[GitHub] [airflow] blpham commented on a diff in pull request #32846: Adding Support for Google Cloud's Data Pipelines Run Operator

["blpham (via GitHub)" <gi...@apache.org>]

blpham commented on code in PR #32846:
URL: https://github.com/apache/airflow/pull/32846#discussion_r1275359928


##########
airflow/providers/google/cloud/example_dags/google-datapipeline.py:
##########
@@ -0,0 +1,56 @@
+#
+# 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 testing Google Dataflow Beam Pipeline Operator with Java.
+Important Note:
+    This test downloads Java JAR file from the public bucket. In case the JAR file cannot be downloaded
+    or is not compatible with the Java version used in the test, the source code for this test can be
+    downloaded from here (https://beam.apache.org/get-started/wordcount-example) and needs to be compiled
+    manually in order to work.
+    You can follow the instructions on how to pack a self-executing jar here:
+    https://beam.apache.org/documentation/runners/dataflow/
+Requirements:
+    These operators require the gcloud command and Java's JRE to run.
+"""
+from __future__ import annotations
+
+import os
+from datetime import datetime
+
+from airflow import models
+from airflow.providers.apache.beam.hooks.beam import BeamRunnerType
+from airflow.providers.google.cloud.operators.datapipeline import CreateDataPipelineOperator, RunDataPipelineOperator
+from airflow.providers.google.cloud.operators.gcs import GCSCreateBucketOperator, GCSDeleteBucketOperator
+from airflow.providers.google.cloud.transfers.gcs_to_local import GCSToLocalFilesystemOperator
+from airflow.utils.trigger_rule import TriggerRule
+
+DAG_ID = "google-datapipeline"
+
+with models.DAG(
+    DAG_ID,
+    schedule="@once",
+    start_date=datetime(2021, 1, 1),
+    catchup=False,
+    tags=["example", "datapipeline"],
+) as dag:
+    run_data_pipeline = RunDataPipelineOperator(
+        task_id = "run_data_pipeline",
+        data_pipeline_name = "dp-create-1642676351302-mp--1675461000"

Review Comment:
   added global variable DATA_PIPELINE_NAME for use in DAG



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