The following types of jobs can be executed:
Publish job: This job publishes results generated by the platform to a different location or datastore.
Ingest job: This job manages the import of large volumes of data from a JDBC source into the default datastore for purposes of running a transformation job.
For more information, see Run Job Page.
When a job fails to execute, a failure message appears in following locations:
The following is an example from the Jobs 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.
From the job's context menu, select Download Logs. You can download the jobs logs to look for reasons for the failure. See Review Logs below.
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:
Have an administrator restart the platform. See Start and Stop the Platform.
Submit the job on the restarted platform.
You can try to re-execute the job using different options.
deduplicatetransform 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 with the running environment. See Samples Panel.
Change the running environment. If the job failed on the , try to execute it on Hadoop.
Tip: The is not suitable for jobs on large datasets. You should accept the running environment recommended in the Run Job page.
In the listing for the job on the Jobs page, click Download Logs to send the job-related logs to your local desktop.
When you unzip the ZIP file, you should see a numbered folder with the internal identifier for your job on it. If you executed a transform job and a profile job, the ZIP contains two numbered folders with the lower number representing the transform job.
job.log. Review this log file for information on how the job was handled by the application.
Tip: Search this log file for
NOTE: You must be an administrator to access these logs.
On the , these logs are located in the following directory:
This directory contains the following logs:
batch-job-runner.log. This log contains vital information about the state of any launched jobs.
webapp.log. This log monitors interactions with the web application. Issues related to jobs running locally on the running environment can appear here.
In addition to these logs, you can also use the Hadoop job logs to troubleshoot job failures.
If you are unable to diagnose your job failure, please contact .
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.