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Message type: E = Error
Message class: RSANA_UMM_API - UMM API Messages
Message number: 585
Message text: Training is already scheduled for this model. Try again later.
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RSANA_UMM_API585
- Training is already scheduled for this model. Try again later. ?The SAP error message RSANA_UMM_API585 indicates that a training session for a specific model is already scheduled, and therefore, the system cannot process a new training request at that moment. This is typically encountered in the context of SAP Analytics Cloud or SAP BW/4HANA when working with predictive models or machine learning scenarios.
Cause:
- Concurrent Training Sessions: The model is already undergoing a training process, which prevents additional training requests from being processed simultaneously.
- System Lock: The model may be locked due to ongoing operations or maintenance activities.
- Resource Constraints: The system may be experiencing resource limitations, causing it to reject new training requests.
Solution:
- Wait and Retry: The simplest solution is to wait for the current training session to complete. You can check the status of the training job in the monitoring tools provided by SAP.
- Check Job Status: Use transaction codes like
SM37
(for job monitoring) to see if there are any active jobs related to the model. If a job is running, you may need to wait until it finishes.- Cancel Running Jobs: If you determine that the training job is stuck or taking too long, you may consider canceling it (if you have the necessary permissions) and then resubmitting your training request.
- Review Logs: Check the logs for any additional error messages or warnings that might provide more context on why the training is taking longer than expected.
- Consult Documentation: Refer to the SAP documentation for your specific version and module to see if there are any known issues or additional troubleshooting steps.
- Contact Support: If the issue persists and you cannot determine the cause, consider reaching out to SAP support for assistance.
Related Information:
By following these steps, you should be able to resolve the error and successfully schedule training for your model.
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