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97 lines
2.7 KiB
Python
97 lines
2.7 KiB
Python
# Licensed to the Apache Software Foundation (ASF) under one or more
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# contributor license agreements. See the NOTICE file distributed with
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# this work for additional information regarding copyright ownership.
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# The ASF licenses this file to You under the Apache License, Version 2.0
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# (the "License"); you may not use this file except in compliance with
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# the License. You may obtain a copy of the License at
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#
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# http://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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import pathlib
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from datetime import timedelta
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from airflow import DAG
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import json
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try:
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from airflow.operators.python import PythonOperator
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except ModuleNotFoundError:
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from airflow.operators.python_operator import PythonOperator
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from metadata.config.common import load_config_file
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from metadata.ingestion.api.workflow import Workflow
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from airflow.utils.dates import days_ago
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default_args = {
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"owner": "user_name",
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"email": ["username@org.com"],
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"email_on_failure": False,
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"retries": 3,
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"retry_delay": timedelta(minutes=5),
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"execution_timeout": timedelta(minutes=60)
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}
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config = """
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{
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"source": {
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"type": "sample-usage",
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"config": {
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"database": "warehouse",
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"service_name": "gcp_bigquery",
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"sample_data_folder": "./examples/sample_data"
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}
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},
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"processor": {
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"type": "query-parser",
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"config": {
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"filter": ""
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}
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},
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"stage": {
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"type": "table-usage",
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"config": {
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"filename": "/tmp/sample_usage"
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}
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},
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"bulk_sink": {
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"type": "metadata-usage",
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"config": {
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"filename": "/tmp/sample_usage"
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}
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},
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"metadata_server": {
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"type": "metadata-server",
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"config": {
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"api_endpoint": "http://localhost:8585/api",
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"auth_provider_type": "no-auth"
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}
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}
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}
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"""
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def metadata_ingestion_workflow():
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workflow_config = json.loads(config)
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workflow = Workflow.create(workflow_config)
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workflow.execute()
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workflow.raise_from_status()
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workflow.print_status()
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workflow.stop()
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with DAG(
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"sample_usage",
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default_args=default_args,
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description="An example DAG which runs a OpenMetadata ingestion workflow",
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schedule_interval=timedelta(days=1),
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start_date=days_ago(1),
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is_paused_upon_creation=False,
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catchup=False,
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) as dag:
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ingest_task = PythonOperator(
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task_id="ingest_using_recipe",
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python_callable=metadata_ingestion_workflow,
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) |