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https://issues.apache.org/jira/browse/GOBBLIN-1947?focusedWorklogId=893472&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-893472
]
ASF GitHub Bot logged work on GOBBLIN-1947:
-------------------------------------------
Author: ASF GitHub Bot
Created on: 01/Dec/23 19:55
Start Date: 01/Dec/23 19:55
Worklog Time Spent: 10m
Work Description: hanghangliu commented on code in PR #3832:
URL: https://github.com/apache/gobblin/pull/3832#discussion_r1412518727
##########
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:
this is actually needed and may easily get overlooked. It's a process that
make sure the workUnit can handle shards for target directory. Took me a while
the figure out and debug when testing in the cluster...
Issue Time Tracking
-------------------
Worklog Id: (was: 893472)
Time Spent: 1h 20m (was: 1h 10m)
> 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: 1h 20m
> 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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