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https://issues.apache.org/jira/browse/SPARK-6221?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14352735#comment-14352735
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Sean Owen commented on SPARK-6221:
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Interesting idea, though you could make this argument for any output from
Spark. The problem is knowing how far to merge; Spark can't in general know
that. The caller does, but the caller can already repartition to address this
situation. What would this buy over just repartitioning before persisting?
> SparkSQL should support auto merging output files
> -------------------------------------------------
>
> Key: SPARK-6221
> URL: https://issues.apache.org/jira/browse/SPARK-6221
> Project: Spark
> Issue Type: New Feature
> Components: SQL
> Reporter: Yi Tian
>
> Hive has a feature that could automatically merge small files in HQL's output
> path.
> This feature is quite useful for some cases that people use {{insert into}}
> to handle minute data from the input path to a daily table.
> In that case, if the SQL includes {{group by}} or {{join}} operation, we
> always set the {{reduce number}} at least 200 to avoid the possible OOM in
> reduce side.
> That will cause this SQL output at least 200 files at the end of the
> execution. So the daily table will finally contains more than 50000 files.
> If we could provide the same feature in SparkSQL, it will extremely reduce
> hdfs operations and spark tasks when we run other sql on this table.
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