This release is a pre-release and may not be stable for production use.
DataHub Airflow Plugin
Automatic lineage and run metadata from Apache Airflow into DataHub — captures DAG structure, task inputs/outputs, and run history with no manual instrumentation.
What you can do
- Capture pipeline lineage — automatically extract dataset-level and column-level lineage from SQL operators
- Track run history — record task execution status, duration, and failures in DataHub
- Enhance OpenLineage — patches Airflow's OpenLineage extractors with DataHub's advanced SQL parser for richer lineage
- Support multiple emitters — send metadata via REST, Kafka, or file
Version compatibility
| Airflow Version | Support |
|---|---|
| 3.0+ | ✅ Fully supported |
| 2.x | ❌ Use acryl-datahub-airflow-plugin <= 1.6.0 |
Installation
pip install acryl-datahub-airflow-plugin
# With Kafka emitter
pip install 'acryl-datahub-airflow-plugin[datahub-kafka]'
Configuration
Add to airflow.cfg:
[datahub]
enabled = True
conn_id = datahub_rest_default # Airflow connection pointing to your DataHub GMS
Set up the Airflow connection:
airflow connections add datahub_rest_default \
--conn-type HTTP \
--conn-host http://localhost:8080
The plugin activates automatically — no changes to your DAG code required.
Key configuration options
| Option | Default | Description |
|---|---|---|
enable_extractors |
True |
Enhance OpenLineage extractors |
patch_sql_parser |
True |
Use DataHub's SQL parser for column-level lineage |
enable_multi_statement_sql_parsing |
False |
Resolve temp tables across multi-statement tasks |
Links
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