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https://issues.apache.org/jira/browse/YARN-8617?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16569983#comment-16569983
 ] 

Bibin A Chundatt commented on YARN-8617:
----------------------------------------

[~Prabhu Joseph]

IIUC LogAggregationService ->  AggregatorImpl every upload cycle for each node 
you will have new files per node

{code}
node3.openstack_45454_1533315091898
node3.openstack_45454_<uploaded time1>
node3.openstack_45454_<uploaded time2>
{code}

{{node3.openstack_45454_1533315091898}} file will not be changed once uploaded. 
So AggregationDeletionService should delete the file after log retain time


{code}
       Set<Path> uploadedFilePathsInThisCycle =
            aggregator.doContainerLogAggregation(logAggregationFileController,
            appFinished, finishedContainers.contains(container));
...

      logControllerContext.setLogUploadTimeStamp(System.currentTimeMillis());

      try {
        this.logAggregationFileController.postWrite(logControllerContext);
        diagnosticMessage = "Log uploaded successfully for Application: "
            + appId + " in NodeManager: "
            + LogAggregationUtils.getNodeString(nodeId) + " at "
            + Times.format(logControllerContext.getLogUploadTimeStamp())
            + "\n";
{code}

this.logAggregationFileController.postWrite(logControllerContext); --> renames 
the file with time stamp




> Aggregated Application Logs accumulates for long running jobs
> -------------------------------------------------------------
>
>                 Key: YARN-8617
>                 URL: https://issues.apache.org/jira/browse/YARN-8617
>             Project: Hadoop YARN
>          Issue Type: New Feature
>          Components: log-aggregation
>    Affects Versions: 2.7.4
>            Reporter: Prabhu Joseph
>            Priority: Major
>
> Currently AggregationDeletionService will delete older aggregated log files 
> once when they are complete. This will cause logs to accumulate for Long 
> Running Jobs like Llap, Spark Streaming.



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