List Jobs

All the saved Jobs by a logged-in user get listed by using this option.

The List Jobs option opens the available Jobs List for the logged-in user. All the saved Jobs by a user get listed on this page. By clicking on the Job name the Details tab on the right side of the page gets displayed with the basic details of the selected job.

Job List

  • Navigate to the Data Pipeline Homepage.

  • Click on the List Jobs option.

  • The List Jobs page opens displaying the created jobs.

Job Details & History Tabs

  • Select a Job from the displayed list, and click on it.

  • This will open a panel below the selected Job. It will contain two tabs:

    • Job Details - The following details get displayed for the selected Job:

      • Tasks

      • Created By

      • Updated Date

      • Cron Expression

      • Trigger Interval

      • Description

  • Click on the History tab to see all the relevant information about the selected Job's past runs, including whether it was successful or not.

    • The Clear option is also provided under the History tab to clear the Job history.

    • Click the Refresh icon to refresh the displayed Job history.

  • The user can also view and download the pod logs for Python and PySpark jobs from the history tab in the List Jobs page. Please see the below given image for the reference.

  • Clear: It will clear all the job run history from the History tab. Please refer the below given image for reference.

Searching Job

The user can search for a specific Job by using the Search bar on the Job List. By typing a common name all the existing jobs having that word will list. E.g., By typing sand all the existing Jobs with the word sand in it get listed as displayed in the following image:

The user can also customize the Job List by choosing available filters such as Job Status, Job Type, Job Running Status:

Please Note:

  • The user can open the Job Editor for the selected job from the list by clicking the View icon.

  • The view/download pod logs feature is only available for Python and PySpark jobs.

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