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Comment: Published by Scroll Versions from space DEV and version r091

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For more information, see Run Job Page.

Info

NOTE: For each collected sample, a sample job ID is generated. In the Samples panel, you can view the sample job IDs for your samples. These job IDs enable you to identify the sample jobs in the Sample Jobs page.

Identify Job Failures

When a job fails to execute, a failure message appears in following locations:

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In the above example, the Transform and Profile jobs completed, but the Publish job failed. In this case, the results exist and, if the source of the problem is diagnosed, they can be published separately.

Invalid file paths

When your job uses files as inputs or outputs, you may receive invalid file path errors. Depending on the backend datastore, these can be one of the following:

  • Path to the file is invalid for the current user. Path may be been created by another user that had access to the location. 
  • Path contains invalid characters in it. For more information, see Supported File Formats.
  • Resource was deleted.

Jobs that Hang

In some cases, a job may stay in a pending state indefinitely. Typically, these errors are related to a failure of the job tracking service. You can try to the following:

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You can try to re-execute the job using different options.

Tips:

  • Disable flow optimizations. If your job is using data from a relational source that supports pushdowns, you can try to disable flow optimizations and then re-run the job. For more information, see Flow Optimization Settings Dialog
  • Look to cut data volume. Some job failures occur due to high data volumes. For jobs that execute across a large dataset, you can re-examine your data to remove unneeded rows and columns of data. Use the Deduplicate transformation to remove duplicate rows. See Remove Data.
  • Gather a new sample. In some cases, jobs can fail when run at scale because the sample displayed in the Transformer page did not include problematic data. If you have modified the number of rows or columns in your dataset, you can generate a new sample, which might illuminate the problematic data. However, gathering a new sample may fail as well, which can indicate a broader problem. See Samples Panel.
  • Change the running environment. If the job failed on

    D s photon
    , try executing it on another running environment. 

    Tip

    Tip: The 

    D s photon
    running environment is not suitable for jobs on large datasets. You should accept the running environment recommended in the Run Job page.

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