Contents:
Contents:
Job Types
The following types of jobs can be executed in Dataprep by Trifacta:
- 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.
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 in the Jobs page. See Jobs Page.
The following is an example from the Jobs page:
Figure: 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.
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:
- Resubmit the job.
Try Other Job Options
You can try to re-execute the job using different options.
Tips:
- 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.
Contact Support
If you are unable to diagnose your job failure, please contact Google Support.
NOTE: When you contact support about a job failure, please be sure to download and include the entire zip file, your recipe, and (if possible) your dataset.
This page has no comments.