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https://issues.apache.org/jira/browse/MAPREDUCE-7029?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Jason Lowe updated MAPREDUCE-7029:
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Release Note: MapReduce jobs that output to filesystems without direct
support for recursive delete can set
mapreduce.fileoutputcommitter.task.cleanup.enabled=true to have each task
delete their intermediate work directory rather than waiting for the
ApplicationMaster to clean up at the end of the job. This can significantly
speed up the cleanup phase for large jobs on such filesystems.
+1 for the branch-2 patch as well. Committing this.
> FileOutputCommitter#commitTask should delete task directory
> -----------------------------------------------------------
>
> Key: MAPREDUCE-7029
> URL: https://issues.apache.org/jira/browse/MAPREDUCE-7029
> Project: Hadoop Map/Reduce
> Issue Type: Improvement
> Affects Versions: 2.8.2
> Environment: - Google Cloud Storage (with the GCS connector:
> https://github.com/GoogleCloudPlatform/bigdata-interop/tree/master/gcs) for
> HCFS compatibility.
> - FileOutputCommitter algorithm v2.
> - Running on Google Compute Engine with Java 8, Debian 8, Hadoop 2.8.2, Spark
> 2.2.0.
> Reporter: Karthik Palaniappan
> Assignee: Karthik Palaniappan
> Priority: Minor
> Attachments: MAPREDUCE-7029-branch-2.004.patch,
> MAPREDUCE-7029-branch-2.005.patch, MAPREDUCE-7029-branch-2.005.patch,
> MAPREDUCE-7029.001.patch, MAPREDUCE-7029.002.patch, MAPREDUCE-7029.003.patch,
> MAPREDUCE-7029.004.patch, MAPREDUCE-7029.005.patch
>
>
> I ran a Spark job that outputs thousands of parquet files (aka there are
> thousands of reducers), and it hung for several minutes in the driver after
> all tasks were complete. Here is a very simple repro of the job (to be run in
> a spark-shell):
> {code:scala}
> spark.range(1L << 20).repartition(1 << 14).write.save("gs://some/path")
> {code}
> Spark actually calls into Mapreduce's FileOuputCommitter. Job committing
> (specifically cleanupJob()) recursively deletes the job temporary directory,
> which is something like "gs://some/path/_temporary". If I understand
> correctly, on HDFS, this would be O(1), but on GCS (and every HCFS I know),
> this requires a full file tree walk. Deleting tens of thousands of objects in
> GCS takes several minutes.
> I propose that commitTask() recursively deletes its the task attempt temp
> directory (something like "gs://some/path/_temporary/attempt1/task1"). On
> HDFS, this is O(1) per task, so this is very little overhead per task. On GCS
> (and other HCFSs), this adds parallelism for deleting the job temp directory.
> With the attached patch, the repro above went from taking ~10 minutes to
> taking ~5 minutes, and task time did not significantly change.
> Side note: I found this issue with Spark, but I assume it applies to a
> Mapreduce job with thousands of reducers as well.
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