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* AIP-47 - Migrate beam DAGs to new design #22439
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airflow/providers/apache/beam/example_dags/example_beam.py
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,66 @@ | ||
| # | ||
| # 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, | ||
| ) | ||
|
|
||
| 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: | ||
|
|
||
| # [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", | ||
| ) | ||
|
|
||
| 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', | ||
| ) | ||
|
|
||
| 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 | ||
|
|
||
| # 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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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -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_FLINK_RUNNER_BUCKET_NAME, | ||
| GCS_JAR_FLINK_RUNNER_OBJECT_NAME, | ||
| START_DATE, | ||
| ) | ||
|
|
||
| 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: | ||
|
|
||
| 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", | ||
| ) | ||
|
|
||
| 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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|
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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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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -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, | ||
| ) | ||
|
|
||
| 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: | ||
|
|
||
| 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", | ||
| ) | ||
|
|
||
| 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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|
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| from tests.system.utils import get_test_run | ||
|
|
||
| # 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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