acryl-datahub-airflow-plugin 1.6.0.5rc1

Datahub Airflow plugin to capture executions and send to Datahub

Datahub Airflow Plugin

See the DataHub Airflow docs for details.

Version Compatibility

The plugin supports Apache Airflow 3.0+. Airflow 2.x is not supported — pin acryl-datahub-airflow-plugin <= 1.6.0 (the last release with Airflow 2 support) if you need to integrate with Airflow 2.

Airflow Version	Status	Notes
2.x	❌ Unsupported	Use version <= 1.6.0
3.0+	✅ Fully Supported

Installation

pip install acryl-datahub-airflow-plugin

This installs:

• acryl-datahub[sql-parser,datahub-rest] — DataHub SDK with SQL parsing and REST emitter
• pydantic>=2.4.0
• apache-airflow>=3.0.0,<4.0.0
• apache-airflow-providers-openlineage>=2.1.0

Optional extras

pip install 'acryl-datahub-airflow-plugin[datahub-kafka]'   # Kafka emitter
pip install 'acryl-datahub-airflow-plugin[datahub-file]'    # File emitter (testing)

Configuration

The plugin can be configured via airflow.cfg under the [datahub] section. Below are the key configuration options:

Extractor Patching (OpenLineage Enhancements)

When enable_extractors=True (default), the DataHub plugin enhances OpenLineage extractors to provide better lineage. You can fine-tune these enhancements:

[datahub]
# Enable/disable all OpenLineage extractors
enable_extractors = True  # Default: True

# Enable multi-statement SQL parsing (resolves temp tables, merges lineage)
enable_multi_statement_sql_parsing = False  # Default: False

# Patch SQLParser to use DataHub's advanced SQL parser (enables column-level lineage)
patch_sql_parser = True  # Default: True

# Use DataHub's enhancements for specific operators
extract_athena_operator = True              # Default: True
extract_bigquery_insert_job_operator = True # Default: True
extract_teradata_operator = True            # Default: True

Multi-Statement SQL Parsing:

When enable_multi_statement_sql_parsing=True, if a task executes multiple SQL statements (e.g., CREATE TEMP TABLE ...; INSERT ... FROM temp_table;), DataHub parses all statements together and resolves temporary table dependencies within that task. By default (False), only the first statement is parsed.

How patches work:

The DataHub plugin monkey-patches OpenLineage extractors at runtime:

• patch_sql_parser=True patches SQLParser.generate_openlineage_metadata_from_sql() to use DataHub's parser, enabling more accurate lineage and column-level lineage.
• extract_athena_operator / extract_bigquery_insert_job_operator / extract_teradata_operator patch the corresponding operator's get_openlineage_facets_on_complete() method with DataHub's enhanced implementation.

Example: disable DataHub's SQL parser

[datahub]
enable_extractors = True
patch_sql_parser = False

Other Configuration Options

For a complete list of configuration options, see the DataHub Airflow documentation.

Developing

See the developing docs.