Completed
Select Jobs > Completed.
Finished jobs appear in the Completed table. By default, jobs older than four weeks are removed from the table. To change the length of time completed jobs appear, adjust the Job History scheduled cleanup task.
The following columns are available to display in the Completed table:
Note: Some fields do not display by default. To control which columns display, click the Customize Columns icon.
Tip: You can filter the list of jobs based on the values of some columns. To set filters, expand the Filters drop-down.
- Id: The unique ID of the completed job.
- Workspace: The workspace request that was run.
- Repository: The repository containing the workspace that was run.
- Username: The FME Server user account name that ran the job. To filter the jobs that appear in this table by user, use the Show Jobs For drop-down.
- Status: The status of the finished job. To learn more click on the job to examine its properties and log file.
- Logs: Indicates if any errors or warnings were logged when the job ran. Click the icon to view the job log, filtered by errors and/or warnings.
- Started: The date and time when the job was started.
- Finished: The date and time when the job was finished.
- Source Name: Identifier of the FME Server mechanism from which the job originated, such as an Automations ID or Schedule Category name.
- Source Type: FME Server mechanism from which the job originated, such as Automations or Schedules.
- Engine: The name of the FME engine that processed the job and the FME Server host on which the engine was running.
- Queue: The queue in which the job ran.
- % CPU: The percentage of total processing time that is recorded as CPU time, calculated as CPU Time / Elapsed Time.
- CPU Time: Total CPU time to run the job, as recorded by the FME Server REST API.
- Elapsed Time: Total processing time of the job, calculated as Finished - Started.
- Peak Memory Usage: The peak memory used by the FME Engine while processing a job, minus the memory in use by the FME Engine at the beginning of the job.
Note: The REST API record of CPU Time differs from that of FME Server and FME Desktop logs because it includes additional start and end scripting, and is a more accurate report of total processing time.
Note: Due to differences between FME Desktop and FME Server in how FME Engines restart between translations, FME Desktop does not subtract the memory in use by the FME Engine at the beginning of the job when reporting Peak Memory Usage, but simply records peak memory at any time during the translation. With this additional calculation, FME Server provides a more accurate report of Peak Memory Usage, and in particular, a more accurate value when reporting Average Peak Memory Usage for workspace metrics.