--- title: Configuring DAG Lineage slug: /connectors/pipeline/airflow/configuring-lineage --- # Configuring DAG Lineage Regardless of the Airflow ingestion process you follow ([Workflow](/connectors/pipeline/airflow), [Lineage Backend](/connectors/pipeline/airflow/lineage-backend) or [Lineage Operator](/connectors/pipeline/airflow/lineage-operator)), OpenMetadata will try to extract the lineage information based on the tasks `inlets` and `outlets`. Let's take a look at the following example: ```python from datetime import timedelta from airflow import DAG from airflow.operators.dummy import DummyOperator from airflow.utils.dates import days_ago default_args = { 'owner': 'airflow', 'depends_on_past': False, 'email': ['airflow@example.com'], 'email_on_failure': False, 'email_on_retry': False, 'retries': 1, 'retry_delay': timedelta(seconds=1), } with DAG( "test-multiple-inlet-keys", default_args=default_args, description="An example DAG which runs a a task group lineage test", start_date=days_ago(1), is_paused_upon_creation=False, catchup=False, ) as dag: t0 = DummyOperator( task_id='task0', inlets={ "tables": ["Table A"], "more_tables": ["Table X"] } ) t1 = DummyOperator( task_id='task10', outlets={ "tables": ["Table B"], "more_tables": ["Table Y"] } ) t0 >> t1 ``` Note how we have two tasks: - `t0`: Informing the `inlets`, with keys `tables` and `more_tables`. - `t1`: Informing the `outlets` with keys `tables` and `more_tables`. {% note %} Make sure to add the table Fully Qualified Name (FQN), which is the unique name of the table in OpenMetadata. This name is composed as `serviceName.databaseName.schemaName.tableName`. {% /note %} What it's important to consider here is that when we are ingesting Airflow lineage, we are actually building a graph: ``` Table A (node) -> DAG (edge) -> Table B (node) ``` Where tables are nodes and DAGs (Pipelines) are considered edges. This means that the correct way of setting this parameters is by making sure that we are informing both `inlets` and `outlets`, so that we have the nodes to build the relationship. ## Keys We can inform the lineage dependencies among different groups of tables. In the example above, we are not building the lineage from all inlets to all outlets, but rather grouping the tables by the dictionary key (`tables` and `more_tables`). This means that after this lineage is processed, the relationship will be: ``` Table A (node) -> DAG (edge) -> Table B (node) ``` and ``` Table X (node) -> DAG (edge) -> Table Y (node) ``` It does not matter in which task of the DAG these inlet/outlet information is specified. During the ingestion process we group all these details at the DAG level.