[jira] [Commented] (MAPREDUCE-7185) Parallelize part files move in FileOutputCommitter

["Hadoop QA (Jira)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/MAPREDUCE-7185?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16952113#comment-16952113 ] 

Hadoop QA commented on MAPREDUCE-7185:
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|| Vote || Subsystem || Runtime || Comment ||
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|| Subsystem || Report/Notes ||
| JIRA Issue | MAPREDUCE-7185 |
| JIRA Patch URL | https://issues.apache.org/jira/secure/attachment/12958315/MAPREDUCE-7185.patch |
| Console output | https://builds.apache.org/job/PreCommit-MAPREDUCE-Build/7674/console |
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> Parallelize part files move in FileOutputCommitter
> --------------------------------------------------
>
>                 Key: MAPREDUCE-7185
>                 URL: https://issues.apache.org/jira/browse/MAPREDUCE-7185
>             Project: Hadoop Map/Reduce
>          Issue Type: Improvement
>    Affects Versions: 3.2.0, 2.9.2
>            Reporter: Igor Dvorzhak
>            Assignee: Igor Dvorzhak
>            Priority: Major
>         Attachments: MAPREDUCE-7185.patch
>
>
> If map task outputs multiple files it could be slow to move them from temp directory to output directory in object stores (GCS, S3, etc).
> To improve performance we need to parallelize move of more than 1 file in FileOutputCommitter.
> Repro:
>  Start spark-shell:
> {code}
> spark-shell --num-executors 2 --executor-memory 10G --executor-cores 4 --conf spark.dynamicAllocation.maxExecutors=2
> {code}
> From spark-shell:
> {code}
> val df = (1 to 10000).toList.toDF("value").withColumn("p", $"value" % 10).repartition(50)
> df.write.partitionBy("p").mode("overwrite").format("parquet").options(Map("path" -> s"gs://some/path")).saveAsTable("parquet_partitioned_bench")
> {code}
> With the fix execution time reduces from 130 seconds to 50 seconds.



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