Airflow is a widely-used workflow automation and scheduling platform that can be used to author and manage data pipelines. Airflow uses workflows made of directed acyclic graphs (DAGs) of tasks. To learn more about Airflow, check out the Airflow documentation.
How does Airflow work with OpenLineage?
Understanding complex inter-DAG dependencies and providing up-to-date runtime visibility into DAG execution can be challenging. OpenLineage integrates with Airflow to collect DAG lineage metadata so that inter-DAG dependencies are easily maintained and viewable via a lineage graph, while also keeping a catalog of historical runs of DAGs.
The DAG metadata collected can answer questions like:
- Why has a DAG failed?
- Why has the DAG runtime increased after a code change?
- What are the upstream dependencies of a DAG?
How can I use this integration?
To instrument your Airflow instance with OpenLineage, follow these instructions.
How to add lineage coverage for more operators?
OpenLineage provides a set of
extractors that extract lineage from operators.
If you want to add lineage coverage for your own custom operators, follow these instructions to add lineage to operators.
If you want to add coverage for operators you can not modify, follow instructions to add custom extractors.
If you want to expose lineage as a one off in your workflow, you can also manually annotate the tasks in your DAG.
Where can I learn more?
- Take a look at Marquez's Airflow example to learn how to enable OpenLineage metadata collection for Airflow DAGs and troubleshoot failing DAGs using Marquez.
- Watch Data Lineage with OpenLineage and Airflow
You can reach out to us on slack and leave us feedback!