indicates if the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\x00' to '\x1F') are preserved.
+ "quote": """, # Optional. The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ("). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true. To include the specific quote character within a quoted value, precede it with an additional matching quote character. For example, if you want to escape the default character ' " ', use ' "" '.
+ "skipLeadingRows": "A String", # Optional. The number of rows at the top of a CSV file that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
+ },
+ "decimalTargetTypes": [ # Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown. Example: Suppose the value of this field is ["NUMERIC", "BIGNUMERIC"]. If (precision,scale) is: * (38,9) -> NUMERIC; * (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits); * (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits); * (76,38) -> BIGNUMERIC; * (77,38) -> BIGNUMERIC (error if value exeeds supported range). This field cannot contain duplicate types. The order of the types in this field is ignored. For example, ["BIGNUMERIC", "NUMERIC"] is the same as ["NUMERIC", "BIGNUMERIC"] and NUMERIC always takes precedence over BIGNUMERIC. Defaults to ["NUMERIC", "STRING"] for ORC and ["NUMERIC"] for the other file formats.
"A String",
],
- "fileSetSpecType": "A String", # [Optional] Specifies how source URIs are interpreted for constructing the file set to load. By default source URIs are expanded against the underlying storage. Other options include specifying manifest files. Only applicable to object storage systems.
- "googleSheetsOptions": { # [Optional] Additional options if sourceFormat is set to GOOGLE_SHEETS.
- "range": "A String", # [Optional] Range of a sheet to query from. Only used when non-empty. Typical format: sheet_name!top_left_cell_id:bottom_right_cell_id For example: sheet1!A1:B20
- "skipLeadingRows": "A String", # [Optional] The number of rows at the top of a sheet that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows that should be skipped. When autodetect is on, behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
+ "fileSetSpecType": "A String", # Optional. Specifies how source URIs are interpreted for constructing the file set to load. By default source URIs are expanded against the underlying storage. Other options include specifying manifest files. Only applicable to object storage systems.
+ "googleSheetsOptions": { # Options specific to Google Sheets data sources. # Optional. Additional options if sourceFormat is set to GOOGLE_SHEETS.
+ "range": "A String", # Optional. Range of a sheet to query from. Only used when non-empty. Typical format: sheet_name!top_left_cell_id:bottom_right_cell_id For example: sheet1!A1:B20
+ "skipLeadingRows": "A String", # Optional. The number of rows at the top of a sheet that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
},
- "hivePartitioningOptions": { # [Optional] Options to configure hive partitioning support.
- "fields": [ # [Output-only] For permanent external tables, this field is populated with the hive partition keys in the order they were inferred. The types of the partition keys can be deduced by checking the table schema (which will include the partition keys). Not every API will populate this field in the output. For example, Tables.Get will populate it, but Tables.List will not contain this field.
+ "hivePartitioningOptions": { # Options for configuring hive partitioning detect. # Optional. When set, configures hive partitioning support. Not all storage formats support hive partitioning -- requesting hive partitioning on an unsupported format will lead to an error, as will providing an invalid specification.
+ "fields": [ # Output only. For permanent external tables, this field is populated with the hive partition keys in the order they were inferred. The types of the partition keys can be deduced by checking the table schema (which will include the partition keys). Not every API will populate this field in the output. For example, Tables.Get will populate it, but Tables.List will not contain this field.
"A String",
],
- "mode": "A String", # [Optional] When set, what mode of hive partitioning to use when reading data. The following modes are supported. (1) AUTO: automatically infer partition key name(s) and type(s). (2) STRINGS: automatically infer partition key name(s). All types are interpreted as strings. (3) CUSTOM: partition key schema is encoded in the source URI prefix. Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported types include: AVRO, CSV, JSON, ORC and Parquet.
- "requirePartitionFilter": True or False, # [Optional] If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. Note that this field should only be true when creating a permanent external table or querying a temporary external table. Hive-partitioned loads with requirePartitionFilter explicitly set to true will fail.
- "sourceUriPrefix": "A String", # [Optional] When hive partition detection is requested, a common prefix for all source uris should be supplied. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout. gs://bucket/path_to_table/dt=2019-01-01/country=BR/id=7/file.avro gs://bucket/path_to_table/dt=2018-12-31/country=CA/id=3/file.avro When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/ (trailing slash does not matter).
- },
- "ignoreUnknownValues": True or False, # [Optional] Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names Google Cloud Bigtable: This setting is ignored. Google Cloud Datastore backups: This setting is ignored. Avro: This setting is ignored.
- "jsonOptions": { # Additional properties to set if `sourceFormat` is set to `NEWLINE_DELIMITED_JSON`.
- "encoding": "A String", # [Optional] The character encoding of the data. The supported values are UTF-8, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8.
- },
- "maxBadRecords": 42, # [Optional] The maximum number of bad records that BigQuery can ignore when reading data. If the number of bad records exceeds this value, an invalid error is returned in the job result. This is only valid for CSV, JSON, and Google Sheets. The default value is 0, which requires that all records are valid. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups and Avro formats.
- "metadataCacheMode": "A String", # [Optional] Metadata Cache Mode for the table. Set this to enable caching of metadata from external data source.
- "objectMetadata": "A String", # ObjectMetadata is used to create Object Tables. Object Tables contain a listing of objects (with their metadata) found at the source_uris. If ObjectMetadata is set, source_format should be omitted. Currently SIMPLE is the only supported Object Metadata type.
- "parquetOptions": { # Additional properties to set if sourceFormat is set to Parquet.
- "enableListInference": True or False, # [Optional] Indicates whether to use schema inference specifically for Parquet LIST logical type.
- "enumAsString": True or False, # [Optional] Indicates whether to infer Parquet ENUM logical type as STRING instead of BYTES by default.
- },
- "referenceFileSchemaUri": "A String", # [Optional] Provide a referencing file with the expected table schema. Enabled for the format: AVRO, PARQUET, ORC.
- "schema": { # [Optional] The schema for the data. Schema is required for CSV and JSON formats. Schema is disallowed for Google Cloud Bigtable, Cloud Datastore backups, and Avro formats.
+ "mode": "A String", # Optional. When set, what mode of hive partitioning to use when reading data. The following modes are supported: * AUTO: automatically infer partition key name(s) and type(s). * STRINGS: automatically infer partition key name(s). All types are strings. * CUSTOM: partition key schema is encoded in the source URI prefix. Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported formats are: JSON, CSV, ORC, Avro and Parquet.
+ "requirePartitionFilter": false, # Optional. If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. Note that this field should only be true when creating a permanent external table or querying a temporary external table. Hive-partitioned loads with require_partition_filter explicitly set to true will fail.
+ "sourceUriPrefix": "A String", # Optional. When hive partition detection is requested, a common prefix for all source uris must be required. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout: gs://bucket/path_to_table/dt=2019-06-01/country=USA/id=7/file.avro gs://bucket/path_to_table/dt=2019-05-31/country=CA/id=3/file.avro When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/. CUSTOM detection requires encoding the partitioning schema immediately after the common prefix. For CUSTOM, any of * gs://bucket/path_to_table/{dt:DATE}/{country:STRING}/{id:INTEGER} * gs://bucket/path_to_table/{dt:STRING}/{country:STRING}/{id:INTEGER} * gs://bucket/path_to_table/{dt:DATE}/{country:STRING}/{id:STRING} would all be valid source URI prefixes.
+ },
+ "ignoreUnknownValues": True or False, # Optional. Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names Google Cloud Bigtable: This setting is ignored. Google Cloud Datastore backups: This setting is ignored. Avro: This setting is ignored. ORC: This setting is ignored. Parquet: This setting is ignored.
+ "jsonExtension": "A String", # Optional. Load option to be used together with source_format newline-delimited JSON to indicate that a variant of JSON is being loaded. To load newline-delimited GeoJSON, specify GEOJSON (and source_format must be set to NEWLINE_DELIMITED_JSON).
+ "jsonOptions": { # Json Options for load and make external tables. # Optional. Additional properties to set if sourceFormat is set to JSON.
+ "encoding": "A String", # Optional. The character encoding of the data. The supported values are UTF-8, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8.
+ },
+ "maxBadRecords": 42, # Optional. The maximum number of bad records that BigQuery can ignore when reading data. If the number of bad records exceeds this value, an invalid error is returned in the job result. The default value is 0, which requires that all records are valid. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups, Avro, ORC and Parquet formats.
+ "metadataCacheMode": "A String", # Optional. Metadata Cache Mode for the table. Set this to enable caching of metadata from external data source.
+ "objectMetadata": "A String", # Optional. ObjectMetadata is used to create Object Tables. Object Tables contain a listing of objects (with their metadata) found at the source_uris. If ObjectMetadata is set, source_format should be omitted. Currently SIMPLE is the only supported Object Metadata type.
+ "parquetOptions": { # Parquet Options for load and make external tables. # Optional. Additional properties to set if sourceFormat is set to PARQUET.
+ "enableListInference": True or False, # Optional. Indicates whether to use schema inference specifically for Parquet LIST logical type.
+ "enumAsString": True or False, # Optional. Indicates whether to infer Parquet ENUM logical type as STRING instead of BYTES by default.
+ },
+ "referenceFileSchemaUri": "A String", # Optional. When creating an external table, the user can provide a reference file with the table schema. This is enabled for the following formats: AVRO, PARQUET, ORC.
+ "schema": { # Schema of a table # Optional. The schema for the data. Schema is required for CSV and JSON formats if autodetect is not on. Schema is disallowed for Google Cloud Bigtable, Cloud Datastore backups, Avro, ORC and Parquet formats.
"fields": [ # Describes the fields in a table.
- {
- "categories": { # [Optional] The categories attached to this field, used for field-level access control.
- "names": [ # A list of category resource names. For example, "projects/1/taxonomies/2/categories/3". At most 5 categories are allowed.
+ { # A field in TableSchema
+ "categories": { # Deprecated.
+ "names": [ # Deprecated.
"A String",
],
},
- "collation": "A String", # Optional. Collation specification of the field. It only can be set on string type field.
- "defaultValueExpression": "A String", # Optional. A SQL expression to specify the default value for this field. It can only be set for top level fields (columns). You can use struct or array expression to specify default value for the entire struct or array. The valid SQL expressions are: - Literals for all data types, including STRUCT and ARRAY. - Following functions: - CURRENT_TIMESTAMP - CURRENT_TIME - CURRENT_DATE - CURRENT_DATETIME - GENERATE_UUID - RAND - SESSION_USER - ST_GEOGPOINT - Struct or array composed with the above allowed functions, for example, [CURRENT_DATE(), DATE '2020-01-01']
- "description": "A String", # [Optional] The field description. The maximum length is 1,024 characters.
- "fields": [ # [Optional] Describes the nested schema fields if the type property is set to RECORD.
+ "collation": "A String", # Optional. Field collation can be set only when the type of field is STRING. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.
+ "defaultValueExpression": "A String", # Optional. A SQL expression to specify the [default value] (https://cloud.google.com/bigquery/docs/default-values) for this field.
+ "description": "A String", # Optional. The field description. The maximum length is 1,024 characters.
+ "fields": [ # Optional. Describes the nested schema fields if the type property is set to RECORD.
# Object with schema name: TableFieldSchema
],
- "maxLength": "A String", # [Optional] Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
- "mode": "A String", # [Optional] The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
- "name": "A String", # [Required] The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
- "policyTags": {
- "names": [ # A list of category resource names. For example, "projects/1/location/eu/taxonomies/2/policyTags/3". At most 1 policy tag is allowed.
+ "maxLength": "A String", # Optional. Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
+ "mode": "A String", # Optional. The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
+ "name": "A String", # Required. The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
+ "policyTags": { # Optional. The policy tags attached to this field, used for field-level access control. If not set, defaults to empty policy_tags.
+ "names": [ # A list of policy tag resource names. For example, "projects/1/locations/eu/taxonomies/2/policyTags/3". At most 1 policy tag is currently allowed.
"A String",
],
},
- "precision": "A String", # [Optional] Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: - Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] - Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: - If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. - If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): - If type = "NUMERIC": 1 ≤ precision ≤ 29. - If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
- "rangeElementType": { # Optional. The subtype of the RANGE, if the type of this field is RANGE. If the type is RANGE, this field is required. Possible values for the field element type of a RANGE include: - DATE - DATETIME - TIMESTAMP
- "type": "A String", # The field element type of a RANGE
+ "precision": "A String", # Optional. Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: * Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] * Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: * If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. * If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): * If type = "NUMERIC": 1 ≤ precision ≤ 29. * If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
+ "rangeElementType": { # Represents the type of a field element.
+ "type": "A String", # Required. The type of a field element. See TableFieldSchema.type.
},
- "roundingMode": "A String", # Optional. Rounding Mode specification of the field. It only can be set on NUMERIC or BIGNUMERIC type fields.
- "scale": "A String", # [Optional] See documentation for precision.
- "type": "A String", # [Required] The field data type. Possible values include STRING, BYTES, INTEGER, INT64 (same as INTEGER), FLOAT, FLOAT64 (same as FLOAT), NUMERIC, BIGNUMERIC, BOOLEAN, BOOL (same as BOOLEAN), TIMESTAMP, DATE, TIME, DATETIME, INTERVAL, RECORD (where RECORD indicates that the field contains a nested schema) or STRUCT (same as RECORD).
+ "roundingMode": "A String", # Optional. Specifies the rounding mode to be used when storing values of NUMERIC and BIGNUMERIC type.
+ "scale": "A String", # Optional. See documentation for precision.
+ "type": "A String", # Required. The field data type. Possible values include: * STRING * BYTES * INTEGER (or INT64) * FLOAT (or FLOAT64) * BOOLEAN (or BOOL) * TIMESTAMP * DATE * TIME * DATETIME * GEOGRAPHY * NUMERIC * BIGNUMERIC * JSON * RECORD (or STRUCT) Use of RECORD/STRUCT indicates that the field contains a nested schema.
},
],
},
- "sourceFormat": "A String", # [Required] The data format. For CSV files, specify "CSV". For Google sheets, specify "GOOGLE_SHEETS". For newline-delimited JSON, specify "NEWLINE_DELIMITED_JSON". For Avro files, specify "AVRO". For Google Cloud Datastore backups, specify "DATASTORE_BACKUP". [Beta] For Google Cloud Bigtable, specify "BIGTABLE".
+ "sourceFormat": "A String", # [Required] The data format. For CSV files, specify "CSV". For Google sheets, specify "GOOGLE_SHEETS". For newline-delimited JSON, specify "NEWLINE_DELIMITED_JSON". For Avro files, specify "AVRO". For Google Cloud Datastore backups, specify "DATASTORE_BACKUP". For Apache Iceberg tables, specify "ICEBERG". For ORC files, specify "ORC". For Parquet files, specify "PARQUET". [Beta] For Google Cloud Bigtable, specify "BIGTABLE".
"sourceUris": [ # [Required] The fully-qualified URIs that point to your data in Google Cloud. For Google Cloud Storage URIs: Each URI can contain one '*' wildcard character and it must come after the 'bucket' name. Size limits related to load jobs apply to external data sources. For Google Cloud Bigtable URIs: Exactly one URI can be specified and it has be a fully specified and valid HTTPS URL for a Google Cloud Bigtable table. For Google Cloud Datastore backups, exactly one URI can be specified. Also, the '*' wildcard character is not allowed.
"A String",
],
},
- "friendlyName": "A String", # [Optional] A descriptive name for this table.
- "id": "A String", # [Output-only] An opaque ID uniquely identifying the table.
- "kind": "bigquery#table", # [Output-only] The type of the resource.
+ "friendlyName": "A String", # Optional. A descriptive name for this table.
+ "id": "A String", # Output only. An opaque ID uniquely identifying the table.
+ "kind": "bigquery#table", # The type of resource ID.
"labels": { # The labels associated with this table. You can use these to organize and group your tables. Label keys and values can be no longer than 63 characters, can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. Label values are optional. Label keys must start with a letter and each label in the list must have a different key.
"a_key": "A String",
},
- "lastModifiedTime": "A String", # [Output-only] The time when this table was last modified, in milliseconds since the epoch.
- "location": "A String", # [Output-only] The geographic location where the table resides. This value is inherited from the dataset.
- "materializedView": { # [Optional] Materialized view definition.
- "allowNonIncrementalDefinition": True or False, # [Optional] Allow non incremental materialized view definition. The default value is "false".
- "enableRefresh": True or False, # [Optional] [TrustedTester] Enable automatic refresh of the materialized view when the base table is updated. The default value is "true".
- "lastRefreshTime": "A String", # [Output-only] [TrustedTester] The time when this materialized view was last modified, in milliseconds since the epoch.
+ "lastModifiedTime": "A String", # Output only. The time when this table was last modified, in milliseconds since the epoch.
+ "location": "A String", # Output only. The geographic location where the table resides. This value is inherited from the dataset.
+ "materializedView": { # Definition and configuration of a materialized view. # Optional. The materialized view definition.
+ "allowNonIncrementalDefinition": True or False, # Optional. This option declares authors intention to construct a materialized view that will not be refreshed incrementally.
+ "enableRefresh": True or False, # Optional. Enable automatic refresh of the materialized view when the base table is updated. The default value is "true".
+ "lastRefreshTime": "A String", # Output only. The time when this materialized view was last refreshed, in milliseconds since the epoch.
"maxStaleness": "A String", # [Optional] Max staleness of data that could be returned when materizlized view is queried (formatted as Google SQL Interval type).
- "query": "A String", # [Required] A query whose result is persisted.
- "refreshIntervalMs": "A String", # [Optional] [TrustedTester] The maximum frequency at which this materialized view will be refreshed. The default value is "1800000" (30 minutes).
+ "query": "A String", # Required. A query whose results are persisted.
+ "refreshIntervalMs": "A String", # Optional. The maximum frequency at which this materialized view will be refreshed. The default value is "1800000" (30 minutes).
},
- "maxStaleness": "A String", # [Optional] Max staleness of data that could be returned when table or materialized view is queried (formatted as Google SQL Interval type).
- "model": { # [Output-only, Beta] Present iff this table represents a ML model. Describes the training information for the model, and it is required to run 'PREDICT' queries.
- "modelOptions": { # [Output-only, Beta] Model options used for the first training run. These options are immutable for subsequent training runs. Default values are used for any options not specified in the input query.
+ "materializedViewStatus": { # Status of a materialized view. The last refresh timestamp status is omitted here, but is present in the MaterializedViewDefinition message. # Output only. The materialized view status.
+ "lastRefreshStatus": { # Error details. # Output only. Error result of the last automatic refresh. If present, indicates that the last automatic refresh was unsuccessful.
+ "debugInfo": "A String", # Debugging information. This property is internal to Google and should not be used.
+ "location": "A String", # Specifies where the error occurred, if present.
+ "message": "A String", # A human-readable description of the error.
+ "reason": "A String", # A short error code that summarizes the error.
+ },
+ "refreshWatermark": "A String", # Output only. Refresh watermark of materialized view. The base tables' data were collected into the materialized view cache until this time.
+ },
+ "maxStaleness": "A String", # Optional. The maximum staleness of data that could be returned when the table (or stale MV) is queried. Staleness encoded as a string encoding of sql IntervalValue type.
+ "model": { # Deprecated.
+ "modelOptions": { # Deprecated.
"labels": [
"A String",
],
"lossType": "A String",
"modelType": "A String",
},
- "trainingRuns": [ # [Output-only, Beta] Information about ml training runs, each training run comprises of multiple iterations and there may be multiple training runs for the model if warm start is used or if a user decides to continue a previously cancelled query.
+ "trainingRuns": [ # Deprecated.
{
- "iterationResults": [ # [Output-only, Beta] List of each iteration results.
+ "iterationResults": [ # Deprecated.
{
- "durationMs": "A String", # [Output-only, Beta] Time taken to run the training iteration in milliseconds.
- "evalLoss": 3.14, # [Output-only, Beta] Eval loss computed on the eval data at the end of the iteration. The eval loss is used for early stopping to avoid overfitting. No eval loss if eval_split_method option is specified as no_split or auto_split with input data size less than 500 rows.
- "index": 42, # [Output-only, Beta] Index of the ML training iteration, starting from zero for each training run.
- "learnRate": 3.14, # [Output-only, Beta] Learning rate used for this iteration, it varies for different training iterations if learn_rate_strategy option is not constant.
- "trainingLoss": 3.14, # [Output-only, Beta] Training loss computed on the training data at the end of the iteration. The training loss function is defined by model type.
+ "durationMs": "A String", # Deprecated.
+ "evalLoss": 3.14, # Deprecated.
+ "index": 42, # Deprecated.
+ "learnRate": 3.14, # Deprecated.
+ "trainingLoss": 3.14, # Deprecated.
},
],
- "startTime": "A String", # [Output-only, Beta] Training run start time in milliseconds since the epoch.
- "state": "A String", # [Output-only, Beta] Different state applicable for a training run. IN PROGRESS: Training run is in progress. FAILED: Training run ended due to a non-retryable failure. SUCCEEDED: Training run successfully completed. CANCELLED: Training run cancelled by the user.
- "trainingOptions": { # [Output-only, Beta] Training options used by this training run. These options are mutable for subsequent training runs. Default values are explicitly stored for options not specified in the input query of the first training run. For subsequent training runs, any option not explicitly specified in the input query will be copied from the previous training run.
+ "startTime": "A String", # Deprecated.
+ "state": "A String", # Deprecated.
+ "trainingOptions": { # Deprecated.
"earlyStop": True or False,
"l1Reg": 3.14,
"l2Reg": 3.14,
@@ -1391,86 +1557,93 @@ Method Details
},
],
},
- "numActiveLogicalBytes": "A String", # [Output-only] Number of logical bytes that are less than 90 days old.
- "numActivePhysicalBytes": "A String", # [Output-only] Number of physical bytes less than 90 days old. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
- "numBytes": "A String", # [Output-only] The size of this table in bytes, excluding any data in the streaming buffer.
- "numLongTermBytes": "A String", # [Output-only] The number of bytes in the table that are considered "long-term storage".
- "numLongTermLogicalBytes": "A String", # [Output-only] Number of logical bytes that are more than 90 days old.
- "numLongTermPhysicalBytes": "A String", # [Output-only] Number of physical bytes more than 90 days old. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
- "numPartitions": "A String", # [Output-only] The number of partitions present in the table or materialized view. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
- "numPhysicalBytes": "A String", # [Output-only] [TrustedTester] The physical size of this table in bytes, excluding any data in the streaming buffer. This includes compression and storage used for time travel.
- "numRows": "A String", # [Output-only] The number of rows of data in this table, excluding any data in the streaming buffer.
- "numTimeTravelPhysicalBytes": "A String", # [Output-only] Number of physical bytes used by time travel storage (deleted or changed data). This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
- "numTotalLogicalBytes": "A String", # [Output-only] Total number of logical bytes in the table or materialized view.
- "numTotalPhysicalBytes": "A String", # [Output-only] The physical size of this table in bytes. This also includes storage used for time travel. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
- "rangePartitioning": { # [TrustedTester] Range partitioning specification for this table. Only one of timePartitioning and rangePartitioning should be specified.
- "field": "A String", # [TrustedTester] [Required] The table is partitioned by this field. The field must be a top-level NULLABLE/REQUIRED field. The only supported type is INTEGER/INT64.
- "range": { # [TrustedTester] [Required] Defines the ranges for range partitioning.
- "end": "A String", # [TrustedTester] [Required] The end of range partitioning, exclusive.
- "interval": "A String", # [TrustedTester] [Required] The width of each interval.
- "start": "A String", # [TrustedTester] [Required] The start of range partitioning, inclusive.
- },
- },
- "requirePartitionFilter": false, # [Optional] If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified.
+ "numActiveLogicalBytes": "A String", # Output only. Number of logical bytes that are less than 90 days old.
+ "numActivePhysicalBytes": "A String", # Output only. Number of physical bytes less than 90 days old. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
+ "numBytes": "A String", # Output only. The size of this table in logical bytes, excluding any data in the streaming buffer.
+ "numLongTermBytes": "A String", # Output only. The number of logical bytes in the table that are considered "long-term storage".
+ "numLongTermLogicalBytes": "A String", # Output only. Number of logical bytes that are more than 90 days old.
+ "numLongTermPhysicalBytes": "A String", # Output only. Number of physical bytes more than 90 days old. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
+ "numPartitions": "A String", # Output only. The number of partitions present in the table or materialized view. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
+ "numPhysicalBytes": "A String", # Output only. The physical size of this table in bytes. This includes storage used for time travel.
+ "numRows": "A String", # Output only. The number of rows of data in this table, excluding any data in the streaming buffer.
+ "numTimeTravelPhysicalBytes": "A String", # Output only. Number of physical bytes used by time travel storage (deleted or changed data). This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
+ "numTotalLogicalBytes": "A String", # Output only. Total number of logical bytes in the table or materialized view.
+ "numTotalPhysicalBytes": "A String", # Output only. The physical size of this table in bytes. This also includes storage used for time travel. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
+ "rangePartitioning": { # If specified, configures range partitioning for this table.
+ "field": "A String", # Required. [Experimental] The table is partitioned by this field. The field must be a top-level NULLABLE/REQUIRED field. The only supported type is INTEGER/INT64.
+ "range": { # [Experimental] Defines the ranges for range partitioning.
+ "end": "A String", # [Experimental] The end of range partitioning, exclusive.
+ "interval": "A String", # [Experimental] The width of each interval.
+ "start": "A String", # [Experimental] The start of range partitioning, inclusive.
+ },
+ },
+ "replicas": [ # Optional. Output only. Table references of all replicas currently active on the table.
+ {
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ ],
+ "requirePartitionFilter": false, # Optional. If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified.
"resourceTags": { # [Optional] The tags associated with this table. Tag keys are globally unique. See additional information on [tags](https://cloud.google.com/iam/docs/tags-access-control#definitions). An object containing a list of "key": value pairs. The key is the namespaced friendly name of the tag key, e.g. "12345/environment" where 12345 is parent id. The value is the friendly short name of the tag value, e.g. "production".
"a_key": "A String",
},
- "schema": { # [Optional] Describes the schema of this table.
+ "schema": { # Schema of a table # Optional. Describes the schema of this table.
"fields": [ # Describes the fields in a table.
- {
- "categories": { # [Optional] The categories attached to this field, used for field-level access control.
- "names": [ # A list of category resource names. For example, "projects/1/taxonomies/2/categories/3". At most 5 categories are allowed.
+ { # A field in TableSchema
+ "categories": { # Deprecated.
+ "names": [ # Deprecated.
"A String",
],
},
- "collation": "A String", # Optional. Collation specification of the field. It only can be set on string type field.
- "defaultValueExpression": "A String", # Optional. A SQL expression to specify the default value for this field. It can only be set for top level fields (columns). You can use struct or array expression to specify default value for the entire struct or array. The valid SQL expressions are: - Literals for all data types, including STRUCT and ARRAY. - Following functions: - CURRENT_TIMESTAMP - CURRENT_TIME - CURRENT_DATE - CURRENT_DATETIME - GENERATE_UUID - RAND - SESSION_USER - ST_GEOGPOINT - Struct or array composed with the above allowed functions, for example, [CURRENT_DATE(), DATE '2020-01-01']
- "description": "A String", # [Optional] The field description. The maximum length is 1,024 characters.
- "fields": [ # [Optional] Describes the nested schema fields if the type property is set to RECORD.
+ "collation": "A String", # Optional. Field collation can be set only when the type of field is STRING. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.
+ "defaultValueExpression": "A String", # Optional. A SQL expression to specify the [default value] (https://cloud.google.com/bigquery/docs/default-values) for this field.
+ "description": "A String", # Optional. The field description. The maximum length is 1,024 characters.
+ "fields": [ # Optional. Describes the nested schema fields if the type property is set to RECORD.
# Object with schema name: TableFieldSchema
],
- "maxLength": "A String", # [Optional] Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
- "mode": "A String", # [Optional] The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
- "name": "A String", # [Required] The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
- "policyTags": {
- "names": [ # A list of category resource names. For example, "projects/1/location/eu/taxonomies/2/policyTags/3". At most 1 policy tag is allowed.
+ "maxLength": "A String", # Optional. Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
+ "mode": "A String", # Optional. The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
+ "name": "A String", # Required. The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
+ "policyTags": { # Optional. The policy tags attached to this field, used for field-level access control. If not set, defaults to empty policy_tags.
+ "names": [ # A list of policy tag resource names. For example, "projects/1/locations/eu/taxonomies/2/policyTags/3". At most 1 policy tag is currently allowed.
"A String",
],
},
- "precision": "A String", # [Optional] Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: - Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] - Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: - If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. - If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): - If type = "NUMERIC": 1 ≤ precision ≤ 29. - If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
- "rangeElementType": { # Optional. The subtype of the RANGE, if the type of this field is RANGE. If the type is RANGE, this field is required. Possible values for the field element type of a RANGE include: - DATE - DATETIME - TIMESTAMP
- "type": "A String", # The field element type of a RANGE
+ "precision": "A String", # Optional. Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: * Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] * Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: * If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. * If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): * If type = "NUMERIC": 1 ≤ precision ≤ 29. * If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
+ "rangeElementType": { # Represents the type of a field element.
+ "type": "A String", # Required. The type of a field element. See TableFieldSchema.type.
},
- "roundingMode": "A String", # Optional. Rounding Mode specification of the field. It only can be set on NUMERIC or BIGNUMERIC type fields.
- "scale": "A String", # [Optional] See documentation for precision.
- "type": "A String", # [Required] The field data type. Possible values include STRING, BYTES, INTEGER, INT64 (same as INTEGER), FLOAT, FLOAT64 (same as FLOAT), NUMERIC, BIGNUMERIC, BOOLEAN, BOOL (same as BOOLEAN), TIMESTAMP, DATE, TIME, DATETIME, INTERVAL, RECORD (where RECORD indicates that the field contains a nested schema) or STRUCT (same as RECORD).
+ "roundingMode": "A String", # Optional. Specifies the rounding mode to be used when storing values of NUMERIC and BIGNUMERIC type.
+ "scale": "A String", # Optional. See documentation for precision.
+ "type": "A String", # Required. The field data type. Possible values include: * STRING * BYTES * INTEGER (or INT64) * FLOAT (or FLOAT64) * BOOLEAN (or BOOL) * TIMESTAMP * DATE * TIME * DATETIME * GEOGRAPHY * NUMERIC * BIGNUMERIC * JSON * RECORD (or STRUCT) Use of RECORD/STRUCT indicates that the field contains a nested schema.
},
],
},
- "selfLink": "A String", # [Output-only] A URL that can be used to access this resource again.
- "snapshotDefinition": { # [Output-only] Snapshot definition.
- "baseTableReference": { # [Required] Reference describing the ID of the table that was snapshot.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- },
- "snapshotTime": "A String", # [Required] The time at which the base table was snapshot. This value is reported in the JSON response using RFC3339 format.
- },
- "streamingBuffer": { # [Output-only] Contains information regarding this table's streaming buffer, if one is present. This field will be absent if the table is not being streamed to or if there is no data in the streaming buffer.
- "estimatedBytes": "A String", # [Output-only] A lower-bound estimate of the number of bytes currently in the streaming buffer.
- "estimatedRows": "A String", # [Output-only] A lower-bound estimate of the number of rows currently in the streaming buffer.
- "oldestEntryTime": "A String", # [Output-only] Contains the timestamp of the oldest entry in the streaming buffer, in milliseconds since the epoch, if the streaming buffer is available.
- },
- "tableConstraints": { # [Optional] The table constraints on the table.
- "foreignKeys": [ # [Optional] The foreign keys of the tables.
- {
- "columnReferences": [
- {
- "referencedColumn": "A String",
- "referencingColumn": "A String",
+ "selfLink": "A String", # Output only. A URL that can be used to access this resource again.
+ "snapshotDefinition": { # Information about base table and snapshot time of the snapshot. # Output only. Contains information about the snapshot. This value is set via snapshot creation.
+ "baseTableReference": { # Required. Reference describing the ID of the table that was snapshot.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ "snapshotTime": "A String", # Required. The time at which the base table was snapshot. This value is reported in the JSON response using RFC3339 format.
+ },
+ "streamingBuffer": { # Output only. Contains information regarding this table's streaming buffer, if one is present. This field will be absent if the table is not being streamed to or if there is no data in the streaming buffer.
+ "estimatedBytes": "A String", # Output only. A lower-bound estimate of the number of bytes currently in the streaming buffer.
+ "estimatedRows": "A String", # Output only. A lower-bound estimate of the number of rows currently in the streaming buffer.
+ "oldestEntryTime": "A String", # Output only. Contains the timestamp of the oldest entry in the streaming buffer, in milliseconds since the epoch, if the streaming buffer is available.
+ },
+ "tableConstraints": { # The TableConstraints defines the primary key and foreign key. # Optional. Tables Primary Key and Foreign Key information
+ "foreignKeys": [ # Optional. Present only if the table has a foreign key. The foreign key is not enforced.
+ { # Represents a foreign key constraint on a table's columns.
+ "columnReferences": [ # Required. The columns that compose the foreign key.
+ { # The pair of the foreign key column and primary key column.
+ "referencedColumn": "A String", # Required. The column in the primary key that are referenced by the referencing_column.
+ "referencingColumn": "A String", # Required. The column that composes the foreign key.
},
],
- "name": "A String",
+ "name": "A String", # Optional. Set only if the foreign key constraint is named.
"referencedTable": {
"datasetId": "A String",
"projectId": "A String",
@@ -1478,30 +1651,54 @@ Method Details
},
},
],
- "primaryKey": { # [Optional] The primary key of the table.
- "columns": [
+ "primaryKey": { # Represents the primary key constraint on a table's columns.
+ "columns": [ # Required. The columns that are composed of the primary key constraint.
"A String",
],
},
},
- "tableReference": { # [Required] Reference describing the ID of this table.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- },
- "timePartitioning": { # Time-based partitioning specification for this table. Only one of timePartitioning and rangePartitioning should be specified.
- "expirationMs": "A String", # [Optional] Number of milliseconds for which to keep the storage for partitions in the table. The storage in a partition will have an expiration time of its partition time plus this value.
- "field": "A String", # [Beta] [Optional] If not set, the table is partitioned by pseudo column, referenced via either '_PARTITIONTIME' as TIMESTAMP type, or '_PARTITIONDATE' as DATE type. If field is specified, the table is instead partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED.
- "requirePartitionFilter": True or False,
- "type": "A String", # [Required] The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively. When the type is not specified, the default behavior is DAY.
- },
- "type": "A String", # [Output-only] Describes the table type. The following values are supported: TABLE: A normal BigQuery table. VIEW: A virtual table defined by a SQL query. SNAPSHOT: An immutable, read-only table that is a copy of another table. [TrustedTester] MATERIALIZED_VIEW: SQL query whose result is persisted. EXTERNAL: A table that references data stored in an external storage system, such as Google Cloud Storage. The default value is TABLE.
- "view": { # [Optional] The view definition.
- "query": "A String", # [Required] A query that BigQuery executes when the view is referenced.
- "useExplicitColumnNames": True or False, # True if the column names are explicitly specified. For example by using the 'CREATE VIEW v(c1, c2) AS ...' syntax. Can only be set using BigQuery's standard SQL: https://cloud.google.com/bigquery/sql-reference/
- "useLegacySql": True or False, # Specifies whether to use BigQuery's legacy SQL for this view. The default value is true. If set to false, the view will use BigQuery's standard SQL: https://cloud.google.com/bigquery/sql-reference/ Queries and views that reference this view must use the same flag value.
+ "tableReference": { # Required. Reference describing the ID of this table.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ "tableReplicationInfo": { # Replication info of a table created using `AS REPLICA` DDL like: `CREATE MATERIALIZED VIEW mv1 AS REPLICA OF src_mv` # Optional. Table replication info for table created `AS REPLICA` DDL like: `CREATE MATERIALIZED VIEW mv1 AS REPLICA OF src_mv`
+ "replicatedSourceLastRefreshTime": "A String", # Optional. Output only. If source is a materialized view, this field signifies the last refresh time of the source.
+ "replicationError": { # Error details. # Optional. Output only. Replication error that will permanently stopped table replication.
+ "debugInfo": "A String", # Debugging information. This property is internal to Google and should not be used.
+ "location": "A String", # Specifies where the error occurred, if present.
+ "message": "A String", # A human-readable description of the error.
+ "reason": "A String", # A short error code that summarizes the error.
+ },
+ "replicationIntervalMs": "A String", # Required. Specifies the interval at which the source table is polled for updates.
+ "replicationStatus": "A String", # Optional. Output only. Replication status of configured replication.
+ "sourceTable": { # Required. Source table reference that is replicated.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ },
+ "timePartitioning": { # If specified, configures time-based partitioning for this table.
+ "expirationMs": "A String", # Optional. Number of milliseconds for which to keep the storage for a partition. A wrapper is used here because 0 is an invalid value.
+ "field": "A String", # Optional. If not set, the table is partitioned by pseudo column '_PARTITIONTIME'; if set, the table is partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED. A wrapper is used here because an empty string is an invalid value.
+ "requirePartitionFilter": false, # If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. This field is deprecated; please set the field with the same name on the table itself instead. This field needs a wrapper because we want to output the default value, false, if the user explicitly set it.
+ "type": "A String", # Required. The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively.
+ },
+ "type": "A String", # Output only. Describes the table type. The following values are supported: * `TABLE`: A normal BigQuery table. * `VIEW`: A virtual table defined by a SQL query. * `EXTERNAL`: A table that references data stored in an external storage system, such as Google Cloud Storage. * `MATERIALIZED_VIEW`: A precomputed view defined by a SQL query. * `SNAPSHOT`: An immutable BigQuery table that preserves the contents of a base table at a particular time. See additional information on [table snapshots](/bigquery/docs/table-snapshots-intro). The default value is `TABLE`.
+ "view": { # Describes the definition of a logical view. # Optional. The view definition.
+ "privacyPolicy": { # Represents privacy policy that contains the privacy requirements specified by the data owner. Currently, this is only supported on views. # Optional. Specifices the privacy policy for the view.
+ "aggregationThresholdPolicy": { # Represents privacy policy associated with "aggregation threshold" method. # Optional. Policy used for aggregation thresholds.
+ "privacyUnitColumns": [ # Optional. The privacy unit column(s) associated with this policy. For now, only one column per data source object (table, view) is allowed as a privacy unit column. Representing as a repeated field in metadata for extensibility to multiple columns in future. Duplicates and Repeated struct fields are not allowed. For nested fields, use dot notation ("outer.inner")
+ "A String",
+ ],
+ "threshold": "A String", # Optional. The threshold for the "aggregation threshold" policy.
+ },
+ },
+ "query": "A String", # Required. A query that BigQuery executes when the view is referenced.
+ "useExplicitColumnNames": True or False, # True if the column names are explicitly specified. For example by using the 'CREATE VIEW v(c1, c2) AS ...' syntax. Can only be set for GoogleSQL views.
+ "useLegacySql": True or False, # Specifies whether to use BigQuery's legacy SQL for this view. The default value is true. If set to false, the view will use BigQuery's GoogleSQL: https://cloud.google.com/bigquery/sql-reference/ Queries and views that reference this view must use the same flag value. A wrapper is used here because the default value is True.
"userDefinedFunctionResources": [ # Describes user-defined function resources used in the query.
- { # This is used for defining User Defined Function (UDF) resources only when using legacy SQL. Users of Standard SQL should leverage either DDL (e.g. CREATE [TEMPORARY] FUNCTION ... ) or the Routines API to define UDF resources. For additional information on migrating, see: https://cloud.google.com/bigquery/docs/reference/standard-sql/migrating-from-legacy-sql#differences_in_user-defined_javascript_functions
+ { # This is used for defining User Defined Function (UDF) resources only when using legacy SQL. Users of GoogleSQL should leverage either DDL (e.g. CREATE [TEMPORARY] FUNCTION ... ) or the Routines API to define UDF resources. For additional information on migrating, see: https://cloud.google.com/bigquery/docs/reference/standard-sql/migrating-from-legacy-sql#differences_in_user-defined_javascript_functions
"inlineCode": "A String", # [Pick one] An inline resource that contains code for a user-defined function (UDF). Providing a inline code resource is equivalent to providing a URI for a file containing the same code.
"resourceUri": "A String", # [Pick one] A code resource to load from a Google Cloud Storage URI (gs://bucket/path).
},
@@ -1509,183 +1706,198 @@ Method Details
},
}
- autodetect_schema: boolean, When true will autodetect schema, else will keep original schema
+ autodetect_schema: boolean, Optional. When true will autodetect schema, else will keep original schema
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
Returns:
An object of the form:
{
- "biglakeConfiguration": { # [Optional] Specifies the configuration of a BigLake managed table.
- "connectionId": "A String", # [Required] Required and immutable. Credential reference for accessing external storage system. Normalized as project_id.location_id.connection_id.
- "fileFormat": "A String", # [Required] Required and immutable. Open source file format that the table data is stored in. Currently only PARQUET is supported.
- "storageUri": "A String", # [Required] Required and immutable. Fully qualified location prefix of the external folder where data is stored. Normalized to standard format: "gs:////". Starts with "gs://" rather than "/bigstore/". Ends with "/". Does not contain "*". See also BigLakeStorageMetadata on how it is used.
- "tableFormat": "A String", # [Required] Required and immutable. Open source file format that the table data is stored in. Currently only PARQUET is supported.
- },
- "cloneDefinition": { # [Output-only] Clone definition.
- "baseTableReference": { # [Required] Reference describing the ID of the table that was cloned.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- },
- "cloneTime": "A String", # [Required] The time at which the base table was cloned. This value is reported in the JSON response using RFC3339 format.
- },
- "clustering": { # [Beta] Clustering specification for the table. Must be specified with partitioning, data in the table will be first partitioned and subsequently clustered.
- "fields": [ # [Repeated] One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. When you cluster a table using multiple columns, the order of columns you specify is important. The order of the specified columns determines the sort order of the data.
+ "biglakeConfiguration": { # Configuration for BigLake managed tables. # Optional. Specifies the configuration of a BigLake managed table.
+ "connectionId": "A String", # Required. The connection specifying the credentials to be used to read and write to external storage, such as Cloud Storage. The connection_id can have the form "<project\_id>.<location\_id>.<connection\_id>" or "projects/<project\_id>/locations/<location\_id>/connections/<connection\_id>".
+ "fileFormat": "A String", # Required. The file format the table data is stored in.
+ "storageUri": "A String", # Required. The fully qualified location prefix of the external folder where table data is stored. The '*' wildcard character is not allowed. The URI should be in the format "gs://bucket/path_to_table/"
+ "tableFormat": "A String", # Required. The table format the metadata only snapshots are stored in.
+ },
+ "cloneDefinition": { # Information about base table and clone time of a table clone. # Output only. Contains information about the clone. This value is set via the clone operation.
+ "baseTableReference": { # Required. Reference describing the ID of the table that was cloned.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ "cloneTime": "A String", # Required. The time at which the base table was cloned. This value is reported in the JSON response using RFC3339 format.
+ },
+ "clustering": { # Configures table clustering. # Clustering specification for the table. Must be specified with time-based partitioning, data in the table will be first partitioned and subsequently clustered.
+ "fields": [ # One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. The ordering of the clustering fields should be prioritized from most to least important for filtering purposes. Additional information on limitations can be found here: https://cloud.google.com/bigquery/docs/creating-clustered-tables#limitations
"A String",
],
},
- "creationTime": "A String", # [Output-only] The time when this table was created, in milliseconds since the epoch.
- "defaultCollation": "A String", # [Output-only] The default collation of the table.
- "defaultRoundingMode": "A String", # [Output-only] The default rounding mode of the table.
- "description": "A String", # [Optional] A user-friendly description of this table.
+ "creationTime": "A String", # Output only. The time when this table was created, in milliseconds since the epoch.
+ "defaultCollation": "A String", # Optional. Defines the default collation specification of new STRING fields in the table. During table creation or update, if a STRING field is added to this table without explicit collation specified, then the table inherits the table default collation. A change to this field affects only fields added afterwards, and does not alter the existing fields. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.
+ "defaultRoundingMode": "A String", # Optional. Defines the default rounding mode specification of new decimal fields (NUMERIC OR BIGNUMERIC) in the table. During table creation or update, if a decimal field is added to this table without an explicit rounding mode specified, then the field inherits the table default rounding mode. Changing this field doesn't affect existing fields.
+ "description": "A String", # Optional. A user-friendly description of this table.
"encryptionConfiguration": { # Custom encryption configuration (e.g., Cloud KMS keys).
"kmsKeyName": "A String", # Optional. Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key.
},
- "etag": "A String", # [Output-only] A hash of the table metadata. Used to ensure there were no concurrent modifications to the resource when attempting an update. Not guaranteed to change when the table contents or the fields numRows, numBytes, numLongTermBytes or lastModifiedTime change.
- "expirationTime": "A String", # [Optional] The time when this table expires, in milliseconds since the epoch. If not present, the table will persist indefinitely. Expired tables will be deleted and their storage reclaimed. The defaultTableExpirationMs property of the encapsulating dataset can be used to set a default expirationTime on newly created tables.
- "externalDataConfiguration": { # [Optional] Describes the data format, location, and other properties of a table stored outside of BigQuery. By defining these properties, the data source can then be queried as if it were a standard BigQuery table.
+ "etag": "A String", # Output only. A hash of this resource.
+ "expirationTime": "A String", # Optional. The time when this table expires, in milliseconds since the epoch. If not present, the table will persist indefinitely. Expired tables will be deleted and their storage reclaimed. The defaultTableExpirationMs property of the encapsulating dataset can be used to set a default expirationTime on newly created tables.
+ "externalDataConfiguration": { # Optional. Describes the data format, location, and other properties of a table stored outside of BigQuery. By defining these properties, the data source can then be queried as if it were a standard BigQuery table.
"autodetect": True or False, # Try to detect schema and format options automatically. Any option specified explicitly will be honored.
- "avroOptions": { # Additional properties to set if sourceFormat is set to Avro.
- "useAvroLogicalTypes": True or False, # [Optional] If sourceFormat is set to "AVRO", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER).
- },
- "bigtableOptions": { # [Optional] Additional options if sourceFormat is set to BIGTABLE.
- "columnFamilies": [ # [Optional] List of column families to expose in the table schema along with their types. This list restricts the column families that can be referenced in queries and specifies their value types. You can use this list to do type conversions - see the 'type' field for more details. If you leave this list empty, all column families are present in the table schema and their values are read as BYTES. During a query only the column families referenced in that query are read from Bigtable.
- {
- "columns": [ # [Optional] Lists of columns that should be exposed as individual fields as opposed to a list of (column name, value) pairs. All columns whose qualifier matches a qualifier in this list can be accessed as .. Other columns can be accessed as a list through .Column field.
- {
- "encoding": "A String", # [Optional] The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. 'encoding' can also be set at the column family level. However, the setting at this level takes precedence if 'encoding' is set at both levels.
- "fieldName": "A String", # [Optional] If the qualifier is not a valid BigQuery field identifier i.e. does not match [a-zA-Z][a-zA-Z0-9_]*, a valid identifier must be provided as the column field name and is used as field name in queries.
- "onlyReadLatest": True or False, # [Optional] If this is set, only the latest version of value in this column are exposed. 'onlyReadLatest' can also be set at the column family level. However, the setting at this level takes precedence if 'onlyReadLatest' is set at both levels.
- "qualifierEncoded": "A String", # [Required] Qualifier of the column. Columns in the parent column family that has this exact qualifier are exposed as . field. If the qualifier is valid UTF-8 string, it can be specified in the qualifier_string field. Otherwise, a base-64 encoded value must be set to qualifier_encoded. The column field name is the same as the column qualifier. However, if the qualifier is not a valid BigQuery field identifier i.e. does not match [a-zA-Z][a-zA-Z0-9_]*, a valid identifier must be provided as field_name.
- "qualifierString": "A String",
- "type": "A String", # [Optional] The type to convert the value in cells of this column. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive) - BYTES STRING INTEGER FLOAT BOOLEAN Default type is BYTES. 'type' can also be set at the column family level. However, the setting at this level takes precedence if 'type' is set at both levels.
+ "avroOptions": { # Options for external data sources. # Optional. Additional properties to set if sourceFormat is set to AVRO.
+ "useAvroLogicalTypes": True or False, # Optional. If sourceFormat is set to "AVRO", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER).
+ },
+ "bigtableOptions": { # Options specific to Google Cloud Bigtable data sources. # Optional. Additional options if sourceFormat is set to BIGTABLE.
+ "columnFamilies": [ # Optional. List of column families to expose in the table schema along with their types. This list restricts the column families that can be referenced in queries and specifies their value types. You can use this list to do type conversions - see the 'type' field for more details. If you leave this list empty, all column families are present in the table schema and their values are read as BYTES. During a query only the column families referenced in that query are read from Bigtable.
+ { # Information related to a Bigtable column family.
+ "columns": [ # Optional. Lists of columns that should be exposed as individual fields as opposed to a list of (column name, value) pairs. All columns whose qualifier matches a qualifier in this list can be accessed as .. Other columns can be accessed as a list through .Column field.
+ { # Information related to a Bigtable column.
+ "encoding": "A String", # Optional. The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. 'encoding' can also be set at the column family level. However, the setting at this level takes precedence if 'encoding' is set at both levels.
+ "fieldName": "A String", # Optional. If the qualifier is not a valid BigQuery field identifier i.e. does not match a-zA-Z*, a valid identifier must be provided as the column field name and is used as field name in queries.
+ "onlyReadLatest": True or False, # Optional. If this is set, only the latest version of value in this column are exposed. 'onlyReadLatest' can also be set at the column family level. However, the setting at this level takes precedence if 'onlyReadLatest' is set at both levels.
+ "qualifierEncoded": "A String", # [Required] Qualifier of the column. Columns in the parent column family that has this exact qualifier are exposed as . field. If the qualifier is valid UTF-8 string, it can be specified in the qualifier_string field. Otherwise, a base-64 encoded value must be set to qualifier_encoded. The column field name is the same as the column qualifier. However, if the qualifier is not a valid BigQuery field identifier i.e. does not match a-zA-Z*, a valid identifier must be provided as field_name.
+ "qualifierString": "A String", # Qualifier string.
+ "type": "A String", # Optional. The type to convert the value in cells of this column. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive): * BYTES * STRING * INTEGER * FLOAT * BOOLEAN * JSON Default type is BYTES. 'type' can also be set at the column family level. However, the setting at this level takes precedence if 'type' is set at both levels.
},
],
- "encoding": "A String", # [Optional] The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. This can be overridden for a specific column by listing that column in 'columns' and specifying an encoding for it.
+ "encoding": "A String", # Optional. The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. This can be overridden for a specific column by listing that column in 'columns' and specifying an encoding for it.
"familyId": "A String", # Identifier of the column family.
- "onlyReadLatest": True or False, # [Optional] If this is set only the latest version of value are exposed for all columns in this column family. This can be overridden for a specific column by listing that column in 'columns' and specifying a different setting for that column.
- "type": "A String", # [Optional] The type to convert the value in cells of this column family. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive) - BYTES STRING INTEGER FLOAT BOOLEAN Default type is BYTES. This can be overridden for a specific column by listing that column in 'columns' and specifying a type for it.
+ "onlyReadLatest": True or False, # Optional. If this is set only the latest version of value are exposed for all columns in this column family. This can be overridden for a specific column by listing that column in 'columns' and specifying a different setting for that column.
+ "type": "A String", # Optional. The type to convert the value in cells of this column family. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive): * BYTES * STRING * INTEGER * FLOAT * BOOLEAN * JSON Default type is BYTES. This can be overridden for a specific column by listing that column in 'columns' and specifying a type for it.
},
],
- "ignoreUnspecifiedColumnFamilies": True or False, # [Optional] If field is true, then the column families that are not specified in columnFamilies list are not exposed in the table schema. Otherwise, they are read with BYTES type values. The default value is false.
- "readRowkeyAsString": True or False, # [Optional] If field is true, then the rowkey column families will be read and converted to string. Otherwise they are read with BYTES type values and users need to manually cast them with CAST if necessary. The default value is false.
- },
- "compression": "A String", # [Optional] The compression type of the data source. Possible values include GZIP and NONE. The default value is NONE. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups and Avro formats.
- "connectionId": "A String", # [Optional, Trusted Tester] Connection for external data source.
- "csvOptions": { # Additional properties to set if sourceFormat is set to CSV.
- "allowJaggedRows": True or False, # [Optional] Indicates if BigQuery should accept rows that are missing trailing optional columns. If true, BigQuery treats missing trailing columns as null values. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false.
- "allowQuotedNewlines": True or False, # [Optional] Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false.
- "encoding": "A String", # [Optional] The character encoding of the data. The supported values are UTF-8 or ISO-8859-1. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the quote and fieldDelimiter properties.
- "fieldDelimiter": "A String", # [Optional] The separator for fields in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. BigQuery also supports the escape sequence "\t" to specify a tab separator. The default value is a comma (',').
- "nullMarker": "A String", # [Optional] An custom string that will represent a NULL value in CSV import data.
- "preserveAsciiControlCharacters": True or False, # [Optional] Preserves the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\x00' to '\x1F') when loading from CSV. Only applicable to CSV, ignored for other formats.
- "quote": """, # [Optional] The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ('"'). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true.
- "skipLeadingRows": "A String", # [Optional] The number of rows at the top of a CSV file that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
- },
- "decimalTargetTypes": [ # [Optional] Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown. Example: Suppose the value of this field is ["NUMERIC", "BIGNUMERIC"]. If (precision,scale) is: (38,9) -> NUMERIC; (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits); (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits); (76,38) -> BIGNUMERIC; (77,38) -> BIGNUMERIC (error if value exeeds supported range). This field cannot contain duplicate types. The order of the types in this field is ignored. For example, ["BIGNUMERIC", "NUMERIC"] is the same as ["NUMERIC", "BIGNUMERIC"] and NUMERIC always takes precedence over BIGNUMERIC. Defaults to ["NUMERIC", "STRING"] for ORC and ["NUMERIC"] for the other file formats.
+ "ignoreUnspecifiedColumnFamilies": True or False, # Optional. If field is true, then the column families that are not specified in columnFamilies list are not exposed in the table schema. Otherwise, they are read with BYTES type values. The default value is false.
+ "outputColumnFamiliesAsJson": True or False, # Optional. If field is true, then each column family will be read as a single JSON column. Otherwise they are read as a repeated cell structure containing timestamp/value tuples. The default value is false.
+ "readRowkeyAsString": True or False, # Optional. If field is true, then the rowkey column families will be read and converted to string. Otherwise they are read with BYTES type values and users need to manually cast them with CAST if necessary. The default value is false.
+ },
+ "compression": "A String", # Optional. The compression type of the data source. Possible values include GZIP and NONE. The default value is NONE. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups, Avro, ORC and Parquet formats. An empty string is an invalid value.
+ "connectionId": "A String", # Optional. The connection specifying the credentials to be used to read external storage, such as Azure Blob, Cloud Storage, or S3. The connection_id can have the form "<project\_id>.<location\_id>.<connection\_id>" or "projects/<project\_id>/locations/<location\_id>/connections/<connection\_id>".
+ "csvOptions": { # Information related to a CSV data source. # Optional. Additional properties to set if sourceFormat is set to CSV.
+ "allowJaggedRows": True or False, # Optional. Indicates if BigQuery should accept rows that are missing trailing optional columns. If true, BigQuery treats missing trailing columns as null values. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false.
+ "allowQuotedNewlines": True or False, # Optional. Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false.
+ "encoding": "A String", # Optional. The character encoding of the data. The supported values are UTF-8, ISO-8859-1, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the quote and fieldDelimiter properties.
+ "fieldDelimiter": "A String", # Optional. The separator character for fields in a CSV file. The separator is interpreted as a single byte. For files encoded in ISO-8859-1, any single character can be used as a separator. For files encoded in UTF-8, characters represented in decimal range 1-127 (U+0001-U+007F) can be used without any modification. UTF-8 characters encoded with multiple bytes (i.e. U+0080 and above) will have only the first byte used for separating fields. The remaining bytes will be treated as a part of the field. BigQuery also supports the escape sequence "\t" (U+0009) to specify a tab separator. The default value is comma (",", U+002C).
+ "nullMarker": "A String", # [Optional] A custom string that will represent a NULL value in CSV import data.
+ "preserveAsciiControlCharacters": True or False, # Optional. Indicates if the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\x00' to '\x1F') are preserved.
+ "quote": """, # Optional. The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ("). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true. To include the specific quote character within a quoted value, precede it with an additional matching quote character. For example, if you want to escape the default character ' " ', use ' "" '.
+ "skipLeadingRows": "A String", # Optional. The number of rows at the top of a CSV file that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
+ },
+ "decimalTargetTypes": [ # Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown. Example: Suppose the value of this field is ["NUMERIC", "BIGNUMERIC"]. If (precision,scale) is: * (38,9) -> NUMERIC; * (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits); * (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits); * (76,38) -> BIGNUMERIC; * (77,38) -> BIGNUMERIC (error if value exeeds supported range). This field cannot contain duplicate types. The order of the types in this field is ignored. For example, ["BIGNUMERIC", "NUMERIC"] is the same as ["NUMERIC", "BIGNUMERIC"] and NUMERIC always takes precedence over BIGNUMERIC. Defaults to ["NUMERIC", "STRING"] for ORC and ["NUMERIC"] for the other file formats.
"A String",
],
- "fileSetSpecType": "A String", # [Optional] Specifies how source URIs are interpreted for constructing the file set to load. By default source URIs are expanded against the underlying storage. Other options include specifying manifest files. Only applicable to object storage systems.
- "googleSheetsOptions": { # [Optional] Additional options if sourceFormat is set to GOOGLE_SHEETS.
- "range": "A String", # [Optional] Range of a sheet to query from. Only used when non-empty. Typical format: sheet_name!top_left_cell_id:bottom_right_cell_id For example: sheet1!A1:B20
- "skipLeadingRows": "A String", # [Optional] The number of rows at the top of a sheet that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows that should be skipped. When autodetect is on, behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
+ "fileSetSpecType": "A String", # Optional. Specifies how source URIs are interpreted for constructing the file set to load. By default source URIs are expanded against the underlying storage. Other options include specifying manifest files. Only applicable to object storage systems.
+ "googleSheetsOptions": { # Options specific to Google Sheets data sources. # Optional. Additional options if sourceFormat is set to GOOGLE_SHEETS.
+ "range": "A String", # Optional. Range of a sheet to query from. Only used when non-empty. Typical format: sheet_name!top_left_cell_id:bottom_right_cell_id For example: sheet1!A1:B20
+ "skipLeadingRows": "A String", # Optional. The number of rows at the top of a sheet that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
},
- "hivePartitioningOptions": { # [Optional] Options to configure hive partitioning support.
- "fields": [ # [Output-only] For permanent external tables, this field is populated with the hive partition keys in the order they were inferred. The types of the partition keys can be deduced by checking the table schema (which will include the partition keys). Not every API will populate this field in the output. For example, Tables.Get will populate it, but Tables.List will not contain this field.
+ "hivePartitioningOptions": { # Options for configuring hive partitioning detect. # Optional. When set, configures hive partitioning support. Not all storage formats support hive partitioning -- requesting hive partitioning on an unsupported format will lead to an error, as will providing an invalid specification.
+ "fields": [ # Output only. For permanent external tables, this field is populated with the hive partition keys in the order they were inferred. The types of the partition keys can be deduced by checking the table schema (which will include the partition keys). Not every API will populate this field in the output. For example, Tables.Get will populate it, but Tables.List will not contain this field.
"A String",
],
- "mode": "A String", # [Optional] When set, what mode of hive partitioning to use when reading data. The following modes are supported. (1) AUTO: automatically infer partition key name(s) and type(s). (2) STRINGS: automatically infer partition key name(s). All types are interpreted as strings. (3) CUSTOM: partition key schema is encoded in the source URI prefix. Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported types include: AVRO, CSV, JSON, ORC and Parquet.
- "requirePartitionFilter": True or False, # [Optional] If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. Note that this field should only be true when creating a permanent external table or querying a temporary external table. Hive-partitioned loads with requirePartitionFilter explicitly set to true will fail.
- "sourceUriPrefix": "A String", # [Optional] When hive partition detection is requested, a common prefix for all source uris should be supplied. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout. gs://bucket/path_to_table/dt=2019-01-01/country=BR/id=7/file.avro gs://bucket/path_to_table/dt=2018-12-31/country=CA/id=3/file.avro When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/ (trailing slash does not matter).
- },
- "ignoreUnknownValues": True or False, # [Optional] Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names Google Cloud Bigtable: This setting is ignored. Google Cloud Datastore backups: This setting is ignored. Avro: This setting is ignored.
- "jsonOptions": { # Additional properties to set if `sourceFormat` is set to `NEWLINE_DELIMITED_JSON`.
- "encoding": "A String", # [Optional] The character encoding of the data. The supported values are UTF-8, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8.
- },
- "maxBadRecords": 42, # [Optional] The maximum number of bad records that BigQuery can ignore when reading data. If the number of bad records exceeds this value, an invalid error is returned in the job result. This is only valid for CSV, JSON, and Google Sheets. The default value is 0, which requires that all records are valid. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups and Avro formats.
- "metadataCacheMode": "A String", # [Optional] Metadata Cache Mode for the table. Set this to enable caching of metadata from external data source.
- "objectMetadata": "A String", # ObjectMetadata is used to create Object Tables. Object Tables contain a listing of objects (with their metadata) found at the source_uris. If ObjectMetadata is set, source_format should be omitted. Currently SIMPLE is the only supported Object Metadata type.
- "parquetOptions": { # Additional properties to set if sourceFormat is set to Parquet.
- "enableListInference": True or False, # [Optional] Indicates whether to use schema inference specifically for Parquet LIST logical type.
- "enumAsString": True or False, # [Optional] Indicates whether to infer Parquet ENUM logical type as STRING instead of BYTES by default.
- },
- "referenceFileSchemaUri": "A String", # [Optional] Provide a referencing file with the expected table schema. Enabled for the format: AVRO, PARQUET, ORC.
- "schema": { # [Optional] The schema for the data. Schema is required for CSV and JSON formats. Schema is disallowed for Google Cloud Bigtable, Cloud Datastore backups, and Avro formats.
+ "mode": "A String", # Optional. When set, what mode of hive partitioning to use when reading data. The following modes are supported: * AUTO: automatically infer partition key name(s) and type(s). * STRINGS: automatically infer partition key name(s). All types are strings. * CUSTOM: partition key schema is encoded in the source URI prefix. Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported formats are: JSON, CSV, ORC, Avro and Parquet.
+ "requirePartitionFilter": false, # Optional. If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. Note that this field should only be true when creating a permanent external table or querying a temporary external table. Hive-partitioned loads with require_partition_filter explicitly set to true will fail.
+ "sourceUriPrefix": "A String", # Optional. When hive partition detection is requested, a common prefix for all source uris must be required. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout: gs://bucket/path_to_table/dt=2019-06-01/country=USA/id=7/file.avro gs://bucket/path_to_table/dt=2019-05-31/country=CA/id=3/file.avro When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/. CUSTOM detection requires encoding the partitioning schema immediately after the common prefix. For CUSTOM, any of * gs://bucket/path_to_table/{dt:DATE}/{country:STRING}/{id:INTEGER} * gs://bucket/path_to_table/{dt:STRING}/{country:STRING}/{id:INTEGER} * gs://bucket/path_to_table/{dt:DATE}/{country:STRING}/{id:STRING} would all be valid source URI prefixes.
+ },
+ "ignoreUnknownValues": True or False, # Optional. Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names Google Cloud Bigtable: This setting is ignored. Google Cloud Datastore backups: This setting is ignored. Avro: This setting is ignored. ORC: This setting is ignored. Parquet: This setting is ignored.
+ "jsonExtension": "A String", # Optional. Load option to be used together with source_format newline-delimited JSON to indicate that a variant of JSON is being loaded. To load newline-delimited GeoJSON, specify GEOJSON (and source_format must be set to NEWLINE_DELIMITED_JSON).
+ "jsonOptions": { # Json Options for load and make external tables. # Optional. Additional properties to set if sourceFormat is set to JSON.
+ "encoding": "A String", # Optional. The character encoding of the data. The supported values are UTF-8, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8.
+ },
+ "maxBadRecords": 42, # Optional. The maximum number of bad records that BigQuery can ignore when reading data. If the number of bad records exceeds this value, an invalid error is returned in the job result. The default value is 0, which requires that all records are valid. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups, Avro, ORC and Parquet formats.
+ "metadataCacheMode": "A String", # Optional. Metadata Cache Mode for the table. Set this to enable caching of metadata from external data source.
+ "objectMetadata": "A String", # Optional. ObjectMetadata is used to create Object Tables. Object Tables contain a listing of objects (with their metadata) found at the source_uris. If ObjectMetadata is set, source_format should be omitted. Currently SIMPLE is the only supported Object Metadata type.
+ "parquetOptions": { # Parquet Options for load and make external tables. # Optional. Additional properties to set if sourceFormat is set to PARQUET.
+ "enableListInference": True or False, # Optional. Indicates whether to use schema inference specifically for Parquet LIST logical type.
+ "enumAsString": True or False, # Optional. Indicates whether to infer Parquet ENUM logical type as STRING instead of BYTES by default.
+ },
+ "referenceFileSchemaUri": "A String", # Optional. When creating an external table, the user can provide a reference file with the table schema. This is enabled for the following formats: AVRO, PARQUET, ORC.
+ "schema": { # Schema of a table # Optional. The schema for the data. Schema is required for CSV and JSON formats if autodetect is not on. Schema is disallowed for Google Cloud Bigtable, Cloud Datastore backups, Avro, ORC and Parquet formats.
"fields": [ # Describes the fields in a table.
- {
- "categories": { # [Optional] The categories attached to this field, used for field-level access control.
- "names": [ # A list of category resource names. For example, "projects/1/taxonomies/2/categories/3". At most 5 categories are allowed.
+ { # A field in TableSchema
+ "categories": { # Deprecated.
+ "names": [ # Deprecated.
"A String",
],
},
- "collation": "A String", # Optional. Collation specification of the field. It only can be set on string type field.
- "defaultValueExpression": "A String", # Optional. A SQL expression to specify the default value for this field. It can only be set for top level fields (columns). You can use struct or array expression to specify default value for the entire struct or array. The valid SQL expressions are: - Literals for all data types, including STRUCT and ARRAY. - Following functions: - CURRENT_TIMESTAMP - CURRENT_TIME - CURRENT_DATE - CURRENT_DATETIME - GENERATE_UUID - RAND - SESSION_USER - ST_GEOGPOINT - Struct or array composed with the above allowed functions, for example, [CURRENT_DATE(), DATE '2020-01-01']
- "description": "A String", # [Optional] The field description. The maximum length is 1,024 characters.
- "fields": [ # [Optional] Describes the nested schema fields if the type property is set to RECORD.
+ "collation": "A String", # Optional. Field collation can be set only when the type of field is STRING. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.
+ "defaultValueExpression": "A String", # Optional. A SQL expression to specify the [default value] (https://cloud.google.com/bigquery/docs/default-values) for this field.
+ "description": "A String", # Optional. The field description. The maximum length is 1,024 characters.
+ "fields": [ # Optional. Describes the nested schema fields if the type property is set to RECORD.
# Object with schema name: TableFieldSchema
],
- "maxLength": "A String", # [Optional] Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
- "mode": "A String", # [Optional] The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
- "name": "A String", # [Required] The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
- "policyTags": {
- "names": [ # A list of category resource names. For example, "projects/1/location/eu/taxonomies/2/policyTags/3". At most 1 policy tag is allowed.
+ "maxLength": "A String", # Optional. Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
+ "mode": "A String", # Optional. The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
+ "name": "A String", # Required. The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
+ "policyTags": { # Optional. The policy tags attached to this field, used for field-level access control. If not set, defaults to empty policy_tags.
+ "names": [ # A list of policy tag resource names. For example, "projects/1/locations/eu/taxonomies/2/policyTags/3". At most 1 policy tag is currently allowed.
"A String",
],
},
- "precision": "A String", # [Optional] Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: - Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] - Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: - If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. - If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): - If type = "NUMERIC": 1 ≤ precision ≤ 29. - If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
- "rangeElementType": { # Optional. The subtype of the RANGE, if the type of this field is RANGE. If the type is RANGE, this field is required. Possible values for the field element type of a RANGE include: - DATE - DATETIME - TIMESTAMP
- "type": "A String", # The field element type of a RANGE
+ "precision": "A String", # Optional. Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: * Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] * Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: * If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. * If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): * If type = "NUMERIC": 1 ≤ precision ≤ 29. * If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
+ "rangeElementType": { # Represents the type of a field element.
+ "type": "A String", # Required. The type of a field element. See TableFieldSchema.type.
},
- "roundingMode": "A String", # Optional. Rounding Mode specification of the field. It only can be set on NUMERIC or BIGNUMERIC type fields.
- "scale": "A String", # [Optional] See documentation for precision.
- "type": "A String", # [Required] The field data type. Possible values include STRING, BYTES, INTEGER, INT64 (same as INTEGER), FLOAT, FLOAT64 (same as FLOAT), NUMERIC, BIGNUMERIC, BOOLEAN, BOOL (same as BOOLEAN), TIMESTAMP, DATE, TIME, DATETIME, INTERVAL, RECORD (where RECORD indicates that the field contains a nested schema) or STRUCT (same as RECORD).
+ "roundingMode": "A String", # Optional. Specifies the rounding mode to be used when storing values of NUMERIC and BIGNUMERIC type.
+ "scale": "A String", # Optional. See documentation for precision.
+ "type": "A String", # Required. The field data type. Possible values include: * STRING * BYTES * INTEGER (or INT64) * FLOAT (or FLOAT64) * BOOLEAN (or BOOL) * TIMESTAMP * DATE * TIME * DATETIME * GEOGRAPHY * NUMERIC * BIGNUMERIC * JSON * RECORD (or STRUCT) Use of RECORD/STRUCT indicates that the field contains a nested schema.
},
],
},
- "sourceFormat": "A String", # [Required] The data format. For CSV files, specify "CSV". For Google sheets, specify "GOOGLE_SHEETS". For newline-delimited JSON, specify "NEWLINE_DELIMITED_JSON". For Avro files, specify "AVRO". For Google Cloud Datastore backups, specify "DATASTORE_BACKUP". [Beta] For Google Cloud Bigtable, specify "BIGTABLE".
+ "sourceFormat": "A String", # [Required] The data format. For CSV files, specify "CSV". For Google sheets, specify "GOOGLE_SHEETS". For newline-delimited JSON, specify "NEWLINE_DELIMITED_JSON". For Avro files, specify "AVRO". For Google Cloud Datastore backups, specify "DATASTORE_BACKUP". For Apache Iceberg tables, specify "ICEBERG". For ORC files, specify "ORC". For Parquet files, specify "PARQUET". [Beta] For Google Cloud Bigtable, specify "BIGTABLE".
"sourceUris": [ # [Required] The fully-qualified URIs that point to your data in Google Cloud. For Google Cloud Storage URIs: Each URI can contain one '*' wildcard character and it must come after the 'bucket' name. Size limits related to load jobs apply to external data sources. For Google Cloud Bigtable URIs: Exactly one URI can be specified and it has be a fully specified and valid HTTPS URL for a Google Cloud Bigtable table. For Google Cloud Datastore backups, exactly one URI can be specified. Also, the '*' wildcard character is not allowed.
"A String",
],
},
- "friendlyName": "A String", # [Optional] A descriptive name for this table.
- "id": "A String", # [Output-only] An opaque ID uniquely identifying the table.
- "kind": "bigquery#table", # [Output-only] The type of the resource.
+ "friendlyName": "A String", # Optional. A descriptive name for this table.
+ "id": "A String", # Output only. An opaque ID uniquely identifying the table.
+ "kind": "bigquery#table", # The type of resource ID.
"labels": { # The labels associated with this table. You can use these to organize and group your tables. Label keys and values can be no longer than 63 characters, can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. Label values are optional. Label keys must start with a letter and each label in the list must have a different key.
"a_key": "A String",
},
- "lastModifiedTime": "A String", # [Output-only] The time when this table was last modified, in milliseconds since the epoch.
- "location": "A String", # [Output-only] The geographic location where the table resides. This value is inherited from the dataset.
- "materializedView": { # [Optional] Materialized view definition.
- "allowNonIncrementalDefinition": True or False, # [Optional] Allow non incremental materialized view definition. The default value is "false".
- "enableRefresh": True or False, # [Optional] [TrustedTester] Enable automatic refresh of the materialized view when the base table is updated. The default value is "true".
- "lastRefreshTime": "A String", # [Output-only] [TrustedTester] The time when this materialized view was last modified, in milliseconds since the epoch.
+ "lastModifiedTime": "A String", # Output only. The time when this table was last modified, in milliseconds since the epoch.
+ "location": "A String", # Output only. The geographic location where the table resides. This value is inherited from the dataset.
+ "materializedView": { # Definition and configuration of a materialized view. # Optional. The materialized view definition.
+ "allowNonIncrementalDefinition": True or False, # Optional. This option declares authors intention to construct a materialized view that will not be refreshed incrementally.
+ "enableRefresh": True or False, # Optional. Enable automatic refresh of the materialized view when the base table is updated. The default value is "true".
+ "lastRefreshTime": "A String", # Output only. The time when this materialized view was last refreshed, in milliseconds since the epoch.
"maxStaleness": "A String", # [Optional] Max staleness of data that could be returned when materizlized view is queried (formatted as Google SQL Interval type).
- "query": "A String", # [Required] A query whose result is persisted.
- "refreshIntervalMs": "A String", # [Optional] [TrustedTester] The maximum frequency at which this materialized view will be refreshed. The default value is "1800000" (30 minutes).
+ "query": "A String", # Required. A query whose results are persisted.
+ "refreshIntervalMs": "A String", # Optional. The maximum frequency at which this materialized view will be refreshed. The default value is "1800000" (30 minutes).
+ },
+ "materializedViewStatus": { # Status of a materialized view. The last refresh timestamp status is omitted here, but is present in the MaterializedViewDefinition message. # Output only. The materialized view status.
+ "lastRefreshStatus": { # Error details. # Output only. Error result of the last automatic refresh. If present, indicates that the last automatic refresh was unsuccessful.
+ "debugInfo": "A String", # Debugging information. This property is internal to Google and should not be used.
+ "location": "A String", # Specifies where the error occurred, if present.
+ "message": "A String", # A human-readable description of the error.
+ "reason": "A String", # A short error code that summarizes the error.
+ },
+ "refreshWatermark": "A String", # Output only. Refresh watermark of materialized view. The base tables' data were collected into the materialized view cache until this time.
},
- "maxStaleness": "A String", # [Optional] Max staleness of data that could be returned when table or materialized view is queried (formatted as Google SQL Interval type).
- "model": { # [Output-only, Beta] Present iff this table represents a ML model. Describes the training information for the model, and it is required to run 'PREDICT' queries.
- "modelOptions": { # [Output-only, Beta] Model options used for the first training run. These options are immutable for subsequent training runs. Default values are used for any options not specified in the input query.
+ "maxStaleness": "A String", # Optional. The maximum staleness of data that could be returned when the table (or stale MV) is queried. Staleness encoded as a string encoding of sql IntervalValue type.
+ "model": { # Deprecated.
+ "modelOptions": { # Deprecated.
"labels": [
"A String",
],
"lossType": "A String",
"modelType": "A String",
},
- "trainingRuns": [ # [Output-only, Beta] Information about ml training runs, each training run comprises of multiple iterations and there may be multiple training runs for the model if warm start is used or if a user decides to continue a previously cancelled query.
+ "trainingRuns": [ # Deprecated.
{
- "iterationResults": [ # [Output-only, Beta] List of each iteration results.
+ "iterationResults": [ # Deprecated.
{
- "durationMs": "A String", # [Output-only, Beta] Time taken to run the training iteration in milliseconds.
- "evalLoss": 3.14, # [Output-only, Beta] Eval loss computed on the eval data at the end of the iteration. The eval loss is used for early stopping to avoid overfitting. No eval loss if eval_split_method option is specified as no_split or auto_split with input data size less than 500 rows.
- "index": 42, # [Output-only, Beta] Index of the ML training iteration, starting from zero for each training run.
- "learnRate": 3.14, # [Output-only, Beta] Learning rate used for this iteration, it varies for different training iterations if learn_rate_strategy option is not constant.
- "trainingLoss": 3.14, # [Output-only, Beta] Training loss computed on the training data at the end of the iteration. The training loss function is defined by model type.
+ "durationMs": "A String", # Deprecated.
+ "evalLoss": 3.14, # Deprecated.
+ "index": 42, # Deprecated.
+ "learnRate": 3.14, # Deprecated.
+ "trainingLoss": 3.14, # Deprecated.
},
],
- "startTime": "A String", # [Output-only, Beta] Training run start time in milliseconds since the epoch.
- "state": "A String", # [Output-only, Beta] Different state applicable for a training run. IN PROGRESS: Training run is in progress. FAILED: Training run ended due to a non-retryable failure. SUCCEEDED: Training run successfully completed. CANCELLED: Training run cancelled by the user.
- "trainingOptions": { # [Output-only, Beta] Training options used by this training run. These options are mutable for subsequent training runs. Default values are explicitly stored for options not specified in the input query of the first training run. For subsequent training runs, any option not explicitly specified in the input query will be copied from the previous training run.
+ "startTime": "A String", # Deprecated.
+ "state": "A String", # Deprecated.
+ "trainingOptions": { # Deprecated.
"earlyStop": True or False,
"l1Reg": 3.14,
"l2Reg": 3.14,
@@ -1699,86 +1911,93 @@ Method Details
},
],
},
- "numActiveLogicalBytes": "A String", # [Output-only] Number of logical bytes that are less than 90 days old.
- "numActivePhysicalBytes": "A String", # [Output-only] Number of physical bytes less than 90 days old. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
- "numBytes": "A String", # [Output-only] The size of this table in bytes, excluding any data in the streaming buffer.
- "numLongTermBytes": "A String", # [Output-only] The number of bytes in the table that are considered "long-term storage".
- "numLongTermLogicalBytes": "A String", # [Output-only] Number of logical bytes that are more than 90 days old.
- "numLongTermPhysicalBytes": "A String", # [Output-only] Number of physical bytes more than 90 days old. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
- "numPartitions": "A String", # [Output-only] The number of partitions present in the table or materialized view. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
- "numPhysicalBytes": "A String", # [Output-only] [TrustedTester] The physical size of this table in bytes, excluding any data in the streaming buffer. This includes compression and storage used for time travel.
- "numRows": "A String", # [Output-only] The number of rows of data in this table, excluding any data in the streaming buffer.
- "numTimeTravelPhysicalBytes": "A String", # [Output-only] Number of physical bytes used by time travel storage (deleted or changed data). This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
- "numTotalLogicalBytes": "A String", # [Output-only] Total number of logical bytes in the table or materialized view.
- "numTotalPhysicalBytes": "A String", # [Output-only] The physical size of this table in bytes. This also includes storage used for time travel. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
- "rangePartitioning": { # [TrustedTester] Range partitioning specification for this table. Only one of timePartitioning and rangePartitioning should be specified.
- "field": "A String", # [TrustedTester] [Required] The table is partitioned by this field. The field must be a top-level NULLABLE/REQUIRED field. The only supported type is INTEGER/INT64.
- "range": { # [TrustedTester] [Required] Defines the ranges for range partitioning.
- "end": "A String", # [TrustedTester] [Required] The end of range partitioning, exclusive.
- "interval": "A String", # [TrustedTester] [Required] The width of each interval.
- "start": "A String", # [TrustedTester] [Required] The start of range partitioning, inclusive.
- },
- },
- "requirePartitionFilter": false, # [Optional] If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified.
+ "numActiveLogicalBytes": "A String", # Output only. Number of logical bytes that are less than 90 days old.
+ "numActivePhysicalBytes": "A String", # Output only. Number of physical bytes less than 90 days old. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
+ "numBytes": "A String", # Output only. The size of this table in logical bytes, excluding any data in the streaming buffer.
+ "numLongTermBytes": "A String", # Output only. The number of logical bytes in the table that are considered "long-term storage".
+ "numLongTermLogicalBytes": "A String", # Output only. Number of logical bytes that are more than 90 days old.
+ "numLongTermPhysicalBytes": "A String", # Output only. Number of physical bytes more than 90 days old. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
+ "numPartitions": "A String", # Output only. The number of partitions present in the table or materialized view. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
+ "numPhysicalBytes": "A String", # Output only. The physical size of this table in bytes. This includes storage used for time travel.
+ "numRows": "A String", # Output only. The number of rows of data in this table, excluding any data in the streaming buffer.
+ "numTimeTravelPhysicalBytes": "A String", # Output only. Number of physical bytes used by time travel storage (deleted or changed data). This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
+ "numTotalLogicalBytes": "A String", # Output only. Total number of logical bytes in the table or materialized view.
+ "numTotalPhysicalBytes": "A String", # Output only. The physical size of this table in bytes. This also includes storage used for time travel. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
+ "rangePartitioning": { # If specified, configures range partitioning for this table.
+ "field": "A String", # Required. [Experimental] The table is partitioned by this field. The field must be a top-level NULLABLE/REQUIRED field. The only supported type is INTEGER/INT64.
+ "range": { # [Experimental] Defines the ranges for range partitioning.
+ "end": "A String", # [Experimental] The end of range partitioning, exclusive.
+ "interval": "A String", # [Experimental] The width of each interval.
+ "start": "A String", # [Experimental] The start of range partitioning, inclusive.
+ },
+ },
+ "replicas": [ # Optional. Output only. Table references of all replicas currently active on the table.
+ {
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ ],
+ "requirePartitionFilter": false, # Optional. If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified.
"resourceTags": { # [Optional] The tags associated with this table. Tag keys are globally unique. See additional information on [tags](https://cloud.google.com/iam/docs/tags-access-control#definitions). An object containing a list of "key": value pairs. The key is the namespaced friendly name of the tag key, e.g. "12345/environment" where 12345 is parent id. The value is the friendly short name of the tag value, e.g. "production".
"a_key": "A String",
},
- "schema": { # [Optional] Describes the schema of this table.
+ "schema": { # Schema of a table # Optional. Describes the schema of this table.
"fields": [ # Describes the fields in a table.
- {
- "categories": { # [Optional] The categories attached to this field, used for field-level access control.
- "names": [ # A list of category resource names. For example, "projects/1/taxonomies/2/categories/3". At most 5 categories are allowed.
+ { # A field in TableSchema
+ "categories": { # Deprecated.
+ "names": [ # Deprecated.
"A String",
],
},
- "collation": "A String", # Optional. Collation specification of the field. It only can be set on string type field.
- "defaultValueExpression": "A String", # Optional. A SQL expression to specify the default value for this field. It can only be set for top level fields (columns). You can use struct or array expression to specify default value for the entire struct or array. The valid SQL expressions are: - Literals for all data types, including STRUCT and ARRAY. - Following functions: - CURRENT_TIMESTAMP - CURRENT_TIME - CURRENT_DATE - CURRENT_DATETIME - GENERATE_UUID - RAND - SESSION_USER - ST_GEOGPOINT - Struct or array composed with the above allowed functions, for example, [CURRENT_DATE(), DATE '2020-01-01']
- "description": "A String", # [Optional] The field description. The maximum length is 1,024 characters.
- "fields": [ # [Optional] Describes the nested schema fields if the type property is set to RECORD.
+ "collation": "A String", # Optional. Field collation can be set only when the type of field is STRING. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.
+ "defaultValueExpression": "A String", # Optional. A SQL expression to specify the [default value] (https://cloud.google.com/bigquery/docs/default-values) for this field.
+ "description": "A String", # Optional. The field description. The maximum length is 1,024 characters.
+ "fields": [ # Optional. Describes the nested schema fields if the type property is set to RECORD.
# Object with schema name: TableFieldSchema
],
- "maxLength": "A String", # [Optional] Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
- "mode": "A String", # [Optional] The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
- "name": "A String", # [Required] The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
- "policyTags": {
- "names": [ # A list of category resource names. For example, "projects/1/location/eu/taxonomies/2/policyTags/3". At most 1 policy tag is allowed.
+ "maxLength": "A String", # Optional. Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
+ "mode": "A String", # Optional. The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
+ "name": "A String", # Required. The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
+ "policyTags": { # Optional. The policy tags attached to this field, used for field-level access control. If not set, defaults to empty policy_tags.
+ "names": [ # A list of policy tag resource names. For example, "projects/1/locations/eu/taxonomies/2/policyTags/3". At most 1 policy tag is currently allowed.
"A String",
],
},
- "precision": "A String", # [Optional] Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: - Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] - Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: - If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. - If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): - If type = "NUMERIC": 1 ≤ precision ≤ 29. - If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
- "rangeElementType": { # Optional. The subtype of the RANGE, if the type of this field is RANGE. If the type is RANGE, this field is required. Possible values for the field element type of a RANGE include: - DATE - DATETIME - TIMESTAMP
- "type": "A String", # The field element type of a RANGE
+ "precision": "A String", # Optional. Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: * Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] * Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: * If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. * If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): * If type = "NUMERIC": 1 ≤ precision ≤ 29. * If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
+ "rangeElementType": { # Represents the type of a field element.
+ "type": "A String", # Required. The type of a field element. See TableFieldSchema.type.
},
- "roundingMode": "A String", # Optional. Rounding Mode specification of the field. It only can be set on NUMERIC or BIGNUMERIC type fields.
- "scale": "A String", # [Optional] See documentation for precision.
- "type": "A String", # [Required] The field data type. Possible values include STRING, BYTES, INTEGER, INT64 (same as INTEGER), FLOAT, FLOAT64 (same as FLOAT), NUMERIC, BIGNUMERIC, BOOLEAN, BOOL (same as BOOLEAN), TIMESTAMP, DATE, TIME, DATETIME, INTERVAL, RECORD (where RECORD indicates that the field contains a nested schema) or STRUCT (same as RECORD).
+ "roundingMode": "A String", # Optional. Specifies the rounding mode to be used when storing values of NUMERIC and BIGNUMERIC type.
+ "scale": "A String", # Optional. See documentation for precision.
+ "type": "A String", # Required. The field data type. Possible values include: * STRING * BYTES * INTEGER (or INT64) * FLOAT (or FLOAT64) * BOOLEAN (or BOOL) * TIMESTAMP * DATE * TIME * DATETIME * GEOGRAPHY * NUMERIC * BIGNUMERIC * JSON * RECORD (or STRUCT) Use of RECORD/STRUCT indicates that the field contains a nested schema.
},
],
},
- "selfLink": "A String", # [Output-only] A URL that can be used to access this resource again.
- "snapshotDefinition": { # [Output-only] Snapshot definition.
- "baseTableReference": { # [Required] Reference describing the ID of the table that was snapshot.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- },
- "snapshotTime": "A String", # [Required] The time at which the base table was snapshot. This value is reported in the JSON response using RFC3339 format.
- },
- "streamingBuffer": { # [Output-only] Contains information regarding this table's streaming buffer, if one is present. This field will be absent if the table is not being streamed to or if there is no data in the streaming buffer.
- "estimatedBytes": "A String", # [Output-only] A lower-bound estimate of the number of bytes currently in the streaming buffer.
- "estimatedRows": "A String", # [Output-only] A lower-bound estimate of the number of rows currently in the streaming buffer.
- "oldestEntryTime": "A String", # [Output-only] Contains the timestamp of the oldest entry in the streaming buffer, in milliseconds since the epoch, if the streaming buffer is available.
- },
- "tableConstraints": { # [Optional] The table constraints on the table.
- "foreignKeys": [ # [Optional] The foreign keys of the tables.
- {
- "columnReferences": [
- {
- "referencedColumn": "A String",
- "referencingColumn": "A String",
+ "selfLink": "A String", # Output only. A URL that can be used to access this resource again.
+ "snapshotDefinition": { # Information about base table and snapshot time of the snapshot. # Output only. Contains information about the snapshot. This value is set via snapshot creation.
+ "baseTableReference": { # Required. Reference describing the ID of the table that was snapshot.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ "snapshotTime": "A String", # Required. The time at which the base table was snapshot. This value is reported in the JSON response using RFC3339 format.
+ },
+ "streamingBuffer": { # Output only. Contains information regarding this table's streaming buffer, if one is present. This field will be absent if the table is not being streamed to or if there is no data in the streaming buffer.
+ "estimatedBytes": "A String", # Output only. A lower-bound estimate of the number of bytes currently in the streaming buffer.
+ "estimatedRows": "A String", # Output only. A lower-bound estimate of the number of rows currently in the streaming buffer.
+ "oldestEntryTime": "A String", # Output only. Contains the timestamp of the oldest entry in the streaming buffer, in milliseconds since the epoch, if the streaming buffer is available.
+ },
+ "tableConstraints": { # The TableConstraints defines the primary key and foreign key. # Optional. Tables Primary Key and Foreign Key information
+ "foreignKeys": [ # Optional. Present only if the table has a foreign key. The foreign key is not enforced.
+ { # Represents a foreign key constraint on a table's columns.
+ "columnReferences": [ # Required. The columns that compose the foreign key.
+ { # The pair of the foreign key column and primary key column.
+ "referencedColumn": "A String", # Required. The column in the primary key that are referenced by the referencing_column.
+ "referencingColumn": "A String", # Required. The column that composes the foreign key.
},
],
- "name": "A String",
+ "name": "A String", # Optional. Set only if the foreign key constraint is named.
"referencedTable": {
"datasetId": "A String",
"projectId": "A String",
@@ -1786,30 +2005,54 @@ Method Details
},
},
],
- "primaryKey": { # [Optional] The primary key of the table.
- "columns": [
+ "primaryKey": { # Represents the primary key constraint on a table's columns.
+ "columns": [ # Required. The columns that are composed of the primary key constraint.
"A String",
],
},
},
- "tableReference": { # [Required] Reference describing the ID of this table.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- },
- "timePartitioning": { # Time-based partitioning specification for this table. Only one of timePartitioning and rangePartitioning should be specified.
- "expirationMs": "A String", # [Optional] Number of milliseconds for which to keep the storage for partitions in the table. The storage in a partition will have an expiration time of its partition time plus this value.
- "field": "A String", # [Beta] [Optional] If not set, the table is partitioned by pseudo column, referenced via either '_PARTITIONTIME' as TIMESTAMP type, or '_PARTITIONDATE' as DATE type. If field is specified, the table is instead partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED.
- "requirePartitionFilter": True or False,
- "type": "A String", # [Required] The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively. When the type is not specified, the default behavior is DAY.
- },
- "type": "A String", # [Output-only] Describes the table type. The following values are supported: TABLE: A normal BigQuery table. VIEW: A virtual table defined by a SQL query. SNAPSHOT: An immutable, read-only table that is a copy of another table. [TrustedTester] MATERIALIZED_VIEW: SQL query whose result is persisted. EXTERNAL: A table that references data stored in an external storage system, such as Google Cloud Storage. The default value is TABLE.
- "view": { # [Optional] The view definition.
- "query": "A String", # [Required] A query that BigQuery executes when the view is referenced.
- "useExplicitColumnNames": True or False, # True if the column names are explicitly specified. For example by using the 'CREATE VIEW v(c1, c2) AS ...' syntax. Can only be set using BigQuery's standard SQL: https://cloud.google.com/bigquery/sql-reference/
- "useLegacySql": True or False, # Specifies whether to use BigQuery's legacy SQL for this view. The default value is true. If set to false, the view will use BigQuery's standard SQL: https://cloud.google.com/bigquery/sql-reference/ Queries and views that reference this view must use the same flag value.
+ "tableReference": { # Required. Reference describing the ID of this table.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ "tableReplicationInfo": { # Replication info of a table created using `AS REPLICA` DDL like: `CREATE MATERIALIZED VIEW mv1 AS REPLICA OF src_mv` # Optional. Table replication info for table created `AS REPLICA` DDL like: `CREATE MATERIALIZED VIEW mv1 AS REPLICA OF src_mv`
+ "replicatedSourceLastRefreshTime": "A String", # Optional. Output only. If source is a materialized view, this field signifies the last refresh time of the source.
+ "replicationError": { # Error details. # Optional. Output only. Replication error that will permanently stopped table replication.
+ "debugInfo": "A String", # Debugging information. This property is internal to Google and should not be used.
+ "location": "A String", # Specifies where the error occurred, if present.
+ "message": "A String", # A human-readable description of the error.
+ "reason": "A String", # A short error code that summarizes the error.
+ },
+ "replicationIntervalMs": "A String", # Required. Specifies the interval at which the source table is polled for updates.
+ "replicationStatus": "A String", # Optional. Output only. Replication status of configured replication.
+ "sourceTable": { # Required. Source table reference that is replicated.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ },
+ "timePartitioning": { # If specified, configures time-based partitioning for this table.
+ "expirationMs": "A String", # Optional. Number of milliseconds for which to keep the storage for a partition. A wrapper is used here because 0 is an invalid value.
+ "field": "A String", # Optional. If not set, the table is partitioned by pseudo column '_PARTITIONTIME'; if set, the table is partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED. A wrapper is used here because an empty string is an invalid value.
+ "requirePartitionFilter": false, # If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. This field is deprecated; please set the field with the same name on the table itself instead. This field needs a wrapper because we want to output the default value, false, if the user explicitly set it.
+ "type": "A String", # Required. The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively.
+ },
+ "type": "A String", # Output only. Describes the table type. The following values are supported: * `TABLE`: A normal BigQuery table. * `VIEW`: A virtual table defined by a SQL query. * `EXTERNAL`: A table that references data stored in an external storage system, such as Google Cloud Storage. * `MATERIALIZED_VIEW`: A precomputed view defined by a SQL query. * `SNAPSHOT`: An immutable BigQuery table that preserves the contents of a base table at a particular time. See additional information on [table snapshots](/bigquery/docs/table-snapshots-intro). The default value is `TABLE`.
+ "view": { # Describes the definition of a logical view. # Optional. The view definition.
+ "privacyPolicy": { # Represents privacy policy that contains the privacy requirements specified by the data owner. Currently, this is only supported on views. # Optional. Specifices the privacy policy for the view.
+ "aggregationThresholdPolicy": { # Represents privacy policy associated with "aggregation threshold" method. # Optional. Policy used for aggregation thresholds.
+ "privacyUnitColumns": [ # Optional. The privacy unit column(s) associated with this policy. For now, only one column per data source object (table, view) is allowed as a privacy unit column. Representing as a repeated field in metadata for extensibility to multiple columns in future. Duplicates and Repeated struct fields are not allowed. For nested fields, use dot notation ("outer.inner")
+ "A String",
+ ],
+ "threshold": "A String", # Optional. The threshold for the "aggregation threshold" policy.
+ },
+ },
+ "query": "A String", # Required. A query that BigQuery executes when the view is referenced.
+ "useExplicitColumnNames": True or False, # True if the column names are explicitly specified. For example by using the 'CREATE VIEW v(c1, c2) AS ...' syntax. Can only be set for GoogleSQL views.
+ "useLegacySql": True or False, # Specifies whether to use BigQuery's legacy SQL for this view. The default value is true. If set to false, the view will use BigQuery's GoogleSQL: https://cloud.google.com/bigquery/sql-reference/ Queries and views that reference this view must use the same flag value. A wrapper is used here because the default value is True.
"userDefinedFunctionResources": [ # Describes user-defined function resources used in the query.
- { # This is used for defining User Defined Function (UDF) resources only when using legacy SQL. Users of Standard SQL should leverage either DDL (e.g. CREATE [TEMPORARY] FUNCTION ... ) or the Routines API to define UDF resources. For additional information on migrating, see: https://cloud.google.com/bigquery/docs/reference/standard-sql/migrating-from-legacy-sql#differences_in_user-defined_javascript_functions
+ { # This is used for defining User Defined Function (UDF) resources only when using legacy SQL. Users of GoogleSQL should leverage either DDL (e.g. CREATE [TEMPORARY] FUNCTION ... ) or the Routines API to define UDF resources. For additional information on migrating, see: https://cloud.google.com/bigquery/docs/reference/standard-sql/migrating-from-legacy-sql#differences_in_user-defined_javascript_functions
"inlineCode": "A String", # [Pick one] An inline resource that contains code for a user-defined function (UDF). Providing a inline code resource is equivalent to providing a URI for a file containing the same code.
"resourceUri": "A String", # [Pick one] A code resource to load from a Google Cloud Storage URI (gs://bucket/path).
},
@@ -1819,7 +2062,7 @@ Method Details
- setIamPolicy(resource, body=None)
+ setIamPolicy(resource, body=None, x__xgafv=None)
Sets the access control policy on the specified resource. Replaces any existing policy. Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED` errors.
Args:
@@ -1853,7 +2096,7 @@ Method Details
"members": [ # Specifies the principals requesting access for a Google Cloud resource. `members` can have the following values: * `allUsers`: A special identifier that represents anyone who is on the internet; with or without a Google account. * `allAuthenticatedUsers`: A special identifier that represents anyone who is authenticated with a Google account or a service account. Does not include identities that come from external identity providers (IdPs) through identity federation. * `user:{emailid}`: An email address that represents a specific Google account. For example, `alice@example.com` . * `serviceAccount:{emailid}`: An email address that represents a Google service account. For example, `my-other-app@appspot.gserviceaccount.com`. * `serviceAccount:{projectid}.svc.id.goog[{namespace}/{kubernetes-sa}]`: An identifier for a [Kubernetes service account](https://cloud.google.com/kubernetes-engine/docs/how-to/kubernetes-service-accounts). For example, `my-project.svc.id.goog[my-namespace/my-kubernetes-sa]`. * `group:{emailid}`: An email address that represents a Google group. For example, `admins@example.com`. * `domain:{domain}`: The G Suite domain (primary) that represents all the users of that domain. For example, `google.com` or `example.com`. * `principal://iam.googleapis.com/locations/global/workforcePools/{pool_id}/subject/{subject_attribute_value}`: A single identity in a workforce identity pool. * `principalSet://iam.googleapis.com/locations/global/workforcePools/{pool_id}/group/{group_id}`: All workforce identities in a group. * `principalSet://iam.googleapis.com/locations/global/workforcePools/{pool_id}/attribute.{attribute_name}/{attribute_value}`: All workforce identities with a specific attribute value. * `principalSet://iam.googleapis.com/locations/global/workforcePools/{pool_id}/*`: All identities in a workforce identity pool. * `principal://iam.googleapis.com/projects/{project_number}/locations/global/workloadIdentityPools/{pool_id}/subject/{subject_attribute_value}`: A single identity in a workload identity pool. * `principalSet://iam.googleapis.com/projects/{project_number}/locations/global/workloadIdentityPools/{pool_id}/group/{group_id}`: A workload identity pool group. * `principalSet://iam.googleapis.com/projects/{project_number}/locations/global/workloadIdentityPools/{pool_id}/attribute.{attribute_name}/{attribute_value}`: All identities in a workload identity pool with a certain attribute. * `principalSet://iam.googleapis.com/projects/{project_number}/locations/global/workloadIdentityPools/{pool_id}/*`: All identities in a workload identity pool. * `deleted:user:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a user that has been recently deleted. For example, `alice@example.com?uid=123456789012345678901`. If the user is recovered, this value reverts to `user:{emailid}` and the recovered user retains the role in the binding. * `deleted:serviceAccount:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a service account that has been recently deleted. For example, `my-other-app@appspot.gserviceaccount.com?uid=123456789012345678901`. If the service account is undeleted, this value reverts to `serviceAccount:{emailid}` and the undeleted service account retains the role in the binding. * `deleted:group:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a Google group that has been recently deleted. For example, `admins@example.com?uid=123456789012345678901`. If the group is recovered, this value reverts to `group:{emailid}` and the recovered group retains the role in the binding. * `deleted:principal://iam.googleapis.com/locations/global/workforcePools/{pool_id}/subject/{subject_attribute_value}`: Deleted single identity in a workforce identity pool. For example, `deleted:principal://iam.googleapis.com/locations/global/workforcePools/my-pool-id/subject/my-subject-attribute-value`.
"A String",
],
- "role": "A String", # Role that is assigned to the list of `members`, or principals. For example, `roles/viewer`, `roles/editor`, or `roles/owner`.
+ "role": "A String", # Role that is assigned to the list of `members`, or principals. For example, `roles/viewer`, `roles/editor`, or `roles/owner`. For an overview of the IAM roles and permissions, see the [IAM documentation](https://cloud.google.com/iam/docs/roles-overview). For a list of the available pre-defined roles, see [here](https://cloud.google.com/iam/docs/understanding-roles).
},
],
"etag": "A String", # `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform policy updates in order to avoid race conditions: An `etag` is returned in the response to `getIamPolicy`, and systems are expected to put that etag in the request to `setIamPolicy` to ensure that their change will be applied to the same version of the policy. **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost.
@@ -1862,6 +2105,10 @@ Method Details
"updateMask": "A String", # OPTIONAL: A FieldMask specifying which fields of the policy to modify. Only the fields in the mask will be modified. If no mask is provided, the following default mask is used: `paths: "bindings, etag"`
}
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
Returns:
An object of the form:
@@ -1891,7 +2138,7 @@ Method Details
"members": [ # Specifies the principals requesting access for a Google Cloud resource. `members` can have the following values: * `allUsers`: A special identifier that represents anyone who is on the internet; with or without a Google account. * `allAuthenticatedUsers`: A special identifier that represents anyone who is authenticated with a Google account or a service account. Does not include identities that come from external identity providers (IdPs) through identity federation. * `user:{emailid}`: An email address that represents a specific Google account. For example, `alice@example.com` . * `serviceAccount:{emailid}`: An email address that represents a Google service account. For example, `my-other-app@appspot.gserviceaccount.com`. * `serviceAccount:{projectid}.svc.id.goog[{namespace}/{kubernetes-sa}]`: An identifier for a [Kubernetes service account](https://cloud.google.com/kubernetes-engine/docs/how-to/kubernetes-service-accounts). For example, `my-project.svc.id.goog[my-namespace/my-kubernetes-sa]`. * `group:{emailid}`: An email address that represents a Google group. For example, `admins@example.com`. * `domain:{domain}`: The G Suite domain (primary) that represents all the users of that domain. For example, `google.com` or `example.com`. * `principal://iam.googleapis.com/locations/global/workforcePools/{pool_id}/subject/{subject_attribute_value}`: A single identity in a workforce identity pool. * `principalSet://iam.googleapis.com/locations/global/workforcePools/{pool_id}/group/{group_id}`: All workforce identities in a group. * `principalSet://iam.googleapis.com/locations/global/workforcePools/{pool_id}/attribute.{attribute_name}/{attribute_value}`: All workforce identities with a specific attribute value. * `principalSet://iam.googleapis.com/locations/global/workforcePools/{pool_id}/*`: All identities in a workforce identity pool. * `principal://iam.googleapis.com/projects/{project_number}/locations/global/workloadIdentityPools/{pool_id}/subject/{subject_attribute_value}`: A single identity in a workload identity pool. * `principalSet://iam.googleapis.com/projects/{project_number}/locations/global/workloadIdentityPools/{pool_id}/group/{group_id}`: A workload identity pool group. * `principalSet://iam.googleapis.com/projects/{project_number}/locations/global/workloadIdentityPools/{pool_id}/attribute.{attribute_name}/{attribute_value}`: All identities in a workload identity pool with a certain attribute. * `principalSet://iam.googleapis.com/projects/{project_number}/locations/global/workloadIdentityPools/{pool_id}/*`: All identities in a workload identity pool. * `deleted:user:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a user that has been recently deleted. For example, `alice@example.com?uid=123456789012345678901`. If the user is recovered, this value reverts to `user:{emailid}` and the recovered user retains the role in the binding. * `deleted:serviceAccount:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a service account that has been recently deleted. For example, `my-other-app@appspot.gserviceaccount.com?uid=123456789012345678901`. If the service account is undeleted, this value reverts to `serviceAccount:{emailid}` and the undeleted service account retains the role in the binding. * `deleted:group:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a Google group that has been recently deleted. For example, `admins@example.com?uid=123456789012345678901`. If the group is recovered, this value reverts to `group:{emailid}` and the recovered group retains the role in the binding. * `deleted:principal://iam.googleapis.com/locations/global/workforcePools/{pool_id}/subject/{subject_attribute_value}`: Deleted single identity in a workforce identity pool. For example, `deleted:principal://iam.googleapis.com/locations/global/workforcePools/my-pool-id/subject/my-subject-attribute-value`.
"A String",
],
- "role": "A String", # Role that is assigned to the list of `members`, or principals. For example, `roles/viewer`, `roles/editor`, or `roles/owner`.
+ "role": "A String", # Role that is assigned to the list of `members`, or principals. For example, `roles/viewer`, `roles/editor`, or `roles/owner`. For an overview of the IAM roles and permissions, see the [IAM documentation](https://cloud.google.com/iam/docs/roles-overview). For a list of the available pre-defined roles, see [here](https://cloud.google.com/iam/docs/understanding-roles).
},
],
"etag": "A String", # `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read-modify-write cycle to perform policy updates in order to avoid race conditions: An `etag` is returned in the response to `getIamPolicy`, and systems are expected to put that etag in the request to `setIamPolicy` to ensure that their change will be applied to the same version of the policy. **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost.
@@ -1900,7 +2147,7 @@ Method Details
- testIamPermissions(resource, body=None)
+ testIamPermissions(resource, body=None, x__xgafv=None)
Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a `NOT_FOUND` error. Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may "fail open" without warning.
Args:
@@ -1914,6 +2161,10 @@ Method Details
],
}
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
Returns:
An object of the form:
@@ -1926,188 +2177,199 @@ Method Details
- update(projectId, datasetId, tableId, autodetect_schema=None, body=None)
- Updates information in an existing table. The update method replaces the entire table resource, whereas the patch method only replaces fields that are provided in the submitted table resource.
+ update(projectId, datasetId, tableId, autodetect_schema=None, body=None, x__xgafv=None)
+ Updates information in an existing table. The update method replaces the entire Table resource, whereas the patch method only replaces fields that are provided in the submitted Table resource.
Args:
- projectId: string, Project ID of the table to update (required)
- datasetId: string, Dataset ID of the table to update (required)
- tableId: string, Table ID of the table to update (required)
+ projectId: string, Required. Project ID of the table to update (required)
+ datasetId: string, Required. Dataset ID of the table to update (required)
+ tableId: string, Required. Table ID of the table to update (required)
body: object, The request body.
The object takes the form of:
{
- "biglakeConfiguration": { # [Optional] Specifies the configuration of a BigLake managed table.
- "connectionId": "A String", # [Required] Required and immutable. Credential reference for accessing external storage system. Normalized as project_id.location_id.connection_id.
- "fileFormat": "A String", # [Required] Required and immutable. Open source file format that the table data is stored in. Currently only PARQUET is supported.
- "storageUri": "A String", # [Required] Required and immutable. Fully qualified location prefix of the external folder where data is stored. Normalized to standard format: "gs:////". Starts with "gs://" rather than "/bigstore/". Ends with "/". Does not contain "*". See also BigLakeStorageMetadata on how it is used.
- "tableFormat": "A String", # [Required] Required and immutable. Open source file format that the table data is stored in. Currently only PARQUET is supported.
- },
- "cloneDefinition": { # [Output-only] Clone definition.
- "baseTableReference": { # [Required] Reference describing the ID of the table that was cloned.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- },
- "cloneTime": "A String", # [Required] The time at which the base table was cloned. This value is reported in the JSON response using RFC3339 format.
- },
- "clustering": { # [Beta] Clustering specification for the table. Must be specified with partitioning, data in the table will be first partitioned and subsequently clustered.
- "fields": [ # [Repeated] One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. When you cluster a table using multiple columns, the order of columns you specify is important. The order of the specified columns determines the sort order of the data.
+ "biglakeConfiguration": { # Configuration for BigLake managed tables. # Optional. Specifies the configuration of a BigLake managed table.
+ "connectionId": "A String", # Required. The connection specifying the credentials to be used to read and write to external storage, such as Cloud Storage. The connection_id can have the form "<project\_id>.<location\_id>.<connection\_id>" or "projects/<project\_id>/locations/<location\_id>/connections/<connection\_id>".
+ "fileFormat": "A String", # Required. The file format the table data is stored in.
+ "storageUri": "A String", # Required. The fully qualified location prefix of the external folder where table data is stored. The '*' wildcard character is not allowed. The URI should be in the format "gs://bucket/path_to_table/"
+ "tableFormat": "A String", # Required. The table format the metadata only snapshots are stored in.
+ },
+ "cloneDefinition": { # Information about base table and clone time of a table clone. # Output only. Contains information about the clone. This value is set via the clone operation.
+ "baseTableReference": { # Required. Reference describing the ID of the table that was cloned.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ "cloneTime": "A String", # Required. The time at which the base table was cloned. This value is reported in the JSON response using RFC3339 format.
+ },
+ "clustering": { # Configures table clustering. # Clustering specification for the table. Must be specified with time-based partitioning, data in the table will be first partitioned and subsequently clustered.
+ "fields": [ # One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. The ordering of the clustering fields should be prioritized from most to least important for filtering purposes. Additional information on limitations can be found here: https://cloud.google.com/bigquery/docs/creating-clustered-tables#limitations
"A String",
],
},
- "creationTime": "A String", # [Output-only] The time when this table was created, in milliseconds since the epoch.
- "defaultCollation": "A String", # [Output-only] The default collation of the table.
- "defaultRoundingMode": "A String", # [Output-only] The default rounding mode of the table.
- "description": "A String", # [Optional] A user-friendly description of this table.
+ "creationTime": "A String", # Output only. The time when this table was created, in milliseconds since the epoch.
+ "defaultCollation": "A String", # Optional. Defines the default collation specification of new STRING fields in the table. During table creation or update, if a STRING field is added to this table without explicit collation specified, then the table inherits the table default collation. A change to this field affects only fields added afterwards, and does not alter the existing fields. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.
+ "defaultRoundingMode": "A String", # Optional. Defines the default rounding mode specification of new decimal fields (NUMERIC OR BIGNUMERIC) in the table. During table creation or update, if a decimal field is added to this table without an explicit rounding mode specified, then the field inherits the table default rounding mode. Changing this field doesn't affect existing fields.
+ "description": "A String", # Optional. A user-friendly description of this table.
"encryptionConfiguration": { # Custom encryption configuration (e.g., Cloud KMS keys).
"kmsKeyName": "A String", # Optional. Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key.
},
- "etag": "A String", # [Output-only] A hash of the table metadata. Used to ensure there were no concurrent modifications to the resource when attempting an update. Not guaranteed to change when the table contents or the fields numRows, numBytes, numLongTermBytes or lastModifiedTime change.
- "expirationTime": "A String", # [Optional] The time when this table expires, in milliseconds since the epoch. If not present, the table will persist indefinitely. Expired tables will be deleted and their storage reclaimed. The defaultTableExpirationMs property of the encapsulating dataset can be used to set a default expirationTime on newly created tables.
- "externalDataConfiguration": { # [Optional] Describes the data format, location, and other properties of a table stored outside of BigQuery. By defining these properties, the data source can then be queried as if it were a standard BigQuery table.
+ "etag": "A String", # Output only. A hash of this resource.
+ "expirationTime": "A String", # Optional. The time when this table expires, in milliseconds since the epoch. If not present, the table will persist indefinitely. Expired tables will be deleted and their storage reclaimed. The defaultTableExpirationMs property of the encapsulating dataset can be used to set a default expirationTime on newly created tables.
+ "externalDataConfiguration": { # Optional. Describes the data format, location, and other properties of a table stored outside of BigQuery. By defining these properties, the data source can then be queried as if it were a standard BigQuery table.
"autodetect": True or False, # Try to detect schema and format options automatically. Any option specified explicitly will be honored.
- "avroOptions": { # Additional properties to set if sourceFormat is set to Avro.
- "useAvroLogicalTypes": True or False, # [Optional] If sourceFormat is set to "AVRO", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER).
- },
- "bigtableOptions": { # [Optional] Additional options if sourceFormat is set to BIGTABLE.
- "columnFamilies": [ # [Optional] List of column families to expose in the table schema along with their types. This list restricts the column families that can be referenced in queries and specifies their value types. You can use this list to do type conversions - see the 'type' field for more details. If you leave this list empty, all column families are present in the table schema and their values are read as BYTES. During a query only the column families referenced in that query are read from Bigtable.
- {
- "columns": [ # [Optional] Lists of columns that should be exposed as individual fields as opposed to a list of (column name, value) pairs. All columns whose qualifier matches a qualifier in this list can be accessed as .. Other columns can be accessed as a list through .Column field.
- {
- "encoding": "A String", # [Optional] The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. 'encoding' can also be set at the column family level. However, the setting at this level takes precedence if 'encoding' is set at both levels.
- "fieldName": "A String", # [Optional] If the qualifier is not a valid BigQuery field identifier i.e. does not match [a-zA-Z][a-zA-Z0-9_]*, a valid identifier must be provided as the column field name and is used as field name in queries.
- "onlyReadLatest": True or False, # [Optional] If this is set, only the latest version of value in this column are exposed. 'onlyReadLatest' can also be set at the column family level. However, the setting at this level takes precedence if 'onlyReadLatest' is set at both levels.
- "qualifierEncoded": "A String", # [Required] Qualifier of the column. Columns in the parent column family that has this exact qualifier are exposed as . field. If the qualifier is valid UTF-8 string, it can be specified in the qualifier_string field. Otherwise, a base-64 encoded value must be set to qualifier_encoded. The column field name is the same as the column qualifier. However, if the qualifier is not a valid BigQuery field identifier i.e. does not match [a-zA-Z][a-zA-Z0-9_]*, a valid identifier must be provided as field_name.
- "qualifierString": "A String",
- "type": "A String", # [Optional] The type to convert the value in cells of this column. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive) - BYTES STRING INTEGER FLOAT BOOLEAN Default type is BYTES. 'type' can also be set at the column family level. However, the setting at this level takes precedence if 'type' is set at both levels.
+ "avroOptions": { # Options for external data sources. # Optional. Additional properties to set if sourceFormat is set to AVRO.
+ "useAvroLogicalTypes": True or False, # Optional. If sourceFormat is set to "AVRO", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER).
+ },
+ "bigtableOptions": { # Options specific to Google Cloud Bigtable data sources. # Optional. Additional options if sourceFormat is set to BIGTABLE.
+ "columnFamilies": [ # Optional. List of column families to expose in the table schema along with their types. This list restricts the column families that can be referenced in queries and specifies their value types. You can use this list to do type conversions - see the 'type' field for more details. If you leave this list empty, all column families are present in the table schema and their values are read as BYTES. During a query only the column families referenced in that query are read from Bigtable.
+ { # Information related to a Bigtable column family.
+ "columns": [ # Optional. Lists of columns that should be exposed as individual fields as opposed to a list of (column name, value) pairs. All columns whose qualifier matches a qualifier in this list can be accessed as .. Other columns can be accessed as a list through .Column field.
+ { # Information related to a Bigtable column.
+ "encoding": "A String", # Optional. The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. 'encoding' can also be set at the column family level. However, the setting at this level takes precedence if 'encoding' is set at both levels.
+ "fieldName": "A String", # Optional. If the qualifier is not a valid BigQuery field identifier i.e. does not match a-zA-Z*, a valid identifier must be provided as the column field name and is used as field name in queries.
+ "onlyReadLatest": True or False, # Optional. If this is set, only the latest version of value in this column are exposed. 'onlyReadLatest' can also be set at the column family level. However, the setting at this level takes precedence if 'onlyReadLatest' is set at both levels.
+ "qualifierEncoded": "A String", # [Required] Qualifier of the column. Columns in the parent column family that has this exact qualifier are exposed as . field. If the qualifier is valid UTF-8 string, it can be specified in the qualifier_string field. Otherwise, a base-64 encoded value must be set to qualifier_encoded. The column field name is the same as the column qualifier. However, if the qualifier is not a valid BigQuery field identifier i.e. does not match a-zA-Z*, a valid identifier must be provided as field_name.
+ "qualifierString": "A String", # Qualifier string.
+ "type": "A String", # Optional. The type to convert the value in cells of this column. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive): * BYTES * STRING * INTEGER * FLOAT * BOOLEAN * JSON Default type is BYTES. 'type' can also be set at the column family level. However, the setting at this level takes precedence if 'type' is set at both levels.
},
],
- "encoding": "A String", # [Optional] The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. This can be overridden for a specific column by listing that column in 'columns' and specifying an encoding for it.
+ "encoding": "A String", # Optional. The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. This can be overridden for a specific column by listing that column in 'columns' and specifying an encoding for it.
"familyId": "A String", # Identifier of the column family.
- "onlyReadLatest": True or False, # [Optional] If this is set only the latest version of value are exposed for all columns in this column family. This can be overridden for a specific column by listing that column in 'columns' and specifying a different setting for that column.
- "type": "A String", # [Optional] The type to convert the value in cells of this column family. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive) - BYTES STRING INTEGER FLOAT BOOLEAN Default type is BYTES. This can be overridden for a specific column by listing that column in 'columns' and specifying a type for it.
+ "onlyReadLatest": True or False, # Optional. If this is set only the latest version of value are exposed for all columns in this column family. This can be overridden for a specific column by listing that column in 'columns' and specifying a different setting for that column.
+ "type": "A String", # Optional. The type to convert the value in cells of this column family. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive): * BYTES * STRING * INTEGER * FLOAT * BOOLEAN * JSON Default type is BYTES. This can be overridden for a specific column by listing that column in 'columns' and specifying a type for it.
},
],
- "ignoreUnspecifiedColumnFamilies": True or False, # [Optional] If field is true, then the column families that are not specified in columnFamilies list are not exposed in the table schema. Otherwise, they are read with BYTES type values. The default value is false.
- "readRowkeyAsString": True or False, # [Optional] If field is true, then the rowkey column families will be read and converted to string. Otherwise they are read with BYTES type values and users need to manually cast them with CAST if necessary. The default value is false.
- },
- "compression": "A String", # [Optional] The compression type of the data source. Possible values include GZIP and NONE. The default value is NONE. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups and Avro formats.
- "connectionId": "A String", # [Optional, Trusted Tester] Connection for external data source.
- "csvOptions": { # Additional properties to set if sourceFormat is set to CSV.
- "allowJaggedRows": True or False, # [Optional] Indicates if BigQuery should accept rows that are missing trailing optional columns. If true, BigQuery treats missing trailing columns as null values. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false.
- "allowQuotedNewlines": True or False, # [Optional] Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false.
- "encoding": "A String", # [Optional] The character encoding of the data. The supported values are UTF-8 or ISO-8859-1. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the quote and fieldDelimiter properties.
- "fieldDelimiter": "A String", # [Optional] The separator for fields in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. BigQuery also supports the escape sequence "\t" to specify a tab separator. The default value is a comma (',').
- "nullMarker": "A String", # [Optional] An custom string that will represent a NULL value in CSV import data.
- "preserveAsciiControlCharacters": True or False, # [Optional] Preserves the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\x00' to '\x1F') when loading from CSV. Only applicable to CSV, ignored for other formats.
- "quote": """, # [Optional] The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ('"'). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true.
- "skipLeadingRows": "A String", # [Optional] The number of rows at the top of a CSV file that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
- },
- "decimalTargetTypes": [ # [Optional] Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown. Example: Suppose the value of this field is ["NUMERIC", "BIGNUMERIC"]. If (precision,scale) is: (38,9) -> NUMERIC; (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits); (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits); (76,38) -> BIGNUMERIC; (77,38) -> BIGNUMERIC (error if value exeeds supported range). This field cannot contain duplicate types. The order of the types in this field is ignored. For example, ["BIGNUMERIC", "NUMERIC"] is the same as ["NUMERIC", "BIGNUMERIC"] and NUMERIC always takes precedence over BIGNUMERIC. Defaults to ["NUMERIC", "STRING"] for ORC and ["NUMERIC"] for the other file formats.
+ "ignoreUnspecifiedColumnFamilies": True or False, # Optional. If field is true, then the column families that are not specified in columnFamilies list are not exposed in the table schema. Otherwise, they are read with BYTES type values. The default value is false.
+ "outputColumnFamiliesAsJson": True or False, # Optional. If field is true, then each column family will be read as a single JSON column. Otherwise they are read as a repeated cell structure containing timestamp/value tuples. The default value is false.
+ "readRowkeyAsString": True or False, # Optional. If field is true, then the rowkey column families will be read and converted to string. Otherwise they are read with BYTES type values and users need to manually cast them with CAST if necessary. The default value is false.
+ },
+ "compression": "A String", # Optional. The compression type of the data source. Possible values include GZIP and NONE. The default value is NONE. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups, Avro, ORC and Parquet formats. An empty string is an invalid value.
+ "connectionId": "A String", # Optional. The connection specifying the credentials to be used to read external storage, such as Azure Blob, Cloud Storage, or S3. The connection_id can have the form "<project\_id>.<location\_id>.<connection\_id>" or "projects/<project\_id>/locations/<location\_id>/connections/<connection\_id>".
+ "csvOptions": { # Information related to a CSV data source. # Optional. Additional properties to set if sourceFormat is set to CSV.
+ "allowJaggedRows": True or False, # Optional. Indicates if BigQuery should accept rows that are missing trailing optional columns. If true, BigQuery treats missing trailing columns as null values. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false.
+ "allowQuotedNewlines": True or False, # Optional. Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false.
+ "encoding": "A String", # Optional. The character encoding of the data. The supported values are UTF-8, ISO-8859-1, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the quote and fieldDelimiter properties.
+ "fieldDelimiter": "A String", # Optional. The separator character for fields in a CSV file. The separator is interpreted as a single byte. For files encoded in ISO-8859-1, any single character can be used as a separator. For files encoded in UTF-8, characters represented in decimal range 1-127 (U+0001-U+007F) can be used without any modification. UTF-8 characters encoded with multiple bytes (i.e. U+0080 and above) will have only the first byte used for separating fields. The remaining bytes will be treated as a part of the field. BigQuery also supports the escape sequence "\t" (U+0009) to specify a tab separator. The default value is comma (",", U+002C).
+ "nullMarker": "A String", # [Optional] A custom string that will represent a NULL value in CSV import data.
+ "preserveAsciiControlCharacters": True or False, # Optional. Indicates if the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\x00' to '\x1F') are preserved.
+ "quote": """, # Optional. The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ("). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true. To include the specific quote character within a quoted value, precede it with an additional matching quote character. For example, if you want to escape the default character ' " ', use ' "" '.
+ "skipLeadingRows": "A String", # Optional. The number of rows at the top of a CSV file that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
+ },
+ "decimalTargetTypes": [ # Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown. Example: Suppose the value of this field is ["NUMERIC", "BIGNUMERIC"]. If (precision,scale) is: * (38,9) -> NUMERIC; * (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits); * (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits); * (76,38) -> BIGNUMERIC; * (77,38) -> BIGNUMERIC (error if value exeeds supported range). This field cannot contain duplicate types. The order of the types in this field is ignored. For example, ["BIGNUMERIC", "NUMERIC"] is the same as ["NUMERIC", "BIGNUMERIC"] and NUMERIC always takes precedence over BIGNUMERIC. Defaults to ["NUMERIC", "STRING"] for ORC and ["NUMERIC"] for the other file formats.
"A String",
],
- "fileSetSpecType": "A String", # [Optional] Specifies how source URIs are interpreted for constructing the file set to load. By default source URIs are expanded against the underlying storage. Other options include specifying manifest files. Only applicable to object storage systems.
- "googleSheetsOptions": { # [Optional] Additional options if sourceFormat is set to GOOGLE_SHEETS.
- "range": "A String", # [Optional] Range of a sheet to query from. Only used when non-empty. Typical format: sheet_name!top_left_cell_id:bottom_right_cell_id For example: sheet1!A1:B20
- "skipLeadingRows": "A String", # [Optional] The number of rows at the top of a sheet that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows that should be skipped. When autodetect is on, behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
+ "fileSetSpecType": "A String", # Optional. Specifies how source URIs are interpreted for constructing the file set to load. By default source URIs are expanded against the underlying storage. Other options include specifying manifest files. Only applicable to object storage systems.
+ "googleSheetsOptions": { # Options specific to Google Sheets data sources. # Optional. Additional options if sourceFormat is set to GOOGLE_SHEETS.
+ "range": "A String", # Optional. Range of a sheet to query from. Only used when non-empty. Typical format: sheet_name!top_left_cell_id:bottom_right_cell_id For example: sheet1!A1:B20
+ "skipLeadingRows": "A String", # Optional. The number of rows at the top of a sheet that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
},
- "hivePartitioningOptions": { # [Optional] Options to configure hive partitioning support.
- "fields": [ # [Output-only] For permanent external tables, this field is populated with the hive partition keys in the order they were inferred. The types of the partition keys can be deduced by checking the table schema (which will include the partition keys). Not every API will populate this field in the output. For example, Tables.Get will populate it, but Tables.List will not contain this field.
+ "hivePartitioningOptions": { # Options for configuring hive partitioning detect. # Optional. When set, configures hive partitioning support. Not all storage formats support hive partitioning -- requesting hive partitioning on an unsupported format will lead to an error, as will providing an invalid specification.
+ "fields": [ # Output only. For permanent external tables, this field is populated with the hive partition keys in the order they were inferred. The types of the partition keys can be deduced by checking the table schema (which will include the partition keys). Not every API will populate this field in the output. For example, Tables.Get will populate it, but Tables.List will not contain this field.
"A String",
],
- "mode": "A String", # [Optional] When set, what mode of hive partitioning to use when reading data. The following modes are supported. (1) AUTO: automatically infer partition key name(s) and type(s). (2) STRINGS: automatically infer partition key name(s). All types are interpreted as strings. (3) CUSTOM: partition key schema is encoded in the source URI prefix. Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported types include: AVRO, CSV, JSON, ORC and Parquet.
- "requirePartitionFilter": True or False, # [Optional] If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. Note that this field should only be true when creating a permanent external table or querying a temporary external table. Hive-partitioned loads with requirePartitionFilter explicitly set to true will fail.
- "sourceUriPrefix": "A String", # [Optional] When hive partition detection is requested, a common prefix for all source uris should be supplied. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout. gs://bucket/path_to_table/dt=2019-01-01/country=BR/id=7/file.avro gs://bucket/path_to_table/dt=2018-12-31/country=CA/id=3/file.avro When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/ (trailing slash does not matter).
- },
- "ignoreUnknownValues": True or False, # [Optional] Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names Google Cloud Bigtable: This setting is ignored. Google Cloud Datastore backups: This setting is ignored. Avro: This setting is ignored.
- "jsonOptions": { # Additional properties to set if `sourceFormat` is set to `NEWLINE_DELIMITED_JSON`.
- "encoding": "A String", # [Optional] The character encoding of the data. The supported values are UTF-8, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8.
- },
- "maxBadRecords": 42, # [Optional] The maximum number of bad records that BigQuery can ignore when reading data. If the number of bad records exceeds this value, an invalid error is returned in the job result. This is only valid for CSV, JSON, and Google Sheets. The default value is 0, which requires that all records are valid. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups and Avro formats.
- "metadataCacheMode": "A String", # [Optional] Metadata Cache Mode for the table. Set this to enable caching of metadata from external data source.
- "objectMetadata": "A String", # ObjectMetadata is used to create Object Tables. Object Tables contain a listing of objects (with their metadata) found at the source_uris. If ObjectMetadata is set, source_format should be omitted. Currently SIMPLE is the only supported Object Metadata type.
- "parquetOptions": { # Additional properties to set if sourceFormat is set to Parquet.
- "enableListInference": True or False, # [Optional] Indicates whether to use schema inference specifically for Parquet LIST logical type.
- "enumAsString": True or False, # [Optional] Indicates whether to infer Parquet ENUM logical type as STRING instead of BYTES by default.
- },
- "referenceFileSchemaUri": "A String", # [Optional] Provide a referencing file with the expected table schema. Enabled for the format: AVRO, PARQUET, ORC.
- "schema": { # [Optional] The schema for the data. Schema is required for CSV and JSON formats. Schema is disallowed for Google Cloud Bigtable, Cloud Datastore backups, and Avro formats.
+ "mode": "A String", # Optional. When set, what mode of hive partitioning to use when reading data. The following modes are supported: * AUTO: automatically infer partition key name(s) and type(s). * STRINGS: automatically infer partition key name(s). All types are strings. * CUSTOM: partition key schema is encoded in the source URI prefix. Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported formats are: JSON, CSV, ORC, Avro and Parquet.
+ "requirePartitionFilter": false, # Optional. If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. Note that this field should only be true when creating a permanent external table or querying a temporary external table. Hive-partitioned loads with require_partition_filter explicitly set to true will fail.
+ "sourceUriPrefix": "A String", # Optional. When hive partition detection is requested, a common prefix for all source uris must be required. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout: gs://bucket/path_to_table/dt=2019-06-01/country=USA/id=7/file.avro gs://bucket/path_to_table/dt=2019-05-31/country=CA/id=3/file.avro When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/. CUSTOM detection requires encoding the partitioning schema immediately after the common prefix. For CUSTOM, any of * gs://bucket/path_to_table/{dt:DATE}/{country:STRING}/{id:INTEGER} * gs://bucket/path_to_table/{dt:STRING}/{country:STRING}/{id:INTEGER} * gs://bucket/path_to_table/{dt:DATE}/{country:STRING}/{id:STRING} would all be valid source URI prefixes.
+ },
+ "ignoreUnknownValues": True or False, # Optional. Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names Google Cloud Bigtable: This setting is ignored. Google Cloud Datastore backups: This setting is ignored. Avro: This setting is ignored. ORC: This setting is ignored. Parquet: This setting is ignored.
+ "jsonExtension": "A String", # Optional. Load option to be used together with source_format newline-delimited JSON to indicate that a variant of JSON is being loaded. To load newline-delimited GeoJSON, specify GEOJSON (and source_format must be set to NEWLINE_DELIMITED_JSON).
+ "jsonOptions": { # Json Options for load and make external tables. # Optional. Additional properties to set if sourceFormat is set to JSON.
+ "encoding": "A String", # Optional. The character encoding of the data. The supported values are UTF-8, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8.
+ },
+ "maxBadRecords": 42, # Optional. The maximum number of bad records that BigQuery can ignore when reading data. If the number of bad records exceeds this value, an invalid error is returned in the job result. The default value is 0, which requires that all records are valid. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups, Avro, ORC and Parquet formats.
+ "metadataCacheMode": "A String", # Optional. Metadata Cache Mode for the table. Set this to enable caching of metadata from external data source.
+ "objectMetadata": "A String", # Optional. ObjectMetadata is used to create Object Tables. Object Tables contain a listing of objects (with their metadata) found at the source_uris. If ObjectMetadata is set, source_format should be omitted. Currently SIMPLE is the only supported Object Metadata type.
+ "parquetOptions": { # Parquet Options for load and make external tables. # Optional. Additional properties to set if sourceFormat is set to PARQUET.
+ "enableListInference": True or False, # Optional. Indicates whether to use schema inference specifically for Parquet LIST logical type.
+ "enumAsString": True or False, # Optional. Indicates whether to infer Parquet ENUM logical type as STRING instead of BYTES by default.
+ },
+ "referenceFileSchemaUri": "A String", # Optional. When creating an external table, the user can provide a reference file with the table schema. This is enabled for the following formats: AVRO, PARQUET, ORC.
+ "schema": { # Schema of a table # Optional. The schema for the data. Schema is required for CSV and JSON formats if autodetect is not on. Schema is disallowed for Google Cloud Bigtable, Cloud Datastore backups, Avro, ORC and Parquet formats.
"fields": [ # Describes the fields in a table.
- {
- "categories": { # [Optional] The categories attached to this field, used for field-level access control.
- "names": [ # A list of category resource names. For example, "projects/1/taxonomies/2/categories/3". At most 5 categories are allowed.
+ { # A field in TableSchema
+ "categories": { # Deprecated.
+ "names": [ # Deprecated.
"A String",
],
},
- "collation": "A String", # Optional. Collation specification of the field. It only can be set on string type field.
- "defaultValueExpression": "A String", # Optional. A SQL expression to specify the default value for this field. It can only be set for top level fields (columns). You can use struct or array expression to specify default value for the entire struct or array. The valid SQL expressions are: - Literals for all data types, including STRUCT and ARRAY. - Following functions: - CURRENT_TIMESTAMP - CURRENT_TIME - CURRENT_DATE - CURRENT_DATETIME - GENERATE_UUID - RAND - SESSION_USER - ST_GEOGPOINT - Struct or array composed with the above allowed functions, for example, [CURRENT_DATE(), DATE '2020-01-01']
- "description": "A String", # [Optional] The field description. The maximum length is 1,024 characters.
- "fields": [ # [Optional] Describes the nested schema fields if the type property is set to RECORD.
+ "collation": "A String", # Optional. Field collation can be set only when the type of field is STRING. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.
+ "defaultValueExpression": "A String", # Optional. A SQL expression to specify the [default value] (https://cloud.google.com/bigquery/docs/default-values) for this field.
+ "description": "A String", # Optional. The field description. The maximum length is 1,024 characters.
+ "fields": [ # Optional. Describes the nested schema fields if the type property is set to RECORD.
# Object with schema name: TableFieldSchema
],
- "maxLength": "A String", # [Optional] Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
- "mode": "A String", # [Optional] The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
- "name": "A String", # [Required] The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
- "policyTags": {
- "names": [ # A list of category resource names. For example, "projects/1/location/eu/taxonomies/2/policyTags/3". At most 1 policy tag is allowed.
+ "maxLength": "A String", # Optional. Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
+ "mode": "A String", # Optional. The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
+ "name": "A String", # Required. The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
+ "policyTags": { # Optional. The policy tags attached to this field, used for field-level access control. If not set, defaults to empty policy_tags.
+ "names": [ # A list of policy tag resource names. For example, "projects/1/locations/eu/taxonomies/2/policyTags/3". At most 1 policy tag is currently allowed.
"A String",
],
},
- "precision": "A String", # [Optional] Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: - Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] - Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: - If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. - If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): - If type = "NUMERIC": 1 ≤ precision ≤ 29. - If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
- "rangeElementType": { # Optional. The subtype of the RANGE, if the type of this field is RANGE. If the type is RANGE, this field is required. Possible values for the field element type of a RANGE include: - DATE - DATETIME - TIMESTAMP
- "type": "A String", # The field element type of a RANGE
+ "precision": "A String", # Optional. Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: * Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] * Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: * If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. * If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): * If type = "NUMERIC": 1 ≤ precision ≤ 29. * If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
+ "rangeElementType": { # Represents the type of a field element.
+ "type": "A String", # Required. The type of a field element. See TableFieldSchema.type.
},
- "roundingMode": "A String", # Optional. Rounding Mode specification of the field. It only can be set on NUMERIC or BIGNUMERIC type fields.
- "scale": "A String", # [Optional] See documentation for precision.
- "type": "A String", # [Required] The field data type. Possible values include STRING, BYTES, INTEGER, INT64 (same as INTEGER), FLOAT, FLOAT64 (same as FLOAT), NUMERIC, BIGNUMERIC, BOOLEAN, BOOL (same as BOOLEAN), TIMESTAMP, DATE, TIME, DATETIME, INTERVAL, RECORD (where RECORD indicates that the field contains a nested schema) or STRUCT (same as RECORD).
+ "roundingMode": "A String", # Optional. Specifies the rounding mode to be used when storing values of NUMERIC and BIGNUMERIC type.
+ "scale": "A String", # Optional. See documentation for precision.
+ "type": "A String", # Required. The field data type. Possible values include: * STRING * BYTES * INTEGER (or INT64) * FLOAT (or FLOAT64) * BOOLEAN (or BOOL) * TIMESTAMP * DATE * TIME * DATETIME * GEOGRAPHY * NUMERIC * BIGNUMERIC * JSON * RECORD (or STRUCT) Use of RECORD/STRUCT indicates that the field contains a nested schema.
},
],
},
- "sourceFormat": "A String", # [Required] The data format. For CSV files, specify "CSV". For Google sheets, specify "GOOGLE_SHEETS". For newline-delimited JSON, specify "NEWLINE_DELIMITED_JSON". For Avro files, specify "AVRO". For Google Cloud Datastore backups, specify "DATASTORE_BACKUP". [Beta] For Google Cloud Bigtable, specify "BIGTABLE".
+ "sourceFormat": "A String", # [Required] The data format. For CSV files, specify "CSV". For Google sheets, specify "GOOGLE_SHEETS". For newline-delimited JSON, specify "NEWLINE_DELIMITED_JSON". For Avro files, specify "AVRO". For Google Cloud Datastore backups, specify "DATASTORE_BACKUP". For Apache Iceberg tables, specify "ICEBERG". For ORC files, specify "ORC". For Parquet files, specify "PARQUET". [Beta] For Google Cloud Bigtable, specify "BIGTABLE".
"sourceUris": [ # [Required] The fully-qualified URIs that point to your data in Google Cloud. For Google Cloud Storage URIs: Each URI can contain one '*' wildcard character and it must come after the 'bucket' name. Size limits related to load jobs apply to external data sources. For Google Cloud Bigtable URIs: Exactly one URI can be specified and it has be a fully specified and valid HTTPS URL for a Google Cloud Bigtable table. For Google Cloud Datastore backups, exactly one URI can be specified. Also, the '*' wildcard character is not allowed.
"A String",
],
},
- "friendlyName": "A String", # [Optional] A descriptive name for this table.
- "id": "A String", # [Output-only] An opaque ID uniquely identifying the table.
- "kind": "bigquery#table", # [Output-only] The type of the resource.
+ "friendlyName": "A String", # Optional. A descriptive name for this table.
+ "id": "A String", # Output only. An opaque ID uniquely identifying the table.
+ "kind": "bigquery#table", # The type of resource ID.
"labels": { # The labels associated with this table. You can use these to organize and group your tables. Label keys and values can be no longer than 63 characters, can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. Label values are optional. Label keys must start with a letter and each label in the list must have a different key.
"a_key": "A String",
},
- "lastModifiedTime": "A String", # [Output-only] The time when this table was last modified, in milliseconds since the epoch.
- "location": "A String", # [Output-only] The geographic location where the table resides. This value is inherited from the dataset.
- "materializedView": { # [Optional] Materialized view definition.
- "allowNonIncrementalDefinition": True or False, # [Optional] Allow non incremental materialized view definition. The default value is "false".
- "enableRefresh": True or False, # [Optional] [TrustedTester] Enable automatic refresh of the materialized view when the base table is updated. The default value is "true".
- "lastRefreshTime": "A String", # [Output-only] [TrustedTester] The time when this materialized view was last modified, in milliseconds since the epoch.
+ "lastModifiedTime": "A String", # Output only. The time when this table was last modified, in milliseconds since the epoch.
+ "location": "A String", # Output only. The geographic location where the table resides. This value is inherited from the dataset.
+ "materializedView": { # Definition and configuration of a materialized view. # Optional. The materialized view definition.
+ "allowNonIncrementalDefinition": True or False, # Optional. This option declares authors intention to construct a materialized view that will not be refreshed incrementally.
+ "enableRefresh": True or False, # Optional. Enable automatic refresh of the materialized view when the base table is updated. The default value is "true".
+ "lastRefreshTime": "A String", # Output only. The time when this materialized view was last refreshed, in milliseconds since the epoch.
"maxStaleness": "A String", # [Optional] Max staleness of data that could be returned when materizlized view is queried (formatted as Google SQL Interval type).
- "query": "A String", # [Required] A query whose result is persisted.
- "refreshIntervalMs": "A String", # [Optional] [TrustedTester] The maximum frequency at which this materialized view will be refreshed. The default value is "1800000" (30 minutes).
+ "query": "A String", # Required. A query whose results are persisted.
+ "refreshIntervalMs": "A String", # Optional. The maximum frequency at which this materialized view will be refreshed. The default value is "1800000" (30 minutes).
+ },
+ "materializedViewStatus": { # Status of a materialized view. The last refresh timestamp status is omitted here, but is present in the MaterializedViewDefinition message. # Output only. The materialized view status.
+ "lastRefreshStatus": { # Error details. # Output only. Error result of the last automatic refresh. If present, indicates that the last automatic refresh was unsuccessful.
+ "debugInfo": "A String", # Debugging information. This property is internal to Google and should not be used.
+ "location": "A String", # Specifies where the error occurred, if present.
+ "message": "A String", # A human-readable description of the error.
+ "reason": "A String", # A short error code that summarizes the error.
+ },
+ "refreshWatermark": "A String", # Output only. Refresh watermark of materialized view. The base tables' data were collected into the materialized view cache until this time.
},
- "maxStaleness": "A String", # [Optional] Max staleness of data that could be returned when table or materialized view is queried (formatted as Google SQL Interval type).
- "model": { # [Output-only, Beta] Present iff this table represents a ML model. Describes the training information for the model, and it is required to run 'PREDICT' queries.
- "modelOptions": { # [Output-only, Beta] Model options used for the first training run. These options are immutable for subsequent training runs. Default values are used for any options not specified in the input query.
+ "maxStaleness": "A String", # Optional. The maximum staleness of data that could be returned when the table (or stale MV) is queried. Staleness encoded as a string encoding of sql IntervalValue type.
+ "model": { # Deprecated.
+ "modelOptions": { # Deprecated.
"labels": [
"A String",
],
"lossType": "A String",
"modelType": "A String",
},
- "trainingRuns": [ # [Output-only, Beta] Information about ml training runs, each training run comprises of multiple iterations and there may be multiple training runs for the model if warm start is used or if a user decides to continue a previously cancelled query.
+ "trainingRuns": [ # Deprecated.
{
- "iterationResults": [ # [Output-only, Beta] List of each iteration results.
+ "iterationResults": [ # Deprecated.
{
- "durationMs": "A String", # [Output-only, Beta] Time taken to run the training iteration in milliseconds.
- "evalLoss": 3.14, # [Output-only, Beta] Eval loss computed on the eval data at the end of the iteration. The eval loss is used for early stopping to avoid overfitting. No eval loss if eval_split_method option is specified as no_split or auto_split with input data size less than 500 rows.
- "index": 42, # [Output-only, Beta] Index of the ML training iteration, starting from zero for each training run.
- "learnRate": 3.14, # [Output-only, Beta] Learning rate used for this iteration, it varies for different training iterations if learn_rate_strategy option is not constant.
- "trainingLoss": 3.14, # [Output-only, Beta] Training loss computed on the training data at the end of the iteration. The training loss function is defined by model type.
+ "durationMs": "A String", # Deprecated.
+ "evalLoss": 3.14, # Deprecated.
+ "index": 42, # Deprecated.
+ "learnRate": 3.14, # Deprecated.
+ "trainingLoss": 3.14, # Deprecated.
},
],
- "startTime": "A String", # [Output-only, Beta] Training run start time in milliseconds since the epoch.
- "state": "A String", # [Output-only, Beta] Different state applicable for a training run. IN PROGRESS: Training run is in progress. FAILED: Training run ended due to a non-retryable failure. SUCCEEDED: Training run successfully completed. CANCELLED: Training run cancelled by the user.
- "trainingOptions": { # [Output-only, Beta] Training options used by this training run. These options are mutable for subsequent training runs. Default values are explicitly stored for options not specified in the input query of the first training run. For subsequent training runs, any option not explicitly specified in the input query will be copied from the previous training run.
+ "startTime": "A String", # Deprecated.
+ "state": "A String", # Deprecated.
+ "trainingOptions": { # Deprecated.
"earlyStop": True or False,
"l1Reg": 3.14,
"l2Reg": 3.14,
@@ -2121,86 +2383,93 @@ Method Details
},
],
},
- "numActiveLogicalBytes": "A String", # [Output-only] Number of logical bytes that are less than 90 days old.
- "numActivePhysicalBytes": "A String", # [Output-only] Number of physical bytes less than 90 days old. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
- "numBytes": "A String", # [Output-only] The size of this table in bytes, excluding any data in the streaming buffer.
- "numLongTermBytes": "A String", # [Output-only] The number of bytes in the table that are considered "long-term storage".
- "numLongTermLogicalBytes": "A String", # [Output-only] Number of logical bytes that are more than 90 days old.
- "numLongTermPhysicalBytes": "A String", # [Output-only] Number of physical bytes more than 90 days old. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
- "numPartitions": "A String", # [Output-only] The number of partitions present in the table or materialized view. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
- "numPhysicalBytes": "A String", # [Output-only] [TrustedTester] The physical size of this table in bytes, excluding any data in the streaming buffer. This includes compression and storage used for time travel.
- "numRows": "A String", # [Output-only] The number of rows of data in this table, excluding any data in the streaming buffer.
- "numTimeTravelPhysicalBytes": "A String", # [Output-only] Number of physical bytes used by time travel storage (deleted or changed data). This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
- "numTotalLogicalBytes": "A String", # [Output-only] Total number of logical bytes in the table or materialized view.
- "numTotalPhysicalBytes": "A String", # [Output-only] The physical size of this table in bytes. This also includes storage used for time travel. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
- "rangePartitioning": { # [TrustedTester] Range partitioning specification for this table. Only one of timePartitioning and rangePartitioning should be specified.
- "field": "A String", # [TrustedTester] [Required] The table is partitioned by this field. The field must be a top-level NULLABLE/REQUIRED field. The only supported type is INTEGER/INT64.
- "range": { # [TrustedTester] [Required] Defines the ranges for range partitioning.
- "end": "A String", # [TrustedTester] [Required] The end of range partitioning, exclusive.
- "interval": "A String", # [TrustedTester] [Required] The width of each interval.
- "start": "A String", # [TrustedTester] [Required] The start of range partitioning, inclusive.
- },
- },
- "requirePartitionFilter": false, # [Optional] If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified.
+ "numActiveLogicalBytes": "A String", # Output only. Number of logical bytes that are less than 90 days old.
+ "numActivePhysicalBytes": "A String", # Output only. Number of physical bytes less than 90 days old. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
+ "numBytes": "A String", # Output only. The size of this table in logical bytes, excluding any data in the streaming buffer.
+ "numLongTermBytes": "A String", # Output only. The number of logical bytes in the table that are considered "long-term storage".
+ "numLongTermLogicalBytes": "A String", # Output only. Number of logical bytes that are more than 90 days old.
+ "numLongTermPhysicalBytes": "A String", # Output only. Number of physical bytes more than 90 days old. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
+ "numPartitions": "A String", # Output only. The number of partitions present in the table or materialized view. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
+ "numPhysicalBytes": "A String", # Output only. The physical size of this table in bytes. This includes storage used for time travel.
+ "numRows": "A String", # Output only. The number of rows of data in this table, excluding any data in the streaming buffer.
+ "numTimeTravelPhysicalBytes": "A String", # Output only. Number of physical bytes used by time travel storage (deleted or changed data). This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
+ "numTotalLogicalBytes": "A String", # Output only. Total number of logical bytes in the table or materialized view.
+ "numTotalPhysicalBytes": "A String", # Output only. The physical size of this table in bytes. This also includes storage used for time travel. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
+ "rangePartitioning": { # If specified, configures range partitioning for this table.
+ "field": "A String", # Required. [Experimental] The table is partitioned by this field. The field must be a top-level NULLABLE/REQUIRED field. The only supported type is INTEGER/INT64.
+ "range": { # [Experimental] Defines the ranges for range partitioning.
+ "end": "A String", # [Experimental] The end of range partitioning, exclusive.
+ "interval": "A String", # [Experimental] The width of each interval.
+ "start": "A String", # [Experimental] The start of range partitioning, inclusive.
+ },
+ },
+ "replicas": [ # Optional. Output only. Table references of all replicas currently active on the table.
+ {
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ ],
+ "requirePartitionFilter": false, # Optional. If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified.
"resourceTags": { # [Optional] The tags associated with this table. Tag keys are globally unique. See additional information on [tags](https://cloud.google.com/iam/docs/tags-access-control#definitions). An object containing a list of "key": value pairs. The key is the namespaced friendly name of the tag key, e.g. "12345/environment" where 12345 is parent id. The value is the friendly short name of the tag value, e.g. "production".
"a_key": "A String",
},
- "schema": { # [Optional] Describes the schema of this table.
+ "schema": { # Schema of a table # Optional. Describes the schema of this table.
"fields": [ # Describes the fields in a table.
- {
- "categories": { # [Optional] The categories attached to this field, used for field-level access control.
- "names": [ # A list of category resource names. For example, "projects/1/taxonomies/2/categories/3". At most 5 categories are allowed.
+ { # A field in TableSchema
+ "categories": { # Deprecated.
+ "names": [ # Deprecated.
"A String",
],
},
- "collation": "A String", # Optional. Collation specification of the field. It only can be set on string type field.
- "defaultValueExpression": "A String", # Optional. A SQL expression to specify the default value for this field. It can only be set for top level fields (columns). You can use struct or array expression to specify default value for the entire struct or array. The valid SQL expressions are: - Literals for all data types, including STRUCT and ARRAY. - Following functions: - CURRENT_TIMESTAMP - CURRENT_TIME - CURRENT_DATE - CURRENT_DATETIME - GENERATE_UUID - RAND - SESSION_USER - ST_GEOGPOINT - Struct or array composed with the above allowed functions, for example, [CURRENT_DATE(), DATE '2020-01-01']
- "description": "A String", # [Optional] The field description. The maximum length is 1,024 characters.
- "fields": [ # [Optional] Describes the nested schema fields if the type property is set to RECORD.
+ "collation": "A String", # Optional. Field collation can be set only when the type of field is STRING. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.
+ "defaultValueExpression": "A String", # Optional. A SQL expression to specify the [default value] (https://cloud.google.com/bigquery/docs/default-values) for this field.
+ "description": "A String", # Optional. The field description. The maximum length is 1,024 characters.
+ "fields": [ # Optional. Describes the nested schema fields if the type property is set to RECORD.
# Object with schema name: TableFieldSchema
],
- "maxLength": "A String", # [Optional] Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
- "mode": "A String", # [Optional] The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
- "name": "A String", # [Required] The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
- "policyTags": {
- "names": [ # A list of category resource names. For example, "projects/1/location/eu/taxonomies/2/policyTags/3". At most 1 policy tag is allowed.
+ "maxLength": "A String", # Optional. Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
+ "mode": "A String", # Optional. The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
+ "name": "A String", # Required. The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
+ "policyTags": { # Optional. The policy tags attached to this field, used for field-level access control. If not set, defaults to empty policy_tags.
+ "names": [ # A list of policy tag resource names. For example, "projects/1/locations/eu/taxonomies/2/policyTags/3". At most 1 policy tag is currently allowed.
"A String",
],
},
- "precision": "A String", # [Optional] Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: - Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] - Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: - If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. - If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): - If type = "NUMERIC": 1 ≤ precision ≤ 29. - If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
- "rangeElementType": { # Optional. The subtype of the RANGE, if the type of this field is RANGE. If the type is RANGE, this field is required. Possible values for the field element type of a RANGE include: - DATE - DATETIME - TIMESTAMP
- "type": "A String", # The field element type of a RANGE
+ "precision": "A String", # Optional. Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: * Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] * Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: * If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. * If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): * If type = "NUMERIC": 1 ≤ precision ≤ 29. * If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
+ "rangeElementType": { # Represents the type of a field element.
+ "type": "A String", # Required. The type of a field element. See TableFieldSchema.type.
},
- "roundingMode": "A String", # Optional. Rounding Mode specification of the field. It only can be set on NUMERIC or BIGNUMERIC type fields.
- "scale": "A String", # [Optional] See documentation for precision.
- "type": "A String", # [Required] The field data type. Possible values include STRING, BYTES, INTEGER, INT64 (same as INTEGER), FLOAT, FLOAT64 (same as FLOAT), NUMERIC, BIGNUMERIC, BOOLEAN, BOOL (same as BOOLEAN), TIMESTAMP, DATE, TIME, DATETIME, INTERVAL, RECORD (where RECORD indicates that the field contains a nested schema) or STRUCT (same as RECORD).
+ "roundingMode": "A String", # Optional. Specifies the rounding mode to be used when storing values of NUMERIC and BIGNUMERIC type.
+ "scale": "A String", # Optional. See documentation for precision.
+ "type": "A String", # Required. The field data type. Possible values include: * STRING * BYTES * INTEGER (or INT64) * FLOAT (or FLOAT64) * BOOLEAN (or BOOL) * TIMESTAMP * DATE * TIME * DATETIME * GEOGRAPHY * NUMERIC * BIGNUMERIC * JSON * RECORD (or STRUCT) Use of RECORD/STRUCT indicates that the field contains a nested schema.
},
],
},
- "selfLink": "A String", # [Output-only] A URL that can be used to access this resource again.
- "snapshotDefinition": { # [Output-only] Snapshot definition.
- "baseTableReference": { # [Required] Reference describing the ID of the table that was snapshot.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- },
- "snapshotTime": "A String", # [Required] The time at which the base table was snapshot. This value is reported in the JSON response using RFC3339 format.
- },
- "streamingBuffer": { # [Output-only] Contains information regarding this table's streaming buffer, if one is present. This field will be absent if the table is not being streamed to or if there is no data in the streaming buffer.
- "estimatedBytes": "A String", # [Output-only] A lower-bound estimate of the number of bytes currently in the streaming buffer.
- "estimatedRows": "A String", # [Output-only] A lower-bound estimate of the number of rows currently in the streaming buffer.
- "oldestEntryTime": "A String", # [Output-only] Contains the timestamp of the oldest entry in the streaming buffer, in milliseconds since the epoch, if the streaming buffer is available.
- },
- "tableConstraints": { # [Optional] The table constraints on the table.
- "foreignKeys": [ # [Optional] The foreign keys of the tables.
- {
- "columnReferences": [
- {
- "referencedColumn": "A String",
- "referencingColumn": "A String",
+ "selfLink": "A String", # Output only. A URL that can be used to access this resource again.
+ "snapshotDefinition": { # Information about base table and snapshot time of the snapshot. # Output only. Contains information about the snapshot. This value is set via snapshot creation.
+ "baseTableReference": { # Required. Reference describing the ID of the table that was snapshot.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ "snapshotTime": "A String", # Required. The time at which the base table was snapshot. This value is reported in the JSON response using RFC3339 format.
+ },
+ "streamingBuffer": { # Output only. Contains information regarding this table's streaming buffer, if one is present. This field will be absent if the table is not being streamed to or if there is no data in the streaming buffer.
+ "estimatedBytes": "A String", # Output only. A lower-bound estimate of the number of bytes currently in the streaming buffer.
+ "estimatedRows": "A String", # Output only. A lower-bound estimate of the number of rows currently in the streaming buffer.
+ "oldestEntryTime": "A String", # Output only. Contains the timestamp of the oldest entry in the streaming buffer, in milliseconds since the epoch, if the streaming buffer is available.
+ },
+ "tableConstraints": { # The TableConstraints defines the primary key and foreign key. # Optional. Tables Primary Key and Foreign Key information
+ "foreignKeys": [ # Optional. Present only if the table has a foreign key. The foreign key is not enforced.
+ { # Represents a foreign key constraint on a table's columns.
+ "columnReferences": [ # Required. The columns that compose the foreign key.
+ { # The pair of the foreign key column and primary key column.
+ "referencedColumn": "A String", # Required. The column in the primary key that are referenced by the referencing_column.
+ "referencingColumn": "A String", # Required. The column that composes the foreign key.
},
],
- "name": "A String",
+ "name": "A String", # Optional. Set only if the foreign key constraint is named.
"referencedTable": {
"datasetId": "A String",
"projectId": "A String",
@@ -2208,30 +2477,54 @@ Method Details
},
},
],
- "primaryKey": { # [Optional] The primary key of the table.
- "columns": [
+ "primaryKey": { # Represents the primary key constraint on a table's columns.
+ "columns": [ # Required. The columns that are composed of the primary key constraint.
"A String",
],
},
},
- "tableReference": { # [Required] Reference describing the ID of this table.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- },
- "timePartitioning": { # Time-based partitioning specification for this table. Only one of timePartitioning and rangePartitioning should be specified.
- "expirationMs": "A String", # [Optional] Number of milliseconds for which to keep the storage for partitions in the table. The storage in a partition will have an expiration time of its partition time plus this value.
- "field": "A String", # [Beta] [Optional] If not set, the table is partitioned by pseudo column, referenced via either '_PARTITIONTIME' as TIMESTAMP type, or '_PARTITIONDATE' as DATE type. If field is specified, the table is instead partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED.
- "requirePartitionFilter": True or False,
- "type": "A String", # [Required] The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively. When the type is not specified, the default behavior is DAY.
- },
- "type": "A String", # [Output-only] Describes the table type. The following values are supported: TABLE: A normal BigQuery table. VIEW: A virtual table defined by a SQL query. SNAPSHOT: An immutable, read-only table that is a copy of another table. [TrustedTester] MATERIALIZED_VIEW: SQL query whose result is persisted. EXTERNAL: A table that references data stored in an external storage system, such as Google Cloud Storage. The default value is TABLE.
- "view": { # [Optional] The view definition.
- "query": "A String", # [Required] A query that BigQuery executes when the view is referenced.
- "useExplicitColumnNames": True or False, # True if the column names are explicitly specified. For example by using the 'CREATE VIEW v(c1, c2) AS ...' syntax. Can only be set using BigQuery's standard SQL: https://cloud.google.com/bigquery/sql-reference/
- "useLegacySql": True or False, # Specifies whether to use BigQuery's legacy SQL for this view. The default value is true. If set to false, the view will use BigQuery's standard SQL: https://cloud.google.com/bigquery/sql-reference/ Queries and views that reference this view must use the same flag value.
+ "tableReference": { # Required. Reference describing the ID of this table.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ "tableReplicationInfo": { # Replication info of a table created using `AS REPLICA` DDL like: `CREATE MATERIALIZED VIEW mv1 AS REPLICA OF src_mv` # Optional. Table replication info for table created `AS REPLICA` DDL like: `CREATE MATERIALIZED VIEW mv1 AS REPLICA OF src_mv`
+ "replicatedSourceLastRefreshTime": "A String", # Optional. Output only. If source is a materialized view, this field signifies the last refresh time of the source.
+ "replicationError": { # Error details. # Optional. Output only. Replication error that will permanently stopped table replication.
+ "debugInfo": "A String", # Debugging information. This property is internal to Google and should not be used.
+ "location": "A String", # Specifies where the error occurred, if present.
+ "message": "A String", # A human-readable description of the error.
+ "reason": "A String", # A short error code that summarizes the error.
+ },
+ "replicationIntervalMs": "A String", # Required. Specifies the interval at which the source table is polled for updates.
+ "replicationStatus": "A String", # Optional. Output only. Replication status of configured replication.
+ "sourceTable": { # Required. Source table reference that is replicated.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ },
+ "timePartitioning": { # If specified, configures time-based partitioning for this table.
+ "expirationMs": "A String", # Optional. Number of milliseconds for which to keep the storage for a partition. A wrapper is used here because 0 is an invalid value.
+ "field": "A String", # Optional. If not set, the table is partitioned by pseudo column '_PARTITIONTIME'; if set, the table is partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED. A wrapper is used here because an empty string is an invalid value.
+ "requirePartitionFilter": false, # If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. This field is deprecated; please set the field with the same name on the table itself instead. This field needs a wrapper because we want to output the default value, false, if the user explicitly set it.
+ "type": "A String", # Required. The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively.
+ },
+ "type": "A String", # Output only. Describes the table type. The following values are supported: * `TABLE`: A normal BigQuery table. * `VIEW`: A virtual table defined by a SQL query. * `EXTERNAL`: A table that references data stored in an external storage system, such as Google Cloud Storage. * `MATERIALIZED_VIEW`: A precomputed view defined by a SQL query. * `SNAPSHOT`: An immutable BigQuery table that preserves the contents of a base table at a particular time. See additional information on [table snapshots](/bigquery/docs/table-snapshots-intro). The default value is `TABLE`.
+ "view": { # Describes the definition of a logical view. # Optional. The view definition.
+ "privacyPolicy": { # Represents privacy policy that contains the privacy requirements specified by the data owner. Currently, this is only supported on views. # Optional. Specifices the privacy policy for the view.
+ "aggregationThresholdPolicy": { # Represents privacy policy associated with "aggregation threshold" method. # Optional. Policy used for aggregation thresholds.
+ "privacyUnitColumns": [ # Optional. The privacy unit column(s) associated with this policy. For now, only one column per data source object (table, view) is allowed as a privacy unit column. Representing as a repeated field in metadata for extensibility to multiple columns in future. Duplicates and Repeated struct fields are not allowed. For nested fields, use dot notation ("outer.inner")
+ "A String",
+ ],
+ "threshold": "A String", # Optional. The threshold for the "aggregation threshold" policy.
+ },
+ },
+ "query": "A String", # Required. A query that BigQuery executes when the view is referenced.
+ "useExplicitColumnNames": True or False, # True if the column names are explicitly specified. For example by using the 'CREATE VIEW v(c1, c2) AS ...' syntax. Can only be set for GoogleSQL views.
+ "useLegacySql": True or False, # Specifies whether to use BigQuery's legacy SQL for this view. The default value is true. If set to false, the view will use BigQuery's GoogleSQL: https://cloud.google.com/bigquery/sql-reference/ Queries and views that reference this view must use the same flag value. A wrapper is used here because the default value is True.
"userDefinedFunctionResources": [ # Describes user-defined function resources used in the query.
- { # This is used for defining User Defined Function (UDF) resources only when using legacy SQL. Users of Standard SQL should leverage either DDL (e.g. CREATE [TEMPORARY] FUNCTION ... ) or the Routines API to define UDF resources. For additional information on migrating, see: https://cloud.google.com/bigquery/docs/reference/standard-sql/migrating-from-legacy-sql#differences_in_user-defined_javascript_functions
+ { # This is used for defining User Defined Function (UDF) resources only when using legacy SQL. Users of GoogleSQL should leverage either DDL (e.g. CREATE [TEMPORARY] FUNCTION ... ) or the Routines API to define UDF resources. For additional information on migrating, see: https://cloud.google.com/bigquery/docs/reference/standard-sql/migrating-from-legacy-sql#differences_in_user-defined_javascript_functions
"inlineCode": "A String", # [Pick one] An inline resource that contains code for a user-defined function (UDF). Providing a inline code resource is equivalent to providing a URI for a file containing the same code.
"resourceUri": "A String", # [Pick one] A code resource to load from a Google Cloud Storage URI (gs://bucket/path).
},
@@ -2239,183 +2532,198 @@ Method Details
},
}
- autodetect_schema: boolean, When true will autodetect schema, else will keep original schema
+ autodetect_schema: boolean, Optional. When true will autodetect schema, else will keep original schema
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
Returns:
An object of the form:
{
- "biglakeConfiguration": { # [Optional] Specifies the configuration of a BigLake managed table.
- "connectionId": "A String", # [Required] Required and immutable. Credential reference for accessing external storage system. Normalized as project_id.location_id.connection_id.
- "fileFormat": "A String", # [Required] Required and immutable. Open source file format that the table data is stored in. Currently only PARQUET is supported.
- "storageUri": "A String", # [Required] Required and immutable. Fully qualified location prefix of the external folder where data is stored. Normalized to standard format: "gs:////". Starts with "gs://" rather than "/bigstore/". Ends with "/". Does not contain "*". See also BigLakeStorageMetadata on how it is used.
- "tableFormat": "A String", # [Required] Required and immutable. Open source file format that the table data is stored in. Currently only PARQUET is supported.
- },
- "cloneDefinition": { # [Output-only] Clone definition.
- "baseTableReference": { # [Required] Reference describing the ID of the table that was cloned.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- },
- "cloneTime": "A String", # [Required] The time at which the base table was cloned. This value is reported in the JSON response using RFC3339 format.
- },
- "clustering": { # [Beta] Clustering specification for the table. Must be specified with partitioning, data in the table will be first partitioned and subsequently clustered.
- "fields": [ # [Repeated] One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. When you cluster a table using multiple columns, the order of columns you specify is important. The order of the specified columns determines the sort order of the data.
+ "biglakeConfiguration": { # Configuration for BigLake managed tables. # Optional. Specifies the configuration of a BigLake managed table.
+ "connectionId": "A String", # Required. The connection specifying the credentials to be used to read and write to external storage, such as Cloud Storage. The connection_id can have the form "<project\_id>.<location\_id>.<connection\_id>" or "projects/<project\_id>/locations/<location\_id>/connections/<connection\_id>".
+ "fileFormat": "A String", # Required. The file format the table data is stored in.
+ "storageUri": "A String", # Required. The fully qualified location prefix of the external folder where table data is stored. The '*' wildcard character is not allowed. The URI should be in the format "gs://bucket/path_to_table/"
+ "tableFormat": "A String", # Required. The table format the metadata only snapshots are stored in.
+ },
+ "cloneDefinition": { # Information about base table and clone time of a table clone. # Output only. Contains information about the clone. This value is set via the clone operation.
+ "baseTableReference": { # Required. Reference describing the ID of the table that was cloned.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ "cloneTime": "A String", # Required. The time at which the base table was cloned. This value is reported in the JSON response using RFC3339 format.
+ },
+ "clustering": { # Configures table clustering. # Clustering specification for the table. Must be specified with time-based partitioning, data in the table will be first partitioned and subsequently clustered.
+ "fields": [ # One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. The ordering of the clustering fields should be prioritized from most to least important for filtering purposes. Additional information on limitations can be found here: https://cloud.google.com/bigquery/docs/creating-clustered-tables#limitations
"A String",
],
},
- "creationTime": "A String", # [Output-only] The time when this table was created, in milliseconds since the epoch.
- "defaultCollation": "A String", # [Output-only] The default collation of the table.
- "defaultRoundingMode": "A String", # [Output-only] The default rounding mode of the table.
- "description": "A String", # [Optional] A user-friendly description of this table.
+ "creationTime": "A String", # Output only. The time when this table was created, in milliseconds since the epoch.
+ "defaultCollation": "A String", # Optional. Defines the default collation specification of new STRING fields in the table. During table creation or update, if a STRING field is added to this table without explicit collation specified, then the table inherits the table default collation. A change to this field affects only fields added afterwards, and does not alter the existing fields. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.
+ "defaultRoundingMode": "A String", # Optional. Defines the default rounding mode specification of new decimal fields (NUMERIC OR BIGNUMERIC) in the table. During table creation or update, if a decimal field is added to this table without an explicit rounding mode specified, then the field inherits the table default rounding mode. Changing this field doesn't affect existing fields.
+ "description": "A String", # Optional. A user-friendly description of this table.
"encryptionConfiguration": { # Custom encryption configuration (e.g., Cloud KMS keys).
"kmsKeyName": "A String", # Optional. Describes the Cloud KMS encryption key that will be used to protect destination BigQuery table. The BigQuery Service Account associated with your project requires access to this encryption key.
},
- "etag": "A String", # [Output-only] A hash of the table metadata. Used to ensure there were no concurrent modifications to the resource when attempting an update. Not guaranteed to change when the table contents or the fields numRows, numBytes, numLongTermBytes or lastModifiedTime change.
- "expirationTime": "A String", # [Optional] The time when this table expires, in milliseconds since the epoch. If not present, the table will persist indefinitely. Expired tables will be deleted and their storage reclaimed. The defaultTableExpirationMs property of the encapsulating dataset can be used to set a default expirationTime on newly created tables.
- "externalDataConfiguration": { # [Optional] Describes the data format, location, and other properties of a table stored outside of BigQuery. By defining these properties, the data source can then be queried as if it were a standard BigQuery table.
+ "etag": "A String", # Output only. A hash of this resource.
+ "expirationTime": "A String", # Optional. The time when this table expires, in milliseconds since the epoch. If not present, the table will persist indefinitely. Expired tables will be deleted and their storage reclaimed. The defaultTableExpirationMs property of the encapsulating dataset can be used to set a default expirationTime on newly created tables.
+ "externalDataConfiguration": { # Optional. Describes the data format, location, and other properties of a table stored outside of BigQuery. By defining these properties, the data source can then be queried as if it were a standard BigQuery table.
"autodetect": True or False, # Try to detect schema and format options automatically. Any option specified explicitly will be honored.
- "avroOptions": { # Additional properties to set if sourceFormat is set to Avro.
- "useAvroLogicalTypes": True or False, # [Optional] If sourceFormat is set to "AVRO", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER).
- },
- "bigtableOptions": { # [Optional] Additional options if sourceFormat is set to BIGTABLE.
- "columnFamilies": [ # [Optional] List of column families to expose in the table schema along with their types. This list restricts the column families that can be referenced in queries and specifies their value types. You can use this list to do type conversions - see the 'type' field for more details. If you leave this list empty, all column families are present in the table schema and their values are read as BYTES. During a query only the column families referenced in that query are read from Bigtable.
- {
- "columns": [ # [Optional] Lists of columns that should be exposed as individual fields as opposed to a list of (column name, value) pairs. All columns whose qualifier matches a qualifier in this list can be accessed as .. Other columns can be accessed as a list through .Column field.
- {
- "encoding": "A String", # [Optional] The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. 'encoding' can also be set at the column family level. However, the setting at this level takes precedence if 'encoding' is set at both levels.
- "fieldName": "A String", # [Optional] If the qualifier is not a valid BigQuery field identifier i.e. does not match [a-zA-Z][a-zA-Z0-9_]*, a valid identifier must be provided as the column field name and is used as field name in queries.
- "onlyReadLatest": True or False, # [Optional] If this is set, only the latest version of value in this column are exposed. 'onlyReadLatest' can also be set at the column family level. However, the setting at this level takes precedence if 'onlyReadLatest' is set at both levels.
- "qualifierEncoded": "A String", # [Required] Qualifier of the column. Columns in the parent column family that has this exact qualifier are exposed as . field. If the qualifier is valid UTF-8 string, it can be specified in the qualifier_string field. Otherwise, a base-64 encoded value must be set to qualifier_encoded. The column field name is the same as the column qualifier. However, if the qualifier is not a valid BigQuery field identifier i.e. does not match [a-zA-Z][a-zA-Z0-9_]*, a valid identifier must be provided as field_name.
- "qualifierString": "A String",
- "type": "A String", # [Optional] The type to convert the value in cells of this column. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive) - BYTES STRING INTEGER FLOAT BOOLEAN Default type is BYTES. 'type' can also be set at the column family level. However, the setting at this level takes precedence if 'type' is set at both levels.
+ "avroOptions": { # Options for external data sources. # Optional. Additional properties to set if sourceFormat is set to AVRO.
+ "useAvroLogicalTypes": True or False, # Optional. If sourceFormat is set to "AVRO", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER).
+ },
+ "bigtableOptions": { # Options specific to Google Cloud Bigtable data sources. # Optional. Additional options if sourceFormat is set to BIGTABLE.
+ "columnFamilies": [ # Optional. List of column families to expose in the table schema along with their types. This list restricts the column families that can be referenced in queries and specifies their value types. You can use this list to do type conversions - see the 'type' field for more details. If you leave this list empty, all column families are present in the table schema and their values are read as BYTES. During a query only the column families referenced in that query are read from Bigtable.
+ { # Information related to a Bigtable column family.
+ "columns": [ # Optional. Lists of columns that should be exposed as individual fields as opposed to a list of (column name, value) pairs. All columns whose qualifier matches a qualifier in this list can be accessed as .. Other columns can be accessed as a list through .Column field.
+ { # Information related to a Bigtable column.
+ "encoding": "A String", # Optional. The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. 'encoding' can also be set at the column family level. However, the setting at this level takes precedence if 'encoding' is set at both levels.
+ "fieldName": "A String", # Optional. If the qualifier is not a valid BigQuery field identifier i.e. does not match a-zA-Z*, a valid identifier must be provided as the column field name and is used as field name in queries.
+ "onlyReadLatest": True or False, # Optional. If this is set, only the latest version of value in this column are exposed. 'onlyReadLatest' can also be set at the column family level. However, the setting at this level takes precedence if 'onlyReadLatest' is set at both levels.
+ "qualifierEncoded": "A String", # [Required] Qualifier of the column. Columns in the parent column family that has this exact qualifier are exposed as . field. If the qualifier is valid UTF-8 string, it can be specified in the qualifier_string field. Otherwise, a base-64 encoded value must be set to qualifier_encoded. The column field name is the same as the column qualifier. However, if the qualifier is not a valid BigQuery field identifier i.e. does not match a-zA-Z*, a valid identifier must be provided as field_name.
+ "qualifierString": "A String", # Qualifier string.
+ "type": "A String", # Optional. The type to convert the value in cells of this column. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive): * BYTES * STRING * INTEGER * FLOAT * BOOLEAN * JSON Default type is BYTES. 'type' can also be set at the column family level. However, the setting at this level takes precedence if 'type' is set at both levels.
},
],
- "encoding": "A String", # [Optional] The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. This can be overridden for a specific column by listing that column in 'columns' and specifying an encoding for it.
+ "encoding": "A String", # Optional. The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. This can be overridden for a specific column by listing that column in 'columns' and specifying an encoding for it.
"familyId": "A String", # Identifier of the column family.
- "onlyReadLatest": True or False, # [Optional] If this is set only the latest version of value are exposed for all columns in this column family. This can be overridden for a specific column by listing that column in 'columns' and specifying a different setting for that column.
- "type": "A String", # [Optional] The type to convert the value in cells of this column family. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive) - BYTES STRING INTEGER FLOAT BOOLEAN Default type is BYTES. This can be overridden for a specific column by listing that column in 'columns' and specifying a type for it.
+ "onlyReadLatest": True or False, # Optional. If this is set only the latest version of value are exposed for all columns in this column family. This can be overridden for a specific column by listing that column in 'columns' and specifying a different setting for that column.
+ "type": "A String", # Optional. The type to convert the value in cells of this column family. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive): * BYTES * STRING * INTEGER * FLOAT * BOOLEAN * JSON Default type is BYTES. This can be overridden for a specific column by listing that column in 'columns' and specifying a type for it.
},
],
- "ignoreUnspecifiedColumnFamilies": True or False, # [Optional] If field is true, then the column families that are not specified in columnFamilies list are not exposed in the table schema. Otherwise, they are read with BYTES type values. The default value is false.
- "readRowkeyAsString": True or False, # [Optional] If field is true, then the rowkey column families will be read and converted to string. Otherwise they are read with BYTES type values and users need to manually cast them with CAST if necessary. The default value is false.
- },
- "compression": "A String", # [Optional] The compression type of the data source. Possible values include GZIP and NONE. The default value is NONE. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups and Avro formats.
- "connectionId": "A String", # [Optional, Trusted Tester] Connection for external data source.
- "csvOptions": { # Additional properties to set if sourceFormat is set to CSV.
- "allowJaggedRows": True or False, # [Optional] Indicates if BigQuery should accept rows that are missing trailing optional columns. If true, BigQuery treats missing trailing columns as null values. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false.
- "allowQuotedNewlines": True or False, # [Optional] Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false.
- "encoding": "A String", # [Optional] The character encoding of the data. The supported values are UTF-8 or ISO-8859-1. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the quote and fieldDelimiter properties.
- "fieldDelimiter": "A String", # [Optional] The separator for fields in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. BigQuery also supports the escape sequence "\t" to specify a tab separator. The default value is a comma (',').
- "nullMarker": "A String", # [Optional] An custom string that will represent a NULL value in CSV import data.
- "preserveAsciiControlCharacters": True or False, # [Optional] Preserves the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\x00' to '\x1F') when loading from CSV. Only applicable to CSV, ignored for other formats.
- "quote": """, # [Optional] The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ('"'). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true.
- "skipLeadingRows": "A String", # [Optional] The number of rows at the top of a CSV file that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
- },
- "decimalTargetTypes": [ # [Optional] Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown. Example: Suppose the value of this field is ["NUMERIC", "BIGNUMERIC"]. If (precision,scale) is: (38,9) -> NUMERIC; (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits); (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits); (76,38) -> BIGNUMERIC; (77,38) -> BIGNUMERIC (error if value exeeds supported range). This field cannot contain duplicate types. The order of the types in this field is ignored. For example, ["BIGNUMERIC", "NUMERIC"] is the same as ["NUMERIC", "BIGNUMERIC"] and NUMERIC always takes precedence over BIGNUMERIC. Defaults to ["NUMERIC", "STRING"] for ORC and ["NUMERIC"] for the other file formats.
+ "ignoreUnspecifiedColumnFamilies": True or False, # Optional. If field is true, then the column families that are not specified in columnFamilies list are not exposed in the table schema. Otherwise, they are read with BYTES type values. The default value is false.
+ "outputColumnFamiliesAsJson": True or False, # Optional. If field is true, then each column family will be read as a single JSON column. Otherwise they are read as a repeated cell structure containing timestamp/value tuples. The default value is false.
+ "readRowkeyAsString": True or False, # Optional. If field is true, then the rowkey column families will be read and converted to string. Otherwise they are read with BYTES type values and users need to manually cast them with CAST if necessary. The default value is false.
+ },
+ "compression": "A String", # Optional. The compression type of the data source. Possible values include GZIP and NONE. The default value is NONE. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups, Avro, ORC and Parquet formats. An empty string is an invalid value.
+ "connectionId": "A String", # Optional. The connection specifying the credentials to be used to read external storage, such as Azure Blob, Cloud Storage, or S3. The connection_id can have the form "<project\_id>.<location\_id>.<connection\_id>" or "projects/<project\_id>/locations/<location\_id>/connections/<connection\_id>".
+ "csvOptions": { # Information related to a CSV data source. # Optional. Additional properties to set if sourceFormat is set to CSV.
+ "allowJaggedRows": True or False, # Optional. Indicates if BigQuery should accept rows that are missing trailing optional columns. If true, BigQuery treats missing trailing columns as null values. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false.
+ "allowQuotedNewlines": True or False, # Optional. Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false.
+ "encoding": "A String", # Optional. The character encoding of the data. The supported values are UTF-8, ISO-8859-1, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the quote and fieldDelimiter properties.
+ "fieldDelimiter": "A String", # Optional. The separator character for fields in a CSV file. The separator is interpreted as a single byte. For files encoded in ISO-8859-1, any single character can be used as a separator. For files encoded in UTF-8, characters represented in decimal range 1-127 (U+0001-U+007F) can be used without any modification. UTF-8 characters encoded with multiple bytes (i.e. U+0080 and above) will have only the first byte used for separating fields. The remaining bytes will be treated as a part of the field. BigQuery also supports the escape sequence "\t" (U+0009) to specify a tab separator. The default value is comma (",", U+002C).
+ "nullMarker": "A String", # [Optional] A custom string that will represent a NULL value in CSV import data.
+ "preserveAsciiControlCharacters": True or False, # Optional. Indicates if the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\x00' to '\x1F') are preserved.
+ "quote": """, # Optional. The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ("). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true. To include the specific quote character within a quoted value, precede it with an additional matching quote character. For example, if you want to escape the default character ' " ', use ' "" '.
+ "skipLeadingRows": "A String", # Optional. The number of rows at the top of a CSV file that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
+ },
+ "decimalTargetTypes": [ # Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown. Example: Suppose the value of this field is ["NUMERIC", "BIGNUMERIC"]. If (precision,scale) is: * (38,9) -> NUMERIC; * (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits); * (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits); * (76,38) -> BIGNUMERIC; * (77,38) -> BIGNUMERIC (error if value exeeds supported range). This field cannot contain duplicate types. The order of the types in this field is ignored. For example, ["BIGNUMERIC", "NUMERIC"] is the same as ["NUMERIC", "BIGNUMERIC"] and NUMERIC always takes precedence over BIGNUMERIC. Defaults to ["NUMERIC", "STRING"] for ORC and ["NUMERIC"] for the other file formats.
"A String",
],
- "fileSetSpecType": "A String", # [Optional] Specifies how source URIs are interpreted for constructing the file set to load. By default source URIs are expanded against the underlying storage. Other options include specifying manifest files. Only applicable to object storage systems.
- "googleSheetsOptions": { # [Optional] Additional options if sourceFormat is set to GOOGLE_SHEETS.
- "range": "A String", # [Optional] Range of a sheet to query from. Only used when non-empty. Typical format: sheet_name!top_left_cell_id:bottom_right_cell_id For example: sheet1!A1:B20
- "skipLeadingRows": "A String", # [Optional] The number of rows at the top of a sheet that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows that should be skipped. When autodetect is on, behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
+ "fileSetSpecType": "A String", # Optional. Specifies how source URIs are interpreted for constructing the file set to load. By default source URIs are expanded against the underlying storage. Other options include specifying manifest files. Only applicable to object storage systems.
+ "googleSheetsOptions": { # Options specific to Google Sheets data sources. # Optional. Additional options if sourceFormat is set to GOOGLE_SHEETS.
+ "range": "A String", # Optional. Range of a sheet to query from. Only used when non-empty. Typical format: sheet_name!top_left_cell_id:bottom_right_cell_id For example: sheet1!A1:B20
+ "skipLeadingRows": "A String", # Optional. The number of rows at the top of a sheet that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.
},
- "hivePartitioningOptions": { # [Optional] Options to configure hive partitioning support.
- "fields": [ # [Output-only] For permanent external tables, this field is populated with the hive partition keys in the order they were inferred. The types of the partition keys can be deduced by checking the table schema (which will include the partition keys). Not every API will populate this field in the output. For example, Tables.Get will populate it, but Tables.List will not contain this field.
+ "hivePartitioningOptions": { # Options for configuring hive partitioning detect. # Optional. When set, configures hive partitioning support. Not all storage formats support hive partitioning -- requesting hive partitioning on an unsupported format will lead to an error, as will providing an invalid specification.
+ "fields": [ # Output only. For permanent external tables, this field is populated with the hive partition keys in the order they were inferred. The types of the partition keys can be deduced by checking the table schema (which will include the partition keys). Not every API will populate this field in the output. For example, Tables.Get will populate it, but Tables.List will not contain this field.
"A String",
],
- "mode": "A String", # [Optional] When set, what mode of hive partitioning to use when reading data. The following modes are supported. (1) AUTO: automatically infer partition key name(s) and type(s). (2) STRINGS: automatically infer partition key name(s). All types are interpreted as strings. (3) CUSTOM: partition key schema is encoded in the source URI prefix. Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported types include: AVRO, CSV, JSON, ORC and Parquet.
- "requirePartitionFilter": True or False, # [Optional] If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. Note that this field should only be true when creating a permanent external table or querying a temporary external table. Hive-partitioned loads with requirePartitionFilter explicitly set to true will fail.
- "sourceUriPrefix": "A String", # [Optional] When hive partition detection is requested, a common prefix for all source uris should be supplied. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout. gs://bucket/path_to_table/dt=2019-01-01/country=BR/id=7/file.avro gs://bucket/path_to_table/dt=2018-12-31/country=CA/id=3/file.avro When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/ (trailing slash does not matter).
- },
- "ignoreUnknownValues": True or False, # [Optional] Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names Google Cloud Bigtable: This setting is ignored. Google Cloud Datastore backups: This setting is ignored. Avro: This setting is ignored.
- "jsonOptions": { # Additional properties to set if `sourceFormat` is set to `NEWLINE_DELIMITED_JSON`.
- "encoding": "A String", # [Optional] The character encoding of the data. The supported values are UTF-8, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8.
- },
- "maxBadRecords": 42, # [Optional] The maximum number of bad records that BigQuery can ignore when reading data. If the number of bad records exceeds this value, an invalid error is returned in the job result. This is only valid for CSV, JSON, and Google Sheets. The default value is 0, which requires that all records are valid. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups and Avro formats.
- "metadataCacheMode": "A String", # [Optional] Metadata Cache Mode for the table. Set this to enable caching of metadata from external data source.
- "objectMetadata": "A String", # ObjectMetadata is used to create Object Tables. Object Tables contain a listing of objects (with their metadata) found at the source_uris. If ObjectMetadata is set, source_format should be omitted. Currently SIMPLE is the only supported Object Metadata type.
- "parquetOptions": { # Additional properties to set if sourceFormat is set to Parquet.
- "enableListInference": True or False, # [Optional] Indicates whether to use schema inference specifically for Parquet LIST logical type.
- "enumAsString": True or False, # [Optional] Indicates whether to infer Parquet ENUM logical type as STRING instead of BYTES by default.
- },
- "referenceFileSchemaUri": "A String", # [Optional] Provide a referencing file with the expected table schema. Enabled for the format: AVRO, PARQUET, ORC.
- "schema": { # [Optional] The schema for the data. Schema is required for CSV and JSON formats. Schema is disallowed for Google Cloud Bigtable, Cloud Datastore backups, and Avro formats.
+ "mode": "A String", # Optional. When set, what mode of hive partitioning to use when reading data. The following modes are supported: * AUTO: automatically infer partition key name(s) and type(s). * STRINGS: automatically infer partition key name(s). All types are strings. * CUSTOM: partition key schema is encoded in the source URI prefix. Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported formats are: JSON, CSV, ORC, Avro and Parquet.
+ "requirePartitionFilter": false, # Optional. If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. Note that this field should only be true when creating a permanent external table or querying a temporary external table. Hive-partitioned loads with require_partition_filter explicitly set to true will fail.
+ "sourceUriPrefix": "A String", # Optional. When hive partition detection is requested, a common prefix for all source uris must be required. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout: gs://bucket/path_to_table/dt=2019-06-01/country=USA/id=7/file.avro gs://bucket/path_to_table/dt=2019-05-31/country=CA/id=3/file.avro When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/. CUSTOM detection requires encoding the partitioning schema immediately after the common prefix. For CUSTOM, any of * gs://bucket/path_to_table/{dt:DATE}/{country:STRING}/{id:INTEGER} * gs://bucket/path_to_table/{dt:STRING}/{country:STRING}/{id:INTEGER} * gs://bucket/path_to_table/{dt:DATE}/{country:STRING}/{id:STRING} would all be valid source URI prefixes.
+ },
+ "ignoreUnknownValues": True or False, # Optional. Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names Google Cloud Bigtable: This setting is ignored. Google Cloud Datastore backups: This setting is ignored. Avro: This setting is ignored. ORC: This setting is ignored. Parquet: This setting is ignored.
+ "jsonExtension": "A String", # Optional. Load option to be used together with source_format newline-delimited JSON to indicate that a variant of JSON is being loaded. To load newline-delimited GeoJSON, specify GEOJSON (and source_format must be set to NEWLINE_DELIMITED_JSON).
+ "jsonOptions": { # Json Options for load and make external tables. # Optional. Additional properties to set if sourceFormat is set to JSON.
+ "encoding": "A String", # Optional. The character encoding of the data. The supported values are UTF-8, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8.
+ },
+ "maxBadRecords": 42, # Optional. The maximum number of bad records that BigQuery can ignore when reading data. If the number of bad records exceeds this value, an invalid error is returned in the job result. The default value is 0, which requires that all records are valid. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups, Avro, ORC and Parquet formats.
+ "metadataCacheMode": "A String", # Optional. Metadata Cache Mode for the table. Set this to enable caching of metadata from external data source.
+ "objectMetadata": "A String", # Optional. ObjectMetadata is used to create Object Tables. Object Tables contain a listing of objects (with their metadata) found at the source_uris. If ObjectMetadata is set, source_format should be omitted. Currently SIMPLE is the only supported Object Metadata type.
+ "parquetOptions": { # Parquet Options for load and make external tables. # Optional. Additional properties to set if sourceFormat is set to PARQUET.
+ "enableListInference": True or False, # Optional. Indicates whether to use schema inference specifically for Parquet LIST logical type.
+ "enumAsString": True or False, # Optional. Indicates whether to infer Parquet ENUM logical type as STRING instead of BYTES by default.
+ },
+ "referenceFileSchemaUri": "A String", # Optional. When creating an external table, the user can provide a reference file with the table schema. This is enabled for the following formats: AVRO, PARQUET, ORC.
+ "schema": { # Schema of a table # Optional. The schema for the data. Schema is required for CSV and JSON formats if autodetect is not on. Schema is disallowed for Google Cloud Bigtable, Cloud Datastore backups, Avro, ORC and Parquet formats.
"fields": [ # Describes the fields in a table.
- {
- "categories": { # [Optional] The categories attached to this field, used for field-level access control.
- "names": [ # A list of category resource names. For example, "projects/1/taxonomies/2/categories/3". At most 5 categories are allowed.
+ { # A field in TableSchema
+ "categories": { # Deprecated.
+ "names": [ # Deprecated.
"A String",
],
},
- "collation": "A String", # Optional. Collation specification of the field. It only can be set on string type field.
- "defaultValueExpression": "A String", # Optional. A SQL expression to specify the default value for this field. It can only be set for top level fields (columns). You can use struct or array expression to specify default value for the entire struct or array. The valid SQL expressions are: - Literals for all data types, including STRUCT and ARRAY. - Following functions: - CURRENT_TIMESTAMP - CURRENT_TIME - CURRENT_DATE - CURRENT_DATETIME - GENERATE_UUID - RAND - SESSION_USER - ST_GEOGPOINT - Struct or array composed with the above allowed functions, for example, [CURRENT_DATE(), DATE '2020-01-01']
- "description": "A String", # [Optional] The field description. The maximum length is 1,024 characters.
- "fields": [ # [Optional] Describes the nested schema fields if the type property is set to RECORD.
+ "collation": "A String", # Optional. Field collation can be set only when the type of field is STRING. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.
+ "defaultValueExpression": "A String", # Optional. A SQL expression to specify the [default value] (https://cloud.google.com/bigquery/docs/default-values) for this field.
+ "description": "A String", # Optional. The field description. The maximum length is 1,024 characters.
+ "fields": [ # Optional. Describes the nested schema fields if the type property is set to RECORD.
# Object with schema name: TableFieldSchema
],
- "maxLength": "A String", # [Optional] Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
- "mode": "A String", # [Optional] The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
- "name": "A String", # [Required] The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
- "policyTags": {
- "names": [ # A list of category resource names. For example, "projects/1/location/eu/taxonomies/2/policyTags/3". At most 1 policy tag is allowed.
+ "maxLength": "A String", # Optional. Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
+ "mode": "A String", # Optional. The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
+ "name": "A String", # Required. The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
+ "policyTags": { # Optional. The policy tags attached to this field, used for field-level access control. If not set, defaults to empty policy_tags.
+ "names": [ # A list of policy tag resource names. For example, "projects/1/locations/eu/taxonomies/2/policyTags/3". At most 1 policy tag is currently allowed.
"A String",
],
},
- "precision": "A String", # [Optional] Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: - Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] - Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: - If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. - If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): - If type = "NUMERIC": 1 ≤ precision ≤ 29. - If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
- "rangeElementType": { # Optional. The subtype of the RANGE, if the type of this field is RANGE. If the type is RANGE, this field is required. Possible values for the field element type of a RANGE include: - DATE - DATETIME - TIMESTAMP
- "type": "A String", # The field element type of a RANGE
+ "precision": "A String", # Optional. Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: * Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] * Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: * If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. * If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): * If type = "NUMERIC": 1 ≤ precision ≤ 29. * If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
+ "rangeElementType": { # Represents the type of a field element.
+ "type": "A String", # Required. The type of a field element. See TableFieldSchema.type.
},
- "roundingMode": "A String", # Optional. Rounding Mode specification of the field. It only can be set on NUMERIC or BIGNUMERIC type fields.
- "scale": "A String", # [Optional] See documentation for precision.
- "type": "A String", # [Required] The field data type. Possible values include STRING, BYTES, INTEGER, INT64 (same as INTEGER), FLOAT, FLOAT64 (same as FLOAT), NUMERIC, BIGNUMERIC, BOOLEAN, BOOL (same as BOOLEAN), TIMESTAMP, DATE, TIME, DATETIME, INTERVAL, RECORD (where RECORD indicates that the field contains a nested schema) or STRUCT (same as RECORD).
+ "roundingMode": "A String", # Optional. Specifies the rounding mode to be used when storing values of NUMERIC and BIGNUMERIC type.
+ "scale": "A String", # Optional. See documentation for precision.
+ "type": "A String", # Required. The field data type. Possible values include: * STRING * BYTES * INTEGER (or INT64) * FLOAT (or FLOAT64) * BOOLEAN (or BOOL) * TIMESTAMP * DATE * TIME * DATETIME * GEOGRAPHY * NUMERIC * BIGNUMERIC * JSON * RECORD (or STRUCT) Use of RECORD/STRUCT indicates that the field contains a nested schema.
},
],
},
- "sourceFormat": "A String", # [Required] The data format. For CSV files, specify "CSV". For Google sheets, specify "GOOGLE_SHEETS". For newline-delimited JSON, specify "NEWLINE_DELIMITED_JSON". For Avro files, specify "AVRO". For Google Cloud Datastore backups, specify "DATASTORE_BACKUP". [Beta] For Google Cloud Bigtable, specify "BIGTABLE".
+ "sourceFormat": "A String", # [Required] The data format. For CSV files, specify "CSV". For Google sheets, specify "GOOGLE_SHEETS". For newline-delimited JSON, specify "NEWLINE_DELIMITED_JSON". For Avro files, specify "AVRO". For Google Cloud Datastore backups, specify "DATASTORE_BACKUP". For Apache Iceberg tables, specify "ICEBERG". For ORC files, specify "ORC". For Parquet files, specify "PARQUET". [Beta] For Google Cloud Bigtable, specify "BIGTABLE".
"sourceUris": [ # [Required] The fully-qualified URIs that point to your data in Google Cloud. For Google Cloud Storage URIs: Each URI can contain one '*' wildcard character and it must come after the 'bucket' name. Size limits related to load jobs apply to external data sources. For Google Cloud Bigtable URIs: Exactly one URI can be specified and it has be a fully specified and valid HTTPS URL for a Google Cloud Bigtable table. For Google Cloud Datastore backups, exactly one URI can be specified. Also, the '*' wildcard character is not allowed.
"A String",
],
},
- "friendlyName": "A String", # [Optional] A descriptive name for this table.
- "id": "A String", # [Output-only] An opaque ID uniquely identifying the table.
- "kind": "bigquery#table", # [Output-only] The type of the resource.
+ "friendlyName": "A String", # Optional. A descriptive name for this table.
+ "id": "A String", # Output only. An opaque ID uniquely identifying the table.
+ "kind": "bigquery#table", # The type of resource ID.
"labels": { # The labels associated with this table. You can use these to organize and group your tables. Label keys and values can be no longer than 63 characters, can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. Label values are optional. Label keys must start with a letter and each label in the list must have a different key.
"a_key": "A String",
},
- "lastModifiedTime": "A String", # [Output-only] The time when this table was last modified, in milliseconds since the epoch.
- "location": "A String", # [Output-only] The geographic location where the table resides. This value is inherited from the dataset.
- "materializedView": { # [Optional] Materialized view definition.
- "allowNonIncrementalDefinition": True or False, # [Optional] Allow non incremental materialized view definition. The default value is "false".
- "enableRefresh": True or False, # [Optional] [TrustedTester] Enable automatic refresh of the materialized view when the base table is updated. The default value is "true".
- "lastRefreshTime": "A String", # [Output-only] [TrustedTester] The time when this materialized view was last modified, in milliseconds since the epoch.
+ "lastModifiedTime": "A String", # Output only. The time when this table was last modified, in milliseconds since the epoch.
+ "location": "A String", # Output only. The geographic location where the table resides. This value is inherited from the dataset.
+ "materializedView": { # Definition and configuration of a materialized view. # Optional. The materialized view definition.
+ "allowNonIncrementalDefinition": True or False, # Optional. This option declares authors intention to construct a materialized view that will not be refreshed incrementally.
+ "enableRefresh": True or False, # Optional. Enable automatic refresh of the materialized view when the base table is updated. The default value is "true".
+ "lastRefreshTime": "A String", # Output only. The time when this materialized view was last refreshed, in milliseconds since the epoch.
"maxStaleness": "A String", # [Optional] Max staleness of data that could be returned when materizlized view is queried (formatted as Google SQL Interval type).
- "query": "A String", # [Required] A query whose result is persisted.
- "refreshIntervalMs": "A String", # [Optional] [TrustedTester] The maximum frequency at which this materialized view will be refreshed. The default value is "1800000" (30 minutes).
+ "query": "A String", # Required. A query whose results are persisted.
+ "refreshIntervalMs": "A String", # Optional. The maximum frequency at which this materialized view will be refreshed. The default value is "1800000" (30 minutes).
},
- "maxStaleness": "A String", # [Optional] Max staleness of data that could be returned when table or materialized view is queried (formatted as Google SQL Interval type).
- "model": { # [Output-only, Beta] Present iff this table represents a ML model. Describes the training information for the model, and it is required to run 'PREDICT' queries.
- "modelOptions": { # [Output-only, Beta] Model options used for the first training run. These options are immutable for subsequent training runs. Default values are used for any options not specified in the input query.
+ "materializedViewStatus": { # Status of a materialized view. The last refresh timestamp status is omitted here, but is present in the MaterializedViewDefinition message. # Output only. The materialized view status.
+ "lastRefreshStatus": { # Error details. # Output only. Error result of the last automatic refresh. If present, indicates that the last automatic refresh was unsuccessful.
+ "debugInfo": "A String", # Debugging information. This property is internal to Google and should not be used.
+ "location": "A String", # Specifies where the error occurred, if present.
+ "message": "A String", # A human-readable description of the error.
+ "reason": "A String", # A short error code that summarizes the error.
+ },
+ "refreshWatermark": "A String", # Output only. Refresh watermark of materialized view. The base tables' data were collected into the materialized view cache until this time.
+ },
+ "maxStaleness": "A String", # Optional. The maximum staleness of data that could be returned when the table (or stale MV) is queried. Staleness encoded as a string encoding of sql IntervalValue type.
+ "model": { # Deprecated.
+ "modelOptions": { # Deprecated.
"labels": [
"A String",
],
"lossType": "A String",
"modelType": "A String",
},
- "trainingRuns": [ # [Output-only, Beta] Information about ml training runs, each training run comprises of multiple iterations and there may be multiple training runs for the model if warm start is used or if a user decides to continue a previously cancelled query.
+ "trainingRuns": [ # Deprecated.
{
- "iterationResults": [ # [Output-only, Beta] List of each iteration results.
+ "iterationResults": [ # Deprecated.
{
- "durationMs": "A String", # [Output-only, Beta] Time taken to run the training iteration in milliseconds.
- "evalLoss": 3.14, # [Output-only, Beta] Eval loss computed on the eval data at the end of the iteration. The eval loss is used for early stopping to avoid overfitting. No eval loss if eval_split_method option is specified as no_split or auto_split with input data size less than 500 rows.
- "index": 42, # [Output-only, Beta] Index of the ML training iteration, starting from zero for each training run.
- "learnRate": 3.14, # [Output-only, Beta] Learning rate used for this iteration, it varies for different training iterations if learn_rate_strategy option is not constant.
- "trainingLoss": 3.14, # [Output-only, Beta] Training loss computed on the training data at the end of the iteration. The training loss function is defined by model type.
+ "durationMs": "A String", # Deprecated.
+ "evalLoss": 3.14, # Deprecated.
+ "index": 42, # Deprecated.
+ "learnRate": 3.14, # Deprecated.
+ "trainingLoss": 3.14, # Deprecated.
},
],
- "startTime": "A String", # [Output-only, Beta] Training run start time in milliseconds since the epoch.
- "state": "A String", # [Output-only, Beta] Different state applicable for a training run. IN PROGRESS: Training run is in progress. FAILED: Training run ended due to a non-retryable failure. SUCCEEDED: Training run successfully completed. CANCELLED: Training run cancelled by the user.
- "trainingOptions": { # [Output-only, Beta] Training options used by this training run. These options are mutable for subsequent training runs. Default values are explicitly stored for options not specified in the input query of the first training run. For subsequent training runs, any option not explicitly specified in the input query will be copied from the previous training run.
+ "startTime": "A String", # Deprecated.
+ "state": "A String", # Deprecated.
+ "trainingOptions": { # Deprecated.
"earlyStop": True or False,
"l1Reg": 3.14,
"l2Reg": 3.14,
@@ -2429,86 +2737,93 @@ Method Details
},
],
},
- "numActiveLogicalBytes": "A String", # [Output-only] Number of logical bytes that are less than 90 days old.
- "numActivePhysicalBytes": "A String", # [Output-only] Number of physical bytes less than 90 days old. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
- "numBytes": "A String", # [Output-only] The size of this table in bytes, excluding any data in the streaming buffer.
- "numLongTermBytes": "A String", # [Output-only] The number of bytes in the table that are considered "long-term storage".
- "numLongTermLogicalBytes": "A String", # [Output-only] Number of logical bytes that are more than 90 days old.
- "numLongTermPhysicalBytes": "A String", # [Output-only] Number of physical bytes more than 90 days old. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
- "numPartitions": "A String", # [Output-only] The number of partitions present in the table or materialized view. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
- "numPhysicalBytes": "A String", # [Output-only] [TrustedTester] The physical size of this table in bytes, excluding any data in the streaming buffer. This includes compression and storage used for time travel.
- "numRows": "A String", # [Output-only] The number of rows of data in this table, excluding any data in the streaming buffer.
- "numTimeTravelPhysicalBytes": "A String", # [Output-only] Number of physical bytes used by time travel storage (deleted or changed data). This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
- "numTotalLogicalBytes": "A String", # [Output-only] Total number of logical bytes in the table or materialized view.
- "numTotalPhysicalBytes": "A String", # [Output-only] The physical size of this table in bytes. This also includes storage used for time travel. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
- "rangePartitioning": { # [TrustedTester] Range partitioning specification for this table. Only one of timePartitioning and rangePartitioning should be specified.
- "field": "A String", # [TrustedTester] [Required] The table is partitioned by this field. The field must be a top-level NULLABLE/REQUIRED field. The only supported type is INTEGER/INT64.
- "range": { # [TrustedTester] [Required] Defines the ranges for range partitioning.
- "end": "A String", # [TrustedTester] [Required] The end of range partitioning, exclusive.
- "interval": "A String", # [TrustedTester] [Required] The width of each interval.
- "start": "A String", # [TrustedTester] [Required] The start of range partitioning, inclusive.
- },
- },
- "requirePartitionFilter": false, # [Optional] If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified.
+ "numActiveLogicalBytes": "A String", # Output only. Number of logical bytes that are less than 90 days old.
+ "numActivePhysicalBytes": "A String", # Output only. Number of physical bytes less than 90 days old. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
+ "numBytes": "A String", # Output only. The size of this table in logical bytes, excluding any data in the streaming buffer.
+ "numLongTermBytes": "A String", # Output only. The number of logical bytes in the table that are considered "long-term storage".
+ "numLongTermLogicalBytes": "A String", # Output only. Number of logical bytes that are more than 90 days old.
+ "numLongTermPhysicalBytes": "A String", # Output only. Number of physical bytes more than 90 days old. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
+ "numPartitions": "A String", # Output only. The number of partitions present in the table or materialized view. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
+ "numPhysicalBytes": "A String", # Output only. The physical size of this table in bytes. This includes storage used for time travel.
+ "numRows": "A String", # Output only. The number of rows of data in this table, excluding any data in the streaming buffer.
+ "numTimeTravelPhysicalBytes": "A String", # Output only. Number of physical bytes used by time travel storage (deleted or changed data). This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
+ "numTotalLogicalBytes": "A String", # Output only. Total number of logical bytes in the table or materialized view.
+ "numTotalPhysicalBytes": "A String", # Output only. The physical size of this table in bytes. This also includes storage used for time travel. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.
+ "rangePartitioning": { # If specified, configures range partitioning for this table.
+ "field": "A String", # Required. [Experimental] The table is partitioned by this field. The field must be a top-level NULLABLE/REQUIRED field. The only supported type is INTEGER/INT64.
+ "range": { # [Experimental] Defines the ranges for range partitioning.
+ "end": "A String", # [Experimental] The end of range partitioning, exclusive.
+ "interval": "A String", # [Experimental] The width of each interval.
+ "start": "A String", # [Experimental] The start of range partitioning, inclusive.
+ },
+ },
+ "replicas": [ # Optional. Output only. Table references of all replicas currently active on the table.
+ {
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ ],
+ "requirePartitionFilter": false, # Optional. If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified.
"resourceTags": { # [Optional] The tags associated with this table. Tag keys are globally unique. See additional information on [tags](https://cloud.google.com/iam/docs/tags-access-control#definitions). An object containing a list of "key": value pairs. The key is the namespaced friendly name of the tag key, e.g. "12345/environment" where 12345 is parent id. The value is the friendly short name of the tag value, e.g. "production".
"a_key": "A String",
},
- "schema": { # [Optional] Describes the schema of this table.
+ "schema": { # Schema of a table # Optional. Describes the schema of this table.
"fields": [ # Describes the fields in a table.
- {
- "categories": { # [Optional] The categories attached to this field, used for field-level access control.
- "names": [ # A list of category resource names. For example, "projects/1/taxonomies/2/categories/3". At most 5 categories are allowed.
+ { # A field in TableSchema
+ "categories": { # Deprecated.
+ "names": [ # Deprecated.
"A String",
],
},
- "collation": "A String", # Optional. Collation specification of the field. It only can be set on string type field.
- "defaultValueExpression": "A String", # Optional. A SQL expression to specify the default value for this field. It can only be set for top level fields (columns). You can use struct or array expression to specify default value for the entire struct or array. The valid SQL expressions are: - Literals for all data types, including STRUCT and ARRAY. - Following functions: - CURRENT_TIMESTAMP - CURRENT_TIME - CURRENT_DATE - CURRENT_DATETIME - GENERATE_UUID - RAND - SESSION_USER - ST_GEOGPOINT - Struct or array composed with the above allowed functions, for example, [CURRENT_DATE(), DATE '2020-01-01']
- "description": "A String", # [Optional] The field description. The maximum length is 1,024 characters.
- "fields": [ # [Optional] Describes the nested schema fields if the type property is set to RECORD.
+ "collation": "A String", # Optional. Field collation can be set only when the type of field is STRING. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.
+ "defaultValueExpression": "A String", # Optional. A SQL expression to specify the [default value] (https://cloud.google.com/bigquery/docs/default-values) for this field.
+ "description": "A String", # Optional. The field description. The maximum length is 1,024 characters.
+ "fields": [ # Optional. Describes the nested schema fields if the type property is set to RECORD.
# Object with schema name: TableFieldSchema
],
- "maxLength": "A String", # [Optional] Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
- "mode": "A String", # [Optional] The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
- "name": "A String", # [Required] The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
- "policyTags": {
- "names": [ # A list of category resource names. For example, "projects/1/location/eu/taxonomies/2/policyTags/3". At most 1 policy tag is allowed.
+ "maxLength": "A String", # Optional. Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = "STRING", then max_length represents the maximum UTF-8 length of strings in this field. If type = "BYTES", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type ≠"STRING" and ≠"BYTES".
+ "mode": "A String", # Optional. The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.
+ "name": "A String", # Required. The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.
+ "policyTags": { # Optional. The policy tags attached to this field, used for field-level access control. If not set, defaults to empty policy_tags.
+ "names": [ # A list of policy tag resource names. For example, "projects/1/locations/eu/taxonomies/2/policyTags/3". At most 1 policy tag is currently allowed.
"A String",
],
},
- "precision": "A String", # [Optional] Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: - Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] - Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: - If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. - If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): - If type = "NUMERIC": 1 ≤ precision ≤ 29. - If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
- "rangeElementType": { # Optional. The subtype of the RANGE, if the type of this field is RANGE. If the type is RANGE, this field is required. Possible values for the field element type of a RANGE include: - DATE - DATETIME - TIMESTAMP
- "type": "A String", # The field element type of a RANGE
+ "precision": "A String", # Optional. Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type ≠"NUMERIC" and ≠"BIGNUMERIC". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: * Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] * Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: * If type = "NUMERIC": 1 ≤ precision - scale ≤ 29 and 0 ≤ scale ≤ 9. * If type = "BIGNUMERIC": 1 ≤ precision - scale ≤ 38 and 0 ≤ scale ≤ 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): * If type = "NUMERIC": 1 ≤ precision ≤ 29. * If type = "BIGNUMERIC": 1 ≤ precision ≤ 38. If scale is specified but not precision, then it is invalid.
+ "rangeElementType": { # Represents the type of a field element.
+ "type": "A String", # Required. The type of a field element. See TableFieldSchema.type.
},
- "roundingMode": "A String", # Optional. Rounding Mode specification of the field. It only can be set on NUMERIC or BIGNUMERIC type fields.
- "scale": "A String", # [Optional] See documentation for precision.
- "type": "A String", # [Required] The field data type. Possible values include STRING, BYTES, INTEGER, INT64 (same as INTEGER), FLOAT, FLOAT64 (same as FLOAT), NUMERIC, BIGNUMERIC, BOOLEAN, BOOL (same as BOOLEAN), TIMESTAMP, DATE, TIME, DATETIME, INTERVAL, RECORD (where RECORD indicates that the field contains a nested schema) or STRUCT (same as RECORD).
+ "roundingMode": "A String", # Optional. Specifies the rounding mode to be used when storing values of NUMERIC and BIGNUMERIC type.
+ "scale": "A String", # Optional. See documentation for precision.
+ "type": "A String", # Required. The field data type. Possible values include: * STRING * BYTES * INTEGER (or INT64) * FLOAT (or FLOAT64) * BOOLEAN (or BOOL) * TIMESTAMP * DATE * TIME * DATETIME * GEOGRAPHY * NUMERIC * BIGNUMERIC * JSON * RECORD (or STRUCT) Use of RECORD/STRUCT indicates that the field contains a nested schema.
},
],
},
- "selfLink": "A String", # [Output-only] A URL that can be used to access this resource again.
- "snapshotDefinition": { # [Output-only] Snapshot definition.
- "baseTableReference": { # [Required] Reference describing the ID of the table that was snapshot.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- },
- "snapshotTime": "A String", # [Required] The time at which the base table was snapshot. This value is reported in the JSON response using RFC3339 format.
- },
- "streamingBuffer": { # [Output-only] Contains information regarding this table's streaming buffer, if one is present. This field will be absent if the table is not being streamed to or if there is no data in the streaming buffer.
- "estimatedBytes": "A String", # [Output-only] A lower-bound estimate of the number of bytes currently in the streaming buffer.
- "estimatedRows": "A String", # [Output-only] A lower-bound estimate of the number of rows currently in the streaming buffer.
- "oldestEntryTime": "A String", # [Output-only] Contains the timestamp of the oldest entry in the streaming buffer, in milliseconds since the epoch, if the streaming buffer is available.
- },
- "tableConstraints": { # [Optional] The table constraints on the table.
- "foreignKeys": [ # [Optional] The foreign keys of the tables.
- {
- "columnReferences": [
- {
- "referencedColumn": "A String",
- "referencingColumn": "A String",
+ "selfLink": "A String", # Output only. A URL that can be used to access this resource again.
+ "snapshotDefinition": { # Information about base table and snapshot time of the snapshot. # Output only. Contains information about the snapshot. This value is set via snapshot creation.
+ "baseTableReference": { # Required. Reference describing the ID of the table that was snapshot.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ "snapshotTime": "A String", # Required. The time at which the base table was snapshot. This value is reported in the JSON response using RFC3339 format.
+ },
+ "streamingBuffer": { # Output only. Contains information regarding this table's streaming buffer, if one is present. This field will be absent if the table is not being streamed to or if there is no data in the streaming buffer.
+ "estimatedBytes": "A String", # Output only. A lower-bound estimate of the number of bytes currently in the streaming buffer.
+ "estimatedRows": "A String", # Output only. A lower-bound estimate of the number of rows currently in the streaming buffer.
+ "oldestEntryTime": "A String", # Output only. Contains the timestamp of the oldest entry in the streaming buffer, in milliseconds since the epoch, if the streaming buffer is available.
+ },
+ "tableConstraints": { # The TableConstraints defines the primary key and foreign key. # Optional. Tables Primary Key and Foreign Key information
+ "foreignKeys": [ # Optional. Present only if the table has a foreign key. The foreign key is not enforced.
+ { # Represents a foreign key constraint on a table's columns.
+ "columnReferences": [ # Required. The columns that compose the foreign key.
+ { # The pair of the foreign key column and primary key column.
+ "referencedColumn": "A String", # Required. The column in the primary key that are referenced by the referencing_column.
+ "referencingColumn": "A String", # Required. The column that composes the foreign key.
},
],
- "name": "A String",
+ "name": "A String", # Optional. Set only if the foreign key constraint is named.
"referencedTable": {
"datasetId": "A String",
"projectId": "A String",
@@ -2516,30 +2831,54 @@ Method Details
},
},
],
- "primaryKey": { # [Optional] The primary key of the table.
- "columns": [
+ "primaryKey": { # Represents the primary key constraint on a table's columns.
+ "columns": [ # Required. The columns that are composed of the primary key constraint.
"A String",
],
},
},
- "tableReference": { # [Required] Reference describing the ID of this table.
- "datasetId": "A String", # [Required] The ID of the dataset containing this table.
- "projectId": "A String", # [Required] The ID of the project containing this table.
- "tableId": "A String", # [Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.
- },
- "timePartitioning": { # Time-based partitioning specification for this table. Only one of timePartitioning and rangePartitioning should be specified.
- "expirationMs": "A String", # [Optional] Number of milliseconds for which to keep the storage for partitions in the table. The storage in a partition will have an expiration time of its partition time plus this value.
- "field": "A String", # [Beta] [Optional] If not set, the table is partitioned by pseudo column, referenced via either '_PARTITIONTIME' as TIMESTAMP type, or '_PARTITIONDATE' as DATE type. If field is specified, the table is instead partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED.
- "requirePartitionFilter": True or False,
- "type": "A String", # [Required] The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively. When the type is not specified, the default behavior is DAY.
- },
- "type": "A String", # [Output-only] Describes the table type. The following values are supported: TABLE: A normal BigQuery table. VIEW: A virtual table defined by a SQL query. SNAPSHOT: An immutable, read-only table that is a copy of another table. [TrustedTester] MATERIALIZED_VIEW: SQL query whose result is persisted. EXTERNAL: A table that references data stored in an external storage system, such as Google Cloud Storage. The default value is TABLE.
- "view": { # [Optional] The view definition.
- "query": "A String", # [Required] A query that BigQuery executes when the view is referenced.
- "useExplicitColumnNames": True or False, # True if the column names are explicitly specified. For example by using the 'CREATE VIEW v(c1, c2) AS ...' syntax. Can only be set using BigQuery's standard SQL: https://cloud.google.com/bigquery/sql-reference/
- "useLegacySql": True or False, # Specifies whether to use BigQuery's legacy SQL for this view. The default value is true. If set to false, the view will use BigQuery's standard SQL: https://cloud.google.com/bigquery/sql-reference/ Queries and views that reference this view must use the same flag value.
+ "tableReference": { # Required. Reference describing the ID of this table.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ "tableReplicationInfo": { # Replication info of a table created using `AS REPLICA` DDL like: `CREATE MATERIALIZED VIEW mv1 AS REPLICA OF src_mv` # Optional. Table replication info for table created `AS REPLICA` DDL like: `CREATE MATERIALIZED VIEW mv1 AS REPLICA OF src_mv`
+ "replicatedSourceLastRefreshTime": "A String", # Optional. Output only. If source is a materialized view, this field signifies the last refresh time of the source.
+ "replicationError": { # Error details. # Optional. Output only. Replication error that will permanently stopped table replication.
+ "debugInfo": "A String", # Debugging information. This property is internal to Google and should not be used.
+ "location": "A String", # Specifies where the error occurred, if present.
+ "message": "A String", # A human-readable description of the error.
+ "reason": "A String", # A short error code that summarizes the error.
+ },
+ "replicationIntervalMs": "A String", # Required. Specifies the interval at which the source table is polled for updates.
+ "replicationStatus": "A String", # Optional. Output only. Replication status of configured replication.
+ "sourceTable": { # Required. Source table reference that is replicated.
+ "datasetId": "A String", # Required. The ID of the dataset containing this table.
+ "projectId": "A String", # Required. The ID of the project containing this table.
+ "tableId": "A String", # Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.
+ },
+ },
+ "timePartitioning": { # If specified, configures time-based partitioning for this table.
+ "expirationMs": "A String", # Optional. Number of milliseconds for which to keep the storage for a partition. A wrapper is used here because 0 is an invalid value.
+ "field": "A String", # Optional. If not set, the table is partitioned by pseudo column '_PARTITIONTIME'; if set, the table is partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED. A wrapper is used here because an empty string is an invalid value.
+ "requirePartitionFilter": false, # If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. This field is deprecated; please set the field with the same name on the table itself instead. This field needs a wrapper because we want to output the default value, false, if the user explicitly set it.
+ "type": "A String", # Required. The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively.
+ },
+ "type": "A String", # Output only. Describes the table type. The following values are supported: * `TABLE`: A normal BigQuery table. * `VIEW`: A virtual table defined by a SQL query. * `EXTERNAL`: A table that references data stored in an external storage system, such as Google Cloud Storage. * `MATERIALIZED_VIEW`: A precomputed view defined by a SQL query. * `SNAPSHOT`: An immutable BigQuery table that preserves the contents of a base table at a particular time. See additional information on [table snapshots](/bigquery/docs/table-snapshots-intro). The default value is `TABLE`.
+ "view": { # Describes the definition of a logical view. # Optional. The view definition.
+ "privacyPolicy": { # Represents privacy policy that contains the privacy requirements specified by the data owner. Currently, this is only supported on views. # Optional. Specifices the privacy policy for the view.
+ "aggregationThresholdPolicy": { # Represents privacy policy associated with "aggregation threshold" method. # Optional. Policy used for aggregation thresholds.
+ "privacyUnitColumns": [ # Optional. The privacy unit column(s) associated with this policy. For now, only one column per data source object (table, view) is allowed as a privacy unit column. Representing as a repeated field in metadata for extensibility to multiple columns in future. Duplicates and Repeated struct fields are not allowed. For nested fields, use dot notation ("outer.inner")
+ "A String",
+ ],
+ "threshold": "A String", # Optional. The threshold for the "aggregation threshold" policy.
+ },
+ },
+ "query": "A String", # Required. A query that BigQuery executes when the view is referenced.
+ "useExplicitColumnNames": True or False, # True if the column names are explicitly specified. For example by using the 'CREATE VIEW v(c1, c2) AS ...' syntax. Can only be set for GoogleSQL views.
+ "useLegacySql": True or False, # Specifies whether to use BigQuery's legacy SQL for this view. The default value is true. If set to false, the view will use BigQuery's GoogleSQL: https://cloud.google.com/bigquery/sql-reference/ Queries and views that reference this view must use the same flag value. A wrapper is used here because the default value is True.
"userDefinedFunctionResources": [ # Describes user-defined function resources used in the query.
- { # This is used for defining User Defined Function (UDF) resources only when using legacy SQL. Users of Standard SQL should leverage either DDL (e.g. CREATE [TEMPORARY] FUNCTION ... ) or the Routines API to define UDF resources. For additional information on migrating, see: https://cloud.google.com/bigquery/docs/reference/standard-sql/migrating-from-legacy-sql#differences_in_user-defined_javascript_functions
+ { # This is used for defining User Defined Function (UDF) resources only when using legacy SQL. Users of GoogleSQL should leverage either DDL (e.g. CREATE [TEMPORARY] FUNCTION ... ) or the Routines API to define UDF resources. For additional information on migrating, see: https://cloud.google.com/bigquery/docs/reference/standard-sql/migrating-from-legacy-sql#differences_in_user-defined_javascript_functions
"inlineCode": "A String", # [Pick one] An inline resource that contains code for a user-defined function (UDF). Providing a inline code resource is equivalent to providing a URI for a file containing the same code.
"resourceUri": "A String", # [Pick one] A code resource to load from a Google Cloud Storage URI (gs://bucket/path).
},
diff --git a/googleapiclient/discovery_cache/documents/bigquery.v2.json b/googleapiclient/discovery_cache/documents/bigquery.v2.json
index 5a341023dad..cd56b43d7c4 100644
--- a/googleapiclient/discovery_cache/documents/bigquery.v2.json
+++ b/googleapiclient/discovery_cache/documents/bigquery.v2.json
@@ -29,12 +29,14 @@
"basePath": "/bigquery/v2/",
"baseUrl": "https://bigquery.googleapis.com/bigquery/v2/",
"batchPath": "batch/bigquery/v2",
+"canonicalName": "Bigquery",
"description": "A data platform for customers to create, manage, share and query data.",
"discoveryVersion": "v1",
"documentationLink": "https://cloud.google.com/bigquery/",
+"fullyEncodeReservedExpansion": true,
"icons": {
-"x16": "https://www.google.com/images/icons/product/search-16.gif",
-"x32": "https://www.google.com/images/icons/product/search-32.gif"
+"x16": "http://www.google.com/images/icons/product/search-16.gif",
+"x32": "http://www.google.com/images/icons/product/search-32.gif"
},
"id": "bigquery:v2",
"kind": "discovery#restDescription",
@@ -43,18 +45,45 @@
"ownerDomain": "google.com",
"ownerName": "Google",
"parameters": {
+"$.xgafv": {
+"description": "V1 error format.",
+"enum": [
+"1",
+"2"
+],
+"enumDescriptions": [
+"v1 error format",
+"v2 error format"
+],
+"location": "query",
+"type": "string"
+},
+"access_token": {
+"description": "OAuth access token.",
+"location": "query",
+"type": "string"
+},
"alt": {
"default": "json",
-"description": "Data format for the response.",
+"description": "Data format for response.",
"enum": [
-"json"
+"json",
+"media",
+"proto"
],
"enumDescriptions": [
-"Responses with Content-Type of application/json"
+"Responses with Content-Type of application/json",
+"Media download with context-dependent Content-Type",
+"Responses with Content-Type of application/x-protobuf"
],
"location": "query",
"type": "string"
},
+"callback": {
+"description": "JSONP",
+"location": "query",
+"type": "string"
+},
"fields": {
"description": "Selector specifying which fields to include in a partial response.",
"location": "query",
@@ -77,12 +106,17 @@
"type": "boolean"
},
"quotaUser": {
-"description": "An opaque string that represents a user for quota purposes. Must not exceed 40 characters.",
+"description": "Available to use for quota purposes for server-side applications. Can be any arbitrary string assigned to a user, but should not exceed 40 characters.",
+"location": "query",
+"type": "string"
+},
+"uploadType": {
+"description": "Legacy upload protocol for media (e.g. \"media\", \"multipart\").",
"location": "query",
"type": "string"
},
-"userIp": {
-"description": "Deprecated. Please use quotaUser instead.",
+"upload_protocol": {
+"description": "Upload protocol for media (e.g. \"raw\", \"multipart\").",
"location": "query",
"type": "string"
}
@@ -93,6 +127,7 @@
"methods": {
"delete": {
"description": "Deletes the dataset specified by the datasetId value. Before you can delete a dataset, you must delete all its tables, either manually or by specifying deleteContents. Immediately after deletion, you can create another dataset with the same name.",
+"flatPath": "projects/{projectsId}/datasets/{datasetsId}",
"httpMethod": "DELETE",
"id": "bigquery.datasets.delete",
"parameterOrder": [
@@ -101,8 +136,9 @@
],
"parameters": {
"datasetId": {
-"description": "Dataset ID of dataset being deleted",
+"description": "Required. Dataset ID of dataset being deleted",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
},
@@ -112,13 +148,14 @@
"type": "boolean"
},
"projectId": {
-"description": "Project ID of the dataset being deleted",
+"description": "Required. Project ID of the dataset being deleted",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
}
},
-"path": "projects/{projectId}/datasets/{datasetId}",
+"path": "projects/{+projectId}/datasets/{+datasetId}",
"scopes": [
"https://www.googleapis.com/auth/bigquery",
"https://www.googleapis.com/auth/cloud-platform"
@@ -126,6 +163,7 @@
},
"get": {
"description": "Returns the dataset specified by datasetID.",
+"flatPath": "projects/{projectsId}/datasets/{datasetsId}",
"httpMethod": "GET",
"id": "bigquery.datasets.get",
"parameterOrder": [
@@ -134,24 +172,38 @@
],
"parameters": {
"datasetId": {
-"description": "Dataset ID of the requested dataset",
+"description": "Required. Dataset ID of the requested dataset",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
},
"datasetView": {
-"description": "Specifies the view that determines which dataset information is returned. By default, metadata and ACL information are returned. Allowed values: METADATA, ACL, FULL.",
+"description": "Optional. Specifies the view that determines which dataset information is returned. By default, metadata and ACL information are returned.",
+"enum": [
+"DATASET_VIEW_UNSPECIFIED",
+"METADATA",
+"ACL",
+"FULL"
+],
+"enumDescriptions": [
+"The default value. Default to the FULL view.",
+"Includes metadata information for the dataset, such as location, etag, lastModifiedTime, etc.",
+"Includes ACL information for the dataset, which defines dataset access for one or more entities.",
+"Includes both dataset metadata and ACL information."
+],
"location": "query",
"type": "string"
},
"projectId": {
-"description": "Project ID of the requested dataset",
+"description": "Required. Project ID of the requested dataset",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
}
},
-"path": "projects/{projectId}/datasets/{datasetId}",
+"path": "projects/{+projectId}/datasets/{+datasetId}",
"response": {
"$ref": "Dataset"
},
@@ -163,6 +215,7 @@
},
"insert": {
"description": "Creates a new empty dataset.",
+"flatPath": "projects/{projectsId}/datasets",
"httpMethod": "POST",
"id": "bigquery.datasets.insert",
"parameterOrder": [
@@ -170,13 +223,14 @@
],
"parameters": {
"projectId": {
-"description": "Project ID of the new dataset",
+"description": "Required. Project ID of the new dataset",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
}
},
-"path": "projects/{projectId}/datasets",
+"path": "projects/{+projectId}/datasets",
"request": {
"$ref": "Dataset"
},
@@ -189,7 +243,8 @@
]
},
"list": {
-"description": "Lists all datasets in the specified project to which you have been granted the READER dataset role.",
+"description": "Lists all datasets in the specified project to which the user has been granted the READER dataset role.",
+"flatPath": "projects/{projectsId}/datasets",
"httpMethod": "GET",
"id": "bigquery.datasets.list",
"parameterOrder": [
@@ -202,12 +257,12 @@
"type": "boolean"
},
"filter": {
-"description": "An expression for filtering the results of the request by label. The syntax is \"labels.[:]\". Multiple filters can be ANDed together by connecting with a space. Example: \"labels.department:receiving labels.active\". See Filtering datasets using labels for details.",
+"description": "An expression for filtering the results of the request by label. The syntax is \\\"labels.[:]\\\". Multiple filters can be ANDed together by connecting with a space. Example: \\\"labels.department:receiving labels.active\\\". See [Filtering datasets using labels](/bigquery/docs/labeling-datasets#filtering_datasets_using_labels) for details.",
"location": "query",
"type": "string"
},
"maxResults": {
-"description": "The maximum number of results to return",
+"description": "The maximum number of results to return in a single response page. Leverage the page tokens to iterate through the entire collection.",
"format": "uint32",
"location": "query",
"type": "integer"
@@ -218,13 +273,14 @@
"type": "string"
},
"projectId": {
-"description": "Project ID of the datasets to be listed",
+"description": "Required. Project ID of the datasets to be listed",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
}
},
-"path": "projects/{projectId}/datasets",
+"path": "projects/{+projectId}/datasets",
"response": {
"$ref": "DatasetList"
},
@@ -235,7 +291,8 @@
]
},
"patch": {
-"description": "Updates information in an existing dataset. The update method replaces the entire dataset resource, whereas the patch method only replaces fields that are provided in the submitted dataset resource. This method supports patch semantics.",
+"description": "Updates information in an existing dataset. The update method replaces the entire dataset resource, whereas the patch method only replaces fields that are provided in the submitted dataset resource. This method supports RFC5789 patch semantics.",
+"flatPath": "projects/{projectsId}/datasets/{datasetsId}",
"httpMethod": "PATCH",
"id": "bigquery.datasets.patch",
"parameterOrder": [
@@ -244,19 +301,21 @@
],
"parameters": {
"datasetId": {
-"description": "Dataset ID of the dataset being updated",
+"description": "Required. Dataset ID of the dataset being updated",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
},
"projectId": {
-"description": "Project ID of the dataset being updated",
+"description": "Required. Project ID of the dataset being updated",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
}
},
-"path": "projects/{projectId}/datasets/{datasetId}",
+"path": "projects/{+projectId}/datasets/{+datasetId}",
"request": {
"$ref": "Dataset"
},
@@ -268,8 +327,46 @@
"https://www.googleapis.com/auth/cloud-platform"
]
},
+"undelete": {
+"description": "Undeletes a dataset which is within time travel window based on datasetId. If a time is specified, the dataset version deleted at that time is undeleted, else the last live version is undeleted.",
+"flatPath": "projects/{projectsId}/datasets/{datasetsId}:undelete",
+"httpMethod": "POST",
+"id": "bigquery.datasets.undelete",
+"parameterOrder": [
+"projectId",
+"datasetId"
+],
+"parameters": {
+"datasetId": {
+"description": "Required. Dataset ID of dataset being deleted",
+"location": "path",
+"pattern": "^[^/]+$",
+"required": true,
+"type": "string"
+},
+"projectId": {
+"description": "Required. Project ID of the dataset to be undeleted",
+"location": "path",
+"pattern": "^[^/]+$",
+"required": true,
+"type": "string"
+}
+},
+"path": "projects/{+projectId}/datasets/{+datasetId}:undelete",
+"request": {
+"$ref": "UndeleteDatasetRequest"
+},
+"response": {
+"$ref": "Dataset"
+},
+"scopes": [
+"https://www.googleapis.com/auth/bigquery",
+"https://www.googleapis.com/auth/cloud-platform"
+]
+},
"update": {
"description": "Updates information in an existing dataset. The update method replaces the entire dataset resource, whereas the patch method only replaces fields that are provided in the submitted dataset resource.",
+"flatPath": "projects/{projectsId}/datasets/{datasetsId}",
"httpMethod": "PUT",
"id": "bigquery.datasets.update",
"parameterOrder": [
@@ -278,19 +375,21 @@
],
"parameters": {
"datasetId": {
-"description": "Dataset ID of the dataset being updated",
+"description": "Required. Dataset ID of the dataset being updated",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
},
"projectId": {
-"description": "Project ID of the dataset being updated",
+"description": "Required. Project ID of the dataset being updated",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
}
},
-"path": "projects/{projectId}/datasets/{datasetId}",
+"path": "projects/{+projectId}/datasets/{+datasetId}",
"request": {
"$ref": "Dataset"
},
@@ -308,6 +407,7 @@
"methods": {
"cancel": {
"description": "Requests that a job be cancelled. This call will return immediately, and the client will need to poll for the job status to see if the cancel completed successfully. Cancelled jobs may still incur costs.",
+"flatPath": "projects/{projectsId}/jobs/{jobsId}/cancel",
"httpMethod": "POST",
"id": "bigquery.jobs.cancel",
"parameterOrder": [
@@ -316,24 +416,26 @@
],
"parameters": {
"jobId": {
-"description": "[Required] Job ID of the job to cancel",
+"description": "Required. Job ID of the job to cancel",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
},
"location": {
-"description": "The geographic location of the job. Required except for US and EU. See details at https://cloud.google.com/bigquery/docs/locations#specifying_your_location.",
+"description": "The geographic location of the job. You must specify the location to run the job for the following scenarios: - If the location to run a job is not in the `us` or the `eu` multi-regional location - If the job's location is in a single region (for example, `us-central1`) For more information, see https://cloud.google.com/bigquery/docs/locations#specifying_your_location.",
"location": "query",
"type": "string"
},
"projectId": {
-"description": "[Required] Project ID of the job to cancel",
+"description": "Required. Project ID of the job to cancel",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
}
},
-"path": "projects/{projectId}/jobs/{jobId}/cancel",
+"path": "projects/{+projectId}/jobs/{+jobId}/cancel",
"response": {
"$ref": "JobCancelResponse"
},
@@ -380,6 +482,7 @@
},
"get": {
"description": "Returns information about a specific job. Job information is available for a six month period after creation. Requires that you're the person who ran the job, or have the Is Owner project role.",
+"flatPath": "projects/{projectsId}/jobs/{jobsId}",
"httpMethod": "GET",
"id": "bigquery.jobs.get",
"parameterOrder": [
@@ -388,24 +491,26 @@
],
"parameters": {
"jobId": {
-"description": "[Required] Job ID of the requested job",
+"description": "Required. Job ID of the requested job.",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
},
"location": {
-"description": "The geographic location of the job. Required except for US and EU. See details at https://cloud.google.com/bigquery/docs/locations#specifying_your_location.",
+"description": "The geographic location of the job. You must specify the location to run the job for the following scenarios: - If the location to run a job is not in the `us` or the `eu` multi-regional location - If the job's location is in a single region (for example, `us-central1`) For more information, see https://cloud.google.com/bigquery/docs/locations#specifying_your_location.",
"location": "query",
"type": "string"
},
"projectId": {
-"description": "[Required] Project ID of the requested job",
+"description": "Required. Project ID of the requested job.",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
}
},
-"path": "projects/{projectId}/jobs/{jobId}",
+"path": "projects/{+projectId}/jobs/{+jobId}",
"response": {
"$ref": "Job"
},
@@ -416,7 +521,8 @@
]
},
"getQueryResults": {
-"description": "Retrieves the results of a query job.",
+"description": "RPC to get the results of a query job.",
+"flatPath": "projects/{projectsId}/queries/{queriesId}",
"httpMethod": "GET",
"id": "bigquery.jobs.getQueryResults",
"parameterOrder": [
@@ -424,48 +530,55 @@
"jobId"
],
"parameters": {
+"formatOptions.useInt64Timestamp": {
+"description": "Optional. Output timestamp as usec int64. Default is false.",
+"location": "query",
+"type": "boolean"
+},
"jobId": {
-"description": "[Required] Job ID of the query job",
+"description": "Required. Job ID of the query job.",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
},
"location": {
-"description": "The geographic location where the job should run. Required except for US and EU. See details at https://cloud.google.com/bigquery/docs/locations#specifying_your_location.",
+"description": "The geographic location of the job. You must specify the location to run the job for the following scenarios: - If the location to run a job is not in the `us` or the `eu` multi-regional location - If the job's location is in a single region (for example, `us-central1`) For more information, see https://cloud.google.com/bigquery/docs/locations#specifying_your_location.",
"location": "query",
"type": "string"
},
"maxResults": {
-"description": "Maximum number of results to read",
+"description": "Maximum number of results to read.",
"format": "uint32",
"location": "query",
"type": "integer"
},
"pageToken": {
-"description": "Page token, returned by a previous call, to request the next page of results",
+"description": "Page token, returned by a previous call, to request the next page of results.",
"location": "query",
"type": "string"
},
"projectId": {
-"description": "[Required] Project ID of the query job",
+"description": "Required. Project ID of the query job.",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
},
"startIndex": {
-"description": "Zero-based index of the starting row",
+"description": "Zero-based index of the starting row.",
"format": "uint64",
"location": "query",
"type": "string"
},
"timeoutMs": {
-"description": "How long to wait for the query to complete, in milliseconds, before returning. Default is 10 seconds. If the timeout passes before the job completes, the 'jobComplete' field in the response will be false",
+"description": "Optional: Specifies the maximum amount of time, in milliseconds, that the client is willing to wait for the query to complete. By default, this limit is 10 seconds (10,000 milliseconds). If the query is complete, the jobComplete field in the response is true. If the query has not yet completed, jobComplete is false. You can request a longer timeout period in the timeoutMs field. However, the call is not guaranteed to wait for the specified timeout; it typically returns after around 200 seconds (200,000 milliseconds), even if the query is not complete. If jobComplete is false, you can continue to wait for the query to complete by calling the getQueryResults method until the jobComplete field in the getQueryResults response is true.",
"format": "uint32",
"location": "query",
"type": "integer"
}
},
-"path": "projects/{projectId}/queries/{jobId}",
+"path": "projects/{+projectId}/queries/{+jobId}",
"response": {
"$ref": "GetQueryResultsResponse"
},
@@ -476,7 +589,8 @@
]
},
"insert": {
-"description": "Starts a new asynchronous job. Requires the Can View project role.",
+"description": "Starts a new asynchronous job. This API has two different kinds of endpoint URIs, as this method supports a variety of use cases. * The *Metadata* URI is used for most interactions, as it accepts the job configuration directly. * The *Upload* URI is ONLY for the case when you're sending both a load job configuration and a data stream together. In this case, the Upload URI accepts the job configuration and the data as two distinct multipart MIME parts.",
+"flatPath": "projects/{projectsId}/jobs",
"httpMethod": "POST",
"id": "bigquery.jobs.insert",
"mediaUpload": {
@@ -486,11 +600,11 @@
"protocols": {
"resumable": {
"multipart": true,
-"path": "/resumable/upload/bigquery/v2/projects/{projectId}/jobs"
+"path": "/resumable/upload/bigquery/v2/projects/{+projectId}/jobs"
},
"simple": {
"multipart": true,
-"path": "/upload/bigquery/v2/projects/{projectId}/jobs"
+"path": "/upload/bigquery/v2/projects/{+projectId}/jobs"
}
}
},
@@ -499,13 +613,14 @@
],
"parameters": {
"projectId": {
-"description": "Project ID of the project that will be billed for the job",
+"description": "Project ID of project that will be billed for the job.",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
}
},
-"path": "projects/{projectId}/jobs",
+"path": "projects/{+projectId}/jobs",
"request": {
"$ref": "Job"
},
@@ -523,6 +638,7 @@
},
"list": {
"description": "Lists all jobs that you started in the specified project. Job information is available for a six month period after creation. The job list is sorted in reverse chronological order, by job creation time. Requires the Can View project role, or the Is Owner project role if you set the allUsers property.",
+"flatPath": "projects/{projectsId}/jobs",
"httpMethod": "GET",
"id": "bigquery.jobs.list",
"parameterOrder": [
@@ -530,41 +646,42 @@
],
"parameters": {
"allUsers": {
-"description": "Whether to display jobs owned by all users in the project. Default false",
+"description": "Whether to display jobs owned by all users in the project. Default False.",
"location": "query",
"type": "boolean"
},
"maxCreationTime": {
-"description": "Max value for job creation time, in milliseconds since the POSIX epoch. If set, only jobs created before or at this timestamp are returned",
+"description": "Max value for job creation time, in milliseconds since the POSIX epoch. If set, only jobs created before or at this timestamp are returned.",
"format": "uint64",
"location": "query",
"type": "string"
},
"maxResults": {
-"description": "Maximum number of results to return",
+"description": "The maximum number of results to return in a single response page. Leverage the page tokens to iterate through the entire collection.",
"format": "uint32",
"location": "query",
"type": "integer"
},
"minCreationTime": {
-"description": "Min value for job creation time, in milliseconds since the POSIX epoch. If set, only jobs created after or at this timestamp are returned",
+"description": "Min value for job creation time, in milliseconds since the POSIX epoch. If set, only jobs created after or at this timestamp are returned.",
"format": "uint64",
"location": "query",
"type": "string"
},
"pageToken": {
-"description": "Page token, returned by a previous call, to request the next page of results",
+"description": "Page token, returned by a previous call, to request the next page of results.",
"location": "query",
"type": "string"
},
"parentJobId": {
-"description": "If set, retrieves only jobs whose parent is this job. Otherwise, retrieves only jobs which have no parent",
+"description": "If set, show only child jobs of the specified parent. Otherwise, show all top-level jobs.",
"location": "query",
"type": "string"
},
"projectId": {
-"description": "Project ID of the jobs to list",
+"description": "Project ID of the jobs to list.",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
},
@@ -598,7 +715,7 @@
"type": "string"
}
},
-"path": "projects/{projectId}/jobs",
+"path": "projects/{+projectId}/jobs",
"response": {
"$ref": "JobList"
},
@@ -610,6 +727,7 @@
},
"query": {
"description": "Runs a BigQuery SQL query synchronously and returns query results if the query completes within a specified timeout.",
+"flatPath": "projects/{projectsId}/queries",
"httpMethod": "POST",
"id": "bigquery.jobs.query",
"parameterOrder": [
@@ -617,13 +735,14 @@
],
"parameters": {
"projectId": {
-"description": "Project ID of the project billed for the query",
+"description": "Required. Project ID of the query request.",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
}
},
-"path": "projects/{projectId}/queries",
+"path": "projects/{+projectId}/queries",
"request": {
"$ref": "QueryRequest"
},
@@ -818,7 +937,8 @@
"projects": {
"methods": {
"getServiceAccount": {
-"description": "Returns the email address of the service account for your project used for interactions with Google Cloud KMS.",
+"description": "RPC to get the service account for a project used for interactions with Google Cloud KMS",
+"flatPath": "projects/{projectsId}/serviceAccount",
"httpMethod": "GET",
"id": "bigquery.projects.getServiceAccount",
"parameterOrder": [
@@ -826,13 +946,14 @@
],
"parameters": {
"projectId": {
-"description": "Project ID for which the service account is requested.",
+"description": "Required. ID of the project.",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
}
},
-"path": "projects/{projectId}/serviceAccount",
+"path": "projects/{+projectId}/serviceAccount",
"response": {
"$ref": "GetServiceAccountResponse"
},
@@ -843,18 +964,20 @@
]
},
"list": {
-"description": "Lists all projects to which you have been granted any project role.",
+"description": "RPC to list projects to which the user has been granted any project role. Users of this method are encouraged to consider the [Resource Manager](https://cloud.google.com/resource-manager/docs/) API, which provides the underlying data for this method and has more capabilities.",
+"flatPath": "projects",
"httpMethod": "GET",
"id": "bigquery.projects.list",
+"parameterOrder": [],
"parameters": {
"maxResults": {
-"description": "Maximum number of results to return",
+"description": "`maxResults` unset returns all results, up to 50 per page. Additionally, the number of projects in a page may be fewer than `maxResults` because projects are retrieved and then filtered to only projects with the BigQuery API enabled.",
"format": "uint32",
"location": "query",
"type": "integer"
},
"pageToken": {
-"description": "Page token, returned by a previous call, to request the next page of results",
+"description": "Page token, returned by a previous call, to request the next page of results. If not present, no further pages are present.",
"location": "query",
"type": "string"
}
@@ -1223,7 +1346,8 @@
"tabledata": {
"methods": {
"insertAll": {
-"description": "Streams data into BigQuery one record at a time without needing to run a load job. Requires the WRITER dataset role.",
+"description": "Streams data into BigQuery one record at a time without needing to run a load job.",
+"flatPath": "projects/{projectsId}/datasets/{datasetsId}/tables/{tablesId}/insertAll",
"httpMethod": "POST",
"id": "bigquery.tabledata.insertAll",
"parameterOrder": [
@@ -1233,25 +1357,28 @@
],
"parameters": {
"datasetId": {
-"description": "Dataset ID of the destination table.",
+"description": "Required. Dataset ID of the destination.",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
},
"projectId": {
-"description": "Project ID of the destination table.",
+"description": "Required. Project ID of the destination.",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
},
"tableId": {
-"description": "Table ID of the destination table.",
+"description": "Required. Table ID of the destination.",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
}
},
-"path": "projects/{projectId}/datasets/{datasetId}/tables/{tableId}/insertAll",
+"path": "projects/{+projectId}/datasets/{+datasetId}/tables/{+tableId}/insertAll",
"request": {
"$ref": "TableDataInsertAllRequest"
},
@@ -1265,7 +1392,8 @@
]
},
"list": {
-"description": "Retrieves table data from a specified set of rows. Requires the READER dataset role.",
+"description": "List the content of a table in rows.",
+"flatPath": "projects/{projectsId}/datasets/{datasetsId}/tables/{tablesId}/data",
"httpMethod": "GET",
"id": "bigquery.tabledata.list",
"parameterOrder": [
@@ -1275,47 +1403,55 @@
],
"parameters": {
"datasetId": {
-"description": "Dataset ID of the table to read",
+"description": "Required. Dataset id of the table to list.",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
},
+"formatOptions.useInt64Timestamp": {
+"description": "Optional. Output timestamp as usec int64. Default is false.",
+"location": "query",
+"type": "boolean"
+},
"maxResults": {
-"description": "Maximum number of results to return",
+"description": "Row limit of the table.",
"format": "uint32",
"location": "query",
"type": "integer"
},
"pageToken": {
-"description": "Page token, returned by a previous call, identifying the result set",
+"description": "To retrieve the next page of table data, set this field to the string provided in the pageToken field of the response body from your previous call to tabledata.list.",
"location": "query",
"type": "string"
},
"projectId": {
-"description": "Project ID of the table to read",
+"description": "Required. Project id of the table to list.",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
},
"selectedFields": {
-"description": "List of fields to return (comma-separated). If unspecified, all fields are returned",
+"description": "Subset of fields to return, supports select into sub fields. Example: selected_fields = \"a,e.d.f\";",
"location": "query",
"type": "string"
},
"startIndex": {
-"description": "Zero-based index of the starting row to read",
+"description": "Start row index of the table.",
"format": "uint64",
"location": "query",
"type": "string"
},
"tableId": {
-"description": "Table ID of the table to read",
+"description": "Required. Table id of the table to list.",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
}
},
-"path": "projects/{projectId}/datasets/{datasetId}/tables/{tableId}/data",
+"path": "projects/{+projectId}/datasets/{+datasetId}/tables/{+tableId}/data",
"response": {
"$ref": "TableDataList"
},
@@ -1331,6 +1467,7 @@
"methods": {
"delete": {
"description": "Deletes the table specified by tableId from the dataset. If the table contains data, all the data will be deleted.",
+"flatPath": "projects/{projectsId}/datasets/{datasetsId}/tables/{tablesId}",
"httpMethod": "DELETE",
"id": "bigquery.tables.delete",
"parameterOrder": [
@@ -1340,25 +1477,28 @@
],
"parameters": {
"datasetId": {
-"description": "Dataset ID of the table to delete",
+"description": "Required. Dataset ID of the table to delete",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
},
"projectId": {
-"description": "Project ID of the table to delete",
+"description": "Required. Project ID of the table to delete",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
},
"tableId": {
-"description": "Table ID of the table to delete",
+"description": "Required. Table ID of the table to delete",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
}
},
-"path": "projects/{projectId}/datasets/{datasetId}/tables/{tableId}",
+"path": "projects/{+projectId}/datasets/{+datasetId}/tables/{+tableId}",
"scopes": [
"https://www.googleapis.com/auth/bigquery",
"https://www.googleapis.com/auth/cloud-platform"
@@ -1366,6 +1506,7 @@
},
"get": {
"description": "Gets the specified table resource by table ID. This method does not return the data in the table, it only returns the table resource, which describes the structure of this table.",
+"flatPath": "projects/{projectsId}/datasets/{datasetsId}/tables/{tablesId}",
"httpMethod": "GET",
"id": "bigquery.tables.get",
"parameterOrder": [
@@ -1375,47 +1516,50 @@
],
"parameters": {
"datasetId": {
-"description": "Dataset ID of the requested table",
+"description": "Required. Dataset ID of the requested table",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
},
"projectId": {
-"description": "Project ID of the requested table",
+"description": "Required. Project ID of the requested table",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
},
"selectedFields": {
-"description": "List of fields to return (comma-separated). If unspecified, all fields are returned",
+"description": "List of table schema fields to return (comma-separated). If unspecified, all fields are returned. A fieldMask cannot be used here because the fields will automatically be converted from camelCase to snake_case and the conversion will fail if there are underscores. Since these are fields in BigQuery table schemas, underscores are allowed.",
"location": "query",
"type": "string"
},
"tableId": {
-"description": "Table ID of the requested table",
+"description": "Required. Table ID of the requested table",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
},
"view": {
-"description": "Specifies the view that determines which table information is returned. By default, basic table information and storage statistics (STORAGE_STATS) are returned.",
+"description": "Optional. Specifies the view that determines which table information is returned. By default, basic table information and storage statistics (STORAGE_STATS) are returned.",
"enum": [
+"TABLE_METADATA_VIEW_UNSPECIFIED",
"BASIC",
-"FULL",
"STORAGE_STATS",
-"TABLE_METADATA_VIEW_UNSPECIFIED"
+"FULL"
],
"enumDescriptions": [
+"The default value. Default to the STORAGE_STATS view.",
"Includes basic table information including schema and partitioning specification. This view does not include storage statistics such as numRows or numBytes. This view is significantly more efficient and should be used to support high query rates.",
-"Includes all table information, including storage statistics. It returns same information as STORAGE_STATS view, but may contain additional information in the future.",
"Includes all information in the BASIC view as well as storage statistics (numBytes, numLongTermBytes, numRows and lastModifiedTime).",
-"The default value. Default to the STORAGE_STATS view."
+"Includes all table information, including storage statistics. It returns same information as STORAGE_STATS view, but may contain additional information in the future."
],
"location": "query",
"type": "string"
}
},
-"path": "projects/{projectId}/datasets/{datasetId}/tables/{tableId}",
+"path": "projects/{+projectId}/datasets/{+datasetId}/tables/{+tableId}",
"response": {
"$ref": "Table"
},
@@ -1457,6 +1601,7 @@
},
"insert": {
"description": "Creates a new, empty table in the dataset.",
+"flatPath": "projects/{projectsId}/datasets/{datasetsId}/tables",
"httpMethod": "POST",
"id": "bigquery.tables.insert",
"parameterOrder": [
@@ -1465,19 +1610,21 @@
],
"parameters": {
"datasetId": {
-"description": "Dataset ID of the new table",
+"description": "Required. Dataset ID of the new table",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
},
"projectId": {
-"description": "Project ID of the new table",
+"description": "Required. Project ID of the new table",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
}
},
-"path": "projects/{projectId}/datasets/{datasetId}/tables",
+"path": "projects/{+projectId}/datasets/{+datasetId}/tables",
"request": {
"$ref": "Table"
},
@@ -1491,6 +1638,7 @@
},
"list": {
"description": "Lists all tables in the specified dataset. Requires the READER dataset role.",
+"flatPath": "projects/{projectsId}/datasets/{datasetsId}/tables",
"httpMethod": "GET",
"id": "bigquery.tables.list",
"parameterOrder": [
@@ -1499,13 +1647,14 @@
],
"parameters": {
"datasetId": {
-"description": "Dataset ID of the tables to list",
+"description": "Required. Dataset ID of the tables to list",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
},
"maxResults": {
-"description": "Maximum number of results to return",
+"description": "The maximum number of results to return in a single response page. Leverage the page tokens to iterate through the entire collection.",
"format": "uint32",
"location": "query",
"type": "integer"
@@ -1516,13 +1665,14 @@
"type": "string"
},
"projectId": {
-"description": "Project ID of the tables to list",
+"description": "Required. Project ID of the tables to list",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
}
},
-"path": "projects/{projectId}/datasets/{datasetId}/tables",
+"path": "projects/{+projectId}/datasets/{+datasetId}/tables",
"response": {
"$ref": "TableList"
},
@@ -1533,7 +1683,8 @@
]
},
"patch": {
-"description": "Updates information in an existing table. The update method replaces the entire table resource, whereas the patch method only replaces fields that are provided in the submitted table resource. This method supports patch semantics.",
+"description": "Updates information in an existing table. The update method replaces the entire table resource, whereas the patch method only replaces fields that are provided in the submitted table resource. This method supports RFC5789 patch semantics.",
+"flatPath": "projects/{projectsId}/datasets/{datasetsId}/tables/{tablesId}",
"httpMethod": "PATCH",
"id": "bigquery.tables.patch",
"parameterOrder": [
@@ -1543,30 +1694,33 @@
],
"parameters": {
"autodetect_schema": {
-"description": "When true will autodetect schema, else will keep original schema",
+"description": "Optional. When true will autodetect schema, else will keep original schema",
"location": "query",
"type": "boolean"
},
"datasetId": {
-"description": "Dataset ID of the table to update",
+"description": "Required. Dataset ID of the table to update",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
},
"projectId": {
-"description": "Project ID of the table to update",
+"description": "Required. Project ID of the table to update",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
},
"tableId": {
-"description": "Table ID of the table to update",
+"description": "Required. Table ID of the table to update",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
}
},
-"path": "projects/{projectId}/datasets/{datasetId}/tables/{tableId}",
+"path": "projects/{+projectId}/datasets/{+datasetId}/tables/{+tableId}",
"request": {
"$ref": "Table"
},
@@ -1638,7 +1792,8 @@
]
},
"update": {
-"description": "Updates information in an existing table. The update method replaces the entire table resource, whereas the patch method only replaces fields that are provided in the submitted table resource.",
+"description": "Updates information in an existing table. The update method replaces the entire Table resource, whereas the patch method only replaces fields that are provided in the submitted Table resource.",
+"flatPath": "projects/{projectsId}/datasets/{datasetsId}/tables/{tablesId}",
"httpMethod": "PUT",
"id": "bigquery.tables.update",
"parameterOrder": [
@@ -1648,30 +1803,33 @@
],
"parameters": {
"autodetect_schema": {
-"description": "When true will autodetect schema, else will keep original schema",
+"description": "Optional. When true will autodetect schema, else will keep original schema",
"location": "query",
"type": "boolean"
},
"datasetId": {
-"description": "Dataset ID of the table to update",
+"description": "Required. Dataset ID of the table to update",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
},
"projectId": {
-"description": "Project ID of the table to update",
+"description": "Required. Project ID of the table to update",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
},
"tableId": {
-"description": "Table ID of the table to update",
+"description": "Required. Table ID of the table to update",
"location": "path",
+"pattern": "^[^/]+$",
"required": true,
"type": "string"
}
},
-"path": "projects/{projectId}/datasets/{datasetId}/tables/{tableId}",
+"path": "projects/{+projectId}/datasets/{+datasetId}/tables/{+tableId}",
"request": {
"$ref": "Table"
},
@@ -1686,7 +1844,7 @@
}
}
},
-"revision": "20240105",
+"revision": "20240124",
"rootUrl": "https://bigquery.googleapis.com/",
"schemas": {
"AggregateClassificationMetrics": {
@@ -2169,42 +2327,89 @@
"type": "object"
},
"AvroOptions": {
+"description": "Options for external data sources.",
"id": "AvroOptions",
"properties": {
"useAvroLogicalTypes": {
-"description": "[Optional] If sourceFormat is set to \"AVRO\", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER).",
+"description": "Optional. If sourceFormat is set to \"AVRO\", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER).",
"type": "boolean"
}
},
"type": "object"
},
"BiEngineReason": {
+"description": "Reason why BI Engine didn't accelerate the query (or sub-query).",
"id": "BiEngineReason",
"properties": {
"code": {
-"default": "",
-"description": "[Output-only] High-level BI Engine reason for partial or disabled acceleration.",
+"description": "Output only. High-level BI Engine reason for partial or disabled acceleration",
+"enum": [
+"CODE_UNSPECIFIED",
+"NO_RESERVATION",
+"INSUFFICIENT_RESERVATION",
+"UNSUPPORTED_SQL_TEXT",
+"INPUT_TOO_LARGE",
+"OTHER_REASON",
+"TABLE_EXCLUDED"
+],
+"enumDescriptions": [
+"BiEngineReason not specified.",
+"No reservation available for BI Engine acceleration.",
+"Not enough memory available for BI Engine acceleration.",
+"This particular SQL text is not supported for acceleration by BI Engine.",
+"Input too large for acceleration by BI Engine.",
+"Catch-all code for all other cases for partial or disabled acceleration.",
+"One or more tables were not eligible for BI Engine acceleration."
+],
+"readOnly": true,
"type": "string"
},
"message": {
-"default": "",
-"description": "[Output-only] Free form human-readable reason for partial or disabled acceleration.",
+"description": "Output only. Free form human-readable reason for partial or disabled acceleration.",
+"readOnly": true,
"type": "string"
}
},
"type": "object"
},
"BiEngineStatistics": {
+"description": "Statistics for a BI Engine specific query. Populated as part of JobStatistics2",
"id": "BiEngineStatistics",
"properties": {
"accelerationMode": {
-"default": "",
-"description": "[Output-only] Specifies which mode of BI Engine acceleration was performed (if any).",
+"description": "Output only. Specifies which mode of BI Engine acceleration was performed (if any).",
+"enum": [
+"BI_ENGINE_ACCELERATION_MODE_UNSPECIFIED",
+"BI_ENGINE_DISABLED",
+"PARTIAL_INPUT",
+"FULL_INPUT",
+"FULL_QUERY"
+],
+"enumDescriptions": [
+"BiEngineMode type not specified.",
+"BI Engine acceleration was attempted but disabled. bi_engine_reasons specifies a more detailed reason.",
+"Some inputs were accelerated using BI Engine. See bi_engine_reasons for why parts of the query were not accelerated.",
+"All of the query inputs were accelerated using BI Engine.",
+"All of the query was accelerated using BI Engine."
+],
+"readOnly": true,
"type": "string"
},
"biEngineMode": {
-"default": "",
-"description": "[Output-only] Specifies which mode of BI Engine acceleration was performed (if any).",
+"description": "Output only. Specifies which mode of BI Engine acceleration was performed (if any).",
+"enum": [
+"ACCELERATION_MODE_UNSPECIFIED",
+"DISABLED",
+"PARTIAL",
+"FULL"
+],
+"enumDescriptions": [
+"BiEngineMode type not specified.",
+"BI Engine disabled the acceleration. bi_engine_reasons specifies a more detailed reason.",
+"Part of the query was accelerated using BI Engine. See bi_engine_reasons for why parts of the query were not accelerated.",
+"All of the query was accelerated using BI Engine."
+],
+"readOnly": true,
"type": "string"
},
"biEngineReasons": {
@@ -2218,22 +2423,39 @@
"type": "object"
},
"BigLakeConfiguration": {
+"description": "Configuration for BigLake managed tables.",
"id": "BigLakeConfiguration",
"properties": {
"connectionId": {
-"description": "[Required] Required and immutable. Credential reference for accessing external storage system. Normalized as project_id.location_id.connection_id.",
+"description": "Required. The connection specifying the credentials to be used to read and write to external storage, such as Cloud Storage. The connection_id can have the form \"..\" or \"projects//locations//connections/\".",
"type": "string"
},
"fileFormat": {
-"description": "[Required] Required and immutable. Open source file format that the table data is stored in. Currently only PARQUET is supported.",
+"description": "Required. The file format the table data is stored in.",
+"enum": [
+"FILE_FORMAT_UNSPECIFIED",
+"PARQUET"
+],
+"enumDescriptions": [
+"Default Value.",
+"Apache Parquet format."
+],
"type": "string"
},
"storageUri": {
-"description": "[Required] Required and immutable. Fully qualified location prefix of the external folder where data is stored. Normalized to standard format: \"gs:////\". Starts with \"gs://\" rather than \"/bigstore/\". Ends with \"/\". Does not contain \"*\". See also BigLakeStorageMetadata on how it is used.",
+"description": "Required. The fully qualified location prefix of the external folder where table data is stored. The '*' wildcard character is not allowed. The URI should be in the format \"gs://bucket/path_to_table/\"",
"type": "string"
},
"tableFormat": {
-"description": "[Required] Required and immutable. Open source file format that the table data is stored in. Currently only PARQUET is supported.",
+"description": "Required. The table format the metadata only snapshots are stored in.",
+"enum": [
+"TABLE_FORMAT_UNSPECIFIED",
+"ICEBERG"
+],
+"enumDescriptions": [
+"Default Value.",
+"Apache Iceberg format."
+],
"type": "string"
}
},
@@ -2243,12 +2465,12 @@
"id": "BigQueryModelTraining",
"properties": {
"currentIteration": {
-"description": "[Output-only, Beta] Index of current ML training iteration. Updated during create model query job to show job progress.",
+"description": "Deprecated.",
"format": "int32",
"type": "integer"
},
"expectedTotalIterations": {
-"description": "[Output-only, Beta] Expected number of iterations for the create model query job specified as num_iterations in the input query. The actual total number of iterations may be less than this number due to early stop.",
+"description": "Deprecated.",
"format": "int64",
"type": "string"
}
@@ -2256,47 +2478,50 @@
"type": "object"
},
"BigtableColumn": {
+"description": "Information related to a Bigtable column.",
"id": "BigtableColumn",
"properties": {
"encoding": {
-"description": "[Optional] The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. 'encoding' can also be set at the column family level. However, the setting at this level takes precedence if 'encoding' is set at both levels.",
+"description": "Optional. The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. 'encoding' can also be set at the column family level. However, the setting at this level takes precedence if 'encoding' is set at both levels.",
"type": "string"
},
"fieldName": {
-"description": "[Optional] If the qualifier is not a valid BigQuery field identifier i.e. does not match [a-zA-Z][a-zA-Z0-9_]*, a valid identifier must be provided as the column field name and is used as field name in queries.",
+"description": "Optional. If the qualifier is not a valid BigQuery field identifier i.e. does not match a-zA-Z*, a valid identifier must be provided as the column field name and is used as field name in queries.",
"type": "string"
},
"onlyReadLatest": {
-"description": "[Optional] If this is set, only the latest version of value in this column are exposed. 'onlyReadLatest' can also be set at the column family level. However, the setting at this level takes precedence if 'onlyReadLatest' is set at both levels.",
+"description": "Optional. If this is set, only the latest version of value in this column are exposed. 'onlyReadLatest' can also be set at the column family level. However, the setting at this level takes precedence if 'onlyReadLatest' is set at both levels.",
"type": "boolean"
},
"qualifierEncoded": {
-"description": "[Required] Qualifier of the column. Columns in the parent column family that has this exact qualifier are exposed as . field. If the qualifier is valid UTF-8 string, it can be specified in the qualifier_string field. Otherwise, a base-64 encoded value must be set to qualifier_encoded. The column field name is the same as the column qualifier. However, if the qualifier is not a valid BigQuery field identifier i.e. does not match [a-zA-Z][a-zA-Z0-9_]*, a valid identifier must be provided as field_name.",
+"description": "[Required] Qualifier of the column. Columns in the parent column family that has this exact qualifier are exposed as . field. If the qualifier is valid UTF-8 string, it can be specified in the qualifier_string field. Otherwise, a base-64 encoded value must be set to qualifier_encoded. The column field name is the same as the column qualifier. However, if the qualifier is not a valid BigQuery field identifier i.e. does not match a-zA-Z*, a valid identifier must be provided as field_name.",
"format": "byte",
"type": "string"
},
"qualifierString": {
+"description": "Qualifier string.",
"type": "string"
},
"type": {
-"description": "[Optional] The type to convert the value in cells of this column. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive) - BYTES STRING INTEGER FLOAT BOOLEAN Default type is BYTES. 'type' can also be set at the column family level. However, the setting at this level takes precedence if 'type' is set at both levels.",
+"description": "Optional. The type to convert the value in cells of this column. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive): * BYTES * STRING * INTEGER * FLOAT * BOOLEAN * JSON Default type is BYTES. 'type' can also be set at the column family level. However, the setting at this level takes precedence if 'type' is set at both levels.",
"type": "string"
}
},
"type": "object"
},
"BigtableColumnFamily": {
+"description": "Information related to a Bigtable column family.",
"id": "BigtableColumnFamily",
"properties": {
"columns": {
-"description": "[Optional] Lists of columns that should be exposed as individual fields as opposed to a list of (column name, value) pairs. All columns whose qualifier matches a qualifier in this list can be accessed as .. Other columns can be accessed as a list through .Column field.",
+"description": "Optional. Lists of columns that should be exposed as individual fields as opposed to a list of (column name, value) pairs. All columns whose qualifier matches a qualifier in this list can be accessed as .. Other columns can be accessed as a list through .Column field.",
"items": {
"$ref": "BigtableColumn"
},
"type": "array"
},
"encoding": {
-"description": "[Optional] The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. This can be overridden for a specific column by listing that column in 'columns' and specifying an encoding for it.",
+"description": "Optional. The encoding of the values when the type is not STRING. Acceptable encoding values are: TEXT - indicates values are alphanumeric text strings. BINARY - indicates values are encoded using HBase Bytes.toBytes family of functions. This can be overridden for a specific column by listing that column in 'columns' and specifying an encoding for it.",
"type": "string"
},
"familyId": {
@@ -2304,32 +2529,37 @@
"type": "string"
},
"onlyReadLatest": {
-"description": "[Optional] If this is set only the latest version of value are exposed for all columns in this column family. This can be overridden for a specific column by listing that column in 'columns' and specifying a different setting for that column.",
+"description": "Optional. If this is set only the latest version of value are exposed for all columns in this column family. This can be overridden for a specific column by listing that column in 'columns' and specifying a different setting for that column.",
"type": "boolean"
},
"type": {
-"description": "[Optional] The type to convert the value in cells of this column family. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive) - BYTES STRING INTEGER FLOAT BOOLEAN Default type is BYTES. This can be overridden for a specific column by listing that column in 'columns' and specifying a type for it.",
+"description": "Optional. The type to convert the value in cells of this column family. The values are expected to be encoded using HBase Bytes.toBytes function when using the BINARY encoding value. Following BigQuery types are allowed (case-sensitive): * BYTES * STRING * INTEGER * FLOAT * BOOLEAN * JSON Default type is BYTES. This can be overridden for a specific column by listing that column in 'columns' and specifying a type for it.",
"type": "string"
}
},
"type": "object"
},
"BigtableOptions": {
+"description": "Options specific to Google Cloud Bigtable data sources.",
"id": "BigtableOptions",
"properties": {
"columnFamilies": {
-"description": "[Optional] List of column families to expose in the table schema along with their types. This list restricts the column families that can be referenced in queries and specifies their value types. You can use this list to do type conversions - see the 'type' field for more details. If you leave this list empty, all column families are present in the table schema and their values are read as BYTES. During a query only the column families referenced in that query are read from Bigtable.",
+"description": "Optional. List of column families to expose in the table schema along with their types. This list restricts the column families that can be referenced in queries and specifies their value types. You can use this list to do type conversions - see the 'type' field for more details. If you leave this list empty, all column families are present in the table schema and their values are read as BYTES. During a query only the column families referenced in that query are read from Bigtable.",
"items": {
"$ref": "BigtableColumnFamily"
},
"type": "array"
},
"ignoreUnspecifiedColumnFamilies": {
-"description": "[Optional] If field is true, then the column families that are not specified in columnFamilies list are not exposed in the table schema. Otherwise, they are read with BYTES type values. The default value is false.",
+"description": "Optional. If field is true, then the column families that are not specified in columnFamilies list are not exposed in the table schema. Otherwise, they are read with BYTES type values. The default value is false.",
+"type": "boolean"
+},
+"outputColumnFamiliesAsJson": {
+"description": "Optional. If field is true, then each column family will be read as a single JSON column. Otherwise they are read as a repeated cell structure containing timestamp/value tuples. The default value is false.",
"type": "boolean"
},
"readRowkeyAsString": {
-"description": "[Optional] If field is true, then the rowkey column families will be read and converted to string. Otherwise they are read with BYTES type values and users need to manually cast them with CAST if necessary. The default value is false.",
+"description": "Optional. If field is true, then the rowkey column families will be read and converted to string. Otherwise they are read with BYTES type values and users need to manually cast them with CAST if necessary. The default value is false.",
"type": "boolean"
}
},
@@ -2429,7 +2659,7 @@
"type": "array"
},
"role": {
-"description": "Role that is assigned to the list of `members`, or principals. For example, `roles/viewer`, `roles/editor`, or `roles/owner`.",
+"description": "Role that is assigned to the list of `members`, or principals. For example, `roles/viewer`, `roles/editor`, or `roles/owner`. For an overview of the IAM roles and permissions, see the [IAM documentation](https://cloud.google.com/iam/docs/roles-overview). For a list of the available pre-defined roles, see [here](https://cloud.google.com/iam/docs/understanding-roles).",
"type": "string"
}
},
@@ -2439,27 +2669,27 @@
"id": "BqmlIterationResult",
"properties": {
"durationMs": {
-"description": "[Output-only, Beta] Time taken to run the training iteration in milliseconds.",
+"description": "Deprecated.",
"format": "int64",
"type": "string"
},
"evalLoss": {
-"description": "[Output-only, Beta] Eval loss computed on the eval data at the end of the iteration. The eval loss is used for early stopping to avoid overfitting. No eval loss if eval_split_method option is specified as no_split or auto_split with input data size less than 500 rows.",
+"description": "Deprecated.",
"format": "double",
"type": "number"
},
"index": {
-"description": "[Output-only, Beta] Index of the ML training iteration, starting from zero for each training run.",
+"description": "Deprecated.",
"format": "int32",
"type": "integer"
},
"learnRate": {
-"description": "[Output-only, Beta] Learning rate used for this iteration, it varies for different training iterations if learn_rate_strategy option is not constant.",
+"description": "Deprecated.",
"format": "double",
"type": "number"
},
"trainingLoss": {
-"description": "[Output-only, Beta] Training loss computed on the training data at the end of the iteration. The training loss function is defined by model type.",
+"description": "Deprecated.",
"format": "double",
"type": "number"
}
@@ -2470,23 +2700,23 @@
"id": "BqmlTrainingRun",
"properties": {
"iterationResults": {
-"description": "[Output-only, Beta] List of each iteration results.",
+"description": "Deprecated.",
"items": {
"$ref": "BqmlIterationResult"
},
"type": "array"
},
"startTime": {
-"description": "[Output-only, Beta] Training run start time in milliseconds since the epoch.",
+"description": "Deprecated.",
"format": "date-time",
"type": "string"
},
"state": {
-"description": "[Output-only, Beta] Different state applicable for a training run. IN PROGRESS: Training run is in progress. FAILED: Training run ended due to a non-retryable failure. SUCCEEDED: Training run successfully completed. CANCELLED: Training run cancelled by the user.",
+"description": "Deprecated.",
"type": "string"
},
"trainingOptions": {
-"description": "[Output-only, Beta] Training options used by this training run. These options are mutable for subsequent training runs. Default values are explicitly stored for options not specified in the input query of the first training run. For subsequent training runs, any option not explicitly specified in the input query will be copied from the previous training run.",
+"description": "Deprecated.",
"properties": {
"earlyStop": {
"type": "boolean"
@@ -2558,14 +2788,15 @@
"type": "object"
},
"CloneDefinition": {
+"description": "Information about base table and clone time of a table clone.",
"id": "CloneDefinition",
"properties": {
"baseTableReference": {
"$ref": "TableReference",
-"description": "[Required] Reference describing the ID of the table that was cloned."
+"description": "Required. Reference describing the ID of the table that was cloned."
},
"cloneTime": {
-"description": "[Required] The time at which the base table was cloned. This value is reported in the JSON response using RFC3339 format.",
+"description": "Required. The time at which the base table was cloned. This value is reported in the JSON response using RFC3339 format.",
"format": "date-time",
"type": "string"
}
@@ -2619,10 +2850,11 @@
"type": "object"
},
"Clustering": {
+"description": "Configures table clustering.",
"id": "Clustering",
"properties": {
"fields": {
-"description": "[Repeated] One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. When you cluster a table using multiple columns, the order of columns you specify is important. The order of the specified columns determines the sort order of the data.",
+"description": "One or more fields on which data should be clustered. Only top-level, non-repeated, simple-type fields are supported. The ordering of the clustering fields should be prioritized from most to least important for filtering purposes. Additional information on limitations can be found here: https://cloud.google.com/bigquery/docs/creating-clustered-tables#limitations",
"items": {
"type": "string"
},
@@ -2675,66 +2907,79 @@
"type": "object"
},
"ConnectionProperty": {
+"description": "A connection-level property to customize query behavior. Under JDBC, these correspond directly to connection properties passed to the DriverManager. Under ODBC, these correspond to properties in the connection string. Currently supported connection properties: * **dataset_project_id**: represents the default project for datasets that are used in the query. Setting the system variable `@@dataset_project_id` achieves the same behavior. For more information about system variables, see: https://cloud.google.com/bigquery/docs/reference/system-variables * **time_zone**: represents the default timezone used to run the query. * **session_id**: associates the query with a given session. * **query_label**: associates the query with a given job label. If set, all subsequent queries in a script or session will have this label. For the format in which a you can specify a query label, see labels in the JobConfiguration resource type: https://cloud.google.com/bigquery/docs/reference/rest/v2/Job#jobconfiguration Additional properties are allowed, but ignored. Specifying multiple connection properties with the same key returns an error.",
"id": "ConnectionProperty",
"properties": {
"key": {
-"description": "[Required] Name of the connection property to set.",
+"description": "The key of the property to set.",
"type": "string"
},
"value": {
-"description": "[Required] Value of the connection property.",
+"description": "The value of the property to set.",
"type": "string"
}
},
"type": "object"
},
"CsvOptions": {
+"description": "Information related to a CSV data source.",
"id": "CsvOptions",
"properties": {
"allowJaggedRows": {
-"description": "[Optional] Indicates if BigQuery should accept rows that are missing trailing optional columns. If true, BigQuery treats missing trailing columns as null values. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false.",
+"description": "Optional. Indicates if BigQuery should accept rows that are missing trailing optional columns. If true, BigQuery treats missing trailing columns as null values. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false.",
"type": "boolean"
},
"allowQuotedNewlines": {
-"description": "[Optional] Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false.",
+"description": "Optional. Indicates if BigQuery should allow quoted data sections that contain newline characters in a CSV file. The default value is false.",
"type": "boolean"
},
"encoding": {
-"description": "[Optional] The character encoding of the data. The supported values are UTF-8 or ISO-8859-1. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the quote and fieldDelimiter properties.",
+"description": "Optional. The character encoding of the data. The supported values are UTF-8, ISO-8859-1, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the quote and fieldDelimiter properties.",
"type": "string"
},
"fieldDelimiter": {
-"description": "[Optional] The separator for fields in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. BigQuery also supports the escape sequence \"\\t\" to specify a tab separator. The default value is a comma (',').",
+"description": "Optional. The separator character for fields in a CSV file. The separator is interpreted as a single byte. For files encoded in ISO-8859-1, any single character can be used as a separator. For files encoded in UTF-8, characters represented in decimal range 1-127 (U+0001-U+007F) can be used without any modification. UTF-8 characters encoded with multiple bytes (i.e. U+0080 and above) will have only the first byte used for separating fields. The remaining bytes will be treated as a part of the field. BigQuery also supports the escape sequence \"\\t\" (U+0009) to specify a tab separator. The default value is comma (\",\", U+002C).",
"type": "string"
},
"nullMarker": {
-"description": "[Optional] An custom string that will represent a NULL value in CSV import data.",
+"description": "[Optional] A custom string that will represent a NULL value in CSV import data.",
"type": "string"
},
"preserveAsciiControlCharacters": {
-"description": "[Optional] Preserves the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\\x00' to '\\x1F') when loading from CSV. Only applicable to CSV, ignored for other formats.",
+"description": "Optional. Indicates if the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\\x00' to '\\x1F') are preserved.",
"type": "boolean"
},
"quote": {
"default": "\"",
-"description": "[Optional] The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ('\"'). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true.",
+"description": "Optional. The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote (\"). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true. To include the specific quote character within a quoted value, precede it with an additional matching quote character. For example, if you want to escape the default character ' \" ', use ' \"\" '.",
"pattern": ".?",
"type": "string"
},
"skipLeadingRows": {
-"description": "[Optional] The number of rows at the top of a CSV file that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.",
+"description": "Optional. The number of rows at the top of a CSV file that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.",
"format": "int64",
"type": "string"
}
},
"type": "object"
},
+"DataFormatOptions": {
+"description": "Options for data format adjustments.",
+"id": "DataFormatOptions",
+"properties": {
+"useInt64Timestamp": {
+"description": "Optional. Output timestamp as usec int64. Default is false.",
+"type": "boolean"
+}
+},
+"type": "object"
+},
"DataMaskingStatistics": {
+"description": "Statistics for data-masking.",
"id": "DataMaskingStatistics",
"properties": {
"dataMaskingApplied": {
-"default": "false",
-"description": "[Output-only] [Preview] Whether any accessed data was protected by data masking. The actual evaluation is done by accessStats.masked_field_count > 0. Since this is only used for the discovery_doc generation purpose, as long as the type (boolean) matches, client library can leverage this. The actual evaluation of the variable is done else-where.",
+"description": "Whether any accessed data was protected by the data masking.",
"type": "boolean"
}
},
@@ -2763,8 +3008,9 @@
"id": "Dataset",
"properties": {
"access": {
-"description": "[Optional] An array of objects that define dataset access for one or more entities. You can set this property when inserting or updating a dataset in order to control who is allowed to access the data. If unspecified at dataset creation time, BigQuery adds default dataset access for the following entities: access.specialGroup: projectReaders; access.role: READER; access.specialGroup: projectWriters; access.role: WRITER; access.specialGroup: projectOwners; access.role: OWNER; access.userByEmail: [dataset creator email]; access.role: OWNER;",
+"description": "Optional. An array of objects that define dataset access for one or more entities. You can set this property when inserting or updating a dataset in order to control who is allowed to access the data. If unspecified at dataset creation time, BigQuery adds default dataset access for the following entities: access.specialGroup: projectReaders; access.role: READER; access.specialGroup: projectWriters; access.role: WRITER; access.specialGroup: projectOwners; access.role: OWNER; access.userByEmail: [dataset creator email]; access.role: OWNER;",
"items": {
+"description": "An object that defines dataset access for an entity.",
"properties": {
"dataset": {
"$ref": "DatasetAccessEntry",
@@ -2783,7 +3029,7 @@
"type": "string"
},
"role": {
-"description": "[Required] An IAM role ID that should be granted to the user, group, or domain specified in this access entry. The following legacy mappings will be applied: OWNER roles/bigquery.dataOwner WRITER roles/bigquery.dataEditor READER roles/bigquery.dataViewer This field will accept any of the above formats, but will return only the legacy format. For example, if you set this field to \"roles/bigquery.dataOwner\", it will be returned back as \"OWNER\".",
+"description": "An IAM role ID that should be granted to the user, group, or domain specified in this access entry. The following legacy mappings will be applied: OWNER <=> roles/bigquery.dataOwner WRITER <=> roles/bigquery.dataEditor READER <=> roles/bigquery.dataViewer This field will accept any of the above formats, but will return only the legacy format. For example, if you set this field to \"roles/bigquery.dataOwner\", it will be returned back as \"OWNER\".",
"type": "string"
},
"routine": {
@@ -2800,7 +3046,7 @@
},
"view": {
"$ref": "TableReference",
-"description": "[Pick one] A view from a different dataset to grant access to. Queries executed against that view will have read access to tables in this dataset. The role field is not required when this field is set. If that view is updated by any user, access to the view needs to be granted again via an update operation."
+"description": "[Pick one] A view from a different dataset to grant access to. Queries executed against that view will have read access to views/tables/routines in this dataset. The role field is not required when this field is set. If that view is updated by any user, access to the view needs to be granted again via an update operation."
}
},
"type": "object"
@@ -2808,62 +3054,77 @@
"type": "array"
},
"creationTime": {
-"description": "[Output-only] The time when this dataset was created, in milliseconds since the epoch.",
+"description": "Output only. The time when this dataset was created, in milliseconds since the epoch.",
"format": "int64",
+"readOnly": true,
"type": "string"
},
"datasetReference": {
"$ref": "DatasetReference",
-"description": "[Required] A reference that identifies the dataset."
+"description": "Required. A reference that identifies the dataset."
},
"defaultCollation": {
-"description": "[Output-only] The default collation of the dataset.",
+"description": "Optional. Defines the default collation specification of future tables created in the dataset. If a table is created in this dataset without table-level default collation, then the table inherits the dataset default collation, which is applied to the string fields that do not have explicit collation specified. A change to this field affects only tables created afterwards, and does not alter the existing tables. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.",
"type": "string"
},
"defaultEncryptionConfiguration": {
-"$ref": "EncryptionConfiguration"
+"$ref": "EncryptionConfiguration",
+"description": "The default encryption key for all tables in the dataset. Once this property is set, all newly-created partitioned tables in the dataset will have encryption key set to this value, unless table creation request (or query) overrides the key."
},
"defaultPartitionExpirationMs": {
-"description": "[Optional] The default partition expiration for all partitioned tables in the dataset, in milliseconds. Once this property is set, all newly-created partitioned tables in the dataset will have an expirationMs property in the timePartitioning settings set to this value, and changing the value will only affect new tables, not existing ones. The storage in a partition will have an expiration time of its partition time plus this value. Setting this property overrides the use of defaultTableExpirationMs for partitioned tables: only one of defaultTableExpirationMs and defaultPartitionExpirationMs will be used for any new partitioned table. If you provide an explicit timePartitioning.expirationMs when creating or updating a partitioned table, that value takes precedence over the default partition expiration time indicated by this property.",
+"description": "This default partition expiration, expressed in milliseconds. When new time-partitioned tables are created in a dataset where this property is set, the table will inherit this value, propagated as the `TimePartitioning.expirationMs` property on the new table. If you set `TimePartitioning.expirationMs` explicitly when creating a table, the `defaultPartitionExpirationMs` of the containing dataset is ignored. When creating a partitioned table, if `defaultPartitionExpirationMs` is set, the `defaultTableExpirationMs` value is ignored and the table will not be inherit a table expiration deadline.",
"format": "int64",
"type": "string"
},
"defaultRoundingMode": {
-"description": "[Output-only] The default rounding mode of the dataset.",
+"description": "Optional. Defines the default rounding mode specification of new tables created within this dataset. During table creation, if this field is specified, the table within this dataset will inherit the default rounding mode of the dataset. Setting the default rounding mode on a table overrides this option. Existing tables in the dataset are unaffected. If columns are defined during that table creation, they will immediately inherit the table's default rounding mode, unless otherwise specified.",
+"enum": [
+"ROUNDING_MODE_UNSPECIFIED",
+"ROUND_HALF_AWAY_FROM_ZERO",
+"ROUND_HALF_EVEN"
+],
+"enumDescriptions": [
+"Unspecified will default to using ROUND_HALF_AWAY_FROM_ZERO.",
+"ROUND_HALF_AWAY_FROM_ZERO rounds half values away from zero when applying precision and scale upon writing of NUMERIC and BIGNUMERIC values. For Scale: 0 1.1, 1.2, 1.3, 1.4 => 1 1.5, 1.6, 1.7, 1.8, 1.9 => 2",
+"ROUND_HALF_EVEN rounds half values to the nearest even value when applying precision and scale upon writing of NUMERIC and BIGNUMERIC values. For Scale: 0 1.1, 1.2, 1.3, 1.4 => 1 1.5 => 2 1.6, 1.7, 1.8, 1.9 => 2 2.5 => 2"
+],
"type": "string"
},
"defaultTableExpirationMs": {
-"description": "[Optional] The default lifetime of all tables in the dataset, in milliseconds. The minimum value is 3600000 milliseconds (one hour). Once this property is set, all newly-created tables in the dataset will have an expirationTime property set to the creation time plus the value in this property, and changing the value will only affect new tables, not existing ones. When the expirationTime for a given table is reached, that table will be deleted automatically. If a table's expirationTime is modified or removed before the table expires, or if you provide an explicit expirationTime when creating a table, that value takes precedence over the default expiration time indicated by this property.",
+"description": "Optional. The default lifetime of all tables in the dataset, in milliseconds. The minimum lifetime value is 3600000 milliseconds (one hour). To clear an existing default expiration with a PATCH request, set to 0. Once this property is set, all newly-created tables in the dataset will have an expirationTime property set to the creation time plus the value in this property, and changing the value will only affect new tables, not existing ones. When the expirationTime for a given table is reached, that table will be deleted automatically. If a table's expirationTime is modified or removed before the table expires, or if you provide an explicit expirationTime when creating a table, that value takes precedence over the default expiration time indicated by this property.",
"format": "int64",
"type": "string"
},
"description": {
-"description": "[Optional] A user-friendly description of the dataset.",
+"description": "Optional. A user-friendly description of the dataset.",
"type": "string"
},
"etag": {
-"description": "[Output-only] A hash of the resource.",
+"description": "Output only. A hash of the resource.",
+"readOnly": true,
"type": "string"
},
"externalDatasetReference": {
"$ref": "ExternalDatasetReference",
-"description": "[Optional] Information about the external metadata storage where the dataset is defined. Filled out when the dataset type is EXTERNAL."
+"description": "Optional. Information about the external metadata storage where the dataset is defined. Filled out when the dataset type is EXTERNAL."
},
"friendlyName": {
-"description": "[Optional] A descriptive name for the dataset.",
+"description": "Optional. A descriptive name for the dataset.",
"type": "string"
},
"id": {
-"description": "[Output-only] The fully-qualified unique name of the dataset in the format projectId:datasetId. The dataset name without the project name is given in the datasetId field. When creating a new dataset, leave this field blank, and instead specify the datasetId field.",
+"description": "Output only. The fully-qualified unique name of the dataset in the format projectId:datasetId. The dataset name without the project name is given in the datasetId field. When creating a new dataset, leave this field blank, and instead specify the datasetId field.",
+"readOnly": true,
"type": "string"
},
"isCaseInsensitive": {
-"description": "[Optional] Indicates if table names are case insensitive in the dataset.",
+"description": "Optional. TRUE if the dataset and its table names are case-insensitive, otherwise FALSE. By default, this is FALSE, which means the dataset and its table names are case-sensitive. This field does not affect routine references.",
"type": "boolean"
},
"kind": {
"default": "bigquery#dataset",
-"description": "[Output-only] The resource type.",
+"description": "Output only. The resource type.",
+"readOnly": true,
"type": "string"
},
"labels": {
@@ -2874,59 +3135,85 @@
"type": "object"
},
"lastModifiedTime": {
-"description": "[Output-only] The date when this dataset or any of its tables was last modified, in milliseconds since the epoch.",
+"description": "Output only. The date when this dataset was last modified, in milliseconds since the epoch.",
"format": "int64",
+"readOnly": true,
"type": "string"
},
+"linkedDatasetSource": {
+"$ref": "LinkedDatasetSource",
+"description": "Optional. The source dataset reference when the dataset is of type LINKED. For all other dataset types it is not set. This field cannot be updated once it is set. Any attempt to update this field using Update and Patch API Operations will be ignored."
+},
"location": {
-"description": "The geographic location where the dataset should reside. The default value is US. See details at https://cloud.google.com/bigquery/docs/locations.",
+"description": "The geographic location where the dataset should reside. See https://cloud.google.com/bigquery/docs/locations for supported locations.",
"type": "string"
},
"maxTimeTravelHours": {
-"description": "[Optional] Number of hours for the max time travel for all tables in the dataset.",
+"description": "Optional. Defines the time travel window in hours. The value can be from 48 to 168 hours (2 to 7 days). The default value is 168 hours if this is not set.",
"format": "int64",
"type": "string"
},
"satisfiesPzs": {
-"description": "[Output-only] Reserved for future use.",
+"description": "Output only. Reserved for future use.",
+"readOnly": true,
"type": "boolean"
},
"selfLink": {
-"description": "[Output-only] A URL that can be used to access the resource again. You can use this URL in Get or Update requests to the resource.",
+"description": "Output only. A URL that can be used to access the resource again. You can use this URL in Get or Update requests to the resource.",
+"readOnly": true,
"type": "string"
},
"storageBillingModel": {
-"description": "[Optional] Storage billing model to be used for all tables in the dataset. Can be set to PHYSICAL. Default is LOGICAL.",
+"description": "Optional. Updates storage_billing_model for the dataset.",
+"enum": [
+"STORAGE_BILLING_MODEL_UNSPECIFIED",
+"LOGICAL",
+"PHYSICAL"
+],
+"enumDescriptions": [
+"Value not set.",
+"Billing for logical bytes.",
+"Billing for physical bytes."
+],
"type": "string"
},
"tags": {
-"description": "[Optional]The tags associated with this dataset. Tag keys are globally unique.",
+"description": "Output only. Tags for the Dataset.",
"items": {
+"description": "A global tag managed by Resource Manager. https://cloud.google.com/iam/docs/tags-access-control#definitions",
"properties": {
"tagKey": {
-"description": "[Required] The namespaced friendly name of the tag key, e.g. \"12345/environment\" where 12345 is org id.",
+"description": "Required. The namespaced friendly name of the tag key, e.g. \"12345/environment\" where 12345 is org id.",
"type": "string"
},
"tagValue": {
-"description": "[Required] Friendly short name of the tag value, e.g. \"production\".",
+"description": "Required. The friendly short name of the tag value, e.g. \"production\".",
"type": "string"
}
},
"type": "object"
},
+"readOnly": true,
"type": "array"
+},
+"type": {
+"description": "Output only. Same as `type` in `ListFormatDataset`. The type of the dataset, one of: * DEFAULT - only accessible by owner and authorized accounts, * PUBLIC - accessible by everyone, * LINKED - linked dataset, * EXTERNAL - dataset with definition in external metadata catalog. -- *BIGLAKE_METASTORE - dataset that references a database created in BigLakeMetastore service. --",
+"readOnly": true,
+"type": "string"
}
},
"type": "object"
},
"DatasetAccessEntry": {
+"description": "Grants all resources of particular types in a particular dataset read access to the current dataset. Similar to how individually authorized views work, updates to any resource granted through its dataset (including creation of new resources) requires read permission to referenced resources, plus write permission to the authorizing dataset.",
"id": "DatasetAccessEntry",
"properties": {
"dataset": {
"$ref": "DatasetReference",
-"description": "[Required] The dataset this entry applies to."
+"description": "The dataset this entry applies to"
},
"targetTypes": {
+"description": "Which resources in the dataset this entry applies to. Currently, only views are supported, but additional target types may be added in the future.",
"items": {
"enum": [
"TARGET_TYPE_UNSPECIFIED",
@@ -2946,18 +3233,20 @@
"type": "object"
},
"DatasetList": {
+"description": "Response format for a page of results when listing datasets.",
"id": "DatasetList",
"properties": {
"datasets": {
"description": "An array of the dataset resources in the project. Each resource contains basic information. For full information about a particular dataset resource, use the Datasets: get method. This property is omitted when there are no datasets in the project.",
"items": {
+"description": "A dataset resource with only a subset of fields, to be returned in a list of datasets.",
"properties": {
"datasetReference": {
"$ref": "DatasetReference",
"description": "The dataset reference. Use this property to access specific parts of the dataset's ID, such as project ID or dataset ID."
},
"friendlyName": {
-"description": "A descriptive name for the dataset, if one exists.",
+"description": "An alternate name for the dataset. The friendly name is purely decorative in nature.",
"type": "string"
},
"id": {
@@ -2965,8 +3254,7 @@
"type": "string"
},
"kind": {
-"default": "bigquery#dataset",
-"description": "The resource type. This property always returns the value \"bigquery#dataset\".",
+"description": "The resource type. This property always returns the value \"bigquery#dataset\"",
"type": "string"
},
"labels": {
@@ -2977,7 +3265,7 @@
"type": "object"
},
"location": {
-"description": "The geographic location where the data resides.",
+"description": "The geographic location where the dataset resides.",
"type": "string"
}
},
@@ -2986,17 +3274,26 @@
"type": "array"
},
"etag": {
-"description": "A hash value of the results page. You can use this property to determine if the page has changed since the last request.",
+"description": "Output only. A hash value of the results page. You can use this property to determine if the page has changed since the last request.",
+"readOnly": true,
"type": "string"
},
"kind": {
"default": "bigquery#datasetList",
-"description": "The list type. This property always returns the value \"bigquery#datasetList\".",
+"description": "Output only. The resource type. This property always returns the value \"bigquery#datasetList\"",
+"readOnly": true,
"type": "string"
},
"nextPageToken": {
"description": "A token that can be used to request the next results page. This property is omitted on the final results page.",
"type": "string"
+},
+"unreachable": {
+"description": "A list of skipped locations that were unreachable. For more information about BigQuery locations, see: https://cloud.google.com/bigquery/docs/locations. Example: \"europe-west5\"",
+"items": {
+"type": "string"
+},
+"type": "array"
}
},
"type": "object"
@@ -3005,47 +3302,38 @@
"id": "DatasetReference",
"properties": {
"datasetId": {
-"annotations": {
-"required": [
-"bigquery.datasets.update"
-]
-},
-"description": "[Required] A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.",
+"description": "Required. A unique ID for this dataset, without the project name. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.",
"type": "string"
},
"projectId": {
-"annotations": {
-"required": [
-"bigquery.datasets.update"
-]
-},
-"description": "[Optional] The ID of the project containing this dataset.",
+"description": "Optional. The ID of the project containing this dataset.",
"type": "string"
}
},
"type": "object"
},
"DestinationTableProperties": {
+"description": "Properties for the destination table.",
"id": "DestinationTableProperties",
"properties": {
"description": {
-"description": "[Optional] The description for the destination table. This will only be used if the destination table is newly created. If the table already exists and a value different than the current description is provided, the job will fail.",
+"description": "Optional. The description for the destination table. This will only be used if the destination table is newly created. If the table already exists and a value different than the current description is provided, the job will fail.",
"type": "string"
},
"expirationTime": {
-"description": "[Internal] This field is for Google internal use only.",
+"description": "Internal use only.",
"format": "date-time",
"type": "string"
},
"friendlyName": {
-"description": "[Optional] The friendly name for the destination table. This will only be used if the destination table is newly created. If the table already exists and a value different than the current friendly name is provided, the job will fail.",
+"description": "Optional. Friendly name for the destination table. If the table already exists, it should be same as the existing friendly name.",
"type": "string"
},
"labels": {
"additionalProperties": {
"type": "string"
},
-"description": "[Optional] The labels associated with this table. You can use these to organize and group your tables. This will only be used if the destination table is newly created. If the table already exists and labels are different than the current labels are provided, the job will fail.",
+"description": "Optional. The labels associated with this table. You can use these to organize and group your tables. This will only be used if the destination table is newly created. If the table already exists and labels are different than the current labels are provided, the job will fail.",
"type": "object"
}
},
@@ -3064,21 +3352,25 @@
"type": "object"
},
"DmlStatistics": {
+"description": "Detailed statistics for DML statements",
"id": "DmlStatistics",
"properties": {
"deletedRowCount": {
-"description": "Number of deleted Rows. populated by DML DELETE, MERGE and TRUNCATE statements.",
+"description": "Output only. Number of deleted Rows. populated by DML DELETE, MERGE and TRUNCATE statements.",
"format": "int64",
+"readOnly": true,
"type": "string"
},
"insertedRowCount": {
-"description": "Number of inserted Rows. Populated by DML INSERT and MERGE statements.",
+"description": "Output only. Number of inserted Rows. Populated by DML INSERT and MERGE statements",
"format": "int64",
+"readOnly": true,
"type": "string"
},
"updatedRowCount": {
-"description": "Number of updated Rows. Populated by DML UPDATE and MERGE statements.",
+"description": "Output only. Number of updated Rows. Populated by DML UPDATE and MERGE statements.",
"format": "int64",
+"readOnly": true,
"type": "string"
}
},
@@ -3158,6 +3450,7 @@
"type": "object"
},
"ErrorProto": {
+"description": "Error details.",
"id": "ErrorProto",
"properties": {
"debugInfo": {
@@ -3215,6 +3508,7 @@
"type": "object"
},
"ExplainQueryStage": {
+"description": "A single stage of query execution.",
"id": "ExplainQueryStage",
"properties": {
"completedParallelInputs": {
@@ -3222,6 +3516,21 @@
"format": "int64",
"type": "string"
},
+"computeMode": {
+"description": "Output only. Compute mode for this stage.",
+"enum": [
+"COMPUTE_MODE_UNSPECIFIED",
+"BIGQUERY",
+"BI_ENGINE"
+],
+"enumDescriptions": [
+"ComputeMode type not specified.",
+"This stage was processed using BigQuery slots.",
+"This stage was processed using BI Engine compute."
+],
+"readOnly": true,
+"type": "string"
+},
"computeMsAvg": {
"description": "Milliseconds the average shard spent on CPU-bound tasks.",
"format": "int64",
@@ -3243,12 +3552,12 @@
"type": "number"
},
"endMs": {
-"description": "Stage end time represented as milliseconds since epoch.",
+"description": "Stage end time represented as milliseconds since the epoch.",
"format": "int64",
"type": "string"
},
"id": {
-"description": "Unique ID for stage within plan.",
+"description": "Unique ID for the stage within the plan.",
"format": "int64",
"type": "string"
},
@@ -3261,11 +3570,11 @@
"type": "array"
},
"name": {
-"description": "Human-readable name for stage.",
+"description": "Human-readable name for the stage.",
"type": "string"
},
"parallelInputs": {
-"description": "Number of parallel input segments to be processed.",
+"description": "Number of parallel input segments to be processed",
"format": "int64",
"type": "string"
},
@@ -3315,12 +3624,12 @@
"type": "string"
},
"startMs": {
-"description": "Stage start time represented as milliseconds since epoch.",
+"description": "Stage start time represented as milliseconds since the epoch.",
"format": "int64",
"type": "string"
},
"status": {
-"description": "Current status for the stage.",
+"description": "Current status for this stage.",
"type": "string"
},
"steps": {
@@ -3374,6 +3683,7 @@
"type": "object"
},
"ExplainQueryStep": {
+"description": "An operation within a stage.",
"id": "ExplainQueryStep",
"properties": {
"kind": {
@@ -3381,7 +3691,7 @@
"type": "string"
},
"substeps": {
-"description": "Human-readable stage descriptions.",
+"description": "Human-readable description of the step(s).",
"items": {
"type": "string"
},
@@ -3406,6 +3716,23 @@
},
"type": "object"
},
+"ExportDataStatistics": {
+"description": "Statistics for the EXPORT DATA statement as part of Query Job. EXTRACT JOB statistics are populated in JobStatistics4.",
+"id": "ExportDataStatistics",
+"properties": {
+"fileCount": {
+"description": "Number of destination files generated in case of EXPORT DATA statement only.",
+"format": "int64",
+"type": "string"
+},
+"rowCount": {
+"description": "[Alpha] Number of destination rows generated in case of EXPORT DATA statement only.",
+"format": "int64",
+"type": "string"
+}
+},
+"type": "object"
+},
"Expr": {
"description": "Represents a textual expression in the Common Expression Language (CEL) syntax. CEL is a C-like expression language. The syntax and semantics of CEL are documented at https://github.com/google/cel-spec. Example (Comparison): title: \"Summary size limit\" description: \"Determines if a summary is less than 100 chars\" expression: \"document.summary.size() < 100\" Example (Equality): title: \"Requestor is owner\" description: \"Determines if requestor is the document owner\" expression: \"document.owner == request.auth.claims.email\" Example (Logic): title: \"Public documents\" description: \"Determine whether the document should be publicly visible\" expression: \"document.type != 'private' && document.type != 'internal'\" Example (Data Manipulation): title: \"Notification string\" description: \"Create a notification string with a timestamp.\" expression: \"'New message received at ' + string(document.create_time)\" The exact variables and functions that may be referenced within an expression are determined by the service that evaluates it. See the service documentation for additional information.",
"id": "Expr",
@@ -3438,78 +3765,130 @@
},
"avroOptions": {
"$ref": "AvroOptions",
-"description": "Additional properties to set if sourceFormat is set to Avro."
+"description": "Optional. Additional properties to set if sourceFormat is set to AVRO."
},
"bigtableOptions": {
"$ref": "BigtableOptions",
-"description": "[Optional] Additional options if sourceFormat is set to BIGTABLE."
+"description": "Optional. Additional options if sourceFormat is set to BIGTABLE."
},
"compression": {
-"description": "[Optional] The compression type of the data source. Possible values include GZIP and NONE. The default value is NONE. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups and Avro formats.",
+"description": "Optional. The compression type of the data source. Possible values include GZIP and NONE. The default value is NONE. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups, Avro, ORC and Parquet formats. An empty string is an invalid value.",
"type": "string"
},
"connectionId": {
-"description": "[Optional, Trusted Tester] Connection for external data source.",
+"description": "Optional. The connection specifying the credentials to be used to read external storage, such as Azure Blob, Cloud Storage, or S3. The connection_id can have the form \"..\" or \"projects//locations//connections/\".",
"type": "string"
},
"csvOptions": {
"$ref": "CsvOptions",
-"description": "Additional properties to set if sourceFormat is set to CSV."
+"description": "Optional. Additional properties to set if sourceFormat is set to CSV."
},
"decimalTargetTypes": {
-"description": "[Optional] Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown. Example: Suppose the value of this field is [\"NUMERIC\", \"BIGNUMERIC\"]. If (precision,scale) is: (38,9) -> NUMERIC; (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits); (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits); (76,38) -> BIGNUMERIC; (77,38) -> BIGNUMERIC (error if value exeeds supported range). This field cannot contain duplicate types. The order of the types in this field is ignored. For example, [\"BIGNUMERIC\", \"NUMERIC\"] is the same as [\"NUMERIC\", \"BIGNUMERIC\"] and NUMERIC always takes precedence over BIGNUMERIC. Defaults to [\"NUMERIC\", \"STRING\"] for ORC and [\"NUMERIC\"] for the other file formats.",
+"description": "Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown. Example: Suppose the value of this field is [\"NUMERIC\", \"BIGNUMERIC\"]. If (precision,scale) is: * (38,9) -> NUMERIC; * (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits); * (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits); * (76,38) -> BIGNUMERIC; * (77,38) -> BIGNUMERIC (error if value exeeds supported range). This field cannot contain duplicate types. The order of the types in this field is ignored. For example, [\"BIGNUMERIC\", \"NUMERIC\"] is the same as [\"NUMERIC\", \"BIGNUMERIC\"] and NUMERIC always takes precedence over BIGNUMERIC. Defaults to [\"NUMERIC\", \"STRING\"] for ORC and [\"NUMERIC\"] for the other file formats.",
"items": {
+"enum": [
+"DECIMAL_TARGET_TYPE_UNSPECIFIED",
+"NUMERIC",
+"BIGNUMERIC",
+"STRING"
+],
+"enumDescriptions": [
+"Invalid type.",
+"Decimal values could be converted to NUMERIC type.",
+"Decimal values could be converted to BIGNUMERIC type.",
+"Decimal values could be converted to STRING type."
+],
"type": "string"
},
"type": "array"
},
"fileSetSpecType": {
-"description": "[Optional] Specifies how source URIs are interpreted for constructing the file set to load. By default source URIs are expanded against the underlying storage. Other options include specifying manifest files. Only applicable to object storage systems.",
+"description": "Optional. Specifies how source URIs are interpreted for constructing the file set to load. By default source URIs are expanded against the underlying storage. Other options include specifying manifest files. Only applicable to object storage systems.",
+"enum": [
+"FILE_SET_SPEC_TYPE_FILE_SYSTEM_MATCH",
+"FILE_SET_SPEC_TYPE_NEW_LINE_DELIMITED_MANIFEST"
+],
+"enumDescriptions": [
+"This option expands source URIs by listing files from the object store. It is the default behavior if FileSetSpecType is not set.",
+"This option indicates that the provided URIs are newline-delimited manifest files, with one URI per line. Wildcard URIs are not supported."
+],
"type": "string"
},
"googleSheetsOptions": {
"$ref": "GoogleSheetsOptions",
-"description": "[Optional] Additional options if sourceFormat is set to GOOGLE_SHEETS."
+"description": "Optional. Additional options if sourceFormat is set to GOOGLE_SHEETS."
},
"hivePartitioningOptions": {
"$ref": "HivePartitioningOptions",
-"description": "[Optional] Options to configure hive partitioning support."
+"description": "Optional. When set, configures hive partitioning support. Not all storage formats support hive partitioning -- requesting hive partitioning on an unsupported format will lead to an error, as will providing an invalid specification."
},
"ignoreUnknownValues": {
-"description": "[Optional] Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names Google Cloud Bigtable: This setting is ignored. Google Cloud Datastore backups: This setting is ignored. Avro: This setting is ignored.",
+"description": "Optional. Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names Google Cloud Bigtable: This setting is ignored. Google Cloud Datastore backups: This setting is ignored. Avro: This setting is ignored. ORC: This setting is ignored. Parquet: This setting is ignored.",
"type": "boolean"
},
+"jsonExtension": {
+"description": "Optional. Load option to be used together with source_format newline-delimited JSON to indicate that a variant of JSON is being loaded. To load newline-delimited GeoJSON, specify GEOJSON (and source_format must be set to NEWLINE_DELIMITED_JSON).",
+"enum": [
+"JSON_EXTENSION_UNSPECIFIED",
+"GEOJSON"
+],
+"enumDescriptions": [
+"The default if provided value is not one included in the enum, or the value is not specified. The source formate is parsed without any modification.",
+"Use GeoJSON variant of JSON. See https://tools.ietf.org/html/rfc7946."
+],
+"type": "string"
+},
"jsonOptions": {
"$ref": "JsonOptions",
-"description": "Additional properties to set if `sourceFormat` is set to `NEWLINE_DELIMITED_JSON`."
+"description": "Optional. Additional properties to set if sourceFormat is set to JSON."
},
"maxBadRecords": {
-"description": "[Optional] The maximum number of bad records that BigQuery can ignore when reading data. If the number of bad records exceeds this value, an invalid error is returned in the job result. This is only valid for CSV, JSON, and Google Sheets. The default value is 0, which requires that all records are valid. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups and Avro formats.",
+"description": "Optional. The maximum number of bad records that BigQuery can ignore when reading data. If the number of bad records exceeds this value, an invalid error is returned in the job result. The default value is 0, which requires that all records are valid. This setting is ignored for Google Cloud Bigtable, Google Cloud Datastore backups, Avro, ORC and Parquet formats.",
"format": "int32",
"type": "integer"
},
"metadataCacheMode": {
-"description": "[Optional] Metadata Cache Mode for the table. Set this to enable caching of metadata from external data source.",
+"description": "Optional. Metadata Cache Mode for the table. Set this to enable caching of metadata from external data source.",
+"enum": [
+"METADATA_CACHE_MODE_UNSPECIFIED",
+"AUTOMATIC",
+"MANUAL"
+],
+"enumDescriptions": [
+"Unspecified metadata cache mode.",
+"Set this mode to trigger automatic background refresh of metadata cache from the external source. Queries will use the latest available cache version within the table's maxStaleness interval.",
+"Set this mode to enable triggering manual refresh of the metadata cache from external source. Queries will use the latest manually triggered cache version within the table's maxStaleness interval."
+],
"type": "string"
},
"objectMetadata": {
-"description": "ObjectMetadata is used to create Object Tables. Object Tables contain a listing of objects (with their metadata) found at the source_uris. If ObjectMetadata is set, source_format should be omitted. Currently SIMPLE is the only supported Object Metadata type.",
+"description": "Optional. ObjectMetadata is used to create Object Tables. Object Tables contain a listing of objects (with their metadata) found at the source_uris. If ObjectMetadata is set, source_format should be omitted. Currently SIMPLE is the only supported Object Metadata type.",
+"enum": [
+"OBJECT_METADATA_UNSPECIFIED",
+"DIRECTORY",
+"SIMPLE"
+],
+"enumDescriptions": [
+"Unspecified by default.",
+"A synonym for `SIMPLE`.",
+"Directory listing of objects."
+],
"type": "string"
},
"parquetOptions": {
"$ref": "ParquetOptions",
-"description": "Additional properties to set if sourceFormat is set to Parquet."
+"description": "Optional. Additional properties to set if sourceFormat is set to PARQUET."
},
"referenceFileSchemaUri": {
-"description": "[Optional] Provide a referencing file with the expected table schema. Enabled for the format: AVRO, PARQUET, ORC.",
+"description": "Optional. When creating an external table, the user can provide a reference file with the table schema. This is enabled for the following formats: AVRO, PARQUET, ORC.",
"type": "string"
},
"schema": {
"$ref": "TableSchema",
-"description": "[Optional] The schema for the data. Schema is required for CSV and JSON formats. Schema is disallowed for Google Cloud Bigtable, Cloud Datastore backups, and Avro formats."
+"description": "Optional. The schema for the data. Schema is required for CSV and JSON formats if autodetect is not on. Schema is disallowed for Google Cloud Bigtable, Cloud Datastore backups, Avro, ORC and Parquet formats."
},
"sourceFormat": {
-"description": "[Required] The data format. For CSV files, specify \"CSV\". For Google sheets, specify \"GOOGLE_SHEETS\". For newline-delimited JSON, specify \"NEWLINE_DELIMITED_JSON\". For Avro files, specify \"AVRO\". For Google Cloud Datastore backups, specify \"DATASTORE_BACKUP\". [Beta] For Google Cloud Bigtable, specify \"BIGTABLE\".",
+"description": "[Required] The data format. For CSV files, specify \"CSV\". For Google sheets, specify \"GOOGLE_SHEETS\". For newline-delimited JSON, specify \"NEWLINE_DELIMITED_JSON\". For Avro files, specify \"AVRO\". For Google Cloud Datastore backups, specify \"DATASTORE_BACKUP\". For Apache Iceberg tables, specify \"ICEBERG\". For ORC files, specify \"ORC\". For Parquet files, specify \"PARQUET\". [Beta] For Google Cloud Bigtable, specify \"BIGTABLE\".",
"type": "string"
},
"sourceUris": {
@@ -3523,14 +3902,46 @@
"type": "object"
},
"ExternalDatasetReference": {
+"description": "Configures the access a dataset defined in an external metadata storage.",
"id": "ExternalDatasetReference",
"properties": {
"connection": {
-"description": "[Required] The connection id that is used to access the external_source. Format: projects/{project_id}/locations/{location_id}/connections/{connection_id}",
+"description": "Required. The connection id that is used to access the external_source. Format: projects/{project_id}/locations/{location_id}/connections/{connection_id}",
"type": "string"
},
"externalSource": {
-"description": "[Required] External source that backs this dataset.",
+"description": "Required. External source that backs this dataset.",
+"type": "string"
+}
+},
+"type": "object"
+},
+"ExternalServiceCost": {
+"description": "The external service cost is a portion of the total cost, these costs are not additive with total_bytes_billed. Moreover, this field only track external service costs that will show up as BigQuery costs (e.g. training BigQuery ML job with google cloud CAIP or Automl Tables services), not other costs which may be accrued by running the query (e.g. reading from Bigtable or Cloud Storage). The external service costs with different billing sku (e.g. CAIP job is charged based on VM usage) are converted to BigQuery billed_bytes and slot_ms with equivalent amount of US dollars. Services may not directly correlate to these metrics, but these are the equivalents for billing purposes. Output only.",
+"id": "ExternalServiceCost",
+"properties": {
+"bytesBilled": {
+"description": "External service cost in terms of bigquery bytes billed.",
+"format": "int64",
+"type": "string"
+},
+"bytesProcessed": {
+"description": "External service cost in terms of bigquery bytes processed.",
+"format": "int64",
+"type": "string"
+},
+"externalService": {
+"description": "External service name.",
+"type": "string"
+},
+"reservedSlotCount": {
+"description": "Non-preemptable reserved slots used for external job. For example, reserved slots for Cloua AI Platform job are the VM usages converted to BigQuery slot with equivalent mount of price.",
+"format": "int64",
+"type": "string"
+},
+"slotMs": {
+"description": "External service cost in terms of bigquery slot milliseconds.",
+"format": "int64",
"type": "string"
}
},
@@ -3580,6 +3991,7 @@
"type": "object"
},
"GetQueryResultsResponse": {
+"description": "Response object of GetQueryResults.",
"id": "GetQueryResultsResponse",
"properties": {
"cacheHit": {
@@ -3587,10 +3999,11 @@
"type": "boolean"
},
"errors": {
-"description": "[Output-only] The first errors or warnings encountered during the running of the job. The final message includes the number of errors that caused the process to stop. Errors here do not necessarily mean that the job has completed or was unsuccessful.",
+"description": "Output only. The first errors or warnings encountered during the running of the job. The final message includes the number of errors that caused the process to stop. Errors here do not necessarily mean that the job has completed or was unsuccessful. For more information about error messages, see [Error messages](https://cloud.google.com/bigquery/docs/error-messages).",
"items": {
"$ref": "ErrorProto"
},
+"readOnly": true,
"type": "array"
},
"etag": {
@@ -3611,16 +4024,17 @@
"type": "string"
},
"numDmlAffectedRows": {
-"description": "[Output-only] The number of rows affected by a DML statement. Present only for DML statements INSERT, UPDATE or DELETE.",
+"description": "Output only. The number of rows affected by a DML statement. Present only for DML statements INSERT, UPDATE or DELETE.",
"format": "int64",
+"readOnly": true,
"type": "string"
},
"pageToken": {
-"description": "A token used for paging results.",
+"description": "A token used for paging results. When this token is non-empty, it indicates additional results are available.",
"type": "string"
},
"rows": {
-"description": "An object with as many results as can be contained within the maximum permitted reply size. To get any additional rows, you can call GetQueryResults and specify the jobReference returned above. Present only when the query completes successfully.",
+"description": "An object with as many results as can be contained within the maximum permitted reply size. To get any additional rows, you can call GetQueryResults and specify the jobReference returned above. Present only when the query completes successfully. The REST-based representation of this data leverages a series of JSON f,v objects for indicating fields and values.",
"items": {
"$ref": "TableRow"
},
@@ -3644,6 +4058,7 @@
"type": "object"
},
"GetServiceAccountResponse": {
+"description": "Response object of GetServiceAccount",
"id": "GetServiceAccountResponse",
"properties": {
"email": {
@@ -3677,40 +4092,75 @@
"type": "object"
},
"GoogleSheetsOptions": {
+"description": "Options specific to Google Sheets data sources.",
"id": "GoogleSheetsOptions",
"properties": {
"range": {
-"description": "[Optional] Range of a sheet to query from. Only used when non-empty. Typical format: sheet_name!top_left_cell_id:bottom_right_cell_id For example: sheet1!A1:B20",
+"description": "Optional. Range of a sheet to query from. Only used when non-empty. Typical format: sheet_name!top_left_cell_id:bottom_right_cell_id For example: sheet1!A1:B20",
"type": "string"
},
"skipLeadingRows": {
-"description": "[Optional] The number of rows at the top of a sheet that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows that should be skipped. When autodetect is on, behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.",
+"description": "Optional. The number of rows at the top of a sheet that BigQuery will skip when reading the data. The default value is 0. This property is useful if you have header rows that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.",
"format": "int64",
"type": "string"
}
},
"type": "object"
},
-"HivePartitioningOptions": {
-"id": "HivePartitioningOptions",
+"HighCardinalityJoin": {
+"description": "High cardinality join detailed information.",
+"id": "HighCardinalityJoin",
"properties": {
-"fields": {
-"description": "[Output-only] For permanent external tables, this field is populated with the hive partition keys in the order they were inferred. The types of the partition keys can be deduced by checking the table schema (which will include the partition keys). Not every API will populate this field in the output. For example, Tables.Get will populate it, but Tables.List will not contain this field.",
-"items": {
+"leftRows": {
+"description": "Output only. Count of left input rows.",
+"format": "int64",
+"readOnly": true,
"type": "string"
},
-"type": "array"
+"outputRows": {
+"description": "Output only. Count of the output rows.",
+"format": "int64",
+"readOnly": true,
+"type": "string"
},
-"mode": {
-"description": "[Optional] When set, what mode of hive partitioning to use when reading data. The following modes are supported. (1) AUTO: automatically infer partition key name(s) and type(s). (2) STRINGS: automatically infer partition key name(s). All types are interpreted as strings. (3) CUSTOM: partition key schema is encoded in the source URI prefix. Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported types include: AVRO, CSV, JSON, ORC and Parquet.",
+"rightRows": {
+"description": "Output only. Count of right input rows.",
+"format": "int64",
+"readOnly": true,
"type": "string"
},
-"requirePartitionFilter": {
-"description": "[Optional] If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. Note that this field should only be true when creating a permanent external table or querying a temporary external table. Hive-partitioned loads with requirePartitionFilter explicitly set to true will fail.",
+"stepIndex": {
+"description": "Output only. The index of the join operator in the ExplainQueryStep lists.",
+"format": "int32",
+"readOnly": true,
+"type": "integer"
+}
+},
+"type": "object"
+},
+"HivePartitioningOptions": {
+"description": "Options for configuring hive partitioning detect.",
+"id": "HivePartitioningOptions",
+"properties": {
+"fields": {
+"description": "Output only. For permanent external tables, this field is populated with the hive partition keys in the order they were inferred. The types of the partition keys can be deduced by checking the table schema (which will include the partition keys). Not every API will populate this field in the output. For example, Tables.Get will populate it, but Tables.List will not contain this field.",
+"items": {
+"type": "string"
+},
+"readOnly": true,
+"type": "array"
+},
+"mode": {
+"description": "Optional. When set, what mode of hive partitioning to use when reading data. The following modes are supported: * AUTO: automatically infer partition key name(s) and type(s). * STRINGS: automatically infer partition key name(s). All types are strings. * CUSTOM: partition key schema is encoded in the source URI prefix. Not all storage formats support hive partitioning. Requesting hive partitioning on an unsupported format will lead to an error. Currently supported formats are: JSON, CSV, ORC, Avro and Parquet.",
+"type": "string"
+},
+"requirePartitionFilter": {
+"default": "false",
+"description": "Optional. If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. Note that this field should only be true when creating a permanent external table or querying a temporary external table. Hive-partitioned loads with require_partition_filter explicitly set to true will fail.",
"type": "boolean"
},
"sourceUriPrefix": {
-"description": "[Optional] When hive partition detection is requested, a common prefix for all source uris should be supplied. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout. gs://bucket/path_to_table/dt=2019-01-01/country=BR/id=7/file.avro gs://bucket/path_to_table/dt=2018-12-31/country=CA/id=3/file.avro When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/ (trailing slash does not matter).",
+"description": "Optional. When hive partition detection is requested, a common prefix for all source uris must be required. The prefix must end immediately before the partition key encoding begins. For example, consider files following this data layout: gs://bucket/path_to_table/dt=2019-06-01/country=USA/id=7/file.avro gs://bucket/path_to_table/dt=2019-05-31/country=CA/id=3/file.avro When hive partitioning is requested with either AUTO or STRINGS detection, the common prefix can be either of gs://bucket/path_to_table or gs://bucket/path_to_table/. CUSTOM detection requires encoding the partitioning schema immediately after the common prefix. For CUSTOM, any of * gs://bucket/path_to_table/{dt:DATE}/{country:STRING}/{id:INTEGER} * gs://bucket/path_to_table/{dt:STRING}/{country:STRING}/{id:INTEGER} * gs://bucket/path_to_table/{dt:DATE}/{country:STRING}/{id:STRING} would all be valid source URI prefixes.",
"type": "string"
}
},
@@ -3882,30 +4332,85 @@
"type": "object"
},
"IndexUnusedReason": {
+"description": "Reason about why no search index was used in the search query (or sub-query).",
"id": "IndexUnusedReason",
"properties": {
"baseTable": {
"$ref": "TableReference",
-"description": "[Output-only] Specifies the base table involved in the reason that no search index was used."
+"description": "Specifies the base table involved in the reason that no search index was used."
},
"code": {
-"default": "$(reason.code)",
-"description": "[Output-only] Specifies the high-level reason for the scenario when no search index was used.",
+"description": "Specifies the high-level reason for the scenario when no search index was used.",
+"enum": [
+"CODE_UNSPECIFIED",
+"INDEX_CONFIG_NOT_AVAILABLE",
+"PENDING_INDEX_CREATION",
+"BASE_TABLE_TRUNCATED",
+"INDEX_CONFIG_MODIFIED",
+"TIME_TRAVEL_QUERY",
+"NO_PRUNING_POWER",
+"UNINDEXED_SEARCH_FIELDS",
+"UNSUPPORTED_SEARCH_PATTERN",
+"OPTIMIZED_WITH_MATERIALIZED_VIEW",
+"SECURED_BY_DATA_MASKING",
+"MISMATCHED_TEXT_ANALYZER",
+"BASE_TABLE_TOO_SMALL",
+"BASE_TABLE_TOO_LARGE",
+"ESTIMATED_PERFORMANCE_GAIN_TOO_LOW",
+"NOT_SUPPORTED_IN_STANDARD_EDITION",
+"INDEX_SUPPRESSED_BY_FUNCTION_OPTION",
+"INTERNAL_ERROR",
+"QUERY_CACHE_HIT",
+"OTHER_REASON"
+],
+"enumDescriptions": [
+"Code not specified.",
+"Indicates the search index configuration has not been created.",
+"Indicates the search index creation has not been completed.",
+"Indicates the base table has been truncated (rows have been removed from table with TRUNCATE TABLE statement) since the last time the search index was refreshed.",
+"Indicates the search index configuration has been changed since the last time the search index was refreshed.",
+"Indicates the search query accesses data at a timestamp before the last time the search index was refreshed.",
+"Indicates the usage of search index will not contribute to any pruning improvement for the search function, e.g. when the search predicate is in a disjunction with other non-search predicates.",
+"Indicates the search index does not cover all fields in the search function.",
+"Indicates the search index does not support the given search query pattern.",
+"Indicates the query has been optimized by using a materialized view.",
+"Indicates the query has been secured by data masking, and thus search indexes are not applicable.",
+"Indicates that the search index and the search function call do not have the same text analyzer.",
+"Indicates the base table is too small (below a certain threshold). The index does not provide noticeable search performance gains when the base table is too small.",
+"Indicates that the total size of indexed base tables in your organization exceeds your region's limit and the index is not used in the query. To index larger base tables, you can use your own reservation for index-management jobs.",
+"Indicates that the esitmated performance gain from using the search index is too low for the given search query.",
+"Indicates that search indexes can not be used for search query with STANDARD edition.",
+"Indicates that an option in the search function that cannot make use of the index has been selected.",
+"Indicates an internal error that causes the search index to be unused.",
+"Indicates that the query was cached, and thus the search index was not used.",
+"Indicates that the reason search indexes cannot be used in the query is not covered by any of the other IndexUnusedReason options."
+],
"type": "string"
},
"indexName": {
-"default": "$(reason.index_name)",
-"description": "[Output-only] Specifies the name of the unused search index, if available.",
+"description": "Specifies the name of the unused search index, if available.",
"type": "string"
},
"message": {
-"default": "$(reason.message)",
-"description": "[Output-only] Free form human-readable reason for the scenario when no search index was used.",
+"description": "Free form human-readable reason for the scenario when no search index was used.",
"type": "string"
}
},
"type": "object"
},
+"InputDataChange": {
+"description": "Details about the input data change insight.",
+"id": "InputDataChange",
+"properties": {
+"recordsReadDiffPercentage": {
+"description": "Output only. Records read difference percentage compared to a previous run.",
+"format": "float",
+"readOnly": true,
+"type": "number"
+}
+},
+"type": "object"
+},
"IntArray": {
"description": "An array of int.",
"id": "IntArray",
@@ -3983,8 +4488,20 @@
"type": "object"
},
"IterationResult": {
+"description": "Information about a single iteration of the training run.",
"id": "IterationResult",
"properties": {
+"arimaResult": {
+"$ref": "ArimaResult",
+"description": "Arima result."
+},
+"clusterInfos": {
+"description": "Information about top clusters for clustering models.",
+"items": {
+"$ref": "ClusterInfo"
+},
+"type": "array"
+},
"durationMs": {
"description": "Time taken to run the iteration in milliseconds.",
"format": "int64",
@@ -4005,6 +4522,13 @@
"format": "double",
"type": "number"
},
+"principalComponentInfos": {
+"description": "The information of the principal components.",
+"items": {
+"$ref": "PrincipalComponentInfo"
+},
+"type": "array"
+},
"trainingLoss": {
"description": "Loss computed on the training data at the end of iteration.",
"format": "double",
@@ -4018,49 +4542,63 @@
"properties": {
"configuration": {
"$ref": "JobConfiguration",
-"description": "[Required] Describes the job configuration."
+"description": "Required. Describes the job configuration."
},
"etag": {
-"description": "[Output-only] A hash of this resource.",
+"description": "Output only. A hash of this resource.",
+"readOnly": true,
"type": "string"
},
"id": {
-"description": "[Output-only] Opaque ID field of the job",
+"description": "Output only. Opaque ID field of the job.",
+"readOnly": true,
"type": "string"
},
"jobCreationReason": {
-"description": "[Output-only] If set, it provides the reason why a Job was created. If not set, it should be treated as the default: REQUESTED. This feature is not yet available. Jobs will always be created.",
-"type": "any"
+"$ref": "JobCreationReason",
+"description": "Output only. If set, it provides the reason why a Job was created. If not set, it should be treated as the default: REQUESTED. This feature is not yet available. Jobs will always be created.",
+"readOnly": true
},
"jobReference": {
"$ref": "JobReference",
-"description": "[Optional] Reference describing the unique-per-user name of the job."
+"description": "Optional. Reference describing the unique-per-user name of the job."
},
"kind": {
"default": "bigquery#job",
-"description": "[Output-only] The type of the resource.",
+"description": "Output only. The type of the resource.",
+"readOnly": true,
+"type": "string"
+},
+"principal_subject": {
+"description": "Output only. [Full-projection-only] String representation of identity of requesting party. Populated for both first- and third-party identities. Only present for APIs that support third-party identities.",
+"readOnly": true,
"type": "string"
},
"selfLink": {
-"description": "[Output-only] A URL that can be used to access this resource again.",
+"description": "Output only. A URL that can be used to access the resource again.",
+"readOnly": true,
"type": "string"
},
"statistics": {
"$ref": "JobStatistics",
-"description": "[Output-only] Information about the job, including starting time and ending time of the job."
+"description": "Output only. Information about the job, including starting time and ending time of the job.",
+"readOnly": true
},
"status": {
"$ref": "JobStatus",
-"description": "[Output-only] The status of this job. Examine this value when polling an asynchronous job to see if the job is complete."
+"description": "Output only. The status of this job. Examine this value when polling an asynchronous job to see if the job is complete.",
+"readOnly": true
},
"user_email": {
-"description": "[Output-only] Email address of the user who ran the job.",
+"description": "Output only. Email address of the user who ran the job.",
+"readOnly": true,
"type": "string"
}
},
"type": "object"
},
"JobCancelResponse": {
+"description": "Describes format of a jobs cancellation response.",
"id": "JobCancelResponse",
"properties": {
"job": {
@@ -4083,7 +4621,7 @@
"description": "[Pick one] Copies a table."
},
"dryRun": {
-"description": "[Optional] If set, don't actually run this job. A valid query will return a mostly empty response with some processing statistics, while an invalid query will return the same error it would if it wasn't a dry run. Behavior of non-query jobs is undefined.",
+"description": "Optional. If set, don't actually run this job. A valid query will return a mostly empty response with some processing statistics, while an invalid query will return the same error it would if it wasn't a dry run. Behavior of non-query jobs is undefined.",
"type": "boolean"
},
"extract": {
@@ -4091,12 +4629,12 @@
"description": "[Pick one] Configures an extract job."
},
"jobTimeoutMs": {
-"description": "[Optional] Job timeout in milliseconds. If this time limit is exceeded, BigQuery may attempt to terminate the job.",
+"description": "Optional. Job timeout in milliseconds. If this time limit is exceeded, BigQuery might attempt to stop the job.",
"format": "int64",
"type": "string"
},
"jobType": {
-"description": "[Output-only] The type of the job. Can be QUERY, LOAD, EXTRACT, COPY or UNKNOWN.",
+"description": "Output only. The type of the job. Can be QUERY, LOAD, EXTRACT, COPY or UNKNOWN.",
"type": "string"
},
"labels": {
@@ -4118,14 +4656,15 @@
"type": "object"
},
"JobConfigurationExtract": {
+"description": "JobConfigurationExtract configures a job that exports data from a BigQuery table into Google Cloud Storage.",
"id": "JobConfigurationExtract",
"properties": {
"compression": {
-"description": "[Optional] The compression type to use for exported files. Possible values include GZIP, DEFLATE, SNAPPY, and NONE. The default value is NONE. DEFLATE and SNAPPY are only supported for Avro. Not applicable when extracting models.",
+"description": "Optional. The compression type to use for exported files. Possible values include DEFLATE, GZIP, NONE, SNAPPY, and ZSTD. The default value is NONE. Not all compression formats are support for all file formats. DEFLATE is only supported for Avro. ZSTD is only supported for Parquet. Not applicable when extracting models.",
"type": "string"
},
"destinationFormat": {
-"description": "[Optional] The exported file format. Possible values include CSV, NEWLINE_DELIMITED_JSON, PARQUET or AVRO for tables and ML_TF_SAVED_MODEL or ML_XGBOOST_BOOSTER for models. The default value for tables is CSV. Tables with nested or repeated fields cannot be exported as CSV. The default value for models is ML_TF_SAVED_MODEL.",
+"description": "Optional. The exported file format. Possible values include CSV, NEWLINE_DELIMITED_JSON, PARQUET, or AVRO for tables and ML_TF_SAVED_MODEL or ML_XGBOOST_BOOSTER for models. The default value for tables is CSV. Tables with nested or repeated fields cannot be exported as CSV. The default value for models is ML_TF_SAVED_MODEL.",
"type": "string"
},
"destinationUri": {
@@ -4140,12 +4679,16 @@
"type": "array"
},
"fieldDelimiter": {
-"description": "[Optional] Delimiter to use between fields in the exported data. Default is ','. Not applicable when extracting models.",
+"description": "Optional. When extracting data in CSV format, this defines the delimiter to use between fields in the exported data. Default is ','. Not applicable when extracting models.",
"type": "string"
},
+"modelExtractOptions": {
+"$ref": "ModelExtractOptions",
+"description": "Optional. Model extract options only applicable when extracting models."
+},
"printHeader": {
"default": "true",
-"description": "[Optional] Whether to print out a header row in the results. Default is true. Not applicable when extracting models.",
+"description": "Optional. Whether to print out a header row in the results. Default is true. Not applicable when extracting models.",
"type": "boolean"
},
"sourceModel": {
@@ -4157,17 +4700,18 @@
"description": "A reference to the table being exported."
},
"useAvroLogicalTypes": {
-"description": "[Optional] If destinationFormat is set to \"AVRO\", this flag indicates whether to enable extracting applicable column types (such as TIMESTAMP) to their corresponding AVRO logical types (timestamp-micros), instead of only using their raw types (avro-long). Not applicable when extracting models.",
+"description": "Whether to use logical types when extracting to AVRO format. Not applicable when extracting models.",
"type": "boolean"
}
},
"type": "object"
},
"JobConfigurationLoad": {
+"description": "JobConfigurationLoad contains the configuration properties for loading data into a destination table.",
"id": "JobConfigurationLoad",
"properties": {
"allowJaggedRows": {
-"description": "[Optional] Accept rows that are missing trailing optional columns. The missing values are treated as nulls. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. Only applicable to CSV, ignored for other formats.",
+"description": "Optional. Accept rows that are missing trailing optional columns. The missing values are treated as nulls. If false, records with missing trailing columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. Only applicable to CSV, ignored for other formats.",
"type": "boolean"
},
"allowQuotedNewlines": {
@@ -4175,38 +4719,50 @@
"type": "boolean"
},
"autodetect": {
-"description": "[Optional] Indicates if we should automatically infer the options and schema for CSV and JSON sources.",
+"description": "Optional. Indicates if we should automatically infer the options and schema for CSV and JSON sources.",
"type": "boolean"
},
"clustering": {
"$ref": "Clustering",
-"description": "[Beta] Clustering specification for the destination table. Must be specified with time-based partitioning, data in the table will be first partitioned and subsequently clustered."
+"description": "Clustering specification for the destination table."
},
"connectionProperties": {
-"description": "Connection properties.",
+"description": "Optional. Connection properties which can modify the load job behavior. Currently, only the 'session_id' connection property is supported, and is used to resolve _SESSION appearing as the dataset id.",
"items": {
"$ref": "ConnectionProperty"
},
"type": "array"
},
"createDisposition": {
-"description": "[Optional] Specifies whether the job is allowed to create new tables. The following values are supported: CREATE_IF_NEEDED: If the table does not exist, BigQuery creates the table. CREATE_NEVER: The table must already exist. If it does not, a 'notFound' error is returned in the job result. The default value is CREATE_IF_NEEDED. Creation, truncation and append actions occur as one atomic update upon job completion.",
+"description": "Optional. Specifies whether the job is allowed to create new tables. The following values are supported: * CREATE_IF_NEEDED: If the table does not exist, BigQuery creates the table. * CREATE_NEVER: The table must already exist. If it does not, a 'notFound' error is returned in the job result. The default value is CREATE_IF_NEEDED. Creation, truncation and append actions occur as one atomic update upon job completion.",
"type": "string"
},
"createSession": {
-"description": "If true, creates a new session, where session id will be a server generated random id. If false, runs query with an existing session_id passed in ConnectionProperty, otherwise runs the load job in non-session mode.",
+"description": "Optional. If this property is true, the job creates a new session using a randomly generated session_id. To continue using a created session with subsequent queries, pass the existing session identifier as a `ConnectionProperty` value. The session identifier is returned as part of the `SessionInfo` message within the query statistics. The new session's location will be set to `Job.JobReference.location` if it is present, otherwise it's set to the default location based on existing routing logic.",
"type": "boolean"
},
"decimalTargetTypes": {
-"description": "[Optional] Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown. Example: Suppose the value of this field is [\"NUMERIC\", \"BIGNUMERIC\"]. If (precision,scale) is: (38,9) -> NUMERIC; (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits); (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits); (76,38) -> BIGNUMERIC; (77,38) -> BIGNUMERIC (error if value exeeds supported range). This field cannot contain duplicate types. The order of the types in this field is ignored. For example, [\"BIGNUMERIC\", \"NUMERIC\"] is the same as [\"NUMERIC\", \"BIGNUMERIC\"] and NUMERIC always takes precedence over BIGNUMERIC. Defaults to [\"NUMERIC\", \"STRING\"] for ORC and [\"NUMERIC\"] for the other file formats.",
+"description": "Defines the list of possible SQL data types to which the source decimal values are converted. This list and the precision and the scale parameters of the decimal field determine the target type. In the order of NUMERIC, BIGNUMERIC, and STRING, a type is picked if it is in the specified list and if it supports the precision and the scale. STRING supports all precision and scale values. If none of the listed types supports the precision and the scale, the type supporting the widest range in the specified list is picked, and if a value exceeds the supported range when reading the data, an error will be thrown. Example: Suppose the value of this field is [\"NUMERIC\", \"BIGNUMERIC\"]. If (precision,scale) is: * (38,9) -> NUMERIC; * (39,9) -> BIGNUMERIC (NUMERIC cannot hold 30 integer digits); * (38,10) -> BIGNUMERIC (NUMERIC cannot hold 10 fractional digits); * (76,38) -> BIGNUMERIC; * (77,38) -> BIGNUMERIC (error if value exeeds supported range). This field cannot contain duplicate types. The order of the types in this field is ignored. For example, [\"BIGNUMERIC\", \"NUMERIC\"] is the same as [\"NUMERIC\", \"BIGNUMERIC\"] and NUMERIC always takes precedence over BIGNUMERIC. Defaults to [\"NUMERIC\", \"STRING\"] for ORC and [\"NUMERIC\"] for the other file formats.",
"items": {
+"enum": [
+"DECIMAL_TARGET_TYPE_UNSPECIFIED",
+"NUMERIC",
+"BIGNUMERIC",
+"STRING"
+],
+"enumDescriptions": [
+"Invalid type.",
+"Decimal values could be converted to NUMERIC type.",
+"Decimal values could be converted to BIGNUMERIC type.",
+"Decimal values could be converted to STRING type."
+],
"type": "string"
},
"type": "array"
},
"destinationEncryptionConfiguration": {
"$ref": "EncryptionConfiguration",
-"description": "Custom encryption configuration (e.g., Cloud KMS keys)."
+"description": "Custom encryption configuration (e.g., Cloud KMS keys)"
},
"destinationTable": {
"$ref": "TableReference",
@@ -4214,47 +4770,63 @@
},
"destinationTableProperties": {
"$ref": "DestinationTableProperties",
-"description": "[Beta] [Optional] Properties with which to create the destination table if it is new."
+"description": "Optional. [Experimental] Properties with which to create the destination table if it is new."
},
"encoding": {
-"description": "[Optional] The character encoding of the data. The supported values are UTF-8 or ISO-8859-1. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the quote and fieldDelimiter properties.",
+"description": "Optional. The character encoding of the data. The supported values are UTF-8, ISO-8859-1, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8. BigQuery decodes the data after the raw, binary data has been split using the values of the `quote` and `fieldDelimiter` properties. If you don't specify an encoding, or if you specify a UTF-8 encoding when the CSV file is not UTF-8 encoded, BigQuery attempts to convert the data to UTF-8. Generally, your data loads successfully, but it may not match byte-for-byte what you expect. To avoid this, specify the correct encoding by using the `--encoding` flag. If BigQuery can't convert a character other than the ASCII `0` character, BigQuery converts the character to the standard Unicode replacement character: \ufffd.",
"type": "string"
},
"fieldDelimiter": {
-"description": "[Optional] The separator for fields in a CSV file. The separator can be any ISO-8859-1 single-byte character. To use a character in the range 128-255, you must encode the character as UTF8. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. BigQuery also supports the escape sequence \"\\t\" to specify a tab separator. The default value is a comma (',').",
+"description": "Optional. The separator character for fields in a CSV file. The separator is interpreted as a single byte. For files encoded in ISO-8859-1, any single character can be used as a separator. For files encoded in UTF-8, characters represented in decimal range 1-127 (U+0001-U+007F) can be used without any modification. UTF-8 characters encoded with multiple bytes (i.e. U+0080 and above) will have only the first byte used for separating fields. The remaining bytes will be treated as a part of the field. BigQuery also supports the escape sequence \"\\t\" (U+0009) to specify a tab separator. The default value is comma (\",\", U+002C).",
"type": "string"
},
"fileSetSpecType": {
-"description": "[Optional] Specifies how source URIs are interpreted for constructing the file set to load. By default source URIs are expanded against the underlying storage. Other options include specifying manifest files. Only applicable to object storage systems.",
+"description": "Optional. Specifies how source URIs are interpreted for constructing the file set to load. By default, source URIs are expanded against the underlying storage. You can also specify manifest files to control how the file set is constructed. This option is only applicable to object storage systems.",
+"enum": [
+"FILE_SET_SPEC_TYPE_FILE_SYSTEM_MATCH",
+"FILE_SET_SPEC_TYPE_NEW_LINE_DELIMITED_MANIFEST"
+],
+"enumDescriptions": [
+"This option expands source URIs by listing files from the object store. It is the default behavior if FileSetSpecType is not set.",
+"This option indicates that the provided URIs are newline-delimited manifest files, with one URI per line. Wildcard URIs are not supported."
+],
"type": "string"
},
"hivePartitioningOptions": {
"$ref": "HivePartitioningOptions",
-"description": "[Optional] Options to configure hive partitioning support."
+"description": "Optional. When set, configures hive partitioning support. Not all storage formats support hive partitioning -- requesting hive partitioning on an unsupported format will lead to an error, as will providing an invalid specification."
},
"ignoreUnknownValues": {
-"description": "[Optional] Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names",
+"description": "Optional. Indicates if BigQuery should allow extra values that are not represented in the table schema. If true, the extra values are ignored. If false, records with extra columns are treated as bad records, and if there are too many bad records, an invalid error is returned in the job result. The default value is false. The sourceFormat property determines what BigQuery treats as an extra value: CSV: Trailing columns JSON: Named values that don't match any column names in the table schema Avro, Parquet, ORC: Fields in the file schema that don't exist in the table schema.",
"type": "boolean"
},
"jsonExtension": {
-"description": "[Optional] If sourceFormat is set to newline-delimited JSON, indicates whether it should be processed as a JSON variant such as GeoJSON. For a sourceFormat other than JSON, omit this field. If the sourceFormat is newline-delimited JSON: - for newline-delimited GeoJSON: set to GEOJSON.",
+"description": "Optional. Load option to be used together with source_format newline-delimited JSON to indicate that a variant of JSON is being loaded. To load newline-delimited GeoJSON, specify GEOJSON (and source_format must be set to NEWLINE_DELIMITED_JSON).",
+"enum": [
+"JSON_EXTENSION_UNSPECIFIED",
+"GEOJSON"
+],
+"enumDescriptions": [
+"The default if provided value is not one included in the enum, or the value is not specified. The source formate is parsed without any modification.",
+"Use GeoJSON variant of JSON. See https://tools.ietf.org/html/rfc7946."
+],
"type": "string"
},
"maxBadRecords": {
-"description": "[Optional] The maximum number of bad records that BigQuery can ignore when running the job. If the number of bad records exceeds this value, an invalid error is returned in the job result. This is only valid for CSV and JSON. The default value is 0, which requires that all records are valid.",
+"description": "Optional. The maximum number of bad records that BigQuery can ignore when running the job. If the number of bad records exceeds this value, an invalid error is returned in the job result. The default value is 0, which requires that all records are valid. This is only supported for CSV and NEWLINE_DELIMITED_JSON file formats.",
"format": "int32",
"type": "integer"
},
"nullMarker": {
-"description": "[Optional] Specifies a string that represents a null value in a CSV file. For example, if you specify \"\\N\", BigQuery interprets \"\\N\" as a null value when loading a CSV file. The default value is the empty string. If you set this property to a custom value, BigQuery throws an error if an empty string is present for all data types except for STRING and BYTE. For STRING and BYTE columns, BigQuery interprets the empty string as an empty value.",
+"description": "Optional. Specifies a string that represents a null value in a CSV file. For example, if you specify \"\\N\", BigQuery interprets \"\\N\" as a null value when loading a CSV file. The default value is the empty string. If you set this property to a custom value, BigQuery throws an error if an empty string is present for all data types except for STRING and BYTE. For STRING and BYTE columns, BigQuery interprets the empty string as an empty value.",
"type": "string"
},
"parquetOptions": {
"$ref": "ParquetOptions",
-"description": "[Optional] Options to configure parquet support."
+"description": "Optional. Additional properties to set if sourceFormat is set to PARQUET."
},
"preserveAsciiControlCharacters": {
-"description": "[Optional] Preserves the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\\x00' to '\\x1F') when loading from CSV. Only applicable to CSV, ignored for other formats.",
+"description": "Optional. When sourceFormat is set to \"CSV\", this indicates whether the embedded ASCII control characters (the first 32 characters in the ASCII-table, from '\\x00' to '\\x1F') are preserved.",
"type": "boolean"
},
"projectionFields": {
@@ -4266,21 +4838,21 @@
},
"quote": {
"default": "\"",
-"description": "[Optional] The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ('\"'). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true.",
+"description": "Optional. The value that is used to quote data sections in a CSV file. BigQuery converts the string to ISO-8859-1 encoding, and then uses the first byte of the encoded string to split the data in its raw, binary state. The default value is a double-quote ('\"'). If your data does not contain quoted sections, set the property value to an empty string. If your data contains quoted newline characters, you must also set the allowQuotedNewlines property to true. To include the specific quote character within a quoted value, precede it with an additional matching quote character. For example, if you want to escape the default character ' \" ', use ' \"\" '. @default \"",
"pattern": ".?",
"type": "string"
},
"rangePartitioning": {
"$ref": "RangePartitioning",
-"description": "[TrustedTester] Range partitioning specification for this table. Only one of timePartitioning and rangePartitioning should be specified."
+"description": "Range partitioning specification for the destination table. Only one of timePartitioning and rangePartitioning should be specified."
},
"referenceFileSchemaUri": {
-"description": "User provided referencing file with the expected reader schema, Available for the format: AVRO, PARQUET, ORC.",
+"description": "Optional. The user can provide a reference file with the reader schema. This file is only loaded if it is part of source URIs, but is not loaded otherwise. It is enabled for the following formats: AVRO, PARQUET, ORC.",
"type": "string"
},
"schema": {
"$ref": "TableSchema",
-"description": "[Optional] The schema for the destination table. The schema can be omitted if the destination table already exists, or if you're loading data from Google Cloud Datastore."
+"description": "Optional. The schema for the destination table. The schema can be omitted if the destination table already exists, or if you're loading data from Google Cloud Datastore."
},
"schemaInline": {
"description": "[Deprecated] The inline schema. For CSV schemas, specify as \"Field1:Type1[,Field2:Type2]*\". For example, \"foo:STRING, bar:INTEGER, baz:FLOAT\".",
@@ -4291,19 +4863,19 @@
"type": "string"
},
"schemaUpdateOptions": {
-"description": "Allows the schema of the destination table to be updated as a side effect of the load job if a schema is autodetected or supplied in the job configuration. Schema update options are supported in two cases: when writeDisposition is WRITE_APPEND; when writeDisposition is WRITE_TRUNCATE and the destination table is a partition of a table, specified by partition decorators. For normal tables, WRITE_TRUNCATE will always overwrite the schema. One or more of the following values are specified: ALLOW_FIELD_ADDITION: allow adding a nullable field to the schema. ALLOW_FIELD_RELAXATION: allow relaxing a required field in the original schema to nullable.",
+"description": "Allows the schema of the destination table to be updated as a side effect of the load job if a schema is autodetected or supplied in the job configuration. Schema update options are supported in two cases: when writeDisposition is WRITE_APPEND; when writeDisposition is WRITE_TRUNCATE and the destination table is a partition of a table, specified by partition decorators. For normal tables, WRITE_TRUNCATE will always overwrite the schema. One or more of the following values are specified: * ALLOW_FIELD_ADDITION: allow adding a nullable field to the schema. * ALLOW_FIELD_RELAXATION: allow relaxing a required field in the original schema to nullable.",
"items": {
"type": "string"
},
"type": "array"
},
"skipLeadingRows": {
-"description": "[Optional] The number of rows at the top of a CSV file that BigQuery will skip when loading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped.",
+"description": "Optional. The number of rows at the top of a CSV file that BigQuery will skip when loading the data. The default value is 0. This property is useful if you have header rows in the file that should be skipped. When autodetect is on, the behavior is the following: * skipLeadingRows unspecified - Autodetect tries to detect headers in the first row. If they are not detected, the row is read as data. Otherwise data is read starting from the second row. * skipLeadingRows is 0 - Instructs autodetect that there are no headers and data should be read starting from the first row. * skipLeadingRows = N > 0 - Autodetect skips N-1 rows and tries to detect headers in row N. If headers are not detected, row N is just skipped. Otherwise row N is used to extract column names for the detected schema.",
"format": "int32",
"type": "integer"
},
"sourceFormat": {
-"description": "[Optional] The format of the data files. For CSV files, specify \"CSV\". For datastore backups, specify \"DATASTORE_BACKUP\". For newline-delimited JSON, specify \"NEWLINE_DELIMITED_JSON\". For Avro, specify \"AVRO\". For parquet, specify \"PARQUET\". For orc, specify \"ORC\". The default value is CSV.",
+"description": "Optional. The format of the data files. For CSV files, specify \"CSV\". For datastore backups, specify \"DATASTORE_BACKUP\". For newline-delimited JSON, specify \"NEWLINE_DELIMITED_JSON\". For Avro, specify \"AVRO\". For parquet, specify \"PARQUET\". For orc, specify \"ORC\". The default value is CSV.",
"type": "string"
},
"sourceUris": {
@@ -4318,30 +4890,31 @@
"description": "Time-based partitioning specification for the destination table. Only one of timePartitioning and rangePartitioning should be specified."
},
"useAvroLogicalTypes": {
-"description": "[Optional] If sourceFormat is set to \"AVRO\", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER).",
+"description": "Optional. If sourceFormat is set to \"AVRO\", indicates whether to interpret logical types as the corresponding BigQuery data type (for example, TIMESTAMP), instead of using the raw type (for example, INTEGER).",
"type": "boolean"
},
"writeDisposition": {
-"description": "[Optional] Specifies the action that occurs if the destination table already exists. The following values are supported: WRITE_TRUNCATE: If the table already exists, BigQuery overwrites the table data. WRITE_APPEND: If the table already exists, BigQuery appends the data to the table. WRITE_EMPTY: If the table already exists and contains data, a 'duplicate' error is returned in the job result. The default value is WRITE_APPEND. Each action is atomic and only occurs if BigQuery is able to complete the job successfully. Creation, truncation and append actions occur as one atomic update upon job completion.",
+"description": "Optional. Specifies the action that occurs if the destination table already exists. The following values are supported: * WRITE_TRUNCATE: If the table already exists, BigQuery overwrites the data, removes the constraints and uses the schema from the load job. * WRITE_APPEND: If the table already exists, BigQuery appends the data to the table. * WRITE_EMPTY: If the table already exists and contains data, a 'duplicate' error is returned in the job result. The default value is WRITE_APPEND. Each action is atomic and only occurs if BigQuery is able to complete the job successfully. Creation, truncation and append actions occur as one atomic update upon job completion.",
"type": "string"
}
},
"type": "object"
},
"JobConfigurationQuery": {
+"description": "JobConfigurationQuery configures a BigQuery query job.",
"id": "JobConfigurationQuery",
"properties": {
"allowLargeResults": {
"default": "false",
-"description": "[Optional] If true and query uses legacy SQL dialect, allows the query to produce arbitrarily large result tables at a slight cost in performance. Requires destinationTable to be set. For standard SQL queries, this flag is ignored and large results are always allowed. However, you must still set destinationTable when result size exceeds the allowed maximum response size.",
+"description": "Optional. If true and query uses legacy SQL dialect, allows the query to produce arbitrarily large result tables at a slight cost in performance. Requires destinationTable to be set. For GoogleSQL queries, this flag is ignored and large results are always allowed. However, you must still set destinationTable when result size exceeds the allowed maximum response size.",
"type": "boolean"
},
"clustering": {
"$ref": "Clustering",
-"description": "[Beta] Clustering specification for the destination table. Must be specified with time-based partitioning, data in the table will be first partitioned and subsequently clustered."
+"description": "Clustering specification for the destination table."
},
"connectionProperties": {
-"description": "Connection properties.",
+"description": "Connection properties which can modify the query behavior.",
"items": {
"$ref": "ConnectionProperty"
},
@@ -4352,43 +4925,43 @@
"type": "boolean"
},
"createDisposition": {
-"description": "[Optional] Specifies whether the job is allowed to create new tables. The following values are supported: CREATE_IF_NEEDED: If the table does not exist, BigQuery creates the table. CREATE_NEVER: The table must already exist. If it does not, a 'notFound' error is returned in the job result. The default value is CREATE_IF_NEEDED. Creation, truncation and append actions occur as one atomic update upon job completion.",
+"description": "Optional. Specifies whether the job is allowed to create new tables. The following values are supported: * CREATE_IF_NEEDED: If the table does not exist, BigQuery creates the table. * CREATE_NEVER: The table must already exist. If it does not, a 'notFound' error is returned in the job result. The default value is CREATE_IF_NEEDED. Creation, truncation and append actions occur as one atomic update upon job completion.",
"type": "string"
},
"createSession": {
-"description": "If true, creates a new session, where session id will be a server generated random id. If false, runs query with an existing session_id passed in ConnectionProperty, otherwise runs query in non-session mode.",
+"description": "If this property is true, the job creates a new session using a randomly generated session_id. To continue using a created session with subsequent queries, pass the existing session identifier as a `ConnectionProperty` value. The session identifier is returned as part of the `SessionInfo` message within the query statistics. The new session's location will be set to `Job.JobReference.location` if it is present, otherwise it's set to the default location based on existing routing logic.",
"type": "boolean"
},
"defaultDataset": {
"$ref": "DatasetReference",
-"description": "[Optional] Specifies the default dataset to use for unqualified table names in the query. Note that this does not alter behavior of unqualified dataset names."
+"description": "Optional. Specifies the default dataset to use for unqualified table names in the query. This setting does not alter behavior of unqualified dataset names. Setting the system variable `@@dataset_id` achieves the same behavior. See https://cloud.google.com/bigquery/docs/reference/system-variables for more information on system variables."
},
"destinationEncryptionConfiguration": {
"$ref": "EncryptionConfiguration",
-"description": "Custom encryption configuration (e.g., Cloud KMS keys)."
+"description": "Custom encryption configuration (e.g., Cloud KMS keys)"
},
"destinationTable": {
"$ref": "TableReference",
-"description": "[Optional] Describes the table where the query results should be stored. If not present, a new table will be created to store the results. This property must be set for large results that exceed the maximum response size."
+"description": "Optional. Describes the table where the query results should be stored. This property must be set for large results that exceed the maximum response size. For queries that produce anonymous (cached) results, this field will be populated by BigQuery."
},
"flattenResults": {
"default": "true",
-"description": "[Optional] If true and query uses legacy SQL dialect, flattens all nested and repeated fields in the query results. allowLargeResults must be true if this is set to false. For standard SQL queries, this flag is ignored and results are never flattened.",
+"description": "Optional. If true and query uses legacy SQL dialect, flattens all nested and repeated fields in the query results. allowLargeResults must be true if this is set to false. For GoogleSQL queries, this flag is ignored and results are never flattened.",
"type": "boolean"
},
"maximumBillingTier": {
"default": "1",
-"description": "[Optional] Limits the billing tier for this job. Queries that have resource usage beyond this tier will fail (without incurring a charge). If unspecified, this will be set to your project default.",
+"description": "Optional. [Deprecated] Maximum billing tier allowed for this query. The billing tier controls the amount of compute resources allotted to the query, and multiplies the on-demand cost of the query accordingly. A query that runs within its allotted resources will succeed and indicate its billing tier in statistics.query.billingTier, but if the query exceeds its allotted resources, it will fail with billingTierLimitExceeded. WARNING: The billed byte amount can be multiplied by an amount up to this number! Most users should not need to alter this setting, and we recommend that you avoid introducing new uses of it.",
"format": "int32",
"type": "integer"
},
"maximumBytesBilled": {
-"description": "[Optional] Limits the bytes billed for this job. Queries that will have bytes billed beyond this limit will fail (without incurring a charge). If unspecified, this will be set to your project default.",
+"description": "Limits the bytes billed for this job. Queries that will have bytes billed beyond this limit will fail (without incurring a charge). If unspecified, this will be set to your project default.",
"format": "int64",
"type": "string"
},
"parameterMode": {
-"description": "Standard SQL only. Set to POSITIONAL to use positional (?) query parameters or to NAMED to use named (@myparam) query parameters in this query.",
+"description": "GoogleSQL only. Set to POSITIONAL to use positional (?) query parameters or to NAMED to use named (@myparam) query parameters in this query.",
"type": "string"
},
"preserveNulls": {
@@ -4396,15 +4969,15 @@
"type": "boolean"
},
"priority": {
-"description": "[Optional] Specifies a priority for the query. Possible values include INTERACTIVE and BATCH. The default value is INTERACTIVE.",
+"description": "Optional. Specifies a priority for the query. Possible values include INTERACTIVE and BATCH. The default value is INTERACTIVE.",
"type": "string"
},
"query": {
-"description": "[Required] SQL query text to execute. The useLegacySql field can be used to indicate whether the query uses legacy SQL or standard SQL.",
+"description": "[Required] SQL query text to execute. The useLegacySql field can be used to indicate whether the query uses legacy SQL or GoogleSQL.",
"type": "string"
},
"queryParameters": {
-"description": "Query parameters for standard SQL queries.",
+"description": "Query parameters for GoogleSQL queries.",
"items": {
"$ref": "QueryParameter"
},
@@ -4412,20 +4985,29 @@
},
"rangePartitioning": {
"$ref": "RangePartitioning",
-"description": "[TrustedTester] Range partitioning specification for this table. Only one of timePartitioning and rangePartitioning should be specified."
+"description": "Range partitioning specification for the destination table. Only one of timePartitioning and rangePartitioning should be specified."
},
"schemaUpdateOptions": {
-"description": "Allows the schema of the destination table to be updated as a side effect of the query job. Schema update options are supported in two cases: when writeDisposition is WRITE_APPEND; when writeDisposition is WRITE_TRUNCATE and the destination table is a partition of a table, specified by partition decorators. For normal tables, WRITE_TRUNCATE will always overwrite the schema. One or more of the following values are specified: ALLOW_FIELD_ADDITION: allow adding a nullable field to the schema. ALLOW_FIELD_RELAXATION: allow relaxing a required field in the original schema to nullable.",
+"description": "Allows the schema of the destination table to be updated as a side effect of the query job. Schema update options are supported in two cases: when writeDisposition is WRITE_APPEND; when writeDisposition is WRITE_TRUNCATE and the destination table is a partition of a table, specified by partition decorators. For normal tables, WRITE_TRUNCATE will always overwrite the schema. One or more of the following values are specified: * ALLOW_FIELD_ADDITION: allow adding a nullable field to the schema. * ALLOW_FIELD_RELAXATION: allow relaxing a required field in the original schema to nullable.",
"items": {
"type": "string"
},
"type": "array"
},
+"scriptOptions": {
+"$ref": "ScriptOptions",
+"description": "Options controlling the execution of scripts."
+},
+"systemVariables": {
+"$ref": "SystemVariables",
+"description": "Output only. System variables for GoogleSQL queries. A system variable is output if the variable is settable and its value differs from the system default. \"@@\" prefix is not included in the name of the System variables.",
+"readOnly": true
+},
"tableDefinitions": {
"additionalProperties": {
"$ref": "ExternalDataConfiguration"
},
-"description": "[Optional] If querying an external data source outside of BigQuery, describes the data format, location and other properties of the data source. By defining these properties, the data source can then be queried as if it were a standard BigQuery table.",
+"description": "Optional. You can specify external table definitions, which operate as ephemeral tables that can be queried. These definitions are configured using a JSON map, where the string key represents the table identifier, and the value is the corresponding external data configuration object.",
"type": "object"
},
"timePartitioning": {
@@ -4434,12 +5016,12 @@
},
"useLegacySql": {
"default": "true",
-"description": "Specifies whether to use BigQuery's legacy SQL dialect for this query. The default value is true. If set to false, the query will use BigQuery's standard SQL: https://cloud.google.com/bigquery/sql-reference/ When useLegacySql is set to false, the value of flattenResults is ignored; query will be run as if flattenResults is false.",
+"description": "Optional. Specifies whether to use BigQuery's legacy SQL dialect for this query. The default value is true. If set to false, the query will use BigQuery's GoogleSQL: https://cloud.google.com/bigquery/sql-reference/ When useLegacySql is set to false, the value of flattenResults is ignored; query will be run as if flattenResults is false.",
"type": "boolean"
},
"useQueryCache": {
"default": "true",
-"description": "[Optional] Whether to look for the result in the query cache. The query cache is a best-effort cache that will be flushed whenever tables in the query are modified. Moreover, the query cache is only available when a query does not have a destination table specified. The default value is true.",
+"description": "Optional. Whether to look for the result in the query cache. The query cache is a best-effort cache that will be flushed whenever tables in the query are modified. Moreover, the query cache is only available when a query does not have a destination table specified. The default value is true.",
"type": "boolean"
},
"userDefinedFunctionResources": {
@@ -4450,17 +5032,18 @@
"type": "array"
},
"writeDisposition": {
-"description": "[Optional] Specifies the action that occurs if the destination table already exists. The following values are supported: WRITE_TRUNCATE: If the table already exists, BigQuery overwrites the table data and uses the schema from the query result. WRITE_APPEND: If the table already exists, BigQuery appends the data to the table. WRITE_EMPTY: If the table already exists and contains data, a 'duplicate' error is returned in the job result. The default value is WRITE_EMPTY. Each action is atomic and only occurs if BigQuery is able to complete the job successfully. Creation, truncation and append actions occur as one atomic update upon job completion.",
+"description": "Optional. Specifies the action that occurs if the destination table already exists. The following values are supported: * WRITE_TRUNCATE: If the table already exists, BigQuery overwrites the data, removes the constraints, and uses the schema from the query result. * WRITE_APPEND: If the table already exists, BigQuery appends the data to the table. * WRITE_EMPTY: If the table already exists and contains data, a 'duplicate' error is returned in the job result. The default value is WRITE_EMPTY. Each action is atomic and only occurs if BigQuery is able to complete the job successfully. Creation, truncation and append actions occur as one atomic update upon job completion.",
"type": "string"
}
},
"type": "object"
},
"JobConfigurationTableCopy": {
+"description": "JobConfigurationTableCopy configures a job that copies data from one table to another. For more information on copying tables, see [Copy a table](https://cloud.google.com/bigquery/docs/managing-tables#copy-table).",
"id": "JobConfigurationTableCopy",
"properties": {
"createDisposition": {
-"description": "[Optional] Specifies whether the job is allowed to create new tables. The following values are supported: CREATE_IF_NEEDED: If the table does not exist, BigQuery creates the table. CREATE_NEVER: The table must already exist. If it does not, a 'notFound' error is returned in the job result. The default value is CREATE_IF_NEEDED. Creation, truncation and append actions occur as one atomic update upon job completion.",
+"description": "Optional. Specifies whether the job is allowed to create new tables. The following values are supported: * CREATE_IF_NEEDED: If the table does not exist, BigQuery creates the table. * CREATE_NEVER: The table must already exist. If it does not, a 'notFound' error is returned in the job result. The default value is CREATE_IF_NEEDED. Creation, truncation and append actions occur as one atomic update upon job completion.",
"type": "string"
},
"destinationEncryptionConfiguration": {
@@ -4468,15 +5051,30 @@
"description": "Custom encryption configuration (e.g., Cloud KMS keys)."
},
"destinationExpirationTime": {
-"description": "[Optional] The time when the destination table expires. Expired tables will be deleted and their storage reclaimed.",
-"type": "any"
+"description": "Optional. The time when the destination table expires. Expired tables will be deleted and their storage reclaimed.",
+"format": "google-datetime",
+"type": "string"
},
"destinationTable": {
"$ref": "TableReference",
-"description": "[Required] The destination table"
+"description": "[Required] The destination table."
},
"operationType": {
-"description": "[Optional] Supported operation types in table copy job.",
+"description": "Optional. Supported operation types in table copy job.",
+"enum": [
+"OPERATION_TYPE_UNSPECIFIED",
+"COPY",
+"SNAPSHOT",
+"RESTORE",
+"CLONE"
+],
+"enumDescriptions": [
+"Unspecified operation type.",
+"The source and destination table have the same table type.",
+"The source table type is TABLE and the destination table type is SNAPSHOT.",
+"The source table type is SNAPSHOT and the destination table type is TABLE.",
+"The source and destination table have the same table type, but only bill for unique data."
+],
"type": "string"
},
"sourceTable": {
@@ -4491,7 +5089,7 @@
"type": "array"
},
"writeDisposition": {
-"description": "[Optional] Specifies the action that occurs if the destination table already exists. The following values are supported: WRITE_TRUNCATE: If the table already exists, BigQuery overwrites the table data. WRITE_APPEND: If the table already exists, BigQuery appends the data to the table. WRITE_EMPTY: If the table already exists and contains data, a 'duplicate' error is returned in the job result. The default value is WRITE_EMPTY. Each action is atomic and only occurs if BigQuery is able to complete the job successfully. Creation, truncation and append actions occur as one atomic update upon job completion.",
+"description": "Optional. Specifies the action that occurs if the destination table already exists. The following values are supported: * WRITE_TRUNCATE: If the table already exists, BigQuery overwrites the table data and uses the schema and table constraints from the source table. * WRITE_APPEND: If the table already exists, BigQuery appends the data to the table. * WRITE_EMPTY: If the table already exists and contains data, a 'duplicate' error is returned in the job result. The default value is WRITE_EMPTY. Each action is atomic and only occurs if BigQuery is able to complete the job successfully. Creation, truncation and append actions occur as one atomic update upon job completion.",
"type": "string"
}
},
@@ -4524,6 +5122,7 @@
"type": "object"
},
"JobList": {
+"description": "JobList is the response format for a jobs.list call.",
"id": "JobList",
"properties": {
"etag": {
@@ -4533,10 +5132,11 @@
"jobs": {
"description": "List of jobs that were requested.",
"items": {
+"description": "ListFormatJob is a partial projection of job information returned as part of a jobs.list response.",
"properties": {
"configuration": {
"$ref": "JobConfiguration",
-"description": "[Full-projection-only] Specifies the job configuration."
+"description": "Required. Describes the job configuration."
},
"errorResult": {
"$ref": "ErrorProto",
@@ -4548,24 +5148,28 @@
},
"jobReference": {
"$ref": "JobReference",
-"description": "Job reference uniquely identifying the job."
+"description": "Unique opaque ID of the job."
},
"kind": {
-"default": "bigquery#job",
"description": "The resource type.",
"type": "string"
},
+"principal_subject": {
+"description": "[Full-projection-only] String representation of identity of requesting party. Populated for both first- and third-party identities. Only present for APIs that support third-party identities.",
+"type": "string"
+},
"state": {
"description": "Running state of the job. When the state is DONE, errorResult can be checked to determine whether the job succeeded or failed.",
"type": "string"
},
"statistics": {
"$ref": "JobStatistics",
-"description": "[Output-only] Information about the job, including starting time and ending time of the job."
+"description": "Output only. Information about the job, including starting time and ending time of the job.",
+"readOnly": true
},
"status": {
"$ref": "JobStatus",
-"description": "[Full-projection-only] Describes the state of the job."
+"description": "[Full-projection-only] Describes the status of this job."
},
"user_email": {
"description": "[Full-projection-only] Email address of the user who ran the job.",
@@ -4584,387 +5188,533 @@
"nextPageToken": {
"description": "A token to request the next page of results.",
"type": "string"
+},
+"unreachable": {
+"description": "A list of skipped locations that were unreachable. For more information about BigQuery locations, see: https://cloud.google.com/bigquery/docs/locations. Example: \"europe-west5\"",
+"items": {
+"type": "string"
+},
+"type": "array"
}
},
"type": "object"
},
"JobReference": {
+"description": "A job reference is a fully qualified identifier for referring to a job.",
"id": "JobReference",
"properties": {
"jobId": {
-"annotations": {
-"required": [
-"bigquery.jobs.getQueryResults"
-]
-},
-"description": "[Required] The ID of the job. The ID must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), or dashes (-). The maximum length is 1,024 characters.",
+"description": "Required. The ID of the job. The ID must contain only letters (a-z, A-Z), numbers (0-9), underscores (_), or dashes (-). The maximum length is 1,024 characters.",
"type": "string"
},
"location": {
-"description": "The geographic location of the job. See details at https://cloud.google.com/bigquery/docs/locations#specifying_your_location.",
+"description": "Optional. The geographic location of the job. The default value is US. For more information about BigQuery locations, see: https://cloud.google.com/bigquery/docs/locations",
"type": "string"
},
"projectId": {
-"annotations": {
-"required": [
-"bigquery.jobs.getQueryResults"
-]
-},
-"description": "[Required] The ID of the project containing this job.",
+"description": "Required. The ID of the project containing this job.",
"type": "string"
}
},
"type": "object"
},
"JobStatistics": {
+"description": "Statistics for a single job execution.",
"id": "JobStatistics",
"properties": {
"completionRatio": {
-"description": "[TrustedTester] [Output-only] Job progress (0.0 -> 1.0) for LOAD and EXTRACT jobs.",
+"description": "Output only. [TrustedTester] Job progress (0.0 -> 1.0) for LOAD and EXTRACT jobs.",
"format": "double",
+"readOnly": true,
"type": "number"
},
"copy": {
"$ref": "JobStatistics5",
-"description": "[Output-only] Statistics for a copy job."
+"description": "Output only. Statistics for a copy job.",
+"readOnly": true
},
"creationTime": {
-"description": "[Output-only] Creation time of this job, in milliseconds since the epoch. This field will be present on all jobs.",
+"description": "Output only. Creation time of this job, in milliseconds since the epoch. This field will be present on all jobs.",
"format": "int64",
+"readOnly": true,
"type": "string"
},
"dataMaskingStatistics": {
"$ref": "DataMaskingStatistics",
-"description": "[Output-only] Statistics for data masking. Present only for query and extract jobs."
+"description": "Output only. Statistics for data-masking. Present only for query and extract jobs.",
+"readOnly": true
},
"endTime": {
-"description": "[Output-only] End time of this job, in milliseconds since the epoch. This field will be present whenever a job is in the DONE state.",
+"description": "Output only. End time of this job, in milliseconds since the epoch. This field will be present whenever a job is in the DONE state.",
"format": "int64",
+"readOnly": true,
"type": "string"
},
"extract": {
"$ref": "JobStatistics4",
-"description": "[Output-only] Statistics for an extract job."
+"description": "Output only. Statistics for an extract job.",
+"readOnly": true
+},
+"finalExecutionDurationMs": {
+"description": "Output only. The duration in milliseconds of the execution of the final attempt of this job, as BigQuery may internally re-attempt to execute the job.",
+"format": "int64",
+"readOnly": true,
+"type": "string"
},
"load": {
"$ref": "JobStatistics3",
-"description": "[Output-only] Statistics for a load job."
+"description": "Output only. Statistics for a load job.",
+"readOnly": true
},
"numChildJobs": {
-"description": "[Output-only] Number of child jobs executed.",
+"description": "Output only. Number of child jobs executed.",
"format": "int64",
+"readOnly": true,
"type": "string"
},
"parentJobId": {
-"description": "[Output-only] If this is a child job, the id of the parent.",
+"description": "Output only. If this is a child job, specifies the job ID of the parent.",
+"readOnly": true,
"type": "string"
},
"query": {
"$ref": "JobStatistics2",
-"description": "[Output-only] Statistics for a query job."
+"description": "Output only. Statistics for a query job.",
+"readOnly": true
},
"quotaDeferments": {
-"description": "[Output-only] Quotas which delayed this job's start time.",
+"description": "Output only. Quotas which delayed this job's start time.",
"items": {
"type": "string"
},
+"readOnly": true,
"type": "array"
},
"reservationUsage": {
-"description": "[Output-only] Job resource usage breakdown by reservation.",
+"deprecated": true,
+"description": "Output only. Job resource usage breakdown by reservation. This field reported misleading information and will no longer be populated.",
"items": {
+"description": "Job resource usage breakdown by reservation.",
"properties": {
"name": {
-"description": "[Output-only] Reservation name or \"unreserved\" for on-demand resources usage.",
+"description": "Reservation name or \"unreserved\" for on-demand resources usage.",
"type": "string"
},
"slotMs": {
-"description": "[Output-only] Slot-milliseconds the job spent in the given reservation.",
+"description": "Total slot milliseconds used by the reservation for a particular job.",
"format": "int64",
"type": "string"
}
},
"type": "object"
},
+"readOnly": true,
"type": "array"
},
"reservation_id": {
-"description": "[Output-only] Name of the primary reservation assigned to this job. Note that this could be different than reservations reported in the reservation usage field if parent reservations were used to execute this job.",
+"description": "Output only. Name of the primary reservation assigned to this job. Note that this could be different than reservations reported in the reservation usage field if parent reservations were used to execute this job.",
+"readOnly": true,
"type": "string"
},
"rowLevelSecurityStatistics": {
"$ref": "RowLevelSecurityStatistics",
-"description": "[Output-only] [Preview] Statistics for row-level security. Present only for query and extract jobs."
+"description": "Output only. Statistics for row-level security. Present only for query and extract jobs.",
+"readOnly": true
},
"scriptStatistics": {
"$ref": "ScriptStatistics",
-"description": "[Output-only] Statistics for a child job of a script."
+"description": "Output only. If this a child job of a script, specifies information about the context of this job within the script.",
+"readOnly": true
},
"sessionInfo": {
"$ref": "SessionInfo",
-"description": "[Output-only] [Preview] Information of the session if this job is part of one."
+"description": "Output only. Information of the session if this job is part of one.",
+"readOnly": true
},
"startTime": {
-"description": "[Output-only] Start time of this job, in milliseconds since the epoch. This field will be present when the job transitions from the PENDING state to either RUNNING or DONE.",
+"description": "Output only. Start time of this job, in milliseconds since the epoch. This field will be present when the job transitions from the PENDING state to either RUNNING or DONE.",
"format": "int64",
+"readOnly": true,
"type": "string"
},
"totalBytesProcessed": {
-"description": "[Output-only] [Deprecated] Use the bytes processed in the query statistics instead.",
+"description": "Output only. Total bytes processed for the job.",
"format": "int64",
+"readOnly": true,
"type": "string"
},
"totalSlotMs": {
-"description": "[Output-only] Slot-milliseconds for the job.",
+"description": "Output only. Slot-milliseconds for the job.",
"format": "int64",
+"readOnly": true,
"type": "string"
},
"transactionInfo": {
"$ref": "TransactionInfo",
-"description": "[Output-only] [Alpha] Information of the multi-statement transaction if this job is part of one."
+"description": "Output only. [Alpha] Information of the multi-statement transaction if this job is part of one. This property is only expected on a child job or a job that is in a session. A script parent job is not part of the transaction started in the script.",
+"readOnly": true
}
},
"type": "object"
},
"JobStatistics2": {
+"description": "Statistics for a query job.",
"id": "JobStatistics2",
"properties": {
"biEngineStatistics": {
"$ref": "BiEngineStatistics",
-"description": "BI Engine specific Statistics. [Output only] BI Engine specific Statistics."
+"description": "Output only. BI Engine specific Statistics.",
+"readOnly": true
},
"billingTier": {
-"description": "[Output only] Billing tier for the job.",
+"description": "Output only. Billing tier for the job. This is a BigQuery-specific concept which is not related to the Google Cloud notion of \"free tier\". The value here is a measure of the query's resource consumption relative to the amount of data scanned. For on-demand queries, the limit is 100, and all queries within this limit are billed at the standard on-demand rates. On-demand queries that exceed this limit will fail with a billingTierLimitExceeded error.",
"format": "int32",
+"readOnly": true,
"type": "integer"
},
"cacheHit": {
-"description": "[Output only] Whether the query result was fetched from the query cache.",
+"description": "Output only. Whether the query result was fetched from the query cache.",
+"readOnly": true,
"type": "boolean"
},
+"dclTargetDataset": {
+"$ref": "DatasetReference",
+"description": "Output only. Referenced dataset for DCL statement.",
+"readOnly": true
+},
+"dclTargetTable": {
+"$ref": "TableReference",
+"description": "Output only. Referenced table for DCL statement.",
+"readOnly": true
+},
+"dclTargetView": {
+"$ref": "TableReference",
+"description": "Output only. Referenced view for DCL statement.",
+"readOnly": true
+},
"ddlAffectedRowAccessPolicyCount": {
-"description": "[Output only] [Preview] The number of row access policies affected by a DDL statement. Present only for DROP ALL ROW ACCESS POLICIES queries.",
+"description": "Output only. The number of row access policies affected by a DDL statement. Present only for DROP ALL ROW ACCESS POLICIES queries.",
"format": "int64",
+"readOnly": true,
"type": "string"
},
"ddlDestinationTable": {
"$ref": "TableReference",
-"description": "[Output only] The DDL destination table. Present only for ALTER TABLE RENAME TO queries. Note that ddl_target_table is used just for its type information."
+"description": "Output only. The table after rename. Present only for ALTER TABLE RENAME TO query.",
+"readOnly": true
},
"ddlOperationPerformed": {
-"description": "The DDL operation performed, possibly dependent on the pre-existence of the DDL target. Possible values (new values might be added in the future): \"CREATE\": The query created the DDL target. \"SKIP\": No-op. Example cases: the query is CREATE TABLE IF NOT EXISTS while the table already exists, or the query is DROP TABLE IF EXISTS while the table does not exist. \"REPLACE\": The query replaced the DDL target. Example case: the query is CREATE OR REPLACE TABLE, and the table already exists. \"DROP\": The query deleted the DDL target.",
+"description": "Output only. The DDL operation performed, possibly dependent on the pre-existence of the DDL target.",
+"readOnly": true,
"type": "string"
},
"ddlTargetDataset": {
"$ref": "DatasetReference",
-"description": "[Output only] The DDL target dataset. Present only for CREATE/ALTER/DROP/UNDROP SCHEMA queries."
+"description": "Output only. The DDL target dataset. Present only for CREATE/ALTER/DROP SCHEMA(dataset) queries.",
+"readOnly": true
},
"ddlTargetRoutine": {
"$ref": "RoutineReference",
-"description": "The DDL target routine. Present only for CREATE/DROP FUNCTION/PROCEDURE queries."
+"description": "Output only. [Beta] The DDL target routine. Present only for CREATE/DROP FUNCTION/PROCEDURE queries.",
+"readOnly": true
},
"ddlTargetRowAccessPolicy": {
"$ref": "RowAccessPolicyReference",
-"description": "[Output only] [Preview] The DDL target row access policy. Present only for CREATE/DROP ROW ACCESS POLICY queries."
+"description": "Output only. The DDL target row access policy. Present only for CREATE/DROP ROW ACCESS POLICY queries.",
+"readOnly": true
},
"ddlTargetTable": {
"$ref": "TableReference",
-"description": "[Output only] The DDL target table. Present only for CREATE/DROP TABLE/VIEW and DROP ALL ROW ACCESS POLICIES queries."
+"description": "Output only. The DDL target table. Present only for CREATE/DROP TABLE/VIEW and DROP ALL ROW ACCESS POLICIES queries.",
+"readOnly": true
},
"dmlStats": {
"$ref": "DmlStatistics",
-"description": "[Output only] Detailed statistics for DML statements Present only for DML statements INSERT, UPDATE, DELETE or TRUNCATE."
+"description": "Output only. Detailed statistics for DML statements INSERT, UPDATE, DELETE, MERGE or TRUNCATE.",
+"readOnly": true
},
"estimatedBytesProcessed": {
-"description": "[Output only] The original estimate of bytes processed for the job.",
+"description": "Output only. The original estimate of bytes processed for the job.",
"format": "int64",
+"readOnly": true,
"type": "string"
},
+"exportDataStatistics": {
+"$ref": "ExportDataStatistics",
+"description": "Output only. Stats for EXPORT DATA statement.",
+"readOnly": true
+},
+"externalServiceCosts": {
+"description": "Output only. Job cost breakdown as bigquery internal cost and external service costs.",
+"items": {
+"$ref": "ExternalServiceCost"
+},
+"readOnly": true,
+"type": "array"
+},
+"loadQueryStatistics": {
+"$ref": "LoadQueryStatistics",
+"description": "Output only. Statistics for a LOAD query.",
+"readOnly": true
+},
+"materializedViewStatistics": {
+"$ref": "MaterializedViewStatistics",
+"description": "Output only. Statistics of materialized views of a query job.",
+"readOnly": true
+},
+"metadataCacheStatistics": {
+"$ref": "MetadataCacheStatistics",
+"description": "Output only. Statistics of metadata cache usage in a query for BigLake tables.",
+"readOnly": true
+},
"mlStatistics": {
"$ref": "MlStatistics",
-"description": "[Output only] Statistics of a BigQuery ML training job."
+"description": "Output only. Statistics of a BigQuery ML training job.",
+"readOnly": true
},
"modelTraining": {
"$ref": "BigQueryModelTraining",
-"description": "[Output only, Beta] Information about create model query job progress."
+"description": "Deprecated."
},
"modelTrainingCurrentIteration": {
-"description": "[Output only, Beta] Deprecated; do not use.",
+"description": "Deprecated.",
"format": "int32",
"type": "integer"
},
"modelTrainingExpectedTotalIteration": {
-"description": "[Output only, Beta] Deprecated; do not use.",
+"description": "Deprecated.",
"format": "int64",
"type": "string"
},
"numDmlAffectedRows": {
-"description": "[Output only] The number of rows affected by a DML statement. Present only for DML statements INSERT, UPDATE or DELETE.",
+"description": "Output only. The number of rows affected by a DML statement. Present only for DML statements INSERT, UPDATE or DELETE.",
"format": "int64",
+"readOnly": true,
"type": "string"
},
+"performanceInsights": {
+"$ref": "PerformanceInsights",
+"description": "Output only. Performance insights.",
+"readOnly": true
+},
+"queryInfo": {
+"$ref": "QueryInfo",
+"description": "Output only. Query optimization information for a QUERY job.",
+"readOnly": true
+},
"queryPlan": {
-"description": "[Output only] Describes execution plan for the query.",
+"description": "Output only. Describes execution plan for the query.",
"items": {
"$ref": "ExplainQueryStage"
},
+"readOnly": true,
"type": "array"
},
"referencedRoutines": {
-"description": "[Output only] Referenced routines (persistent user-defined functions and stored procedures) for the job.",
+"description": "Output only. Referenced routines for the job.",
"items": {
"$ref": "RoutineReference"
},
+"readOnly": true,
"type": "array"
},
"referencedTables": {
-"description": "[Output only] Referenced tables for the job. Queries that reference more than 50 tables will not have a complete list.",
+"description": "Output only. Referenced tables for the job. Queries that reference more than 50 tables will not have a complete list.",
"items": {
"$ref": "TableReference"
},
+"readOnly": true,
"type": "array"
},
"reservationUsage": {
-"description": "[Output only] Job resource usage breakdown by reservation.",
+"deprecated": true,
+"description": "Output only. Job resource usage breakdown by reservation. This field reported misleading information and will no longer be populated.",
"items": {
+"description": "Job resource usage breakdown by reservation.",
"properties": {
"name": {
-"description": "[Output only] Reservation name or \"unreserved\" for on-demand resources usage.",
+"description": "Reservation name or \"unreserved\" for on-demand resources usage.",
"type": "string"
},
"slotMs": {
-"description": "[Output only] Slot-milliseconds the job spent in the given reservation.",
+"description": "Total slot milliseconds used by the reservation for a particular job.",
"format": "int64",
"type": "string"
}
},
"type": "object"
},
+"readOnly": true,
"type": "array"
},
"schema": {
"$ref": "TableSchema",
-"description": "[Output only] The schema of the results. Present only for successful dry run of non-legacy SQL queries."
+"description": "Output only. The schema of the results. Present only for successful dry run of non-legacy SQL queries.",
+"readOnly": true
},
"searchStatistics": {
"$ref": "SearchStatistics",
-"description": "[Output only] Search query specific statistics."
+"description": "Output only. Search query specific statistics.",
+"readOnly": true
},
"sparkStatistics": {
"$ref": "SparkStatistics",
-"description": "[Output only] Statistics of a Spark procedure job."
+"description": "Output only. Statistics of a Spark procedure job.",
+"readOnly": true
},
"statementType": {
-"description": "The type of query statement, if valid. Possible values (new values might be added in the future): \"SELECT\": SELECT query. \"INSERT\": INSERT query; see https://cloud.google.com/bigquery/docs/reference/standard-sql/data-manipulation-language. \"UPDATE\": UPDATE query; see https://cloud.google.com/bigquery/docs/reference/standard-sql/data-manipulation-language. \"DELETE\": DELETE query; see https://cloud.google.com/bigquery/docs/reference/standard-sql/data-manipulation-language. \"MERGE\": MERGE query; see https://cloud.google.com/bigquery/docs/reference/standard-sql/data-manipulation-language. \"ALTER_TABLE\": ALTER TABLE query. \"ALTER_VIEW\": ALTER VIEW query. \"ASSERT\": ASSERT condition AS 'description'. \"CREATE_FUNCTION\": CREATE FUNCTION query. \"CREATE_MODEL\": CREATE [OR REPLACE] MODEL ... AS SELECT ... . \"CREATE_PROCEDURE\": CREATE PROCEDURE query. \"CREATE_TABLE\": CREATE [OR REPLACE] TABLE without AS SELECT. \"CREATE_TABLE_AS_SELECT\": CREATE [OR REPLACE] TABLE ... AS SELECT ... . \"CREATE_VIEW\": CREATE [OR REPLACE] VIEW ... AS SELECT ... . \"DROP_FUNCTION\" : DROP FUNCTION query. \"DROP_PROCEDURE\": DROP PROCEDURE query. \"DROP_TABLE\": DROP TABLE query. \"DROP_VIEW\": DROP VIEW query.",
+"description": "Output only. The type of query statement, if valid. Possible values: * `SELECT`: [`SELECT`](/bigquery/docs/reference/standard-sql/query-syntax#select_list) statement. * `ASSERT`: [`ASSERT`](/bigquery/docs/reference/standard-sql/debugging-statements#assert) statement. * `INSERT`: [`INSERT`](/bigquery/docs/reference/standard-sql/dml-syntax#insert_statement) statement. * `UPDATE`: [`UPDATE`](/bigquery/docs/reference/standard-sql/query-syntax#update_statement) statement. * `DELETE`: [`DELETE`](/bigquery/docs/reference/standard-sql/data-manipulation-language) statement. * `MERGE`: [`MERGE`](/bigquery/docs/reference/standard-sql/data-manipulation-language) statement. * `CREATE_TABLE`: [`CREATE TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#create_table_statement) statement, without `AS SELECT`. * `CREATE_TABLE_AS_SELECT`: [`CREATE TABLE AS SELECT`](/bigquery/docs/reference/standard-sql/data-definition-language#query_statement) statement. * `CREATE_VIEW`: [`CREATE VIEW`](/bigquery/docs/reference/standard-sql/data-definition-language#create_view_statement) statement. * `CREATE_MODEL`: [`CREATE MODEL`](/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-create#create_model_statement) statement. * `CREATE_MATERIALIZED_VIEW`: [`CREATE MATERIALIZED VIEW`](/bigquery/docs/reference/standard-sql/data-definition-language#create_materialized_view_statement) statement. * `CREATE_FUNCTION`: [`CREATE FUNCTION`](/bigquery/docs/reference/standard-sql/data-definition-language#create_function_statement) statement. * `CREATE_TABLE_FUNCTION`: [`CREATE TABLE FUNCTION`](/bigquery/docs/reference/standard-sql/data-definition-language#create_table_function_statement) statement. * `CREATE_PROCEDURE`: [`CREATE PROCEDURE`](/bigquery/docs/reference/standard-sql/data-definition-language#create_procedure) statement. * `CREATE_ROW_ACCESS_POLICY`: [`CREATE ROW ACCESS POLICY`](/bigquery/docs/reference/standard-sql/data-definition-language#create_row_access_policy_statement) statement. * `CREATE_SCHEMA`: [`CREATE SCHEMA`](/bigquery/docs/reference/standard-sql/data-definition-language#create_schema_statement) statement. * `CREATE_SNAPSHOT_TABLE`: [`CREATE SNAPSHOT TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#create_snapshot_table_statement) statement. * `CREATE_SEARCH_INDEX`: [`CREATE SEARCH INDEX`](/bigquery/docs/reference/standard-sql/data-definition-language#create_search_index_statement) statement. * `DROP_TABLE`: [`DROP TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_table_statement) statement. * `DROP_EXTERNAL_TABLE`: [`DROP EXTERNAL TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_external_table_statement) statement. * `DROP_VIEW`: [`DROP VIEW`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_view_statement) statement. * `DROP_MODEL`: [`DROP MODEL`](/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-drop-model) statement. * `DROP_MATERIALIZED_VIEW`: [`DROP MATERIALIZED VIEW`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_materialized_view_statement) statement. * `DROP_FUNCTION` : [`DROP FUNCTION`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_function_statement) statement. * `DROP_TABLE_FUNCTION` : [`DROP TABLE FUNCTION`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_table_function) statement. * `DROP_PROCEDURE`: [`DROP PROCEDURE`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_procedure_statement) statement. * `DROP_SEARCH_INDEX`: [`DROP SEARCH INDEX`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_search_index) statement. * `DROP_SCHEMA`: [`DROP SCHEMA`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_schema_statement) statement. * `DROP_SNAPSHOT_TABLE`: [`DROP SNAPSHOT TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_snapshot_table_statement) statement. * `DROP_ROW_ACCESS_POLICY`: [`DROP [ALL] ROW ACCESS POLICY|POLICIES`](/bigquery/docs/reference/standard-sql/data-definition-language#drop_row_access_policy_statement) statement. * `ALTER_TABLE`: [`ALTER TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#alter_table_set_options_statement) statement. * `ALTER_VIEW`: [`ALTER VIEW`](/bigquery/docs/reference/standard-sql/data-definition-language#alter_view_set_options_statement) statement. * `ALTER_MATERIALIZED_VIEW`: [`ALTER MATERIALIZED VIEW`](/bigquery/docs/reference/standard-sql/data-definition-language#alter_materialized_view_set_options_statement) statement. * `ALTER_SCHEMA`: [`ALTER SCHEMA`](/bigquery/docs/reference/standard-sql/data-definition-language#aalter_schema_set_options_statement) statement. * `SCRIPT`: [`SCRIPT`](/bigquery/docs/reference/standard-sql/procedural-language). * `TRUNCATE_TABLE`: [`TRUNCATE TABLE`](/bigquery/docs/reference/standard-sql/dml-syntax#truncate_table_statement) statement. * `CREATE_EXTERNAL_TABLE`: [`CREATE EXTERNAL TABLE`](/bigquery/docs/reference/standard-sql/data-definition-language#create_external_table_statement) statement. * `EXPORT_DATA`: [`EXPORT DATA`](/bigquery/docs/reference/standard-sql/other-statements#export_data_statement) statement. * `EXPORT_MODEL`: [`EXPORT MODEL`](/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-export-model) statement. * `LOAD_DATA`: [`LOAD DATA`](/bigquery/docs/reference/standard-sql/other-statements#load_data_statement) statement. * `CALL`: [`CALL`](/bigquery/docs/reference/standard-sql/procedural-language#call) statement.",
+"readOnly": true,
"type": "string"
},
"timeline": {
-"description": "[Output only] [Beta] Describes a timeline of job execution.",
+"description": "Output only. Describes a timeline of job execution.",
"items": {
"$ref": "QueryTimelineSample"
},
+"readOnly": true,
"type": "array"
},
"totalBytesBilled": {
-"description": "[Output only] Total bytes billed for the job.",
+"description": "Output only. If the project is configured to use on-demand pricing, then this field contains the total bytes billed for the job. If the project is configured to use flat-rate pricing, then you are not billed for bytes and this field is informational only.",
"format": "int64",
+"readOnly": true,
"type": "string"
},
"totalBytesProcessed": {
-"description": "[Output only] Total bytes processed for the job.",
+"description": "Output only. Total bytes processed for the job.",
"format": "int64",
+"readOnly": true,
"type": "string"
},
"totalBytesProcessedAccuracy": {
-"description": "[Output only] For dry-run jobs, totalBytesProcessed is an estimate and this field specifies the accuracy of the estimate. Possible values can be: UNKNOWN: accuracy of the estimate is unknown. PRECISE: estimate is precise. LOWER_BOUND: estimate is lower bound of what the query would cost. UPPER_BOUND: estimate is upper bound of what the query would cost.",
+"description": "Output only. For dry-run jobs, totalBytesProcessed is an estimate and this field specifies the accuracy of the estimate. Possible values can be: UNKNOWN: accuracy of the estimate is unknown. PRECISE: estimate is precise. LOWER_BOUND: estimate is lower bound of what the query would cost. UPPER_BOUND: estimate is upper bound of what the query would cost.",
+"readOnly": true,
"type": "string"
},
"totalPartitionsProcessed": {
-"description": "[Output only] Total number of partitions processed from all partitioned tables referenced in the job.",
+"description": "Output only. Total number of partitions processed from all partitioned tables referenced in the job.",
"format": "int64",
+"readOnly": true,
"type": "string"
},
"totalSlotMs": {
-"description": "[Output only] Slot-milliseconds for the job.",
+"description": "Output only. Slot-milliseconds for the job.",
"format": "int64",
+"readOnly": true,
"type": "string"
},
"transferredBytes": {
-"description": "[Output-only] Total bytes transferred for cross-cloud queries such as Cross Cloud Transfer and CREATE TABLE AS SELECT (CTAS).",
+"description": "Output only. Total bytes transferred for cross-cloud queries such as Cross Cloud Transfer and CREATE TABLE AS SELECT (CTAS).",
"format": "int64",
+"readOnly": true,
"type": "string"
},
"undeclaredQueryParameters": {
-"description": "Standard SQL only: list of undeclared query parameters detected during a dry run validation.",
+"description": "Output only. GoogleSQL only: list of undeclared query parameters detected during a dry run validation.",
"items": {
"$ref": "QueryParameter"
},
+"readOnly": true,
"type": "array"
+},
+"vectorSearchStatistics": {
+"$ref": "VectorSearchStatistics",
+"description": "Output only. Search query specific statistics.",
+"readOnly": true
}
},
"type": "object"
},
"JobStatistics3": {
+"description": "Statistics for a load job.",
"id": "JobStatistics3",
"properties": {
"badRecords": {
-"description": "[Output-only] The number of bad records encountered. Note that if the job has failed because of more bad records encountered than the maximum allowed in the load job configuration, then this number can be less than the total number of bad records present in the input data.",
+"description": "Output only. The number of bad records encountered. Note that if the job has failed because of more bad records encountered than the maximum allowed in the load job configuration, then this number can be less than the total number of bad records present in the input data.",
"format": "int64",
+"readOnly": true,
"type": "string"
},
"inputFileBytes": {
-"description": "[Output-only] Number of bytes of source data in a load job.",
+"description": "Output only. Number of bytes of source data in a load job.",
"format": "int64",
+"readOnly": true,
"type": "string"
},
"inputFiles": {
-"description": "[Output-only] Number of source files in a load job.",
+"description": "Output only. Number of source files in a load job.",
"format": "int64",
+"readOnly": true,
"type": "string"
},
"outputBytes": {
-"description": "[Output-only] Size of the loaded data in bytes. Note that while a load job is in the running state, this value may change.",
+"description": "Output only. Size of the loaded data in bytes. Note that while a load job is in the running state, this value may change.",
"format": "int64",
+"readOnly": true,
"type": "string"
},
"outputRows": {
-"description": "[Output-only] Number of rows imported in a load job. Note that while an import job is in the running state, this value may change.",
+"description": "Output only. Number of rows imported in a load job. Note that while an import job is in the running state, this value may change.",
"format": "int64",
+"readOnly": true,
"type": "string"
+},
+"timeline": {
+"description": "Output only. Describes a timeline of job execution.",
+"items": {
+"$ref": "QueryTimelineSample"
+},
+"readOnly": true,
+"type": "array"
}
},
"type": "object"
},
"JobStatistics4": {
+"description": "Statistics for an extract job.",
"id": "JobStatistics4",
"properties": {
"destinationUriFileCounts": {
-"description": "[Output-only] Number of files per destination URI or URI pattern specified in the extract configuration. These values will be in the same order as the URIs specified in the 'destinationUris' field.",
+"description": "Output only. Number of files per destination URI or URI pattern specified in the extract configuration. These values will be in the same order as the URIs specified in the 'destinationUris' field.",
"items": {
"format": "int64",
"type": "string"
},
+"readOnly": true,
"type": "array"
},
"inputBytes": {
-"description": "[Output-only] Number of user bytes extracted into the result. This is the byte count as computed by BigQuery for billing purposes.",
+"description": "Output only. Number of user bytes extracted into the result. This is the byte count as computed by BigQuery for billing purposes and doesn't have any relationship with the number of actual result bytes extracted in the desired format.",
"format": "int64",
+"readOnly": true,
"type": "string"
+},
+"timeline": {
+"description": "Output only. Describes a timeline of job execution.",
+"items": {
+"$ref": "QueryTimelineSample"
+},
+"readOnly": true,
+"type": "array"
}
},
"type": "object"
},
"JobStatistics5": {
+"description": "Statistics for a copy job.",
"id": "JobStatistics5",
"properties": {
"copiedLogicalBytes": {
-"description": "[Output-only] Number of logical bytes copied to the destination table.",
+"description": "Output only. Number of logical bytes copied to the destination table.",
"format": "int64",
+"readOnly": true,
"type": "string"
},
"copiedRows": {
-"description": "[Output-only] Number of rows copied to the destination table.",
+"description": "Output only. Number of rows copied to the destination table.",
"format": "int64",
+"readOnly": true,
"type": "string"
}
},
@@ -4975,17 +5725,20 @@
"properties": {
"errorResult": {
"$ref": "ErrorProto",
-"description": "[Output-only] Final error result of the job. If present, indicates that the job has completed and was unsuccessful."
+"description": "Output only. Final error result of the job. If present, indicates that the job has completed and was unsuccessful.",
+"readOnly": true
},
"errors": {
-"description": "[Output-only] The first errors encountered during the running of the job. The final message includes the number of errors that caused the process to stop. Errors here do not necessarily mean that the job has completed or was unsuccessful.",
+"description": "Output only. The first errors encountered during the running of the job. The final message includes the number of errors that caused the process to stop. Errors here do not necessarily mean that the job has not completed or was unsuccessful.",
"items": {
"$ref": "ErrorProto"
},
+"readOnly": true,
"type": "array"
},
"state": {
-"description": "[Output-only] Running state of the job.",
+"description": "Output only. Running state of the job. Valid states include 'PENDING', 'RUNNING', and 'DONE'.",
+"readOnly": true,
"type": "string"
}
},
@@ -5000,10 +5753,11 @@
"type": "object"
},
"JsonOptions": {
+"description": "Json Options for load and make external tables.",
"id": "JsonOptions",
"properties": {
"encoding": {
-"description": "[Optional] The character encoding of the data. The supported values are UTF-8, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8.",
+"description": "Optional. The character encoding of the data. The supported values are UTF-8, UTF-16BE, UTF-16LE, UTF-32BE, and UTF-32LE. The default value is UTF-8.",
"type": "string"
}
},
@@ -5013,6 +5767,17 @@
"id": "JsonValue",
"type": "any"
},
+"LinkedDatasetSource": {
+"description": "A dataset source type which refers to another BigQuery dataset.",
+"id": "LinkedDatasetSource",
+"properties": {
+"sourceDataset": {
+"$ref": "DatasetReference",
+"description": "The source dataset reference contains project numbers and not project ids."
+}
+},
+"type": "object"
+},
"ListModelsResponse": {
"description": "Response format for a single page when listing BigQuery ML models.",
"id": "ListModelsResponse",
@@ -5067,6 +5832,50 @@
},
"type": "object"
},
+"LoadQueryStatistics": {
+"description": "Statistics for a LOAD query.",
+"id": "LoadQueryStatistics",
+"properties": {
+"badRecords": {
+"description": "Output only. The number of bad records encountered while processing a LOAD query. Note that if the job has failed because of more bad records encountered than the maximum allowed in the load job configuration, then this number can be less than the total number of bad records present in the input data.",
+"format": "int64",
+"readOnly": true,
+"type": "string"
+},
+"bytesTransferred": {
+"deprecated": true,
+"description": "Output only. This field is deprecated. The number of bytes of source data copied over the network for a `LOAD` query. `transferred_bytes` has the canonical value for physical transferred bytes, which is used for BigQuery Omni billing.",
+"format": "int64",
+"readOnly": true,
+"type": "string"
+},
+"inputFileBytes": {
+"description": "Output only. Number of bytes of source data in a LOAD query.",
+"format": "int64",
+"readOnly": true,
+"type": "string"
+},
+"inputFiles": {
+"description": "Output only. Number of source files in a LOAD query.",
+"format": "int64",
+"readOnly": true,
+"type": "string"
+},
+"outputBytes": {
+"description": "Output only. Size of the loaded data in bytes. Note that while a LOAD query is in the running state, this value may change.",
+"format": "int64",
+"readOnly": true,
+"type": "string"
+},
+"outputRows": {
+"description": "Output only. Number of rows imported in a LOAD query. Note that while a LOAD query is in the running state, this value may change.",
+"format": "int64",
+"readOnly": true,
+"type": "string"
+}
+},
+"type": "object"
+},
"LocationMetadata": {
"description": "BigQuery-specific metadata about a location. This will be set on google.cloud.location.Location.metadata in Cloud Location API responses.",
"id": "LocationMetadata",
@@ -5078,20 +5887,74 @@
},
"type": "object"
},
+"MaterializedView": {
+"description": "A materialized view considered for a query job.",
+"id": "MaterializedView",
+"properties": {
+"chosen": {
+"description": "Whether the materialized view is chosen for the query. A materialized view can be chosen to rewrite multiple parts of the same query. If a materialized view is chosen to rewrite any part of the query, then this field is true, even if the materialized view was not chosen to rewrite others parts.",
+"type": "boolean"
+},
+"estimatedBytesSaved": {
+"description": "If present, specifies a best-effort estimation of the bytes saved by using the materialized view rather than its base tables.",
+"format": "int64",
+"type": "string"
+},
+"rejectedReason": {
+"description": "If present, specifies the reason why the materialized view was not chosen for the query.",
+"enum": [
+"REJECTED_REASON_UNSPECIFIED",
+"NO_DATA",
+"COST",
+"BASE_TABLE_TRUNCATED",
+"BASE_TABLE_DATA_CHANGE",
+"BASE_TABLE_PARTITION_EXPIRATION_CHANGE",
+"BASE_TABLE_EXPIRED_PARTITION",
+"BASE_TABLE_INCOMPATIBLE_METADATA_CHANGE",
+"TIME_ZONE",
+"OUT_OF_TIME_TRAVEL_WINDOW",
+"BASE_TABLE_FINE_GRAINED_SECURITY_POLICY",
+"BASE_TABLE_TOO_STALE"
+],
+"enumDescriptions": [
+"Default unspecified value.",
+"View has no cached data because it has not refreshed yet.",
+"The estimated cost of the view is more expensive than another view or the base table. Note: The estimate cost might not match the billed cost.",
+"View has no cached data because a base table is truncated.",
+"View is invalidated because of a data change in one or more base tables. It could be any recent change if the [`max_staleness`](https://cloud.google.com/bigquery/docs/materialized-views-create#max_staleness) option is not set for the view, or otherwise any change outside of the staleness window.",
+"View is invalidated because a base table's partition expiration has changed.",
+"View is invalidated because a base table's partition has expired.",
+"View is invalidated because a base table has an incompatible metadata change.",
+"View is invalidated because it was refreshed with a time zone other than that of the current job.",
+"View is outside the time travel window.",
+"View is inaccessible to the user because of a fine-grained security policy on one of its base tables.",
+"One of the view's base tables is too stale. For example, the cached metadata of a biglake table needs to be updated."
+],
+"type": "string"
+},
+"tableReference": {
+"$ref": "TableReference",
+"description": "The candidate materialized view."
+}
+},
+"type": "object"
+},
"MaterializedViewDefinition": {
+"description": "Definition and configuration of a materialized view.",
"id": "MaterializedViewDefinition",
"properties": {
"allowNonIncrementalDefinition": {
-"description": "[Optional] Allow non incremental materialized view definition. The default value is \"false\".",
+"description": "Optional. This option declares authors intention to construct a materialized view that will not be refreshed incrementally.",
"type": "boolean"
},
"enableRefresh": {
-"description": "[Optional] [TrustedTester] Enable automatic refresh of the materialized view when the base table is updated. The default value is \"true\".",
+"description": "Optional. Enable automatic refresh of the materialized view when the base table is updated. The default value is \"true\".",
"type": "boolean"
},
"lastRefreshTime": {
-"description": "[Output-only] [TrustedTester] The time when this materialized view was last modified, in milliseconds since the epoch.",
+"description": "Output only. The time when this materialized view was last refreshed, in milliseconds since the epoch.",
"format": "int64",
+"readOnly": true,
"type": "string"
},
"maxStaleness": {
@@ -5100,30 +5963,158 @@
"type": "string"
},
"query": {
-"description": "[Required] A query whose result is persisted.",
+"description": "Required. A query whose results are persisted.",
"type": "string"
},
"refreshIntervalMs": {
-"description": "[Optional] [TrustedTester] The maximum frequency at which this materialized view will be refreshed. The default value is \"1800000\" (30 minutes).",
+"description": "Optional. The maximum frequency at which this materialized view will be refreshed. The default value is \"1800000\" (30 minutes).",
"format": "int64",
"type": "string"
}
},
"type": "object"
},
+"MaterializedViewStatistics": {
+"description": "Statistics of materialized views considered in a query job.",
+"id": "MaterializedViewStatistics",
+"properties": {
+"materializedView": {
+"description": "Materialized views considered for the query job. Only certain materialized views are used. For a detailed list, see the child message. If many materialized views are considered, then the list might be incomplete.",
+"items": {
+"$ref": "MaterializedView"
+},
+"type": "array"
+}
+},
+"type": "object"
+},
+"MaterializedViewStatus": {
+"description": "Status of a materialized view. The last refresh timestamp status is omitted here, but is present in the MaterializedViewDefinition message.",
+"id": "MaterializedViewStatus",
+"properties": {
+"lastRefreshStatus": {
+"$ref": "ErrorProto",
+"description": "Output only. Error result of the last automatic refresh. If present, indicates that the last automatic refresh was unsuccessful.",
+"readOnly": true
+},
+"refreshWatermark": {
+"description": "Output only. Refresh watermark of materialized view. The base tables' data were collected into the materialized view cache until this time.",
+"format": "google-datetime",
+"readOnly": true,
+"type": "string"
+}
+},
+"type": "object"
+},
+"MetadataCacheStatistics": {
+"description": "Statistics for metadata caching in BigLake tables.",
+"id": "MetadataCacheStatistics",
+"properties": {
+"tableMetadataCacheUsage": {
+"description": "Set for the Metadata caching eligible tables referenced in the query.",
+"items": {
+"$ref": "TableMetadataCacheUsage"
+},
+"type": "array"
+}
+},
+"type": "object"
+},
"MlStatistics": {
+"description": "Job statistics specific to a BigQuery ML training job.",
"id": "MlStatistics",
"properties": {
+"hparamTrials": {
+"description": "Output only. Trials of a [hyperparameter tuning job](/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview) sorted by trial_id.",
+"items": {
+"$ref": "HparamTuningTrial"
+},
+"readOnly": true,
+"type": "array"
+},
"iterationResults": {
-"description": "Results for all completed iterations.",
+"description": "Results for all completed iterations. Empty for [hyperparameter tuning jobs](/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview).",
"items": {
"$ref": "IterationResult"
},
"type": "array"
},
"maxIterations": {
-"description": "Maximum number of iterations specified as max_iterations in the 'CREATE MODEL' query. The actual number of iterations may be less than this number due to early stop.",
+"description": "Output only. Maximum number of iterations specified as max_iterations in the 'CREATE MODEL' query. The actual number of iterations may be less than this number due to early stop.",
"format": "int64",
+"readOnly": true,
+"type": "string"
+},
+"modelType": {
+"description": "Output only. The type of the model that is being trained.",
+"enum": [
+"MODEL_TYPE_UNSPECIFIED",
+"LINEAR_REGRESSION",
+"LOGISTIC_REGRESSION",
+"KMEANS",
+"MATRIX_FACTORIZATION",
+"DNN_CLASSIFIER",
+"TENSORFLOW",
+"DNN_REGRESSOR",
+"XGBOOST",
+"BOOSTED_TREE_REGRESSOR",
+"BOOSTED_TREE_CLASSIFIER",
+"ARIMA",
+"AUTOML_REGRESSOR",
+"AUTOML_CLASSIFIER",
+"PCA",
+"DNN_LINEAR_COMBINED_CLASSIFIER",
+"DNN_LINEAR_COMBINED_REGRESSOR",
+"AUTOENCODER",
+"ARIMA_PLUS",
+"ARIMA_PLUS_XREG",
+"RANDOM_FOREST_REGRESSOR",
+"RANDOM_FOREST_CLASSIFIER",
+"TENSORFLOW_LITE",
+"ONNX"
+],
+"enumDescriptions": [
+"Default value.",
+"Linear regression model.",
+"Logistic regression based classification model.",
+"K-means clustering model.",
+"Matrix factorization model.",
+"DNN classifier model.",
+"An imported TensorFlow model.",
+"DNN regressor model.",
+"An imported XGBoost model.",
+"Boosted tree regressor model.",
+"Boosted tree classifier model.",
+"ARIMA model.",
+"AutoML Tables regression model.",
+"AutoML Tables classification model.",
+"Prinpical Component Analysis model.",
+"Wide-and-deep classifier model.",
+"Wide-and-deep regressor model.",
+"Autoencoder model.",
+"New name for the ARIMA model.",
+"ARIMA with external regressors.",
+"Random forest regressor model.",
+"Random forest classifier model.",
+"An imported TensorFlow Lite model.",
+"An imported ONNX model."
+],
+"readOnly": true,
+"type": "string"
+},
+"trainingType": {
+"description": "Output only. Training type of the job.",
+"enum": [
+"TRAINING_TYPE_UNSPECIFIED",
+"SINGLE_TRAINING",
+"HPARAM_TUNING"
+],
+"enumDescriptions": [
+"Unspecified training type.",
+"Single training with fixed parameter space.",
+"[Hyperparameter tuning training](/bigquery-ml/docs/reference/standard-sql/bigqueryml-syntax-hp-tuning-overview)."
+],
+"readOnly": true,
"type": "string"
}
},
@@ -5316,7 +6307,7 @@
"id": "ModelDefinition",
"properties": {
"modelOptions": {
-"description": "[Output-only, Beta] Model options used for the first training run. These options are immutable for subsequent training runs. Default values are used for any options not specified in the input query.",
+"description": "Deprecated.",
"properties": {
"labels": {
"items": {
@@ -5334,7 +6325,7 @@
"type": "object"
},
"trainingRuns": {
-"description": "[Output-only, Beta] Information about ml training runs, each training run comprises of multiple iterations and there may be multiple training runs for the model if warm start is used or if a user decides to continue a previously cancelled query.",
+"description": "Deprecated.",
"items": {
"$ref": "BqmlTrainingRun"
},
@@ -5343,7 +6334,20 @@
},
"type": "object"
},
+"ModelExtractOptions": {
+"description": "Options related to model extraction.",
+"id": "ModelExtractOptions",
+"properties": {
+"trialId": {
+"description": "The 1-based ID of the trial to be exported from a hyperparameter tuning model. If not specified, the trial with id = [Model](/bigquery/docs/reference/rest/v2/models#resource:-model).defaultTrialId is exported. This field is ignored for models not trained with hyperparameter tuning.",
+"format": "int64",
+"type": "string"
+}
+},
+"type": "object"
+},
"ModelReference": {
+"description": "Id path of a model.",
"id": "ModelReference",
"properties": {
"datasetId": {
@@ -5380,15 +6384,45 @@
"type": "object"
},
"ParquetOptions": {
+"description": "Parquet Options for load and make external tables.",
"id": "ParquetOptions",
"properties": {
"enableListInference": {
-"description": "[Optional] Indicates whether to use schema inference specifically for Parquet LIST logical type.",
+"description": "Optional. Indicates whether to use schema inference specifically for Parquet LIST logical type.",
"type": "boolean"
},
-"enumAsString": {
-"description": "[Optional] Indicates whether to infer Parquet ENUM logical type as STRING instead of BYTES by default.",
-"type": "boolean"
+"enumAsString": {
+"description": "Optional. Indicates whether to infer Parquet ENUM logical type as STRING instead of BYTES by default.",
+"type": "boolean"
+}
+},
+"type": "object"
+},
+"PerformanceInsights": {
+"description": "Performance insights for the job.",
+"id": "PerformanceInsights",
+"properties": {
+"avgPreviousExecutionMs": {
+"description": "Output only. Average execution ms of previous runs. Indicates the job ran slow compared to previous executions. To find previous executions, use INFORMATION_SCHEMA tables and filter jobs with same query hash.",
+"format": "int64",
+"readOnly": true,
+"type": "string"
+},
+"stagePerformanceChangeInsights": {
+"description": "Output only. Query stage performance insights compared to previous runs, for diagnosing performance regression.",
+"items": {
+"$ref": "StagePerformanceChangeInsight"
+},
+"readOnly": true,
+"type": "array"
+},
+"stagePerformanceStandaloneInsights": {
+"description": "Output only. Standalone query stage performance insights, for exploring potential improvements.",
+"items": {
+"$ref": "StagePerformanceStandaloneInsight"
+},
+"readOnly": true,
+"type": "array"
}
},
"type": "object"
@@ -5463,27 +6497,29 @@
"type": "object"
},
"ProjectList": {
+"description": "Response object of ListProjects",
"id": "ProjectList",
"properties": {
"etag": {
-"description": "A hash of the page of results",
+"description": "A hash of the page of results.",
"type": "string"
},
"kind": {
"default": "bigquery#projectList",
-"description": "The type of list.",
+"description": "The resource type of the response.",
"type": "string"
},
"nextPageToken": {
-"description": "A token to request the next page of results.",
+"description": "Use this token to request the next page of results.",
"type": "string"
},
"projects": {
-"description": "Projects to which you have at least READ access.",
+"description": "Projects to which the user has at least READ access.",
"items": {
+"description": "Information about a single project.",
"properties": {
"friendlyName": {
-"description": "A descriptive name for this project.",
+"description": "A descriptive name for this project. A wrapper is used here because friendlyName can be set to the empty string.",
"type": "string"
},
"id": {
@@ -5491,7 +6527,6 @@
"type": "string"
},
"kind": {
-"default": "bigquery#project",
"description": "The resource type.",
"type": "string"
},
@@ -5510,7 +6545,7 @@
"type": "array"
},
"totalItems": {
-"description": "The total number of projects in the list.",
+"description": "The total number of projects in the page. A wrapper is used here because the field should still be in the response when the value is 0.",
"format": "int32",
"type": "integer"
}
@@ -5518,59 +6553,79 @@
"type": "object"
},
"ProjectReference": {
+"description": "A unique reference to a project.",
"id": "ProjectReference",
"properties": {
"projectId": {
-"description": "[Required] ID of the project. Can be either the numeric ID or the assigned ID of the project.",
+"description": "Required. ID of the project. Can be either the numeric ID or the assigned ID of the project.",
"type": "string"
}
},
"type": "object"
},
+"QueryInfo": {
+"description": "Query optimization information for a QUERY job.",
+"id": "QueryInfo",
+"properties": {
+"optimizationDetails": {
+"additionalProperties": {
+"description": "Properties of the object.",
+"type": "any"
+},
+"description": "Output only. Information about query optimizations.",
+"readOnly": true,
+"type": "object"
+}
+},
+"type": "object"
+},
"QueryParameter": {
+"description": "A parameter given to a query.",
"id": "QueryParameter",
"properties": {
"name": {
-"description": "[Optional] If unset, this is a positional parameter. Otherwise, should be unique within a query.",
+"description": "Optional. If unset, this is a positional parameter. Otherwise, should be unique within a query.",
"type": "string"
},
"parameterType": {
"$ref": "QueryParameterType",
-"description": "[Required] The type of this parameter."
+"description": "Required. The type of this parameter."
},
"parameterValue": {
"$ref": "QueryParameterValue",
-"description": "[Required] The value of this parameter."
+"description": "Required. The value of this parameter."
}
},
"type": "object"
},
"QueryParameterType": {
+"description": "The type of a query parameter.",
"id": "QueryParameterType",
"properties": {
"arrayType": {
"$ref": "QueryParameterType",
-"description": "[Optional] The type of the array's elements, if this is an array."
+"description": "Optional. The type of the array's elements, if this is an array."
},
"rangeElementType": {
"$ref": "QueryParameterType",
-"description": "[Optional] The element type of the range, if this is a range."
+"description": "Optional. The element type of the range, if this is a range."
},
"structTypes": {
-"description": "[Optional] The types of the fields of this struct, in order, if this is a struct.",
+"description": "Optional. The types of the fields of this struct, in order, if this is a struct.",
"items": {
+"description": "The type of a struct parameter.",
"properties": {
"description": {
-"description": "[Optional] Human-oriented description of the field.",
+"description": "Optional. Human-oriented description of the field.",
"type": "string"
},
"name": {
-"description": "[Optional] The name of this field.",
+"description": "Optional. The name of this field.",
"type": "string"
},
"type": {
"$ref": "QueryParameterType",
-"description": "[Required] The type of this field."
+"description": "Required. The type of this field."
}
},
"type": "object"
@@ -5578,53 +6633,47 @@
"type": "array"
},
"type": {
-"description": "[Required] The top level type of this field.",
+"description": "Required. The top level type of this field.",
"type": "string"
}
},
"type": "object"
},
"QueryParameterValue": {
+"description": "The value of a query parameter.",
"id": "QueryParameterValue",
"properties": {
"arrayValues": {
-"description": "[Optional] The array values, if this is an array type.",
+"description": "Optional. The array values, if this is an array type.",
"items": {
"$ref": "QueryParameterValue"
},
"type": "array"
},
"rangeValue": {
-"description": "[Optional] The range value, if this is a range type.",
-"properties": {
-"end": {
-"$ref": "QueryParameterValue"
-},
-"start": {
-"$ref": "QueryParameterValue"
-}
-},
-"type": "object"
+"$ref": "RangeValue",
+"description": "Optional. The range value, if this is a range type."
},
"structValues": {
"additionalProperties": {
"$ref": "QueryParameterValue"
},
-"description": "[Optional] The struct field values, in order of the struct type's declaration.",
+"description": "The struct field values.",
"type": "object"
},
"value": {
-"description": "[Optional] The value of this value, if a simple scalar type.",
+"description": "Optional. The value of this value, if a simple scalar type.",
"type": "string"
}
},
"type": "object"
},
"QueryRequest": {
+"description": "Describes the format of the jobs.query request.",
"id": "QueryRequest",
"properties": {
"connectionProperties": {
-"description": "Connection properties.",
+"description": "Optional. Connection properties which can modify the query behavior.",
"items": {
"$ref": "ConnectionProperty"
},
@@ -5635,19 +6684,33 @@
"type": "boolean"
},
"createSession": {
-"description": "If true, creates a new session, where session id will be a server generated random id. If false, runs query with an existing session_id passed in ConnectionProperty, otherwise runs query in non-session mode.",
+"description": "Optional. If true, creates a new session using a randomly generated session_id. If false, runs query with an existing session_id passed in ConnectionProperty, otherwise runs query in non-session mode. The session location will be set to QueryRequest.location if it is present, otherwise it's set to the default location based on existing routing logic.",
"type": "boolean"
},
"defaultDataset": {
"$ref": "DatasetReference",
-"description": "[Optional] Specifies the default datasetId and projectId to assume for any unqualified table names in the query. If not set, all table names in the query string must be qualified in the format 'datasetId.tableId'."
+"description": "Optional. Specifies the default datasetId and projectId to assume for any unqualified table names in the query. If not set, all table names in the query string must be qualified in the format 'datasetId.tableId'."
},
"dryRun": {
-"description": "[Optional] If set to true, BigQuery doesn't run the job. Instead, if the query is valid, BigQuery returns statistics about the job such as how many bytes would be processed. If the query is invalid, an error returns. The default value is false.",
+"description": "Optional. If set to true, BigQuery doesn't run the job. Instead, if the query is valid, BigQuery returns statistics about the job such as how many bytes would be processed. If the query is invalid, an error returns. The default value is false.",
"type": "boolean"
},
+"formatOptions": {
+"$ref": "DataFormatOptions",
+"description": "Optional. Output format adjustments."
+},
"jobCreationMode": {
"description": "Optional. If not set, jobs are always required. If set, the query request will follow the behavior described JobCreationMode. This feature is not yet available. Jobs will always be created.",
+"enum": [
+"JOB_CREATION_MODE_UNSPECIFIED",
+"JOB_CREATION_REQUIRED",
+"JOB_CREATION_OPTIONAL"
+],
+"enumDescriptions": [
+"If unspecified JOB_CREATION_REQUIRED is the default.",
+"Default. Job creation is always required.",
+"Job creation is optional. Returning immediate results is prioritized. BigQuery will automatically determine if a Job needs to be created. The conditions under which BigQuery can decide to not create a Job are subject to change. If Job creation is required, JOB_CREATION_REQUIRED mode should be used, which is the default."
+],
"type": "string"
},
"kind": {
@@ -5659,7 +6722,7 @@
"additionalProperties": {
"type": "string"
},
-"description": "The labels associated with this job. You can use these to organize and group your jobs. Label keys and values can be no longer than 63 characters, can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. Label values are optional. Label keys must start with a letter and each label in the list must have a different key.",
+"description": "Optional. The labels associated with this query. Labels can be used to organize and group query jobs. Label keys and values can be no longer than 63 characters, can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. Label keys must start with a letter and each label in the list must have a different key.",
"type": "object"
},
"location": {
@@ -5667,56 +6730,52 @@
"type": "string"
},
"maxResults": {
-"description": "[Optional] The maximum number of rows of data to return per page of results. Setting this flag to a small value such as 1000 and then paging through results might improve reliability when the query result set is large. In addition to this limit, responses are also limited to 10 MB. By default, there is no maximum row count, and only the byte limit applies.",
+"description": "Optional. The maximum number of rows of data to return per page of results. Setting this flag to a small value such as 1000 and then paging through results might improve reliability when the query result set is large. In addition to this limit, responses are also limited to 10 MB. By default, there is no maximum row count, and only the byte limit applies.",
"format": "uint32",
"type": "integer"
},
"maximumBytesBilled": {
-"description": "[Optional] Limits the bytes billed for this job. Queries that will have bytes billed beyond this limit will fail (without incurring a charge). If unspecified, this will be set to your project default.",
+"description": "Optional. Limits the bytes billed for this query. Queries with bytes billed above this limit will fail (without incurring a charge). If unspecified, the project default is used.",
"format": "int64",
"type": "string"
},
"parameterMode": {
-"description": "Standard SQL only. Set to POSITIONAL to use positional (?) query parameters or to NAMED to use named (@myparam) query parameters in this query.",
+"description": "GoogleSQL only. Set to POSITIONAL to use positional (?) query parameters or to NAMED to use named (@myparam) query parameters in this query.",
"type": "string"
},
"preserveNulls": {
-"description": "[Deprecated] This property is deprecated.",
+"deprecated": true,
+"description": "This property is deprecated.",
"type": "boolean"
},
"query": {
-"annotations": {
-"required": [
-"bigquery.jobs.query"
-]
-},
-"description": "[Required] A query string, following the BigQuery query syntax, of the query to execute. Example: \"SELECT count(f1) FROM [myProjectId:myDatasetId.myTableId]\".",
+"description": "Required. A query string to execute, using Google Standard SQL or legacy SQL syntax. Example: \"SELECT COUNT(f1) FROM myProjectId.myDatasetId.myTableId\".",
"type": "string"
},
"queryParameters": {
-"description": "Query parameters for Standard SQL queries.",
+"description": "Query parameters for GoogleSQL queries.",
"items": {
"$ref": "QueryParameter"
},
"type": "array"
},
"requestId": {
-"description": "A unique user provided identifier to ensure idempotent behavior for queries. Note that this is different from the job_id. It has the following properties: 1. It is case-sensitive, limited to up to 36 ASCII characters. A UUID is recommended. 2. Read only queries can ignore this token since they are nullipotent by definition. 3. For the purposes of idempotency ensured by the request_id, a request is considered duplicate of another only if they have the same request_id and are actually duplicates. When determining whether a request is a duplicate of the previous request, all parameters in the request that may affect the behavior are considered. For example, query, connection_properties, query_parameters, use_legacy_sql are parameters that affect the result and are considered when determining whether a request is a duplicate, but properties like timeout_ms don't affect the result and are thus not considered. Dry run query requests are never considered duplicate of another request. 4. When a duplicate mutating query request is detected, it returns: a. the results of the mutation if it completes successfully within the timeout. b. the running operation if it is still in progress at the end of the timeout. 5. Its lifetime is limited to 15 minutes. In other words, if two requests are sent with the same request_id, but more than 15 minutes apart, idempotency is not guaranteed.",
+"description": "Optional. A unique user provided identifier to ensure idempotent behavior for queries. Note that this is different from the job_id. It has the following properties: 1. It is case-sensitive, limited to up to 36 ASCII characters. A UUID is recommended. 2. Read only queries can ignore this token since they are nullipotent by definition. 3. For the purposes of idempotency ensured by the request_id, a request is considered duplicate of another only if they have the same request_id and are actually duplicates. When determining whether a request is a duplicate of another request, all parameters in the request that may affect the result are considered. For example, query, connection_properties, query_parameters, use_legacy_sql are parameters that affect the result and are considered when determining whether a request is a duplicate, but properties like timeout_ms don't affect the result and are thus not considered. Dry run query requests are never considered duplicate of another request. 4. When a duplicate mutating query request is detected, it returns: a. the results of the mutation if it completes successfully within the timeout. b. the running operation if it is still in progress at the end of the timeout. 5. Its lifetime is limited to 15 minutes. In other words, if two requests are sent with the same request_id, but more than 15 minutes apart, idempotency is not guaranteed.",
"type": "string"
},
"timeoutMs": {
-"description": "[Optional] How long to wait for the query to complete, in milliseconds, before the request times out and returns. Note that this is only a timeout for the request, not the query. If the query takes longer to run than the timeout value, the call returns without any results and with the 'jobComplete' flag set to false. You can call GetQueryResults() to wait for the query to complete and read the results. The default value is 10000 milliseconds (10 seconds).",
+"description": "Optional. Optional: Specifies the maximum amount of time, in milliseconds, that the client is willing to wait for the query to complete. By default, this limit is 10 seconds (10,000 milliseconds). If the query is complete, the jobComplete field in the response is true. If the query has not yet completed, jobComplete is false. You can request a longer timeout period in the timeoutMs field. However, the call is not guaranteed to wait for the specified timeout; it typically returns after around 200 seconds (200,000 milliseconds), even if the query is not complete. If jobComplete is false, you can continue to wait for the query to complete by calling the getQueryResults method until the jobComplete field in the getQueryResults response is true.",
"format": "uint32",
"type": "integer"
},
"useLegacySql": {
"default": "true",
-"description": "Specifies whether to use BigQuery's legacy SQL dialect for this query. The default value is true. If set to false, the query will use BigQuery's standard SQL: https://cloud.google.com/bigquery/sql-reference/ When useLegacySql is set to false, the value of flattenResults is ignored; query will be run as if flattenResults is false.",
+"description": "Specifies whether to use BigQuery's legacy SQL dialect for this query. The default value is true. If set to false, the query will use BigQuery's GoogleSQL: https://cloud.google.com/bigquery/sql-reference/ When useLegacySql is set to false, the value of flattenResults is ignored; query will be run as if flattenResults is false.",
"type": "boolean"
},
"useQueryCache": {
"default": "true",
-"description": "[Optional] Whether to look for the result in the query cache. The query cache is a best-effort cache that will be flushed whenever tables in the query are modified. The default value is true.",
+"description": "Optional. Whether to look for the result in the query cache. The query cache is a best-effort cache that will be flushed whenever tables in the query are modified. The default value is true.",
"type": "boolean"
}
},
@@ -5731,13 +6790,15 @@
},
"dmlStats": {
"$ref": "DmlStatistics",
-"description": "[Output-only] Detailed statistics for DML statements Present only for DML statements INSERT, UPDATE, DELETE or TRUNCATE."
+"description": "Output only. Detailed statistics for DML statements INSERT, UPDATE, DELETE, MERGE or TRUNCATE.",
+"readOnly": true
},
"errors": {
-"description": "[Output-only] The first errors or warnings encountered during the running of the job. The final message includes the number of errors that caused the process to stop. Errors here do not necessarily mean that the job has completed or was unsuccessful.",
+"description": "Output only. The first errors or warnings encountered during the running of the job. The final message includes the number of errors that caused the process to stop. Errors here do not necessarily mean that the job has completed or was unsuccessful. For more information about error messages, see [Error messages](https://cloud.google.com/bigquery/docs/error-messages).",
"items": {
"$ref": "ErrorProto"
},
+"readOnly": true,
"type": "array"
},
"jobComplete": {
@@ -5745,8 +6806,8 @@
"type": "boolean"
},
"jobCreationReason": {
-"description": "Optional. Only relevant when a job_reference is present in the response. If job_reference is not present it will always be unset. When job_reference is present, this field should be interpreted as follows: If set, it will provide the reason of why a Job was created. If not set, it should be treated as the default: REQUESTED. This feature is not yet available. Jobs will always be created.",
-"type": "any"
+"$ref": "JobCreationReason",
+"description": "Optional. Only relevant when a job_reference is present in the response. If job_reference is not present it will always be unset. When job_reference is present, this field should be interpreted as follows: If set, it will provide the reason of why a Job was created. If not set, it should be treated as the default: REQUESTED. This feature is not yet available. Jobs will always be created."
},
"jobReference": {
"$ref": "JobReference",
@@ -5758,12 +6819,13 @@
"type": "string"
},
"numDmlAffectedRows": {
-"description": "[Output-only] The number of rows affected by a DML statement. Present only for DML statements INSERT, UPDATE or DELETE.",
+"description": "Output only. The number of rows affected by a DML statement. Present only for DML statements INSERT, UPDATE or DELETE.",
"format": "int64",
+"readOnly": true,
"type": "string"
},
"pageToken": {
-"description": "A token used for paging results.",
+"description": "A token used for paging results. A non-empty token indicates that additional results are available. To see additional results, query the [`jobs.getQueryResults`](https://cloud.google.com/bigquery/docs/reference/rest/v2/jobs/getQueryResults) method. For more information, see [Paging through table data](https://cloud.google.com/bigquery/docs/paging-results).",
"type": "string"
},
"queryId": {
@@ -5783,7 +6845,8 @@
},
"sessionInfo": {
"$ref": "SessionInfo",
-"description": "[Output-only] [Preview] Information of the session if this job is part of one."
+"description": "Output only. Information of the session if this job is part of one.",
+"readOnly": true
},
"totalBytesProcessed": {
"description": "The total number of bytes processed for this query. If this query was a dry run, this is the number of bytes that would be processed if the query were run.",
@@ -5799,10 +6862,11 @@
"type": "object"
},
"QueryTimelineSample": {
+"description": "Summary of the state of query execution at a given time.",
"id": "QueryTimelineSample",
"properties": {
"activeUnits": {
-"description": "Total number of units currently being processed by workers. This does not correspond directly to slot usage. This is the largest value observed since the last sample.",
+"description": "Total number of active workers. This does not correspond directly to slot usage. This is the largest value observed since the last sample.",
"format": "int64",
"type": "string"
},
@@ -5817,7 +6881,7 @@
"type": "string"
},
"estimatedRunnableUnits": {
-"description": "Units of work that can be scheduled immediately. Providing additional slots for these units of work will speed up the query, provided no other query in the reservation needs additional slots.",
+"description": "Units of work that can be scheduled immediately. Providing additional slots for these units of work will accelerate the query, if no other query in the reservation needs additional slots.",
"format": "int64",
"type": "string"
},
@@ -5838,24 +6902,24 @@
"id": "RangePartitioning",
"properties": {
"field": {
-"description": "[TrustedTester] [Required] The table is partitioned by this field. The field must be a top-level NULLABLE/REQUIRED field. The only supported type is INTEGER/INT64.",
+"description": "Required. [Experimental] The table is partitioned by this field. The field must be a top-level NULLABLE/REQUIRED field. The only supported type is INTEGER/INT64.",
"type": "string"
},
"range": {
-"description": "[TrustedTester] [Required] Defines the ranges for range partitioning.",
+"description": "[Experimental] Defines the ranges for range partitioning.",
"properties": {
"end": {
-"description": "[TrustedTester] [Required] The end of range partitioning, exclusive.",
+"description": "[Experimental] The end of range partitioning, exclusive.",
"format": "int64",
"type": "string"
},
"interval": {
-"description": "[TrustedTester] [Required] The width of each interval.",
+"description": "[Experimental] The width of each interval.",
"format": "int64",
"type": "string"
},
"start": {
-"description": "[TrustedTester] [Required] The start of range partitioning, inclusive.",
+"description": "[Experimental] The start of range partitioning, inclusive.",
"format": "int64",
"type": "string"
}
@@ -6167,6 +7231,7 @@
"type": "object"
},
"RoutineReference": {
+"description": "Id path of a routine.",
"id": "RoutineReference",
"properties": {
"datasetId": {
@@ -6235,6 +7300,7 @@
"type": "object"
},
"RowAccessPolicyReference": {
+"description": "Id path of a row access policy.",
"id": "RowAccessPolicyReference",
"properties": {
"datasetId": {
@@ -6257,54 +7323,104 @@
"type": "object"
},
"RowLevelSecurityStatistics": {
+"description": "Statistics for row-level security.",
"id": "RowLevelSecurityStatistics",
"properties": {
"rowLevelSecurityApplied": {
-"description": "[Output-only] [Preview] Whether any accessed data was protected by row access policies.",
+"description": "Whether any accessed data was protected by row access policies.",
"type": "boolean"
}
},
"type": "object"
},
+"ScriptOptions": {
+"description": "Options related to script execution.",
+"id": "ScriptOptions",
+"properties": {
+"keyResultStatement": {
+"description": "Determines which statement in the script represents the \"key result\", used to populate the schema and query results of the script job. Default is LAST.",
+"enum": [
+"KEY_RESULT_STATEMENT_KIND_UNSPECIFIED",
+"LAST",
+"FIRST_SELECT"
+],
+"enumDescriptions": [
+"Default value.",
+"The last result determines the key result.",
+"The first SELECT statement determines the key result."
+],
+"type": "string"
+},
+"statementByteBudget": {
+"description": "Limit on the number of bytes billed per statement. Exceeding this budget results in an error.",
+"format": "int64",
+"type": "string"
+},
+"statementTimeoutMs": {
+"description": "Timeout period for each statement in a script.",
+"format": "int64",
+"type": "string"
+}
+},
+"type": "object"
+},
"ScriptStackFrame": {
+"description": "Represents the location of the statement/expression being evaluated. Line and column numbers are defined as follows: - Line and column numbers start with one. That is, line 1 column 1 denotes the start of the script. - When inside a stored procedure, all line/column numbers are relative to the procedure body, not the script in which the procedure was defined. - Start/end positions exclude leading/trailing comments and whitespace. The end position always ends with a \";\", when present. - Multi-byte Unicode characters are treated as just one column. - If the original script (or procedure definition) contains TAB characters, a tab \"snaps\" the indentation forward to the nearest multiple of 8 characters, plus 1. For example, a TAB on column 1, 2, 3, 4, 5, 6 , or 8 will advance the next character to column 9. A TAB on column 9, 10, 11, 12, 13, 14, 15, or 16 will advance the next character to column 17.",
"id": "ScriptStackFrame",
"properties": {
"endColumn": {
-"description": "[Output-only] One-based end column.",
+"description": "Output only. One-based end column.",
"format": "int32",
+"readOnly": true,
"type": "integer"
},
"endLine": {
-"description": "[Output-only] One-based end line.",
+"description": "Output only. One-based end line.",
"format": "int32",
+"readOnly": true,
"type": "integer"
},
"procedureId": {
-"description": "[Output-only] Name of the active procedure, empty if in a top-level script.",
+"description": "Output only. Name of the active procedure, empty if in a top-level script.",
+"readOnly": true,
"type": "string"
},
"startColumn": {
-"description": "[Output-only] One-based start column.",
+"description": "Output only. One-based start column.",
"format": "int32",
+"readOnly": true,
"type": "integer"
},
"startLine": {
-"description": "[Output-only] One-based start line.",
+"description": "Output only. One-based start line.",
"format": "int32",
+"readOnly": true,
"type": "integer"
},
"text": {
-"description": "[Output-only] Text of the current statement/expression.",
+"description": "Output only. Text of the current statement/expression.",
+"readOnly": true,
"type": "string"
}
},
"type": "object"
},
"ScriptStatistics": {
+"description": "Job statistics specific to the child job of a script.",
"id": "ScriptStatistics",
"properties": {
"evaluationKind": {
-"description": "[Output-only] Whether this child job was a statement or expression.",
+"description": "Whether this child job was a statement or expression.",
+"enum": [
+"EVALUATION_KIND_UNSPECIFIED",
+"STATEMENT",
+"EXPRESSION"
+],
+"enumDescriptions": [
+"Default value.",
+"The statement appears directly in the script.",
+"The statement evaluates an expression that appears in the script."
+],
"type": "string"
},
"stackFrames": {
@@ -6318,27 +7434,42 @@
"type": "object"
},
"SearchStatistics": {
+"description": "Statistics for a search query. Populated as part of JobStatistics2.",
"id": "SearchStatistics",
"properties": {
"indexUnusedReasons": {
-"description": "When index_usage_mode is UNUSED or PARTIALLY_USED, this field explains why index was not used in all or part of the search query. If index_usage_mode is FULLLY_USED, this field is not populated.",
+"description": "When `indexUsageMode` is `UNUSED` or `PARTIALLY_USED`, this field explains why indexes were not used in all or part of the search query. If `indexUsageMode` is `FULLY_USED`, this field is not populated.",
"items": {
"$ref": "IndexUnusedReason"
},
"type": "array"
},
"indexUsageMode": {
-"description": "Specifies index usage mode for the query.",
+"description": "Specifies the index usage mode for the query.",
+"enum": [
+"INDEX_USAGE_MODE_UNSPECIFIED",
+"UNUSED",
+"PARTIALLY_USED",
+"FULLY_USED"
+],
+"enumDescriptions": [
+"Index usage mode not specified.",
+"No search indexes were used in the search query. See [`indexUnusedReasons`] (/bigquery/docs/reference/rest/v2/Job#IndexUnusedReason) for detailed reasons.",
+"Part of the search query used search indexes. See [`indexUnusedReasons`] (/bigquery/docs/reference/rest/v2/Job#IndexUnusedReason) for why other parts of the query did not use search indexes.",
+"The entire search query used search indexes."
+],
"type": "string"
}
},
"type": "object"
},
"SessionInfo": {
+"description": "[Preview] Information related to sessions.",
"id": "SessionInfo",
"properties": {
"sessionId": {
-"description": "[Output-only] // [Preview] Id of the session.",
+"description": "Output only. The id of the session.",
+"readOnly": true,
"type": "string"
}
},
@@ -6361,14 +7492,15 @@
"type": "object"
},
"SnapshotDefinition": {
+"description": "Information about base table and snapshot time of the snapshot.",
"id": "SnapshotDefinition",
"properties": {
"baseTableReference": {
"$ref": "TableReference",
-"description": "[Required] Reference describing the ID of the table that was snapshot."
+"description": "Required. Reference describing the ID of the table that was snapshot."
},
"snapshotTime": {
-"description": "[Required] The time at which the base table was snapshot. This value is reported in the JSON response using RFC3339 format.",
+"description": "Required. The time at which the base table was snapshot. This value is reported in the JSON response using RFC3339 format.",
"format": "date-time",
"type": "string"
}
@@ -6376,14 +7508,17 @@
"type": "object"
},
"SparkLoggingInfo": {
+"description": "Spark job logs can be filtered by these fields in Cloud Logging.",
"id": "SparkLoggingInfo",
"properties": {
"projectId": {
-"description": "[Output-only] Project ID used for logging",
+"description": "Output only. Project ID where the Spark logs were written.",
+"readOnly": true,
"type": "string"
},
"resourceType": {
-"description": "[Output-only] Resource type used for logging",
+"description": "Output only. Resource type used for logging.",
+"readOnly": true,
"type": "string"
}
},
@@ -6452,25 +7587,97 @@
"type": "object"
},
"SparkStatistics": {
+"description": "Statistics for a BigSpark query. Populated as part of JobStatistics2",
"id": "SparkStatistics",
"properties": {
"endpoints": {
"additionalProperties": {
"type": "string"
},
-"description": "[Output-only] Endpoints generated for the Spark job.",
+"description": "Output only. Endpoints returned from Dataproc. Key list: - history_server_endpoint: A link to Spark job UI.",
+"readOnly": true,
"type": "object"
},
+"gcsStagingBucket": {
+"description": "Output only. The Google Cloud Storage bucket that is used as the default filesystem by the Spark application. This fields is only filled when the Spark procedure uses the INVOKER security mode. It is inferred from the system variable @@spark_proc_properties.staging_bucket if it is provided. Otherwise, BigQuery creates a default staging bucket for the job and returns the bucket name in this field. Example: * `gs://[bucket_name]`",
+"readOnly": true,
+"type": "string"
+},
+"kmsKeyName": {
+"description": "Output only. The Cloud KMS encryption key that is used to protect the resources created by the Spark job. If the Spark procedure uses DEFINER security mode, the Cloud KMS key is inferred from the Spark connection associated with the procedure if it is provided. Otherwise the key is inferred from the default key of the Spark connection's project if the CMEK organization policy is enforced. If the Spark procedure uses INVOKER security mode, the Cloud KMS encryption key is inferred from the system variable @@spark_proc_properties.kms_key_name if it is provided. Otherwise, the key is inferred fromt he default key of the BigQuery job's project if the CMEK organization policy is enforced. Example: * `projects/[kms_project_id]/locations/[region]/keyRings/[key_region]/cryptoKeys/[key]`",
+"readOnly": true,
+"type": "string"
+},
"loggingInfo": {
"$ref": "SparkLoggingInfo",
-"description": "[Output-only] Logging info is used to generate a link to Cloud Logging."
+"description": "Output only. Logging info is used to generate a link to Cloud Logging.",
+"readOnly": true
},
"sparkJobId": {
-"description": "[Output-only] Spark job id if a Spark job is created successfully.",
+"description": "Output only. Spark job ID if a Spark job is created successfully.",
+"readOnly": true,
"type": "string"
},
"sparkJobLocation": {
-"description": "[Output-only] Location where the Spark job is executed.",
+"description": "Output only. Location where the Spark job is executed. A location is selected by BigQueury for jobs configured to run in a multi-region.",
+"readOnly": true,
+"type": "string"
+}
+},
+"type": "object"
+},
+"StagePerformanceChangeInsight": {
+"description": "Performance insights compared to the previous executions for a specific stage.",
+"id": "StagePerformanceChangeInsight",
+"properties": {
+"inputDataChange": {
+"$ref": "InputDataChange",
+"description": "Output only. Input data change insight of the query stage.",
+"readOnly": true
+},
+"stageId": {
+"description": "Output only. The stage id that the insight mapped to.",
+"format": "int64",
+"readOnly": true,
+"type": "string"
+}
+},
+"type": "object"
+},
+"StagePerformanceStandaloneInsight": {
+"description": "Standalone performance insights for a specific stage.",
+"id": "StagePerformanceStandaloneInsight",
+"properties": {
+"biEngineReasons": {
+"description": "Output only. If present, the stage had the following reasons for being disqualified from BI Engine execution.",
+"items": {
+"$ref": "BiEngineReason"
+},
+"readOnly": true,
+"type": "array"
+},
+"highCardinalityJoins": {
+"description": "Output only. High cardinality joins in the stage.",
+"items": {
+"$ref": "HighCardinalityJoin"
+},
+"readOnly": true,
+"type": "array"
+},
+"insufficientShuffleQuota": {
+"description": "Output only. True if the stage has insufficient shuffle quota.",
+"readOnly": true,
+"type": "boolean"
+},
+"slotContention": {
+"description": "Output only. True if the stage has a slot contention issue.",
+"readOnly": true,
+"type": "boolean"
+},
+"stageId": {
+"description": "Output only. The stage id that the insight mapped to.",
+"format": "int64",
+"readOnly": true,
"type": "string"
}
},
@@ -6586,18 +7793,21 @@
"id": "Streamingbuffer",
"properties": {
"estimatedBytes": {
-"description": "[Output-only] A lower-bound estimate of the number of bytes currently in the streaming buffer.",
+"description": "Output only. A lower-bound estimate of the number of bytes currently in the streaming buffer.",
"format": "uint64",
+"readOnly": true,
"type": "string"
},
"estimatedRows": {
-"description": "[Output-only] A lower-bound estimate of the number of rows currently in the streaming buffer.",
+"description": "Output only. A lower-bound estimate of the number of rows currently in the streaming buffer.",
"format": "uint64",
+"readOnly": true,
"type": "string"
},
"oldestEntryTime": {
-"description": "[Output-only] Contains the timestamp of the oldest entry in the streaming buffer, in milliseconds since the epoch, if the streaming buffer is available.",
+"description": "Output only. Contains the timestamp of the oldest entry in the streaming buffer, in milliseconds since the epoch, if the streaming buffer is available.",
"format": "uint64",
+"readOnly": true,
"type": "string"
}
},
@@ -6617,36 +7827,72 @@
},
"type": "object"
},
+"SystemVariables": {
+"description": "System variables given to a query.",
+"id": "SystemVariables",
+"properties": {
+"types": {
+"additionalProperties": {
+"$ref": "StandardSqlDataType"
+},
+"description": "Output only. Data type for each system variable.",
+"readOnly": true,
+"type": "object"
+},
+"values": {
+"additionalProperties": {
+"description": "Properties of the object.",
+"type": "any"
+},
+"description": "Output only. Value for each system variable.",
+"readOnly": true,
+"type": "object"
+}
+},
+"type": "object"
+},
"Table": {
"id": "Table",
"properties": {
"biglakeConfiguration": {
"$ref": "BigLakeConfiguration",
-"description": "[Optional] Specifies the configuration of a BigLake managed table."
+"description": "Optional. Specifies the configuration of a BigLake managed table."
},
"cloneDefinition": {
"$ref": "CloneDefinition",
-"description": "[Output-only] Clone definition."
+"description": "Output only. Contains information about the clone. This value is set via the clone operation.",
+"readOnly": true
},
"clustering": {
"$ref": "Clustering",
-"description": "[Beta] Clustering specification for the table. Must be specified with partitioning, data in the table will be first partitioned and subsequently clustered."
+"description": "Clustering specification for the table. Must be specified with time-based partitioning, data in the table will be first partitioned and subsequently clustered."
},
"creationTime": {
-"description": "[Output-only] The time when this table was created, in milliseconds since the epoch.",
+"description": "Output only. The time when this table was created, in milliseconds since the epoch.",
"format": "int64",
+"readOnly": true,
"type": "string"
},
"defaultCollation": {
-"description": "[Output-only] The default collation of the table.",
+"description": "Optional. Defines the default collation specification of new STRING fields in the table. During table creation or update, if a STRING field is added to this table without explicit collation specified, then the table inherits the table default collation. A change to this field affects only fields added afterwards, and does not alter the existing fields. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.",
"type": "string"
},
"defaultRoundingMode": {
-"description": "[Output-only] The default rounding mode of the table.",
+"description": "Optional. Defines the default rounding mode specification of new decimal fields (NUMERIC OR BIGNUMERIC) in the table. During table creation or update, if a decimal field is added to this table without an explicit rounding mode specified, then the field inherits the table default rounding mode. Changing this field doesn't affect existing fields.",
+"enum": [
+"ROUNDING_MODE_UNSPECIFIED",
+"ROUND_HALF_AWAY_FROM_ZERO",
+"ROUND_HALF_EVEN"
+],
+"enumDescriptions": [
+"Unspecified will default to using ROUND_HALF_AWAY_FROM_ZERO.",
+"ROUND_HALF_AWAY_FROM_ZERO rounds half values away from zero when applying precision and scale upon writing of NUMERIC and BIGNUMERIC values. For Scale: 0 1.1, 1.2, 1.3, 1.4 => 1 1.5, 1.6, 1.7, 1.8, 1.9 => 2",
+"ROUND_HALF_EVEN rounds half values to the nearest even value when applying precision and scale upon writing of NUMERIC and BIGNUMERIC values. For Scale: 0 1.1, 1.2, 1.3, 1.4 => 1 1.5 => 2 1.6, 1.7, 1.8, 1.9 => 2 2.5 => 2"
+],
"type": "string"
},
"description": {
-"description": "[Optional] A user-friendly description of this table.",
+"description": "Optional. A user-friendly description of this table.",
"type": "string"
},
"encryptionConfiguration": {
@@ -6654,29 +7900,31 @@
"description": "Custom encryption configuration (e.g., Cloud KMS keys)."
},
"etag": {
-"description": "[Output-only] A hash of the table metadata. Used to ensure there were no concurrent modifications to the resource when attempting an update. Not guaranteed to change when the table contents or the fields numRows, numBytes, numLongTermBytes or lastModifiedTime change.",
+"description": "Output only. A hash of this resource.",
+"readOnly": true,
"type": "string"
},
"expirationTime": {
-"description": "[Optional] The time when this table expires, in milliseconds since the epoch. If not present, the table will persist indefinitely. Expired tables will be deleted and their storage reclaimed. The defaultTableExpirationMs property of the encapsulating dataset can be used to set a default expirationTime on newly created tables.",
+"description": "Optional. The time when this table expires, in milliseconds since the epoch. If not present, the table will persist indefinitely. Expired tables will be deleted and their storage reclaimed. The defaultTableExpirationMs property of the encapsulating dataset can be used to set a default expirationTime on newly created tables.",
"format": "int64",
"type": "string"
},
"externalDataConfiguration": {
"$ref": "ExternalDataConfiguration",
-"description": "[Optional] Describes the data format, location, and other properties of a table stored outside of BigQuery. By defining these properties, the data source can then be queried as if it were a standard BigQuery table."
+"description": "Optional. Describes the data format, location, and other properties of a table stored outside of BigQuery. By defining these properties, the data source can then be queried as if it were a standard BigQuery table."
},
"friendlyName": {
-"description": "[Optional] A descriptive name for this table.",
+"description": "Optional. A descriptive name for this table.",
"type": "string"
},
"id": {
-"description": "[Output-only] An opaque ID uniquely identifying the table.",
+"description": "Output only. An opaque ID uniquely identifying the table.",
+"readOnly": true,
"type": "string"
},
"kind": {
"default": "bigquery#table",
-"description": "[Output-only] The type of the resource.",
+"description": "The type of resource ID.",
"type": "string"
},
"labels": {
@@ -6687,94 +7935,120 @@
"type": "object"
},
"lastModifiedTime": {
-"description": "[Output-only] The time when this table was last modified, in milliseconds since the epoch.",
+"description": "Output only. The time when this table was last modified, in milliseconds since the epoch.",
"format": "uint64",
+"readOnly": true,
"type": "string"
},
"location": {
-"description": "[Output-only] The geographic location where the table resides. This value is inherited from the dataset.",
+"description": "Output only. The geographic location where the table resides. This value is inherited from the dataset.",
+"readOnly": true,
"type": "string"
},
"materializedView": {
"$ref": "MaterializedViewDefinition",
-"description": "[Optional] Materialized view definition."
+"description": "Optional. The materialized view definition."
+},
+"materializedViewStatus": {
+"$ref": "MaterializedViewStatus",
+"description": "Output only. The materialized view status.",
+"readOnly": true
},
"maxStaleness": {
-"description": "[Optional] Max staleness of data that could be returned when table or materialized view is queried (formatted as Google SQL Interval type).",
-"format": "byte",
+"description": "Optional. The maximum staleness of data that could be returned when the table (or stale MV) is queried. Staleness encoded as a string encoding of sql IntervalValue type.",
"type": "string"
},
"model": {
"$ref": "ModelDefinition",
-"description": "[Output-only, Beta] Present iff this table represents a ML model. Describes the training information for the model, and it is required to run 'PREDICT' queries."
+"description": "Deprecated."
},
"numActiveLogicalBytes": {
-"description": "[Output-only] Number of logical bytes that are less than 90 days old.",
+"description": "Output only. Number of logical bytes that are less than 90 days old.",
"format": "int64",
+"readOnly": true,
"type": "string"
},
"numActivePhysicalBytes": {
-"description": "[Output-only] Number of physical bytes less than 90 days old. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.",
+"description": "Output only. Number of physical bytes less than 90 days old. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.",
"format": "int64",
+"readOnly": true,
"type": "string"
},
"numBytes": {
-"description": "[Output-only] The size of this table in bytes, excluding any data in the streaming buffer.",
+"description": "Output only. The size of this table in logical bytes, excluding any data in the streaming buffer.",
"format": "int64",
+"readOnly": true,
"type": "string"
},
"numLongTermBytes": {
-"description": "[Output-only] The number of bytes in the table that are considered \"long-term storage\".",
+"description": "Output only. The number of logical bytes in the table that are considered \"long-term storage\".",
"format": "int64",
+"readOnly": true,
"type": "string"
},
"numLongTermLogicalBytes": {
-"description": "[Output-only] Number of logical bytes that are more than 90 days old.",
+"description": "Output only. Number of logical bytes that are more than 90 days old.",
"format": "int64",
+"readOnly": true,
"type": "string"
},
"numLongTermPhysicalBytes": {
-"description": "[Output-only] Number of physical bytes more than 90 days old. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.",
+"description": "Output only. Number of physical bytes more than 90 days old. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.",
"format": "int64",
+"readOnly": true,
"type": "string"
},
"numPartitions": {
-"description": "[Output-only] The number of partitions present in the table or materialized view. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.",
+"description": "Output only. The number of partitions present in the table or materialized view. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.",
"format": "int64",
+"readOnly": true,
"type": "string"
},
"numPhysicalBytes": {
-"description": "[Output-only] [TrustedTester] The physical size of this table in bytes, excluding any data in the streaming buffer. This includes compression and storage used for time travel.",
+"description": "Output only. The physical size of this table in bytes. This includes storage used for time travel.",
"format": "int64",
+"readOnly": true,
"type": "string"
},
"numRows": {
-"description": "[Output-only] The number of rows of data in this table, excluding any data in the streaming buffer.",
+"description": "Output only. The number of rows of data in this table, excluding any data in the streaming buffer.",
"format": "uint64",
+"readOnly": true,
"type": "string"
},
"numTimeTravelPhysicalBytes": {
-"description": "[Output-only] Number of physical bytes used by time travel storage (deleted or changed data). This data is not kept in real time, and might be delayed by a few seconds to a few minutes.",
+"description": "Output only. Number of physical bytes used by time travel storage (deleted or changed data). This data is not kept in real time, and might be delayed by a few seconds to a few minutes.",
"format": "int64",
+"readOnly": true,
"type": "string"
},
"numTotalLogicalBytes": {
-"description": "[Output-only] Total number of logical bytes in the table or materialized view.",
+"description": "Output only. Total number of logical bytes in the table or materialized view.",
"format": "int64",
+"readOnly": true,
"type": "string"
},
"numTotalPhysicalBytes": {
-"description": "[Output-only] The physical size of this table in bytes. This also includes storage used for time travel. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.",
+"description": "Output only. The physical size of this table in bytes. This also includes storage used for time travel. This data is not kept in real time, and might be delayed by a few seconds to a few minutes.",
"format": "int64",
+"readOnly": true,
"type": "string"
},
"rangePartitioning": {
"$ref": "RangePartitioning",
-"description": "[TrustedTester] Range partitioning specification for this table. Only one of timePartitioning and rangePartitioning should be specified."
+"description": "If specified, configures range partitioning for this table."
+},
+"replicas": {
+"description": "Optional. Output only. Table references of all replicas currently active on the table.",
+"items": {
+"$ref": "TableReference"
+},
+"readOnly": true,
+"type": "array"
},
"requirePartitionFilter": {
"default": "false",
-"description": "[Optional] If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified.",
+"description": "Optional. If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified.",
"type": "boolean"
},
"resourceTags": {
@@ -6786,39 +8060,47 @@
},
"schema": {
"$ref": "TableSchema",
-"description": "[Optional] Describes the schema of this table."
+"description": "Optional. Describes the schema of this table."
},
"selfLink": {
-"description": "[Output-only] A URL that can be used to access this resource again.",
+"description": "Output only. A URL that can be used to access this resource again.",
+"readOnly": true,
"type": "string"
},
"snapshotDefinition": {
"$ref": "SnapshotDefinition",
-"description": "[Output-only] Snapshot definition."
+"description": "Output only. Contains information about the snapshot. This value is set via snapshot creation.",
+"readOnly": true
},
"streamingBuffer": {
"$ref": "Streamingbuffer",
-"description": "[Output-only] Contains information regarding this table's streaming buffer, if one is present. This field will be absent if the table is not being streamed to or if there is no data in the streaming buffer."
+"description": "Output only. Contains information regarding this table's streaming buffer, if one is present. This field will be absent if the table is not being streamed to or if there is no data in the streaming buffer.",
+"readOnly": true
},
"tableConstraints": {
"$ref": "TableConstraints",
-"description": "[Optional] The table constraints on the table."
+"description": "Optional. Tables Primary Key and Foreign Key information"
},
"tableReference": {
"$ref": "TableReference",
-"description": "[Required] Reference describing the ID of this table."
+"description": "Required. Reference describing the ID of this table."
+},
+"tableReplicationInfo": {
+"$ref": "TableReplicationInfo",
+"description": "Optional. Table replication info for table created `AS REPLICA` DDL like: `CREATE MATERIALIZED VIEW mv1 AS REPLICA OF src_mv`"
},
"timePartitioning": {
"$ref": "TimePartitioning",
-"description": "Time-based partitioning specification for this table. Only one of timePartitioning and rangePartitioning should be specified."
+"description": "If specified, configures time-based partitioning for this table."
},
"type": {
-"description": "[Output-only] Describes the table type. The following values are supported: TABLE: A normal BigQuery table. VIEW: A virtual table defined by a SQL query. SNAPSHOT: An immutable, read-only table that is a copy of another table. [TrustedTester] MATERIALIZED_VIEW: SQL query whose result is persisted. EXTERNAL: A table that references data stored in an external storage system, such as Google Cloud Storage. The default value is TABLE.",
+"description": "Output only. Describes the table type. The following values are supported: * `TABLE`: A normal BigQuery table. * `VIEW`: A virtual table defined by a SQL query. * `EXTERNAL`: A table that references data stored in an external storage system, such as Google Cloud Storage. * `MATERIALIZED_VIEW`: A precomputed view defined by a SQL query. * `SNAPSHOT`: An immutable BigQuery table that preserves the contents of a base table at a particular time. See additional information on [table snapshots](/bigquery/docs/table-snapshots-intro). The default value is `TABLE`.",
+"readOnly": true,
"type": "string"
},
"view": {
"$ref": "ViewDefinition",
-"description": "[Optional] The view definition."
+"description": "Optional. The view definition."
}
},
"type": "object"
@@ -6833,19 +8115,25 @@
"type": "object"
},
"TableConstraints": {
+"description": "The TableConstraints defines the primary key and foreign key.",
"id": "TableConstraints",
"properties": {
"foreignKeys": {
-"description": "[Optional] The foreign keys of the tables.",
+"description": "Optional. Present only if the table has a foreign key. The foreign key is not enforced.",
"items": {
+"description": "Represents a foreign key constraint on a table's columns.",
"properties": {
"columnReferences": {
+"description": "Required. The columns that compose the foreign key.",
"items": {
+"description": "The pair of the foreign key column and primary key column.",
"properties": {
"referencedColumn": {
+"description": "Required. The column in the primary key that are referenced by the referencing_column.",
"type": "string"
},
"referencingColumn": {
+"description": "Required. The column that composes the foreign key.",
"type": "string"
}
},
@@ -6854,6 +8142,7 @@
"type": "array"
},
"name": {
+"description": "Optional. Set only if the foreign key constraint is named.",
"type": "string"
},
"referencedTable": {
@@ -6876,9 +8165,10 @@
"type": "array"
},
"primaryKey": {
-"description": "[Optional] The primary key of the table.",
+"description": "Represents the primary key constraint on a table's columns.",
"properties": {
"columns": {
+"description": "Required. The columns that are composed of the primary key constraint.",
"items": {
"type": "string"
},
@@ -6891,28 +8181,29 @@
"type": "object"
},
"TableDataInsertAllRequest": {
+"description": "Request for sending a single streaming insert.",
"id": "TableDataInsertAllRequest",
"properties": {
"ignoreUnknownValues": {
-"description": "[Optional] Accept rows that contain values that do not match the schema. The unknown values are ignored. Default is false, which treats unknown values as errors.",
+"description": "Optional. Accept rows that contain values that do not match the schema. The unknown values are ignored. Default is false, which treats unknown values as errors.",
"type": "boolean"
},
"kind": {
"default": "bigquery#tableDataInsertAllRequest",
-"description": "The resource type of the response.",
+"description": "Optional. The resource type of the response. The value is not checked at the backend. Historically, it has been set to \"bigquery#tableDataInsertAllRequest\" but you are not required to set it.",
"type": "string"
},
"rows": {
-"description": "The rows to insert.",
"items": {
+"description": "Data for a single insertion row.",
"properties": {
"insertId": {
-"description": "[Optional] A unique ID for each row. BigQuery uses this property to detect duplicate insertion requests on a best-effort basis.",
+"description": "Insertion ID for best-effort deduplication. This feature is not recommended, and users seeking stronger insertion semantics are encouraged to use other mechanisms such as the BigQuery Write API.",
"type": "string"
},
"json": {
"$ref": "JsonObject",
-"description": "[Required] A JSON object that contains a row of data. The object's properties and values must match the destination table's schema."
+"description": "Data for a single row."
}
},
"type": "object"
@@ -6920,22 +8211,28 @@
"type": "array"
},
"skipInvalidRows": {
-"description": "[Optional] Insert all valid rows of a request, even if invalid rows exist. The default value is false, which causes the entire request to fail if any invalid rows exist.",
+"description": "Optional. Insert all valid rows of a request, even if invalid rows exist. The default value is false, which causes the entire request to fail if any invalid rows exist.",
"type": "boolean"
},
"templateSuffix": {
-"description": "If specified, treats the destination table as a base template, and inserts the rows into an instance table named \"{destination}{templateSuffix}\". BigQuery will manage creation of the instance table, using the schema of the base template table. See https://cloud.google.com/bigquery/streaming-data-into-bigquery#template-tables for considerations when working with templates tables.",
+"description": "Optional. If specified, treats the destination table as a base template, and inserts the rows into an instance table named \"{destination}{templateSuffix}\". BigQuery will manage creation of the instance table, using the schema of the base template table. See https://cloud.google.com/bigquery/streaming-data-into-bigquery#template-tables for considerations when working with templates tables.",
+"type": "string"
+},
+"traceId": {
+"description": "Optional. Unique request trace id. Used for debugging purposes only. It is case-sensitive, limited to up to 36 ASCII characters. A UUID is recommended.",
"type": "string"
}
},
"type": "object"
},
"TableDataInsertAllResponse": {
+"description": "Describes the format of a streaming insert response.",
"id": "TableDataInsertAllResponse",
"properties": {
"insertErrors": {
-"description": "An array of errors for rows that were not inserted.",
+"description": "Describes specific errors encountered while processing the request.",
"items": {
+"description": "Error details about a single row's insertion.",
"properties": {
"errors": {
"description": "Error information for the row indicated by the index property.",
@@ -6956,7 +8253,7 @@
},
"kind": {
"default": "bigquery#tableDataInsertAllResponse",
-"description": "The resource type of the response.",
+"description": "Returns \"bigquery#tableDataInsertAllResponse\".",
"type": "string"
}
},
@@ -6986,7 +8283,7 @@
"type": "array"
},
"totalRows": {
-"description": "The total number of rows in the complete table.",
+"description": "Total rows of the entire table. In order to show default value 0 we have to present it as string.",
"format": "int64",
"type": "string"
}
@@ -6994,13 +8291,14 @@
"type": "object"
},
"TableFieldSchema": {
+"description": "A field in TableSchema",
"id": "TableFieldSchema",
"properties": {
"categories": {
-"description": "[Optional] The categories attached to this field, used for field-level access control.",
+"description": "Deprecated.",
"properties": {
"names": {
-"description": "A list of category resource names. For example, \"projects/1/taxonomies/2/categories/3\". At most 5 categories are allowed.",
+"description": "Deprecated.",
"items": {
"type": "string"
},
@@ -7010,41 +8308,42 @@
"type": "object"
},
"collation": {
-"description": "Optional. Collation specification of the field. It only can be set on string type field.",
+"description": "Optional. Field collation can be set only when the type of field is STRING. The following values are supported: * 'und:ci': undetermined locale, case insensitive. * '': empty string. Default to case-sensitive behavior.",
"type": "string"
},
"defaultValueExpression": {
-"description": "Optional. A SQL expression to specify the default value for this field. It can only be set for top level fields (columns). You can use struct or array expression to specify default value for the entire struct or array. The valid SQL expressions are: - Literals for all data types, including STRUCT and ARRAY. - Following functions: - CURRENT_TIMESTAMP - CURRENT_TIME - CURRENT_DATE - CURRENT_DATETIME - GENERATE_UUID - RAND - SESSION_USER - ST_GEOGPOINT - Struct or array composed with the above allowed functions, for example, [CURRENT_DATE(), DATE '2020-01-01']",
+"description": "Optional. A SQL expression to specify the [default value] (https://cloud.google.com/bigquery/docs/default-values) for this field.",
"type": "string"
},
"description": {
-"description": "[Optional] The field description. The maximum length is 1,024 characters.",
+"description": "Optional. The field description. The maximum length is 1,024 characters.",
"type": "string"
},
"fields": {
-"description": "[Optional] Describes the nested schema fields if the type property is set to RECORD.",
+"description": "Optional. Describes the nested schema fields if the type property is set to RECORD.",
"items": {
"$ref": "TableFieldSchema"
},
"type": "array"
},
"maxLength": {
-"description": "[Optional] Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = \"STRING\", then max_length represents the maximum UTF-8 length of strings in this field. If type = \"BYTES\", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type \u2260 \"STRING\" and \u2260 \"BYTES\".",
+"description": "Optional. Maximum length of values of this field for STRINGS or BYTES. If max_length is not specified, no maximum length constraint is imposed on this field. If type = \"STRING\", then max_length represents the maximum UTF-8 length of strings in this field. If type = \"BYTES\", then max_length represents the maximum number of bytes in this field. It is invalid to set this field if type \u2260 \"STRING\" and \u2260 \"BYTES\".",
"format": "int64",
"type": "string"
},
"mode": {
-"description": "[Optional] The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.",
+"description": "Optional. The field mode. Possible values include NULLABLE, REQUIRED and REPEATED. The default value is NULLABLE.",
"type": "string"
},
"name": {
-"description": "[Required] The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.",
+"description": "Required. The field name. The name must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_), and must start with a letter or underscore. The maximum length is 300 characters.",
"type": "string"
},
"policyTags": {
+"description": "Optional. The policy tags attached to this field, used for field-level access control. If not set, defaults to empty policy_tags.",
"properties": {
"names": {
-"description": "A list of category resource names. For example, \"projects/1/location/eu/taxonomies/2/policyTags/3\". At most 1 policy tag is allowed.",
+"description": "A list of policy tag resource names. For example, \"projects/1/locations/eu/taxonomies/2/policyTags/3\". At most 1 policy tag is currently allowed.",
"items": {
"type": "string"
},
@@ -7054,37 +8353,48 @@
"type": "object"
},
"precision": {
-"description": "[Optional] Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type \u2260 \"NUMERIC\" and \u2260 \"BIGNUMERIC\". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: - Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] - Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: - If type = \"NUMERIC\": 1 \u2264 precision - scale \u2264 29 and 0 \u2264 scale \u2264 9. - If type = \"BIGNUMERIC\": 1 \u2264 precision - scale \u2264 38 and 0 \u2264 scale \u2264 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): - If type = \"NUMERIC\": 1 \u2264 precision \u2264 29. - If type = \"BIGNUMERIC\": 1 \u2264 precision \u2264 38. If scale is specified but not precision, then it is invalid.",
+"description": "Optional. Precision (maximum number of total digits in base 10) and scale (maximum number of digits in the fractional part in base 10) constraints for values of this field for NUMERIC or BIGNUMERIC. It is invalid to set precision or scale if type \u2260 \"NUMERIC\" and \u2260 \"BIGNUMERIC\". If precision and scale are not specified, no value range constraint is imposed on this field insofar as values are permitted by the type. Values of this NUMERIC or BIGNUMERIC field must be in this range when: * Precision (P) and scale (S) are specified: [-10P-S + 10-S, 10P-S - 10-S] * Precision (P) is specified but not scale (and thus scale is interpreted to be equal to zero): [-10P + 1, 10P - 1]. Acceptable values for precision and scale if both are specified: * If type = \"NUMERIC\": 1 \u2264 precision - scale \u2264 29 and 0 \u2264 scale \u2264 9. * If type = \"BIGNUMERIC\": 1 \u2264 precision - scale \u2264 38 and 0 \u2264 scale \u2264 38. Acceptable values for precision if only precision is specified but not scale (and thus scale is interpreted to be equal to zero): * If type = \"NUMERIC\": 1 \u2264 precision \u2264 29. * If type = \"BIGNUMERIC\": 1 \u2264 precision \u2264 38. If scale is specified but not precision, then it is invalid.",
"format": "int64",
"type": "string"
},
"rangeElementType": {
-"description": "Optional. The subtype of the RANGE, if the type of this field is RANGE. If the type is RANGE, this field is required. Possible values for the field element type of a RANGE include: - DATE - DATETIME - TIMESTAMP",
+"description": "Represents the type of a field element.",
"properties": {
"type": {
-"description": "The field element type of a RANGE",
+"description": "Required. The type of a field element. See TableFieldSchema.type.",
"type": "string"
}
},
"type": "object"
},
"roundingMode": {
-"description": "Optional. Rounding Mode specification of the field. It only can be set on NUMERIC or BIGNUMERIC type fields.",
+"description": "Optional. Specifies the rounding mode to be used when storing values of NUMERIC and BIGNUMERIC type.",
+"enum": [
+"ROUNDING_MODE_UNSPECIFIED",
+"ROUND_HALF_AWAY_FROM_ZERO",
+"ROUND_HALF_EVEN"
+],
+"enumDescriptions": [
+"Unspecified will default to using ROUND_HALF_AWAY_FROM_ZERO.",
+"ROUND_HALF_AWAY_FROM_ZERO rounds half values away from zero when applying precision and scale upon writing of NUMERIC and BIGNUMERIC values. For Scale: 0 1.1, 1.2, 1.3, 1.4 => 1 1.5, 1.6, 1.7, 1.8, 1.9 => 2",
+"ROUND_HALF_EVEN rounds half values to the nearest even value when applying precision and scale upon writing of NUMERIC and BIGNUMERIC values. For Scale: 0 1.1, 1.2, 1.3, 1.4 => 1 1.5 => 2 1.6, 1.7, 1.8, 1.9 => 2 2.5 => 2"
+],
"type": "string"
},
"scale": {
-"description": "[Optional] See documentation for precision.",
+"description": "Optional. See documentation for precision.",
"format": "int64",
"type": "string"
},
"type": {
-"description": "[Required] The field data type. Possible values include STRING, BYTES, INTEGER, INT64 (same as INTEGER), FLOAT, FLOAT64 (same as FLOAT), NUMERIC, BIGNUMERIC, BOOLEAN, BOOL (same as BOOLEAN), TIMESTAMP, DATE, TIME, DATETIME, INTERVAL, RECORD (where RECORD indicates that the field contains a nested schema) or STRUCT (same as RECORD).",
+"description": "Required. The field data type. Possible values include: * STRING * BYTES * INTEGER (or INT64) * FLOAT (or FLOAT64) * BOOLEAN (or BOOL) * TIMESTAMP * DATE * TIME * DATETIME * GEOGRAPHY * NUMERIC * BIGNUMERIC * JSON * RECORD (or STRUCT) Use of RECORD/STRUCT indicates that the field contains a nested schema.",
"type": "string"
}
},
"type": "object"
},
"TableList": {
+"description": "Partial projection of the metadata for a given table in a list response.",
"id": "TableList",
"properties": {
"etag": {
@@ -7106,15 +8416,16 @@
"properties": {
"clustering": {
"$ref": "Clustering",
-"description": "[Beta] Clustering specification for this table, if configured."
+"description": "Clustering specification for this table, if configured."
},
"creationTime": {
-"description": "The time when this table was created, in milliseconds since the epoch.",
+"description": "Output only. The time when this table was created, in milliseconds since the epoch.",
"format": "int64",
+"readOnly": true,
"type": "string"
},
"expirationTime": {
-"description": "[Optional] The time when this table expires, in milliseconds since the epoch. If not present, the table will persist indefinitely. Expired tables will be deleted and their storage reclaimed.",
+"description": "The time when this table expires, in milliseconds since the epoch. If not present, the table will persist indefinitely. Expired tables will be deleted and their storage reclaimed.",
"format": "int64",
"type": "string"
},
@@ -7123,11 +8434,10 @@
"type": "string"
},
"id": {
-"description": "An opaque ID of the table",
+"description": "An opaque ID of the table.",
"type": "string"
},
"kind": {
-"default": "bigquery#table",
"description": "The resource type.",
"type": "string"
},
@@ -7140,25 +8450,34 @@
},
"rangePartitioning": {
"$ref": "RangePartitioning",
-"description": "The range partitioning specification for this table, if configured."
+"description": "The range partitioning for this table."
+},
+"requirePartitionFilter": {
+"default": "false",
+"description": "Optional. If set to true, queries including this table must specify a partition filter. This filter is used for partition elimination.",
+"type": "boolean"
},
"tableReference": {
"$ref": "TableReference",
-"description": "A reference uniquely identifying the table."
+"description": "A reference uniquely identifying table."
},
"timePartitioning": {
"$ref": "TimePartitioning",
-"description": "The time-based partitioning specification for this table, if configured."
+"description": "The time-based partitioning for this table."
},
"type": {
-"description": "The type of table. Possible values are: TABLE, VIEW.",
+"description": "The type of table.",
"type": "string"
},
"view": {
-"description": "Additional details for a view.",
+"description": "Information about a logical view.",
"properties": {
+"privacyPolicy": {
+"$ref": "PrivacyPolicy",
+"description": "Specifices the privacy policy for the view."
+},
"useLegacySql": {
-"description": "True if view is defined in legacy SQL dialect, false if in standard SQL.",
+"description": "True if view is defined in legacy SQL dialect, false if in GoogleSQL.",
"type": "boolean"
}
},
@@ -7177,35 +8496,101 @@
},
"type": "object"
},
+"TableMetadataCacheUsage": {
+"description": "Table level detail on the usage of metadata caching. Only set for Metadata caching eligible tables referenced in the query.",
+"id": "TableMetadataCacheUsage",
+"properties": {
+"explanation": {
+"description": "Free form human-readable reason metadata caching was unused for the job.",
+"type": "string"
+},
+"tableReference": {
+"$ref": "TableReference",
+"description": "Metadata caching eligible table referenced in the query."
+},
+"tableType": {
+"description": "[Table type](/bigquery/docs/reference/rest/v2/tables#Table.FIELDS.type).",
+"type": "string"
+},
+"unusedReason": {
+"description": "Reason for not using metadata caching for the table.",
+"enum": [
+"UNUSED_REASON_UNSPECIFIED",
+"EXCEEDED_MAX_STALENESS",
+"METADATA_CACHING_NOT_ENABLED",
+"OTHER_REASON"
+],
+"enumDescriptions": [
+"Unused reasons not specified.",
+"Metadata cache was outside the table's maxStaleness.",
+"Metadata caching feature is not enabled. [Update BigLake tables] (/bigquery/docs/create-cloud-storage-table-biglake#update-biglake-tables) to enable the metadata caching.",
+"Other unknown reason."
+],
+"type": "string"
+}
+},
+"type": "object"
+},
"TableReference": {
"id": "TableReference",
"properties": {
"datasetId": {
-"annotations": {
-"required": [
-"bigquery.tables.update"
-]
-},
-"description": "[Required] The ID of the dataset containing this table.",
+"description": "Required. The ID of the dataset containing this table.",
"type": "string"
},
"projectId": {
-"annotations": {
-"required": [
-"bigquery.tables.update"
-]
-},
-"description": "[Required] The ID of the project containing this table.",
+"description": "Required. The ID of the project containing this table.",
"type": "string"
},
"tableId": {
-"annotations": {
-"required": [
-"bigquery.tables.update"
-]
+"description": "Required. The ID of the table. The ID can contain Unicode characters in category L (letter), M (mark), N (number), Pc (connector, including underscore), Pd (dash), and Zs (space). For more information, see [General Category](https://wikipedia.org/wiki/Unicode_character_property#General_Category). The maximum length is 1,024 characters. Certain operations allow suffixing of the table ID with a partition decorator, such as `sample_table$20190123`.",
+"type": "string"
+}
+},
+"type": "object"
+},
+"TableReplicationInfo": {
+"description": "Replication info of a table created using `AS REPLICA` DDL like: `CREATE MATERIALIZED VIEW mv1 AS REPLICA OF src_mv`",
+"id": "TableReplicationInfo",
+"properties": {
+"replicatedSourceLastRefreshTime": {
+"description": "Optional. Output only. If source is a materialized view, this field signifies the last refresh time of the source.",
+"format": "int64",
+"readOnly": true,
+"type": "string"
+},
+"replicationError": {
+"$ref": "ErrorProto",
+"description": "Optional. Output only. Replication error that will permanently stopped table replication.",
+"readOnly": true
+},
+"replicationIntervalMs": {
+"description": "Required. Specifies the interval at which the source table is polled for updates.",
+"format": "int64",
+"type": "string"
},
-"description": "[Required] The ID of the table. The ID must contain only letters (a-z, A-Z), numbers (0-9), or underscores (_). The maximum length is 1,024 characters.",
+"replicationStatus": {
+"description": "Optional. Output only. Replication status of configured replication.",
+"enum": [
+"REPLICATION_STATUS_UNSPECIFIED",
+"ACTIVE",
+"SOURCE_DELETED",
+"PERMISSION_DENIED",
+"UNSUPPORTED_CONFIGURATION"
+],
+"enumDescriptions": [
+"Default value.",
+"Replication is Active with no errors.",
+"Source object is deleted.",
+"Source revoked replication permissions.",
+"Source configuration doesn\u2019t allow replication."
+],
+"readOnly": true,
"type": "string"
+},
+"sourceTable": {
+"$ref": "TableReference",
+"description": "Required. Source table reference that is replicated."
}
},
"type": "object"
@@ -7224,6 +8609,7 @@
"type": "object"
},
"TableSchema": {
+"description": "Schema of a table",
"id": "TableSchema",
"properties": {
"fields": {
@@ -7268,19 +8654,22 @@
"id": "TimePartitioning",
"properties": {
"expirationMs": {
-"description": "[Optional] Number of milliseconds for which to keep the storage for partitions in the table. The storage in a partition will have an expiration time of its partition time plus this value.",
+"description": "Optional. Number of milliseconds for which to keep the storage for a partition. A wrapper is used here because 0 is an invalid value.",
"format": "int64",
"type": "string"
},
"field": {
-"description": "[Beta] [Optional] If not set, the table is partitioned by pseudo column, referenced via either '_PARTITIONTIME' as TIMESTAMP type, or '_PARTITIONDATE' as DATE type. If field is specified, the table is instead partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED.",
+"description": "Optional. If not set, the table is partitioned by pseudo column '_PARTITIONTIME'; if set, the table is partitioned by this field. The field must be a top-level TIMESTAMP or DATE field. Its mode must be NULLABLE or REQUIRED. A wrapper is used here because an empty string is an invalid value.",
"type": "string"
},
"requirePartitionFilter": {
+"default": "false",
+"deprecated": true,
+"description": "If set to true, queries over this table require a partition filter that can be used for partition elimination to be specified. This field is deprecated; please set the field with the same name on the table itself instead. This field needs a wrapper because we want to output the default value, false, if the user explicitly set it.",
"type": "boolean"
},
"type": {
-"description": "[Required] The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively. When the type is not specified, the default behavior is DAY.",
+"description": "Required. The supported types are DAY, HOUR, MONTH, and YEAR, which will generate one partition per day, hour, month, and year, respectively.",
"type": "string"
}
},
@@ -8265,10 +9654,12 @@
"type": "object"
},
"TransactionInfo": {
+"description": "[Alpha] Information of a multi-statement transaction.",
"id": "TransactionInfo",
"properties": {
"transactionId": {
-"description": "[Output-only] // [Alpha] Id of the transaction.",
+"description": "Output only. [Alpha] Id of the transaction.",
+"readOnly": true,
"type": "string"
}
},
@@ -8296,8 +9687,20 @@
},
"type": "object"
},
+"UndeleteDatasetRequest": {
+"description": "Request format for undeleting a dataset.",
+"id": "UndeleteDatasetRequest",
+"properties": {
+"deletionTime": {
+"description": "Optional. The exact time when the dataset was deleted. If not specified, it will undelete the most recently deleted version.",
+"format": "google-datetime",
+"type": "string"
+}
+},
+"type": "object"
+},
"UserDefinedFunctionResource": {
-"description": "This is used for defining User Defined Function (UDF) resources only when using legacy SQL. Users of Standard SQL should leverage either DDL (e.g. CREATE [TEMPORARY] FUNCTION ... ) or the Routines API to define UDF resources. For additional information on migrating, see: https://cloud.google.com/bigquery/docs/reference/standard-sql/migrating-from-legacy-sql#differences_in_user-defined_javascript_functions",
+"description": " This is used for defining User Defined Function (UDF) resources only when using legacy SQL. Users of GoogleSQL should leverage either DDL (e.g. CREATE [TEMPORARY] FUNCTION ... ) or the Routines API to define UDF resources. For additional information on migrating, see: https://cloud.google.com/bigquery/docs/reference/standard-sql/migrating-from-legacy-sql#differences_in_user-defined_javascript_functions",
"id": "UserDefinedFunctionResource",
"properties": {
"inlineCode": {
@@ -8342,18 +9745,23 @@
"type": "object"
},
"ViewDefinition": {
+"description": "Describes the definition of a logical view.",
"id": "ViewDefinition",
"properties": {
+"privacyPolicy": {
+"$ref": "PrivacyPolicy",
+"description": "Optional. Specifices the privacy policy for the view."
+},
"query": {
-"description": "[Required] A query that BigQuery executes when the view is referenced.",
+"description": "Required. A query that BigQuery executes when the view is referenced.",
"type": "string"
},
"useExplicitColumnNames": {
-"description": "True if the column names are explicitly specified. For example by using the 'CREATE VIEW v(c1, c2) AS ...' syntax. Can only be set using BigQuery's standard SQL: https://cloud.google.com/bigquery/sql-reference/",
+"description": "True if the column names are explicitly specified. For example by using the 'CREATE VIEW v(c1, c2) AS ...' syntax. Can only be set for GoogleSQL views.",
"type": "boolean"
},
"useLegacySql": {
-"description": "Specifies whether to use BigQuery's legacy SQL for this view. The default value is true. If set to false, the view will use BigQuery's standard SQL: https://cloud.google.com/bigquery/sql-reference/ Queries and views that reference this view must use the same flag value.",
+"description": "Specifies whether to use BigQuery's legacy SQL for this view. The default value is true. If set to false, the view will use BigQuery's GoogleSQL: https://cloud.google.com/bigquery/sql-reference/ Queries and views that reference this view must use the same flag value. A wrapper is used here because the default value is True.",
"type": "boolean"
},
"userDefinedFunctionResources": {