#
# 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 __future__ import annotations
from airflow import models
from airflow.providers.apache.beam.operators.beam import BeamRunPythonPipelineOperator
from airflow.providers.google.cloud.operators.dataflow import DataflowConfiguration
from tests.system.providers.apache.beam.utils import (
DEFAULT_ARGS,
GCP_PROJECT_ID,
GCS_OUTPUT,
GCS_PYTHON,
GCS_STAGING,
GCS_TMP,
START_DATE,
)
with models.DAG(
dag_id="dataflow_native_python_async",
start_date=START_DATE,
schedule=None, # Override to match your needs
catchup=False,
default_args=DEFAULT_ARGS,
tags=["example"],
) as dag:
# [START howto_operator_start_python_direct_runner_pipeline_local_file_async]
[docs] start_python_pipeline_local_direct_runner = BeamRunPythonPipelineOperator(
task_id="start_python_pipeline_local_direct_runner",
py_file="apache_beam.examples.wordcount",
py_options=["-m"],
py_requirements=["apache-beam[gcp]==2.46.0"],
py_interpreter="python3",
py_system_site_packages=False,
deferrable=True,
)
# [END howto_operator_start_python_direct_runner_pipeline_local_file_async]
# [START howto_operator_start_python_direct_runner_pipeline_gcs_file_async]
start_python_pipeline_direct_runner = BeamRunPythonPipelineOperator(
task_id="start_python_pipeline_direct_runner",
py_file=GCS_PYTHON,
py_options=[],
pipeline_options={"output": GCS_OUTPUT},
py_requirements=["apache-beam[gcp]==2.46.0"],
py_interpreter="python3",
py_system_site_packages=False,
deferrable=True,
)
# [END howto_operator_start_python_direct_runner_pipeline_gcs_file_async]
# [START howto_operator_start_python_dataflow_runner_pipeline_gcs_file_async]
start_python_pipeline_dataflow_runner = BeamRunPythonPipelineOperator(
task_id="start_python_pipeline_dataflow_runner",
runner="DataflowRunner",
py_file=GCS_PYTHON,
pipeline_options={
"tempLocation": GCS_TMP,
"stagingLocation": GCS_STAGING,
"output": GCS_OUTPUT,
},
py_options=[],
py_requirements=["apache-beam[gcp]==2.46.0"],
py_interpreter="python3",
py_system_site_packages=False,
dataflow_config=DataflowConfiguration(
job_name="{{task.task_id}}", project_id=GCP_PROJECT_ID, location="us-central1"
),
deferrable=True,
)
# [END howto_operator_start_python_dataflow_runner_pipeline_gcs_file_async]
# [START howto_operator_start_python_pipeline_local_runner_spark_runner_async]
start_python_pipeline_local_spark_runner = BeamRunPythonPipelineOperator(
task_id="start_python_pipeline_local_spark_runner",
py_file="apache_beam.examples.wordcount",
runner="SparkRunner",
py_options=["-m"],
py_requirements=["apache-beam[gcp]==2.46.0"],
py_interpreter="python3",
py_system_site_packages=False,
deferrable=True,
)
# [END howto_operator_start_python_pipeline_local_runner_spark_runner_async]
# [START howto_operator_start_python_pipeline_local_runner_flink_runner_async]
start_python_pipeline_local_flink_runner = BeamRunPythonPipelineOperator(
task_id="start_python_pipeline_local_flink_runner",
py_file="apache_beam.examples.wordcount",
runner="FlinkRunner",
py_options=["-m"],
pipeline_options={
"output": "/tmp/start_python_pipeline_local_flink_runner",
},
py_requirements=["apache-beam[gcp]==2.46.0"],
py_interpreter="python3",
py_system_site_packages=False,
deferrable=True,
)
# [END howto_operator_start_python_pipeline_local_runner_flink_runner_async]
(
[
start_python_pipeline_local_direct_runner,
start_python_pipeline_direct_runner,
]
>> start_python_pipeline_dataflow_runner
>> start_python_pipeline_local_flink_runner
>> start_python_pipeline_local_spark_runner
)
from tests.system.utils import get_test_run
# Needed to run the example DAG with pytest (see: tests/system/README.md#run_via_pytest)
[docs]test_run = get_test_run(dag)