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https://issues.apache.org/jira/browse/SPARK-32384?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17279293#comment-17279293
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Apache Spark commented on SPARK-32384:
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User 'zhengruifeng' has created a pull request for this issue:
https://github.com/apache/spark/pull/31480
> repartitionAndSortWithinPartitions avoid shuffle with same partitioner
> ----------------------------------------------------------------------
>
> Key: SPARK-32384
> URL: https://issues.apache.org/jira/browse/SPARK-32384
> Project: Spark
> Issue Type: Improvement
> Components: Spark Core
> Affects Versions: 3.1.0
> Reporter: zhengruifeng
> Priority: Minor
>
> In {{combineByKeyWithClassTag}}, there is a check so that if the partitioner
> is the same as the one of the RDD:
> {code:java}
> if (self.partitioner == Some(partitioner)) {
> self.mapPartitions(iter => {
> val context = TaskContext.get()
> new InterruptibleIterator(context, aggregator.combineValuesByKey(iter,
> context))
> }, preservesPartitioning = true)
> } else {
> new ShuffledRDD[K, V, C](self, partitioner)
> .setSerializer(serializer)
> .setAggregator(aggregator)
> .setMapSideCombine(mapSideCombine)
> }
> {code}
>
> In {{repartitionAndSortWithinPartitions}}, this shuffle can also be skipped
> in this case.
>
>
>
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