shaniyaclement commented on code in PR #32843: URL: https://github.com/apache/airflow/pull/32843#discussion_r1277954776
########## airflow/providers/google/cloud/example_dags/google-datapipeline.py: ########## @@ -0,0 +1,99 @@ +# +# 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" + +GCP_PROJECT_ID = os.environ.get("GCP_PROJECT_ID", "example-project") Review Comment: updated ########## airflow/providers/google/cloud/example_dags/google-datapipeline.py: ########## @@ -0,0 +1,99 @@ +# +# 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" + +GCP_PROJECT_ID = os.environ.get("GCP_PROJECT_ID", "example-project") +GCP_LOCATION = os.environ.get("location", "us-central1") +PIPELINE_NAME = "defualt-pipeline-name" +PIPELINE_TYPE = "PIPELINE_TYPE_BATCH" + +DATAPIPELINES_JOB_NAME = os.environ.get("GCP_DATA_PIPELINES_FLEX_TEMPLATE_JOB_NAME", "default-job-name") + +GCS_FLEX_TEMPLATE_TEMPLATE_PATH = os.environ.get( + "GCP_DATA_PIPELINES_GCS_FLEX_TEMPLATE_TEMPLATE_PATH", + "gs://INSERT BUCKET/templates/word-count.json", +) + +TEMP_LOCATION = os.environ.get("GCP_DATA_PIPELINES_GCS_TEMP_LOCATION", "gs://INSERT BUCKET/temp") +INPUT_FILE = os.environ.get("GCP_DATA_PIPELINES_INPUT_FILE", "gs://INSERT BUCKET/examples/kinglear.txt") +OUTPUT = os.environ.get("GCP_DATA_PIPELINES_OUTPUT", "gs://INSERT BUCKET/results/hello") Review Comment: updated -- This is an automated message from the Apache Git Service. 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