# Copyright 2025 Collate # Licensed under the Collate Community License, Version 1.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # https://github.com/open-metadata/OpenMetadata/blob/main/ingestion/LICENSE # 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. import json from datetime import timedelta from airflow import DAG try: from airflow.operators.python import PythonOperator except ModuleNotFoundError: from airflow.operators.python_operator import PythonOperator from airflow.utils.dates import days_ago from metadata.workflow.usage import UsageWorkflow default_args = { "owner": "user_name", "email": ["username@org.com"], "email_on_failure": False, "retries": 3, "retry_delay": timedelta(seconds=10), "execution_timeout": timedelta(minutes=60), } config = """ { "source": { "type": "custom-database", "serviceName": "sample_data", "serviceConnection": { "config": { "type": "CustomDatabase", "sourcePythonClass": "metadata.ingestion.source.database.sample_usage.SampleUsageSource", "connectionOptions": { "sampleDataFolder": "/home/airflow/ingestion/examples/sample_data" } } }, "sourceConfig": { "config":{ "type": "DatabaseUsage" } } }, "processor": { "type": "query-parser", "config": {} }, "stage": { "type": "table-usage", "config": { "filename": "/tmp/sample_usage" } }, "bulkSink": { "type": "metadata-usage", "config": { "filename": "/tmp/sample_usage" } }, "workflowConfig": { "openMetadataServerConfig": { "hostPort": "http://openmetadata-server:8585/api", "authProvider": "openmetadata", "securityConfig":{ "jwtToken": "eyJraWQiOiJHYjM4OWEtOWY3Ni1nZGpzLWE5MmotMDI0MmJrOTQzNTYiLCJ0eXAiOiJKV1QiLCJhbGciOiJSUzI1NiJ9.eyJzdWIiOiJhZG1pbiIsImlzQm90IjpmYWxzZSwiaXNzIjoib3Blbi1tZXRhZGF0YS5vcmciLCJpYXQiOjE2NjM5Mzg0NjIsImVtYWlsIjoiYWRtaW5Ab3Blbm1ldGFkYXRhLm9yZyJ9.tS8um_5DKu7HgzGBzS1VTA5uUjKWOCU0B_j08WXBiEC0mr0zNREkqVfwFDD-d24HlNEbrqioLsBuFRiwIWKc1m_ZlVQbG7P36RUxhuv2vbSp80FKyNM-Tj93FDzq91jsyNmsQhyNv_fNr3TXfzzSPjHt8Go0FMMP66weoKMgW2PbXlhVKwEuXUHyakLLzewm9UMeQaEiRzhiTMU3UkLXcKbYEJJvfNFcLwSl9W8JCO_l0Yj3ud-qt_nQYEZwqW6u5nfdQllN133iikV4fM5QZsMCnm8Rq1mvLR0y9bmJiD7fwM1tmJ791TUWqmKaTnP49U493VanKpUAfzIiOiIbhg" } } } } """ def metadata_ingestion_workflow(): workflow_config = json.loads(config) workflow = UsageWorkflow.create(workflow_config) workflow.execute() workflow.raise_from_status() workflow.print_status() workflow.stop() with DAG( "sample_usage", default_args=default_args, description="An example DAG which runs a OpenMetadata ingestion workflow", schedule_interval=timedelta(days=1), start_date=days_ago(1), is_paused_upon_creation=True, catchup=False, ) as dag: ingest_task = PythonOperator( task_id="ingest_using_recipe", python_callable=metadata_ingestion_workflow, )