Troubleshooting PipelineInitError for Great Expectations Data Source Integration

ingestion
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Original Slack Thread

datahub.ingestion.run.pipeline.PipelineInitError: Failed to find a registered source for type great_expectations: ‘Did not find a registered class for great_expectations’, but great_expectations is installed alongside its datahub connector as well

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<@U06TM7M40RK> Can you help with the questions in this thread?

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To address the error PipelineInitError: Failed to find a registered source for type great_expectations: 'Did not find a registered class for great_expectations', it seems that DataHub is unable to recognize the great_expectations source type. This could be due to a few reasons such as missing dependencies, incorrect configuration, or version incompatibilities.

Here are some steps to troubleshoot and resolve the issue:

  1. Verify Installation:
    Ensure that great_expectations and its DataHub connector are correctly installed. You can do this by running:

    pip list | grep great_expectations
pip list | grep datahub

  2. Check Configuration:
    Ensure that your ingestion configuration file (e.g., recipe.dhub.yaml) is correctly set up. Here is an example configuration for integrating Great Expectations with DataHub:

    pipeline_name: 'Great Expectations Ingestion'
source:
    type: great_expectations
    config:
        expectation_suite_name: 'my_expectation_suite'
        data_context_root_dir: '/path/to/great_expectations'
        server_url: 'http://localhost:8080'
        token: 'your_datahub_token'
sink:
    type: datahub-rest
    config:
        server: 'http://localhost:8080'
        token: 'your_datahub_token'

  3. Update Dependencies:
    Ensure that you are using compatible versions of DataHub and Great Expectations. Sometimes, updating to the latest versions can resolve compatibility issues. You can update the packages using:

    pip install --upgrade acryl-datahub great_expectations

  4. Check for Known Issues:
    There are known issues with certain versions of Great Expectations and DataHub. For example, DataHub currently supports Great Expectations up to version 0.15.50. If you are using a newer version, you might encounter issues. Refer to <Issues · datahub-project/datahub · GitHub GitHub issue> for more details.

  5. Verify DataHub Configuration:
    Ensure that the DataHub server URL and token are correctly specified in your configuration file. Incorrect server URLs or tokens can cause ingestion failures.

  6. Check Logs for Detailed Errors:
    Review the logs from the DataHub ingestion executor and the DataHub GMS to identify any specific error messages. This can provide insights into why the jobs are marked as failed.

Would you like more detailed steps on any of these potential solutions?

Sources: