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AIP-47 - Migrate beam DAGs to new design apache#22439
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airflow/providers/apache/beam/example_dags/example_beam.py
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# | ||
# Licensed to the Apache Software Foundation (ASF) under one | ||
# or more contributor license agreements. See the NOTICE file | ||
# distributed with this work for additional information | ||
# regarding copyright ownership. The ASF licenses this file | ||
# to you under the Apache License, Version 2.0 (the | ||
# "License"); you may not use this file except in compliance | ||
# with the License. You may obtain a copy of the License at | ||
# | ||
# http://www.apache.org/licenses/LICENSE-2.0 | ||
# | ||
# Unless required by applicable law or agreed to in writing, | ||
# software distributed under the License is distributed on an | ||
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY | ||
# KIND, either express or implied. See the License for the | ||
# specific language governing permissions and limitations | ||
# under the License. | ||
|
||
""" | ||
Example Airflow DAG for Apache Beam operators | ||
""" | ||
|
||
from airflow import models | ||
from airflow.providers.apache.beam.operators.beam import BeamRunJavaPipelineOperator | ||
from airflow.providers.google.cloud.transfers.gcs_to_local import GCSToLocalFilesystemOperator | ||
from tests.system.providers.apache.beam.utils import ( | ||
GCS_INPUT, | ||
GCS_JAR_DIRECT_RUNNER_BUCKET_NAME, | ||
GCS_JAR_DIRECT_RUNNER_OBJECT_NAME, | ||
START_DATE, | ||
) | ||
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with models.DAG( | ||
"example_beam_native_java_direct_runner", | ||
schedule_interval=None, # Override to match your needs | ||
start_date=START_DATE, | ||
catchup=False, | ||
tags=['example'], | ||
) as dag: | ||
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# [START howto_operator_start_java_direct_runner_pipeline] | ||
jar_to_local_direct_runner = GCSToLocalFilesystemOperator( | ||
task_id="jar_to_local_direct_runner", | ||
bucket=GCS_JAR_DIRECT_RUNNER_BUCKET_NAME, | ||
object_name=GCS_JAR_DIRECT_RUNNER_OBJECT_NAME, | ||
filename="/tmp/beam_wordcount_direct_runner_{{ ds_nodash }}.jar", | ||
) | ||
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start_java_pipeline_direct_runner = BeamRunJavaPipelineOperator( | ||
task_id="start_java_pipeline_direct_runner", | ||
jar="/tmp/beam_wordcount_direct_runner_{{ ds_nodash }}.jar", | ||
pipeline_options={ | ||
'output': '/tmp/start_java_pipeline_direct_runner', | ||
'inputFile': GCS_INPUT, | ||
}, | ||
job_class='org.apache.beam.examples.WordCount', | ||
) | ||
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jar_to_local_direct_runner >> start_java_pipeline_direct_runner | ||
# [END howto_operator_start_java_direct_runner_pipeline] | ||
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from tests.system.utils import get_test_run | ||
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# Needed to run the example DAG with pytest (see: tests/system/README.md#run_via_pytest) | ||
test_run = get_test_run(dag) |
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tests/system/providers/apache/beam/example_beam_java_flink.py
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# | ||
# Licensed to the Apache Software Foundation (ASF) under one | ||
# or more contributor license agreements. See the NOTICE file | ||
# distributed with this work for additional information | ||
# regarding copyright ownership. The ASF licenses this file | ||
# to you under the Apache License, Version 2.0 (the | ||
# "License"); you may not use this file except in compliance | ||
# with the License. You may obtain a copy of the License at | ||
# | ||
# http://www.apache.org/licenses/LICENSE-2.0 | ||
# | ||
# Unless required by applicable law or agreed to in writing, | ||
# software distributed under the License is distributed on an | ||
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY | ||
# KIND, either express or implied. See the License for the | ||
# specific language governing permissions and limitations | ||
# under the License. | ||
|
||
""" | ||
Example Airflow DAG for Apache Beam operators | ||
""" | ||
|
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from airflow import models | ||
from airflow.providers.apache.beam.operators.beam import BeamRunJavaPipelineOperator | ||
from airflow.providers.google.cloud.transfers.gcs_to_local import GCSToLocalFilesystemOperator | ||
from tests.system.providers.apache.beam.utils import ( | ||
GCS_INPUT, | ||
GCS_JAR_FLINK_RUNNER_BUCKET_NAME, | ||
GCS_JAR_FLINK_RUNNER_OBJECT_NAME, | ||
START_DATE, | ||
) | ||
|
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with models.DAG( | ||
"example_beam_native_java_flink_runner", | ||
schedule_interval=None, # Override to match your needs | ||
start_date=START_DATE, | ||
catchup=False, | ||
tags=['example'], | ||
) as dag: | ||
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jar_to_local_flink_runner = GCSToLocalFilesystemOperator( | ||
task_id="jar_to_local_flink_runner", | ||
bucket=GCS_JAR_FLINK_RUNNER_BUCKET_NAME, | ||
object_name=GCS_JAR_FLINK_RUNNER_OBJECT_NAME, | ||
filename="/tmp/beam_wordcount_flink_runner_{{ ds_nodash }}.jar", | ||
) | ||
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start_java_pipeline_flink_runner = BeamRunJavaPipelineOperator( | ||
task_id="start_java_pipeline_flink_runner", | ||
runner="FlinkRunner", | ||
jar="/tmp/beam_wordcount_flink_runner_{{ ds_nodash }}.jar", | ||
pipeline_options={ | ||
'output': '/tmp/start_java_pipeline_flink_runner', | ||
'inputFile': GCS_INPUT, | ||
}, | ||
job_class='org.apache.beam.examples.WordCount', | ||
) | ||
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jar_to_local_flink_runner >> start_java_pipeline_flink_runner | ||
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from tests.system.utils import get_test_run | ||
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# Needed to run the example DAG with pytest (see: tests/system/README.md#run_via_pytest) | ||
test_run = get_test_run(dag) |
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tests/system/providers/apache/beam/example_beam_java_spark.py
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@@ -0,0 +1,65 @@ | ||
# | ||
# Licensed to the Apache Software Foundation (ASF) under one | ||
# or more contributor license agreements. See the NOTICE file | ||
# distributed with this work for additional information | ||
# regarding copyright ownership. The ASF licenses this file | ||
# to you under the Apache License, Version 2.0 (the | ||
# "License"); you may not use this file except in compliance | ||
# with the License. You may obtain a copy of the License at | ||
# | ||
# http://www.apache.org/licenses/LICENSE-2.0 | ||
# | ||
# Unless required by applicable law or agreed to in writing, | ||
# software distributed under the License is distributed on an | ||
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY | ||
# KIND, either express or implied. See the License for the | ||
# specific language governing permissions and limitations | ||
# under the License. | ||
|
||
""" | ||
Example Airflow DAG for Apache Beam operators | ||
""" | ||
|
||
from airflow import models | ||
from airflow.providers.apache.beam.operators.beam import BeamRunJavaPipelineOperator | ||
from airflow.providers.google.cloud.transfers.gcs_to_local import GCSToLocalFilesystemOperator | ||
from tests.system.providers.apache.beam.utils import ( | ||
GCS_INPUT, | ||
GCS_JAR_SPARK_RUNNER_BUCKET_NAME, | ||
GCS_JAR_SPARK_RUNNER_OBJECT_NAME, | ||
START_DATE, | ||
) | ||
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||
with models.DAG( | ||
"example_beam_native_java_spark_runner", | ||
schedule_interval=None, # Override to match your needs | ||
start_date=START_DATE, | ||
catchup=False, | ||
tags=['example'], | ||
) as dag: | ||
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jar_to_local_spark_runner = GCSToLocalFilesystemOperator( | ||
task_id="jar_to_local_spark_runner", | ||
bucket=GCS_JAR_SPARK_RUNNER_BUCKET_NAME, | ||
object_name=GCS_JAR_SPARK_RUNNER_OBJECT_NAME, | ||
filename="/tmp/beam_wordcount_spark_runner_{{ ds_nodash }}.jar", | ||
) | ||
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start_java_pipeline_spark_runner = BeamRunJavaPipelineOperator( | ||
task_id="start_java_pipeline_spark_runner", | ||
runner="SparkRunner", | ||
jar="/tmp/beam_wordcount_spark_runner_{{ ds_nodash }}.jar", | ||
pipeline_options={ | ||
'output': '/tmp/start_java_pipeline_spark_runner', | ||
'inputFile': GCS_INPUT, | ||
}, | ||
job_class='org.apache.beam.examples.WordCount', | ||
) | ||
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jar_to_local_spark_runner >> start_java_pipeline_spark_runner | ||
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from tests.system.utils import get_test_run | ||
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# Needed to run the example DAG with pytest (see: tests/system/README.md#run_via_pytest) | ||
test_run = get_test_run(dag) |
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