How to fix this error in azure data factory? My dataflow worked fine, now I receive this error.

Question

Error:

Spark job failed: { "text/plain": "{"runId":"83899cfc-c2ab-4e94-a1fa-89e1d3bd2a4c","sessionId":"6e0c1f32-a0c9-47d5-9baf-50f0e4228498","status":"Failed","payload":{"statusCode":400,"shortMessage":"DF-SYS-0 Failure(java.lang.Exception: DfmTokenFetcher parse DFM Token failed, response payload is .) (of class scala.util.Failure)","detailedMessage":"Failure 2024-05-03 14:01:02.302 failed DebugManager.processJob, run=83899cfc-c2ab-4e94-a1fa-89e1d3bd2a4c, errorMessage=DF-SYS-0 Failure(java.lang.Exception: DfmTokenFetcher parse DFM Token failed, response payload is .) (of class scala.util.Failure)"}}\n" } - RunId: 83899cfc-c2ab-4e94-a1fa-89e1d3bd2a4c

Answer 1

@Fatemeh Ghorbani Sini

Thanks for using MS Q&A platform and posting your query.

The error message indicates an issue with the authentication token used by your Spark job to access the data flow. Here's a breakdown of the error and some troubleshooting steps:

Error Message:

• DF-SYS-0 Failure: This signifies a system-level failure within the Data Flow Management system.
• java.lang.Exception: DfmTokenFetcher parse DFM Token failed, response payload is .: This is the core of the problem. The system couldn't parse the Data Flow Management (DFM) token, likely due to an empty or invalid response.

Troubleshooting Steps:

1. Refresh Authentication Token: The most common cause is an expired token. Try refreshing the authentication token used by your Spark job. Refer to your specific platform's documentation for instructions on refreshing tokens.
2. Verify Token Validity: Ensure the token you're using is valid and has the necessary permissions to access the data flow. Check for any typos or configuration mistakes in the token generation process.
3. Connectivity Test: Use a separate tool like Postman to test connectivity to the data flow resources (source and destination) with the same credentials. This helps isolate if the issue is with the token itself or the communication between your Spark job and the data flow service.
4. Check Logs: Look for more detailed error messages in the logs associated with your Spark job execution. These logs might provide additional clues about the cause of the token parsing failure

please refer https://learn.microsoft.com/en-us/azure/data-factory/data-flow-troubleshoot-guide

Hope this helps. Do let us know if you any further queries.

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