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Using the more specific exception will prevent us from accidentally ignoring errors that should be handled.
48 lines
1.3 KiB
Python
48 lines
1.3 KiB
Python
"""Lineage Backend
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An example DAG demonstrating the usage of DataHub's Airflow lineage backend.
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"""
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from datetime import timedelta
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from airflow import DAG
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from airflow.utils.dates import days_ago
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try:
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from airflow.operators.bash import BashOperator
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except ModuleNotFoundError:
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from airflow.operators.bash_operator import BashOperator
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from datahub.integrations.airflow.entities import Dataset
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default_args = {
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"owner": "airflow",
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"depends_on_past": False,
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"email": ["jdoe@example.com"],
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"email_on_failure": False,
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"execution_timeout": timedelta(minutes=5),
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}
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with DAG(
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"datahub_lineage_backend_demo",
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default_args=default_args,
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description="An example DAG demonstrating the usage of DataHub's Airflow lineage backend.",
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schedule_interval=timedelta(days=1),
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start_date=days_ago(2),
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tags=["example_tag"],
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catchup=False,
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) as dag:
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task1 = BashOperator(
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task_id="run_data_task",
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dag=dag,
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bash_command="echo 'This is where you might run your data tooling.'",
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inlets={
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"datasets": [
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Dataset("snowflake", "mydb.schema.tableA"),
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Dataset("snowflake", "mydb.schema.tableB"),
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],
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},
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outlets={"datasets": [Dataset("snowflake", "mydb.schema.tableC")]},
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)
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