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https://issues.apache.org/jira/browse/MAPREDUCE-7185?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17802806#comment-17802806
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Shilun Fan commented on MAPREDUCE-7185:
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Bulk update: moved all 3.4.0 non-blocker issues, please move back if it is a
blocker. Retarget 3.5.0.
> 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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