Troubleshooting Job Failures After Upgrading Python from 3.8 to 3.9
If you have recently upgraded your environment from Python 3.8 to Python 3.9 and are experiencing job failures, the issue may be related to outdated package references or connection configurations still pointing to Python 3.8 artifacts.
Resolution Steps
1. Deploy Python 3.9 Packages
Copy all Python 3.9-specific packages and dependencies to the appropriate cluster(s).
2. Update Sparkflows Connection Configuration
Modify the Sparkflows connection settings to reference the newly deployed Python 3.9 packages.
3. Validate the Connection
Test the updated connection to ensure all package references and configurations are valid.
4. Re-run Failed Jobs
After confirming the connection is functioning correctly, re-run the affected jobs to verify successful execution.
Important Validation Checks
Job failures may occur if any connection settings continue to reference Python 3.8 packages or configurations. Please review and update all relevant settings accordingly.
Navigate to the Livy tab within the connection configuration and verify the following:
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PySpark Files
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Archive Files
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Conf
Ensure that all references have been updated to the appropriate Python 3.9 packages and paths.
Additional Recommendation
Perform a thorough review of the entire connection configuration to identify and replace any remaining references to Python 3.8. Residual references can lead to dependency conflicts and job execution failures after the upgrade.