Understanding Airflow Task Generation in DataHub

ingestion
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Original Slack Thread

how does the airflow plugin generates airflow task in datahub? <@U06TM7M40RK>

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The DataHub Airflow plugin generates Airflow task metadata in DataHub by capturing and emitting metadata events during the execution of Airflow DAGs. Here’s a summary of how this process works:

  1. Installation and Configuration: First, you need to install the DataHub Airflow plugin. For Airflow 2.3+ and Python 3.8+, you should use the v2 plugin by running:

    pip install 'acryl-datahub-airflow-plugin[plugin-v2]'

    Then, set up a DataHub connection in Airflow, either via the command line or the Airflow UI, and configure the plugin in the airflow.cfg file (https://github.com/datahub-project/datahub/blob/master/docs/lineage/airflow.md|source).

  2. Automatic Lineage Extraction: The plugin supports automatic column-level lineage extraction from various operators, such as SQL operators and S3FileTransformOperator. This is enabled by setting enable_extractors to true in the configuration (https://github.com/datahub-project/datahub/blob/master/docs/lineage/airflow.md|source).

  3. Task Metadata Capture: During the execution of a DAG, the plugin captures metadata about the tasks, including properties, ownership, tags, and task run information (successes and failures). This metadata is then emitted to DataHub (https://github.com/datahub-project/datahub/blob/master/docs/lineage/airflow.md|source).

  4. Manual Lineage Annotation: For operators that do not support automatic lineage extraction, you can manually annotate lineage by setting inlets and outlets on your Airflow operators (https://github.com/datahub-project/datahub/blob/master/docs/lineage/airflow.md|source).

  5. Real-Time Emission: The plugin can emit metadata events in real-time as part of the DAG execution, which includes task metadata and lineage information (https://datahubspace.slack.com/archives/C029A3M079U/p1726167407.741999|source).

Would you like more detailed steps or examples on any of these points?

Sources:

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when using Automatic Lineage Extraction for sqlexecutequeryoperator in airflow, i know the plugin uses airflow listener and i can see that the pipeline of the airflow dag in datahub is populated with the task, i want to see the exact source code line that emits the task to the datahub server

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<@U06TM7M40RK>

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To find the exact source code line that emits the task metadata to the DataHub server when using automatic lineage extraction for SqlExecuteQueryOperator in Airflow, you can refer to the DataHub Airflow plugin’s source code. The plugin uses a listener to capture task events and emit metadata to DataHub.

The relevant code is located in the DataHub Airflow plugin’s repository. Specifically, the datahub_listener.py file is responsible for listening to task events and emitting metadata. Here is a general outline of how you can locate the specific line of code:

  1. Locate the Listener: The datahub_listener.py file in the DataHub Airflow plugin contains the logic for listening to task events. This file is responsible for capturing task metadata and emitting it to DataHub.

  2. Emission Logic: Within the listener, look for the function that handles task completion events. This function typically gathers metadata about the task and constructs a metadata change event (MCE) to send to DataHub.

  3. Emission Code: The actual emission of the metadata to the DataHub server is done using an emitter, such as DataHubRestEmitter. The code will include a call to the emitter’s method to send the constructed MCE to the DataHub server.

Unfortunately, the exact line of code is not explicitly mentioned in the provided data sources. However, you can explore the <https://github.com/datahub-project/datahub/blob/master/metadata-ingestion-modules/airflow-plugin/src/datahub_airflow_plugin/datahub_listener.py|DataHub Airflow plugin’s GitHub repository> to find the specific implementation details.

If you need further assistance in navigating the code or understanding the implementation, feel free to ask!

Sources:

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Hi :slight_smile: ! Did this interaction resolve your issue or do you still require assistance ?

Please tag @ RunLLM if you still need further assistance !

Or tag @Datahub Community Support if you require a person to take a look :slight_smile:

Hope this helps ! ><