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https://issues.apache.org/jira/browse/GOBBLIN-1947?focusedWorklogId=893852&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-893852
 ]

ASF GitHub Bot logged work on GOBBLIN-1947:
-------------------------------------------

                Author: ASF GitHub Bot
            Created on: 04/Dec/23 19:10
            Start Date: 04/Dec/23 19:10
    Worklog Time Spent: 10m 
      Work Description: ZihanLi58 commented on code in PR #3832:
URL: https://github.com/apache/gobblin/pull/3832#discussion_r1414362742


##########
gobblin-runtime/src/main/java/org/apache/gobblin/runtime/AbstractJobLauncher.java:
##########
@@ -507,9 +513,10 @@ public void apply(JobListener jobListener, JobContext 
jobContext)
         }
 
         // Perform work needed before writing is done
-        Boolean canCleanUp = 
this.canCleanStagingData(this.jobContext.getJobState());
-        workUnitStream = closer.register(new 
DestinationDatasetHandlerService(jobState, canCleanUp, this.eventSubmitter))
-            .executeHandlers(workUnitStream);
+        this.canCleanUpStagingData = 
this.canCleanStagingData(this.jobContext.getJobState());

Review Comment:
   I'm a little confused for the issue we are trying to solve here. Can you add 
comment in code to explain that?





Issue Time Tracking
-------------------

    Worklog Id:     (was: 893852)
    Time Spent: 1.5h  (was: 1h 20m)

> Send WorkUnitChangeEvent when helix task consistently fail 
> -----------------------------------------------------------
>
>                 Key: GOBBLIN-1947
>                 URL: https://issues.apache.org/jira/browse/GOBBLIN-1947
>             Project: Apache Gobblin
>          Issue Type: New Feature
>          Components: gobblin-cluster
>            Reporter: Hanghang Liu
>            Assignee: Hung Tran
>            Priority: Major
>          Time Spent: 1.5h
>  Remaining Estimate: 0h
>
> When YarnAutoScalingManager detect helix task consistently fail, give an 
> option to send WorkUnitChangeEvent to let GobblinHelixJobLauncher handle the 
> event and split the work unit during runtime. This can help resolving 
> consistent failing containers issue(like OOM) during runtime instead of 
> relying on replaner to restart the whole pipeline



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