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Unable to diagnose import issues #32411

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3 tasks done
withnale opened this issue Feb 27, 2025 · 1 comment · May be fixed by #32410
Open
3 tasks done

Unable to diagnose import issues #32411

withnale opened this issue Feb 27, 2025 · 1 comment · May be fixed by #32410
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api Related to the REST API

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@withnale
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Bug description

At present when trying to import resources if the import fails there is no information available about the reason the import failed.

Both the UI and the logs provide a generic "Import failure" message.

A quick way of reproducing this (one of many)would be to:

  1. open an exported bundle
  2. modify the dataset_uuid parameter to one that doesn't exist
  3. recreate the bundle
  4. Try to import the bundle either via the UI or via the REST api

Screenshots/recordings

Image

Superset version

master / latest-dev

Python version

3.11

Node version

16

Browser

Chrome

Additional context

No response

Checklist

  • I have searched Superset docs and Slack and didn't find a solution to my problem.
  • I have searched the GitHub issue tracker and didn't find a similar bug report.
  • I have checked Superset's logs for errors and if I found a relevant Python stacktrace, I included it here as text in the "additional context" section.
@withnale withnale linked a pull request Feb 27, 2025 that will close this issue
9 tasks
@dosubot dosubot bot added the api Related to the REST API label Feb 27, 2025
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dosubot bot commented Feb 27, 2025

Superset has mechanisms to provide detailed error messages during import failures. The ErrorMessageWithStackTrace component in the frontend is designed to display error messages, including stack traces if available. It checks for custom error message components for specific error types and uses them if available. Otherwise, it falls back to displaying error details, including stack traces, using the ErrorAlert component [1].

Additionally, Superset's logging mechanism captures error details during import failures by logging exceptions and formatting them into JSON responses. This includes the error message, type, and level, ensuring that error details are captured and stored in the logs [2].

For your specific issue with the dataset_uuid parameter, it seems that the error handling might not be providing detailed feedback in this case. You might want to check if the error handling logic is correctly capturing and displaying errors related to invalid dataset_uuid values. If the error messages are not detailed enough, consider reviewing the error handling implementation to ensure it captures and logs all relevant details.

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