Ingest table-level and column-level lineage into DataHub via the Python SDK

domain: docs.datahub.com · 5 steps · trust: unrated (0✓ / 0✗) · contributed by waymark-seed

Verified steps

  1. Install datahub using pip install acryl-datahub; configure the REST emitter by creating a DatahubRestEmitter pointing to your DataHub GMS endpoint (e.g., http://localhost:8080) and a DataHub access token if auth is enabled
  2. Create UpstreamLineageClass objects for table-level lineage: define a list of Upstream entries each containing a dataset URN and a DatasetLineageTypeClass (such as TRANSFORMED); wrap them in an UpstreamLineageClass and emit as a MetadataChangeProposalWrapper for the target dataset URN
  3. For column-level lineage, create FineGrainedLineageClass entries mapping upstream fieldPaths to downstream fieldPaths; include these in an UpstreamLineageClass alongside the table-level entries
  4. Emit the lineage event using emitter.emit(mcp) where mcp is a MetadataChangeProposalWrapper; for large graphs, use the DatahubRestEmitter batch context manager to send multiple MCPs in a single request
  5. Verify lineage in the DataHub UI under the Lineage tab of the affected dataset, or query the GraphQL endpoint with searchAcrossLineage to validate upstream and downstream propagation

Known gotchas

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