[ML] API integration tests for partition_fields_values endpoint

x-pack/plugins/ml/server/models/results_service/get_partition_fields_values.ts

@@ -6,6 +6,7 @@
  */
 
 import Boom from '@hapi/boom';
+import type * as estypes from '@elastic/elasticsearch/lib/api/typesWithBodyKey';
 import { PARTITION_FIELDS } from '../../../common/constants/anomalies';
 import { PartitionFieldsType } from '../../../common/types/anomalies';
 import { CriteriaField } from './results_service';
@@ -18,6 +19,11 @@ type SearchTerm =
     }
   | undefined;
 
+export interface PartitionFieldData {
+  name: string;
+  values: Array<{ value: string; maxRecordScore?: number }>;
+}
+
 /**
  * Gets an object for aggregation query to retrieve field name and values.
  * @param fieldType - Field type
@@ -110,23 +116,38 @@ function getFieldAgg(
  * @param fieldType - Field type
  * @param aggs - Aggregation response
  */
-function getFieldObject(fieldType: PartitionFieldsType, aggs: any) {
-  const fieldNameKey = `${fieldType}_name`;
-  const fieldValueKey = `${fieldType}_value`;
+function getFieldObject(
+  fieldType: PartitionFieldsType,
+  aggs: Record<estypes.AggregateName, estypes.AggregationsAggregate>
+): Record<PartitionFieldsType, PartitionFieldData> | {} {
+  const fieldNameKey = `${fieldType}_name` as const;
+  const fieldValueKey = `${fieldType}_value` as const;
+
+  const fieldNameAgg = aggs[fieldNameKey] as estypes.AggregationsMultiTermsAggregate;
+  const fieldValueAgg = aggs[fieldValueKey] as unknown as {
+    values: estypes.AggregationsMultiBucketAggregateBase<{
+      key: string;
+      maxRecordScore?: { value: number };
+    }>;
+  };
 
-  return aggs[fieldNameKey].buckets.length > 0
+  return Array.isArray(fieldNameAgg.buckets) && fieldNameAgg.buckets.length > 0
     ? {
         [fieldType]: {
-          name: aggs[fieldNameKey].buckets[0].key,
-          values: aggs[fieldValueKey].values.buckets.map(({ key, maxRecordScore }: any) => ({
-            value: key,
-            ...(maxRecordScore ? { maxRecordScore: maxRecordScore.value } : {}),
-          })),
+          name: fieldNameAgg.buckets[0].key,
+          values: Array.isArray(fieldValueAgg.values.buckets)
+            ? fieldValueAgg.values.buckets.map(({ key, maxRecordScore }) => ({
+                value: key,
+                ...(maxRecordScore ? { maxRecordScore: maxRecordScore.value } : {}),
+              }))
+            : [],
         },
       }
     : {};
 }
 
+export type PartitionFieldValueResponse = Record<PartitionFieldsType, PartitionFieldData>;
+
 export const getPartitionFieldsValuesFactory = (mlClient: MlClient) =>
   /**
    * Gets the record of partition fields with possible values that fit the provided queries.
@@ -144,15 +165,15 @@ export const getPartitionFieldsValuesFactory = (mlClient: MlClient) =>
     earliestMs: number,
     latestMs: number,
     fieldsConfig: FieldsConfig = {}
-  ) {
+  ): Promise<PartitionFieldValueResponse | {}> {
     const jobsResponse = await mlClient.getJobs({ job_id: jobId });
     if (jobsResponse.count === 0 || jobsResponse.jobs === undefined) {
       throw Boom.notFound(`Job with the id "${jobId}" not found`);
     }
 
     const job = jobsResponse.jobs[0];
 
-    const isModelPlotEnabled = job?.model_plot_config?.enabled;
+    const isModelPlotEnabled = !!job?.model_plot_config?.enabled;
     const isAnomalousOnly = (Object.entries(fieldsConfig) as Array<[string, FieldConfig]>).some(
       ([k, v]) => {
         return !!v?.anomalousOnly;
@@ -165,14 +186,14 @@ export const getPartitionFieldsValuesFactory = (mlClient: MlClient) =>
       }
     );
 
-    const isModelPlotSearch = !!isModelPlotEnabled && !isAnomalousOnly;
+    const isModelPlotSearch = isModelPlotEnabled && !isAnomalousOnly;
 
     // Remove the time filter in case model plot is not enabled
     // and time range is not applied, so
     // it includes the records that occurred as anomalies historically
     const searchAllTime = !isModelPlotEnabled && !applyTimeRange;
 
-    const requestBody = {
+    const requestBody: estypes.SearchRequest['body'] = {
       query: {
         bool: {
           filter: [
@@ -230,7 +251,7 @@ export const getPartitionFieldsValuesFactory = (mlClient: MlClient) =>
     return PARTITION_FIELDS.reduce((acc, key) => {
       return {
         ...acc,
-        ...getFieldObject(key, body.aggregations),
+        ...getFieldObject(key, body.aggregations!),
       };
     }, {});
   };

x-pack/test/api_integration/apis/ml/results/get_partition_fields_values.ts

@@ -0,0 +1,233 @@
+/*
+ * Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
+ * or more contributor license agreements. Licensed under the Elastic License
+ * 2.0; you may not use this file except in compliance with the Elastic License
+ * 2.0.
+ */
+
+import expect from '@kbn/expect';
+import { Datafeed, Job } from '@kbn/ml-plugin/common/types/anomaly_detection_jobs';
+import type { PartitionFieldValueResponse } from '@kbn/ml-plugin/server/models/results_service/get_partition_fields_values';
+import { USER } from '../../../../functional/services/ml/security_common';
+import { FtrProviderContext } from '../../../ftr_provider_context';
+import { COMMON_REQUEST_HEADERS } from '../../../../functional/services/ml/common_api';
+
+export default ({ getService }: FtrProviderContext) => {
+  const esArchiver = getService('esArchiver');
+  const supertest = getService('supertestWithoutAuth');
+  const ml = getService('ml');
+
+  function getJobConfig(jobId: string, enableModelPlot = true) {
+    return {
+      job_id: jobId,
+      description:
+        'mean/min/max(responsetime) partition=airline on farequote dataset with 1h bucket span',
+      groups: ['farequote', 'automated', 'multi-metric'],
+      analysis_config: {
+        bucket_span: '1h',
+        influencers: ['airline'],
+        detectors: [
+          { function: 'mean', field_name: 'responsetime', partition_field_name: 'airline' },
+          { function: 'min', field_name: 'responsetime', partition_field_name: 'airline' },
+          { function: 'max', field_name: 'responsetime', partition_field_name: 'airline' },
+        ],
+      },
+      data_description: { time_field: '@timestamp' },
+      analysis_limits: { model_memory_limit: '20mb' },
+      model_plot_config: { enabled: enableModelPlot },
+    } as Job;
+  }
+
+  function getDatafeedConfig(jobId: string) {
+    return {
+      datafeed_id: `datafeed-${jobId}`,
+      indices: ['ft_farequote'],
+      job_id: jobId,
+      query: { bool: { must: [{ match_all: {} }] } },
+    } as Datafeed;
+  }
+
+  async function createMockJobs() {
+    await ml.api.createAndRunAnomalyDetectionLookbackJob(
+      getJobConfig('fq_multi_1_ae'),
+      getDatafeedConfig('fq_multi_1_ae')
+    );
+
+    await ml.api.createAndRunAnomalyDetectionLookbackJob(
+      getJobConfig('fq_multi_2_ae', false),
+      getDatafeedConfig('fq_multi_2_ae')
+    );
+  }
+
+  async function runRequest(requestBody: object): Promise<PartitionFieldValueResponse> {
+    const { body, status } = await supertest
+      .post(`/api/ml/results/partition_fields_values`)
+      .auth(USER.ML_VIEWER, ml.securityCommon.getPasswordForUser(USER.ML_VIEWER))
+      .set(COMMON_REQUEST_HEADERS)
+      .send(requestBody);
+    ml.api.assertResponseStatusCode(200, status, body);
+    return body;
+  }
+
+  describe('GetAnomaliesTableData', function () {
+    before(async () => {
+      await esArchiver.loadIfNeeded('x-pack/test/functional/es_archives/ml/farequote');
+      await ml.testResources.setKibanaTimeZoneToUTC();
+      await createMockJobs();
+    });
+
+    after(async () => {
+      await ml.api.cleanMlIndices();
+    });
+
+    describe('when model plot is enabled', () => {
+      it('should fetch anomalous only field values within the time range with an empty search term sorting by anomaly score', async () => {
+        const requestBody = {
+          jobId: 'fq_multi_1_ae',
+          criteriaFields: [{ fieldName: 'detector_index', fieldValue: 0 }],
+          earliestMs: 1454889600000, // February 8, 2016 12:00:00 AM GMT
+          latestMs: 1454976000000, // February 9, 2016 12:00:00 AM GMT,
+          searchTerm: {},
+          fieldsConfig: {
+            partition_field: {
+              applyTimeRange: true,
+              anomalousOnly: true,
+              sort: { by: 'anomaly_score', order: 'desc' },
+            },
+          },
+        };
+
+        const body = await runRequest(requestBody);
+
+        expect(body.partition_field.name).to.eql('airline');
+        expect(body.partition_field.values.length).to.eql(6);
+        expect(body.partition_field.values[0].value).to.eql('ACA');
+        expect(body.partition_field.values[0].maxRecordScore).to.be.above(0);
+        expect(body.partition_field.values[1].value).to.eql('JBU');
+        expect(body.partition_field.values[1].maxRecordScore).to.be.above(0);
+        expect(body.partition_field.values[2].value).to.eql('SWR');
+        expect(body.partition_field.values[2].maxRecordScore).to.be.above(0);
+        expect(body.partition_field.values[3].value).to.eql('BAW');
+        expect(body.partition_field.values[3].maxRecordScore).to.be.above(0);
+        expect(body.partition_field.values[4].value).to.eql('TRS');
+        expect(body.partition_field.values[4].maxRecordScore).to.be.above(0);
+        expect(body.partition_field.values[5].value).to.eql('EGF');
+        expect(body.partition_field.values[5].maxRecordScore).to.be.above(0);
+      });
+
+      it('should fetch all values withing the time range sorting by name', async () => {
+        const requestBody = {
+          jobId: 'fq_multi_1_ae',
+          criteriaFields: [{ fieldName: 'detector_index', fieldValue: 0 }],
+          earliestMs: 1454889600000, // February 8, 2016 12:00:00 AM GMT
+          latestMs: 1454976000000, // February 9, 2016 12:00:00 AM GMT,
+          searchTerm: {},
+          fieldsConfig: {
+            partition_field: {
+              applyTimeRange: true,
+              anomalousOnly: false,
+              sort: { by: 'name', order: 'asc' },
+            },
+          },
+        };
+
+        const body = await runRequest(requestBody);
+
+        expect(body).to.eql({
+          partition_field: {
+            name: 'airline',
+            values: [
+              { value: 'AAL' },
+              { value: 'ACA' },
+              { value: 'AMX' },
+              { value: 'ASA' },
+              { value: 'AWE' },
+              { value: 'BAW' },
+              { value: 'DAL' },
+              { value: 'EGF' },
+              { value: 'FFT' },
+              { value: 'JAL' },
+              { value: 'JBU' },
+              { value: 'JZA' },
+              { value: 'KLM' },
+              { value: 'NKS' },
+              { value: 'SWA' },
+              { value: 'SWR' },
+              { value: 'TRS' },
+              { value: 'UAL' },
+              { value: 'VRD' },
+            ],
+          },
+        });
+      });
+
+      it('should fetch anomalous only field value applying the search term', async () => {
+        const requestBody = {
+          jobId: 'fq_multi_1_ae',
+          criteriaFields: [{ fieldName: 'detector_index', fieldValue: 0 }],
+          earliestMs: 1454889600000, // February 8, 2016 12:00:00 AM GMT
+          latestMs: 1454976000000, // February 9, 2016 12:00:00 AM GMT,
+          searchTerm: {
+            partition_field: 'JB',
+          },
+          fieldsConfig: {
+            partition_field: {
+              applyTimeRange: true,
+              anomalousOnly: true,
+              sort: { by: 'anomaly_score', order: 'asc' },
+            },
+          },
+        };
+
+        const body = await runRequest(requestBody);
+
+        expect(body.partition_field.name).to.eql('airline');
+        expect(body.partition_field.values.length).to.eql(1);
+        expect(body.partition_field.values[0].value).to.eql('JBU');
+        expect(body.partition_field.values[0].maxRecordScore).to.be.above(0);
+      });
+    });
+
+    describe('when model plot is disabled', () => {
+      it('should fetch results within the time range', async () => {
+        const requestBody = {
+          jobId: 'fq_multi_2_ae',
+          criteriaFields: [{ fieldName: 'detector_index', fieldValue: 0 }],
+          earliestMs: 1454889600000, // February 8, 2016 12:00:00 AM GMT
+          latestMs: 1454976000000, // February 9, 2016 12:00:00 AM GMT,
+          searchTerm: {},
+          fieldsConfig: {
+            partition_field: {
+              applyTimeRange: true,
+              anomalousOnly: false,
+              sort: { by: 'name', order: 'asc' },
+            },
+          },
+        };
+
+        const body = await runRequest(requestBody);
+        expect(body.partition_field.values.length).to.eql(6);
+      });
+
+      it('should fetch results outside the time range', async () => {
+        const requestBody = {
+          jobId: 'fq_multi_2_ae',
+          criteriaFields: [{ fieldName: 'detector_index', fieldValue: 0 }],
+          earliestMs: 1454889600000, // February 8, 2016 12:00:00 AM GMT
+          latestMs: 1454976000000, // February 9, 2016 12:00:00 AM GMT,
+          searchTerm: {},
+          fieldsConfig: {
+            partition_field: {
+              applyTimeRange: false,
+              anomalousOnly: false,
+              sort: { by: 'name', order: 'asc' },
+            },
+          },
+        };
+
+        const body = await runRequest(requestBody);
+        expect(body.partition_field.values.length).to.eql(19);
+      });
+    });
+  });
+};

x-pack/test/api_integration/apis/ml/results/index.ts

@@ -14,5 +14,6 @@ export default function ({ loadTestFile }: FtrProviderContext) {
     loadTestFile(require.resolve('./get_stopped_partitions'));
     loadTestFile(require.resolve('./get_category_definition'));
     loadTestFile(require.resolve('./get_category_examples'));
+    loadTestFile(require.resolve('./get_partition_fields_values'));
   });
 }