JkSelf commented on a change in pull request #26434: [SPARK-29544] [SQL]
optimize skewed partition based on data size
URL: https://github.com/apache/spark/pull/26434#discussion_r358583953
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File path:
sql/core/src/main/scala/org/apache/spark/sql/execution/adaptive/ReduceNumShufflePartitions.scala
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@@ -145,39 +156,36 @@ case class ReduceNumShufflePartitions(conf: SQLConf)
extends Rule[SparkPlan] {
distinctNumPreShufflePartitions.length == 1,
"There should be only one distinct value of the number pre-shuffle
partitions " +
"among registered Exchange operator.")
- val numPreShufflePartitions = distinctNumPreShufflePartitions.head
val partitionStartIndices = ArrayBuffer[Int]()
- // The first element of partitionStartIndices is always 0.
- partitionStartIndices += 0
-
- var postShuffleInputSize = 0L
-
- var i = 0
- while (i < numPreShufflePartitions) {
- // We calculate the total size of ith pre-shuffle partitions from all
pre-shuffle stages.
- // Then, we add the total size to postShuffleInputSize.
- var nextShuffleInputSize = 0L
- var j = 0
- while (j < mapOutputStatistics.length) {
- nextShuffleInputSize += mapOutputStatistics(j).bytesByPartitionId(i)
- j += 1
- }
-
- // If including the nextShuffleInputSize would exceed the target
partition size, then start a
- // new partition.
- if (i > 0 && postShuffleInputSize + nextShuffleInputSize >
targetPostShuffleInputSize) {
- partitionStartIndices += i
- // reset postShuffleInputSize.
- postShuffleInputSize = nextShuffleInputSize
- } else {
- postShuffleInputSize += nextShuffleInputSize
- }
-
- i += 1
+ val partitionEndIndices = ArrayBuffer[Int]()
+ val numPartitions = mapOutputStatistics.map(stats =>
stats.bytesByPartitionId.length).head
+ val includedPartitions = (0 until
numPartitions).filter(!excludedPartitions.contains(_))
+ val firstStartIndex = includedPartitions(0)
+ partitionStartIndices += firstStartIndex
+ var postShuffleInputSize =
mapOutputStatistics.map(_.bytesByPartitionId(firstStartIndex)).sum
+ var i = firstStartIndex
+ includedPartitions.filter(_ != firstStartIndex).foreach {
+ nextPartitionIndices =>
+ var nextShuffleInputSize =
+
mapOutputStatistics.map(_.bytesByPartitionId(nextPartitionIndices)).sum
+ // If nextPartitionIndices is skewed and omitted, or including
+ // the nextShuffleInputSize would exceed the target partition size,
+ // then start a new partition.
+ if (nextPartitionIndices != i + 1 ||
Review comment:
The `nextPartitionIndices ` is excluded.
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