[GitHub] [spark] mridulm commented on a change in pull request #31480: [SPARK-32384][CORE] repartitionAndSortWithinPartitions avoid shuffle with same partitioner

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mridulm commented on a change in pull request #31480:
URL: https://github.com/apache/spark/pull/31480#discussion_r579492908



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File path: core/src/main/scala/org/apache/spark/rdd/OrderedRDDFunctions.scala
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@@ -73,7 +75,23 @@ class OrderedRDDFunctions[K : Ordering : ClassTag,
    * because it can push the sorting down into the shuffle machinery.
    */
   def repartitionAndSortWithinPartitions(partitioner: Partitioner): RDD[(K, V)] = self.withScope {
-    new ShuffledRDD[K, V, V](self, partitioner).setKeyOrdering(ordering)
+    if (self.partitioner == Some(partitioner)) {
+      self.mapPartitions(iter => {
+        val context = TaskContext.get
+        val sorter = new ExternalSorter[K, V, V](context, None, None, Some(ordering))
+        sorter.insertAll(iter)
+        context.taskMetrics.incMemoryBytesSpilled(sorter.memoryBytesSpilled)
+        context.taskMetrics.incDiskBytesSpilled(sorter.diskBytesSpilled)
+        context.taskMetrics.incPeakExecutionMemory(sorter.peakMemoryUsedBytes)
+        // Use completion callback to stop sorter if task was finished/cancelled.
+        context.addTaskCompletionListener[Unit](_ => sorter.stop)
+        val outputIter = new InterruptibleIterator(context,
+          sorter.iterator.asInstanceOf[Iterator[(K, V)]])
+        CompletionIterator[(K, V), Iterator[(K, V)]](outputIter, sorter.stop)
+      }, preservesPartitioning = true)
+    } else {

Review comment:
       I probably mentioned this in the earlier version of this PR as well.
   Can we unify the code in this if block with what is in BlockStoreShuffleReader as well ?
   We are duplicating this.




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