To view detailed information about a mapping in advanced mode, such as a mapping instance, task instance, or data preview job, click the job name on the My Jobs page.
The following image shows the job details for a mapping in advanced mode:
Job properties
The job properties display general properties about the instance for each mapping instance, task instance, or data preview job in advanced mode.
The following table describes the job properties:
Property
Description
Task Name
Name of the task.
Instance ID
Instance number for the task. For example, if you are looking at the third run of the task, this field displays "3."
Task Type
Task type, such as Mapping (Advanced Mode).
Started By
Name of the user or schedule that started the job.
Start Time
Date and time that the job was started.
End Time
Date and time that the job completed or stopped.
Duration
Amount of time the job ran before it completed or was stopped.
Runtime Environment
Runtime environment in which the job ran.
Job Priority
Priority used to schedule the job.
Target Duration Status
Indicates whether the job met or exceeded its target duration.
Job results
The job results display the status of the job, a download link to the session log, and an error message for each mapping instance, task instance, or data preview job in advanced mode.
The following table describes the job results:
Property
Description
Status
Job status. A job can have one of the following statuses:
- Starting. The job is starting.
- Running. The job is still running.
- Stopped. The job was stopped by a user or the parent job has stopped running, so the subtask can't start.
- Success. The job completed successfully.
- Warning. The job completed with errors.
- Failed. The job did not complete because it encountered errors.
Session Log
Allows you to download the session log file. By default, Informatica Intelligent Cloud Services stores session logs for 10 runs before it overwrites the logs with the latest runs.If you want to retain session logs for more than 10 runs, you can configure the Maximum Number of Log Files property in the task wizard.
Session log files are written to the following directory:
You can hover over each row in the individual task results to download a detailed log for Data Integration Server subtasks or to download the agent and driver logs for advanced cluster subtasks.
The following table describes the individual task results:
Property
Description
Name
Name of the subtask.
Runtime
Indicates whether the subtask ran on the Data Integration Server or on an advanced cluster.
Start time
Date and time that the subtask started.
End time
Date and time that the subtask completed or stopped.
Success Rows
Number of rows successfully written to the target.
For each source and target in the subtask, this field displays the number of rows successfully read from the source and the number of rows successfully written to the target.
For advanced cluster subtasks, this field displays a value only if the task runs using SQL ELT optimization.
For Spark subtasks, this field displays a value only for supported connectors.
Error Rows
Total number of source error rows, target error rows, and transformation errors.
For each source and target in the subtask, this field displays the number of rows that were not read from the source and the number of rows that were not written to the target.
For advanced cluster subtasks, this field displays a value only if the task runs using SQL ELT optimization.
For Spark subtasks, this field displays a value only for supported connectors.
Error Message
Error message, if any, that is associated with the subtask.
Status
Status of the subtask. A subtask can have one of the following statuses:
- Queued. The subtask is queued on a Secure Agent, but it has not started yet.
- Starting. The subtask is starting.
- Running. The subtask is still running.
- Success. The subtask completed successfully.
- Stopped. The parent task stopped running, so the subtask cannot start.
- Warning. The subtask completed with errors.
- Failed. The subtask did not complete because it encountered errors.
Runtime plan
The runtime plan is a visualization that closely approximates how the data actually flows through the mapping at runtime. You can view which mapping logic runs on the Data Integration Server or on an advanced cluster.
Note: If Monitor fails to retrieve the runtime plan, download the session log and review the mapping compilation log in the archive file. You can search for the following line: [LDTM_7343] Generating runtime plan.
For more information about runtime plans, see Mappings.
Reprocessing job details
If you run a job to reprocess incrementally-loaded source files, you can view details about the reprocessing job.
You can view the start and end times of the time range that the job uses to search for new and modified files in the configured source directories. The start time is the time that you configure in the advanced options. If you configure reprocessing in a time interval, the end time is time that you configure in the advanced options. Otherwise, the time at which the job runs determines the end time.
The following image shows an example of the monitoring details for a reprocessing job:
Note: If you restart a job that reprocessed incrementally-loaded source files, the new job runs as a regular job without the advanced options.
Incremental file load details
If you configure sources to incrementally load files, you can view details about the file load.
You can view the start and end times of the time range that the job uses to search for new and modified files in a directory.
The start load time is derived from the end load time of the previous job. The start load time does not apply when the job runs for the first time or you reset the last load time in the mapping task.
Jobs process all files modified up to the end load time, including up to 999 milliseconds after the second. For example, if the end load time of a job appears as Aug 28, 2019 2:15:22 p.m., the job processes all files modified up to Aug 28, 2019 2:15:22.999 p.m.
CLAIRE recommendations
View CLAIRE recommendations to improve job performance and to reduce job costs in the Recommendations panel. CLAIRE recommendations are available if CLAIRE is enabled in your organization.
The following image shows the Recommendations panel:
1. Actions menu
Use the Actions menu to mark recommendations as complete or incomplete, or to opt in and opt out of recommendations.
CLAIRE automatically applies some recommendations. You can use the Actions menu to opt out of the recommendation or opt back in.
Other recommendations require manual action. These recommendations appear as to-do items. You can use the Actions menu to mark to-do items as complete, or mark them as incomplete. You can also opt out of the recommendation or opt back in.
2. Filter recommendations
Use the Filter menu to filter recommendations. You can use the following filters:
- All shows all recommendations.
- To Do shows recommendations that require manual action.
- Applied shows recommendations that are applied automatically and recommendations that are marked complete.
- Opted-Out shows recommendations that are opted out of.
3. Refresh recommendations
Refresh the recommendations to update the recommendations in the Recommendations panel.
