110 lines
4.0 KiB
Python
110 lines
4.0 KiB
Python
# Copyright 2023 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# https://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# --------------------------------------------------------------------------------
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# Load The Dependencies
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# --------------------------------------------------------------------------------
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import datetime
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from airflow import models
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from airflow.models.variable import Variable
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from airflow.operators import empty
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from airflow.providers.google.cloud.operators.dataflow import DataflowTemplatedJobStartOperator
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# --------------------------------------------------------------------------------
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# Set variables - Needed for the DEMO
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# --------------------------------------------------------------------------------
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BQ_LOCATION = Variable.get("BQ_LOCATION")
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CURATED_PRJ = Variable.get("CURATED_PRJ")
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CURATED_BQ_DATASET = Variable.get("CURATED_BQ_DATASET")
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CURATED_GCS = Variable.get("CURATED_GCS")
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LAND_PRJ = Variable.get("LAND_PRJ")
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LAND_GCS = Variable.get("LAND_GCS")
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PROCESSING_GCS = Variable.get("PROCESSING_GCS")
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PROCESSING_SA = Variable.get("PROCESSING_SA")
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PROCESSING_PRJ = Variable.get("PROCESSING_PRJ")
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PROCESSING_SUBNET = Variable.get("PROCESSING_SUBNET")
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PROCESSING_VPC = Variable.get("PROCESSING_VPC")
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DP_KMS_KEY = Variable.get("DP_KMS_KEY", "")
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DP_REGION = Variable.get("DP_REGION")
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DP_ZONE = Variable.get("DP_REGION") + "-b"
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# --------------------------------------------------------------------------------
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# Set default arguments
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# --------------------------------------------------------------------------------
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# If you are running Airflow in more than one time zone
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# see https://airflow.apache.org/docs/apache-airflow/stable/timezone.html
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# for best practices
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yesterday = datetime.datetime.now() - datetime.timedelta(days=1)
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default_args = {
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'owner': 'airflow',
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'start_date': yesterday,
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'depends_on_past': False,
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'email': [''],
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'email_on_failure': False,
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'email_on_retry': False,
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'retries': 1,
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'retry_delay': datetime.timedelta(minutes=5),
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'dataflow_default_options': {
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'location': DP_REGION,
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'zone': DP_ZONE,
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'stagingLocation': PROCESSING_GCS + "/staging",
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'tempLocation': PROCESSING_GCS + "/tmp",
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'serviceAccountEmail': PROCESSING_SA,
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'subnetwork': PROCESSING_SUBNET,
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'ipConfiguration': "WORKER_IP_PRIVATE",
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'kmsKeyName' : DP_KMS_KEY
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},
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}
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# --------------------------------------------------------------------------------
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# Main DAG
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# --------------------------------------------------------------------------------
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with models.DAG(
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'dataflow_gcs2bq',
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default_args=default_args,
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schedule_interval=None) as dag:
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start = empty.EmptyOperator(
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task_id='start',
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trigger_rule='all_success'
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)
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end = empty.EmptyOperator(
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task_id='end',
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trigger_rule='all_success'
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)
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# Bigquery Tables automatically created for demo porpuse.
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# Consider a dedicated pipeline or tool for a real life scenario.
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customers_import = DataflowTemplatedJobStartOperator(
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task_id="dataflow_customers_import",
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template="gs://dataflow-templates/latest/GCS_Text_to_BigQuery",
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project_id=PROCESSING_PRJ,
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location=DP_REGION,
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parameters={
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"javascriptTextTransformFunctionName": "transform",
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"JSONPath": PROCESSING_GCS + "/customers_schema.json",
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"javascriptTextTransformGcsPath": PROCESSING_GCS + "/customers_udf.js",
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"inputFilePattern": LAND_GCS + "/customers.csv",
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"outputTable": CURATED_PRJ + ":" + CURATED_BQ_DATASET + ".customers",
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"bigQueryLoadingTemporaryDirectory": PROCESSING_GCS + "/tmp/bq/",
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},
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)
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start >> customers_import >> end
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