Use these guidelines and features to begin the process of diagnosing jobs that have failed.
The following types of jobs can be executed in
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- Convert jobs: Some datasources, such as binary file or JSON formats, must be converted to a format that can be easily read by the
. During data ingestion, the datasource is converted to a natively supported file format and stored on backend storage.
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- Transform job: This type of job executes the steps in your recipe against the dataset to generate results in the specified format. When you configure your job, any set of selected output formats causes a transform job to execute according to the job settings.
- Profile job: This type of job builds a visual profile of the generated results. When you configure your job, select Profile Results to generate a profile job.
- Publish job: This job publishes results generated by the platform to a different location or datastore.
- Ingest job: This job manages the import of data from a JDBC source into the default datastore for purposes of running a transform or sampling job.
For more information, see Run Job Page.
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:
- Jobs tab in Flow View. See Flow View Page.Listing
- Individual job listings in the Jobs Job History page. See Jobs Page.
The following is an example from the Jobs Job History page:
Publish job failed
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:
You can try to re-execute the job using different options.
- 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
, try executing it on another running environment.
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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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If you are unable to diagnose your job failure, please contact
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If you believe that your job has failed due to an issue with
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|D s support|
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