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https://issues.apache.org/jira/browse/SPARK-26164?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16762991#comment-16762991
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Thincrs commented on SPARK-26164:
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A user of thincrs has selected this issue. Deadline: Thu, Feb 14, 2019 7:16 PM
> [SQL] Allow FileFormatWriter to write multiple partitions/buckets without sort
> ------------------------------------------------------------------------------
>
> Key: SPARK-26164
> URL: https://issues.apache.org/jira/browse/SPARK-26164
> Project: Spark
> Issue Type: Sub-task
> Components: SQL
> Affects Versions: 2.4.0
> Reporter: Cheng Su
> Priority: Minor
>
> Problem:
> Current spark always requires a local sort before writing to output table on
> partition/bucket columns [1]. The disadvantage is the sort might waste
> reserved CPU time on executor due to spill. Hive does not require the local
> sort before writing output table [2], and we saw performance regression when
> migrating hive workload to spark.
>
> Proposal:
> We can avoid the local sort by keeping the mapping between file path and
> output writer. In case of writing row to a new file path, we create a new
> output writer. Otherwise, re-use the same output writer if the writer already
> exists (mainly change should be in FileFormatDataWriter.scala). This is very
> similar to what hive does in [2].
> Given the new behavior (i.e. avoid sort by keeping multiple output writer)
> consumes more memory on executor (multiple output writer needs to be opened
> in same time), than the current behavior (i.e. only one output writer
> opened). We can add the config to switch between the current and new behavior.
>
> [1]: spark FileFormatWriter.scala -
> [https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/FileFormatWriter.scala#L123]
> [2]: hive FileSinkOperator.java -
> [https://github.com/apache/hive/blob/master/ql/src/java/org/apache/hadoop/hive/ql/exec/FileSinkOperator.java#L510]
>
>
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