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Posted to issues@spark.apache.org by "Apache Spark (Jira)" <ji...@apache.org> on 2020/07/22 07:24:00 UTC
[jira] [Assigned] (SPARK-32384) repartitionAndSortWithinPartitions
avoid shuffle with same partitioner
[ https://issues.apache.org/jira/browse/SPARK-32384?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Apache Spark reassigned SPARK-32384:
------------------------------------
Assignee: Apache Spark
> 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
> Assignee: Apache Spark
> 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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