maryannxue commented on a change in pull request #27493: [SPARK-30751][SQL]
Combine the skewed readers into one in AQE skew join optimizations
URL: https://github.com/apache/spark/pull/27493#discussion_r377137379
##########
File path:
sql/core/src/main/scala/org/apache/spark/sql/execution/adaptive/OptimizeSkewedJoin.scala
##########
@@ -156,60 +155,133 @@ case class OptimizeSkewedJoin(conf: SQLConf) extends
Rule[SparkPlan] {
|${getSizeInfo(rightMedSize, rightStats.bytesByPartitionId.max)}
""".stripMargin)
- val skewedPartitions = mutable.HashSet[Int]()
- val subJoins = mutable.ArrayBuffer[SparkPlan]()
- for (partitionId <- 0 until numPartitions) {
- val isLeftSkew = isSkewed(leftStats, partitionId, leftMedSize)
- val isRightSkew = isSkewed(rightStats, partitionId, rightMedSize)
- val leftMapIdStartIndices = if (isLeftSkew &&
supportSplitOnLeftPartition(joinType)) {
- getMapStartIndices(left, partitionId)
- } else {
- Array(0)
- }
- val rightMapIdStartIndices = if (isRightSkew &&
supportSplitOnRightPartition(joinType)) {
- getMapStartIndices(right, partitionId)
- } else {
- Array(0)
- }
+ val leftSidePartitions = mutable.ArrayBuffer.empty[ShufflePartitionSpec]
+ val rightSidePartitions = mutable.ArrayBuffer.empty[ShufflePartitionSpec]
+ val nonSkewPartitionIndices = mutable.ArrayBuffer.empty[Int]
+ val skewDesc = mutable.ArrayBuffer.empty[String]
+ for (partitionIndex <- 0 until numPartitions) {
+ val leftSize = leftStats.bytesByPartitionId(partitionIndex)
+ val isLeftSkew = isSkewed(leftSize, leftMedSize) &&
canSplitLeftSide(joinType)
+ val rightSize = rightStats.bytesByPartitionId(partitionIndex)
+ val isRightSkew = isSkewed(rightSize, rightMedSize) &&
canSplitRightSide(joinType)
+ if (isLeftSkew || isRightSkew) {
+ if (nonSkewPartitionIndices.nonEmpty) {
Review comment:
code comment: as soon as we see a skew, we'll "flush" out unhandled non-skew
partitions.
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