Troubleshooting DataHub UI Ingestion Error: Finding a Registered Source

ingestion
1

Original Slack Thread

<@U06TM7M40RK> I am having trouble in performing ingestion through the DataHub UI, whenever I try to do ingestion for any data source it is giving the following error:

datahub.ingestion.run.pipeline.PipelineInitError: Failed to find a registered source for type```
I have installed all the packages and necessary modules, still the same error persists. How can I resolve this?
2

The error message you’re encountering indicates that the DataHub ingestion pipeline is unable to find a registered source for the specified type. This typically happens when the necessary plugin for the source type is not installed or configured correctly. Here are some steps to troubleshoot and resolve this issue:

  1. Verify Plugin Installation: Ensure that the required DataHub plugin for the source type is installed. You can do this by running the following command, replacing <source_type> with the actual source type you are trying to ingest:

    pip install 'acryl-datahub[<source_type>]'

  2. Check Plugin Activation: After installation, verify that the plugin is active by running:

    datahub check plugins --verbose

    This command will list all the active plugins, and you should see the plugin for your source type listed.

  3. Review Ingestion Recipe: Ensure that your ingestion recipe is correctly configured. The source section of your YAML configuration should specify the correct type and any necessary configuration details. Here is an example:

    source:
  type: <source_type>
  config:
    # Add your source configuration here
sink:
  type: datahub-rest
  config:
    server: "http://localhost:8080"
    token: "<your-datahub-token>"

  4. Check for Errors in Logs: Review the logs for any additional error messages that might provide more context. You can view the output logs in the UI by clicking DETAILS on the corresponding ingestion run, as mentioned in the <https://datahubproject.io/docs/0.14.0/ui-ingestion#debugging-a-failed-ingestion-run|DataHub UI Ingestion documentation>.

  5. Ensure Correct Version: Make sure you are using a compatible version of DataHub CLI and the necessary plugins. Sometimes, version mismatches can cause issues.

  6. Network and Authentication: Verify that there are no network connectivity issues and that authentication details (such as tokens) are correctly configured in your recipe.

If you have followed these steps and are still encountering issues, please let me know, and I can provide more detailed troubleshooting steps.

Would you like more detailed instructions on any of these steps?

Sources:

3

<@U06TM7M40RK> I have tried all the above steps but still the error persists. Do you have any other solution?

4

If you’ve already tried the steps mentioned and the error persists, here are some additional troubleshooting steps and considerations:

  1. Check for Missing Dependencies: Ensure that all dependencies required by the source type are installed. Sometimes, a missing dependency can cause the source type to not be recognized. You can try reinstalling the DataHub package with all extras:

    pip install 'acryl-datahub[all]'

  2. Use a Clean Environment: Create a new virtual environment to ensure there are no conflicts with existing packages. This can help isolate the issue:

    python -m venv datahub_env
source datahub_env/bin/activate
pip install 'acryl-datahub[all]'

  3. Verify Source Type Support: Double-check that the source type you are trying to use is supported by your version of DataHub. You can refer to the <https://datahubproject.io/docs/0.14.0/metadata-ingestion/developing|DataHub Metadata Ingestion documentation> for a list of supported sources.

  4. Check for Known Issues: Look for any known issues or bugs related to your DataHub version or the specific source type. You can check the <https://github.com/datahub-project/datahub/issues|DataHub GitHub issues> for any related reports.

  5. Review Configuration for Typos: Ensure there are no typos or incorrect configurations in your YAML recipe. Even a small mistake can cause the source type to not be recognized.

  6. Enable Debug Logging: Run the ingestion command with debug logging enabled to get more detailed output, which might help identify the issue:

    export DATAHUB_DEBUG=true
datahub ingest -c your_ingestion_recipe.yml --debug

  7. Consult Community Support: If the issue persists, consider reaching out to the DataHub community for support. You can post your issue on the <https://datahubproject.io/slack|DataHub Slack channel> or open a GitHub issue for more targeted assistance.

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

Sources:

5

<@U0121TRV0FL> Would really appreciate your assistance on this topic please.

6

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 ! ><