hvanhovell 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_r378554332
##########
File path:
sql/core/src/main/scala/org/apache/spark/sql/execution/adaptive/OptimizeSkewedJoin.scala
##########
@@ -156,60 +155,126 @@ 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)
- }
-
- if (leftMapIdStartIndices.length > 1 || rightMapIdStartIndices.length
> 1) {
- skewedPartitions += partitionId
- for (i <- 0 until leftMapIdStartIndices.length;
- j <- 0 until rightMapIdStartIndices.length) {
- val leftEndMapId = if (i == leftMapIdStartIndices.length - 1) {
- getNumMappers(left)
- } else {
- leftMapIdStartIndices(i + 1)
+ val leftSidePartitions = mutable.ArrayBuffer.empty[ShufflePartitionSpec]
+ val rightSidePartitions = mutable.ArrayBuffer.empty[ShufflePartitionSpec]
+ // This is used to delay the creation of non-skew partitions so that we
can potentially
+ // coalesce them like `ReduceNumShufflePartitions` does.
+ val nonSkewPartitionIndices = mutable.ArrayBuffer.empty[Int]
+ val leftSkewDesc = new SkewDesc
+ val rightSkewDesc = new SkewDesc
+ 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) {
+ // As soon as we see a skew, we'll "flush" out unhandled non-skew
partitions.
+ createNonSkewPartitions(leftStats, rightStats,
nonSkewPartitionIndices).foreach { p =>
+ leftSidePartitions += p
+ rightSidePartitions += p
}
- val rightEndMapId = if (j == rightMapIdStartIndices.length - 1) {
- getNumMappers(right)
- } else {
- rightMapIdStartIndices(j + 1)
+ nonSkewPartitionIndices.clear()
+ }
+
+ val leftParts = if (isLeftSkew) {
+ leftSkewDesc.addPartitionSize(leftSize)
+ createSkewPartitions(
+ partitionIndex,
+ getMapStartIndices(left, partitionIndex),
+ getNumMappers(left))
+ } else {
+ Seq(NormalPartitionSpec(partitionIndex))
+ }
+
+ val rightParts = if (isRightSkew) {
+ rightSkewDesc.addPartitionSize(rightSize)
+ createSkewPartitions(
+ partitionIndex,
+ getMapStartIndices(right, partitionIndex),
+ getNumMappers(right))
+ } else {
+ Seq(NormalPartitionSpec(partitionIndex))
+ }
+
+ for {
+ leftSidePartition <- leftParts
+ rightSidePartition <- rightParts
+ } {
+ leftSidePartitions += leftSidePartition
+ rightSidePartitions += rightSidePartition
+ }
+ } else {
+ // Add to `nonSkewPartitionIndices` first, and add real partitions
later, in case we can
+ // coalesce the non-skew partitions.
+ nonSkewPartitionIndices += partitionIndex
+ // If this is the last partition, add real partition immediately.
+ if (partitionIndex == numPartitions - 1) {
+ createNonSkewPartitions(leftStats, rightStats,
nonSkewPartitionIndices).foreach { p =>
+ leftSidePartitions += p
+ rightSidePartitions += p
}
- // TODO: we may can optimize the sort merge join to broad cast
join after
- // obtaining the raw data size of per partition,
- val leftSkewedReader = SkewedPartitionReaderExec(
- left, partitionId, leftMapIdStartIndices(i), leftEndMapId)
- val rightSkewedReader = SkewedPartitionReaderExec(right,
partitionId,
- rightMapIdStartIndices(j), rightEndMapId)
- subJoins += SortMergeJoinExec(leftKeys, rightKeys, joinType,
condition,
- s1.copy(child = leftSkewedReader), s2.copy(child =
rightSkewedReader), true)
+ nonSkewPartitionIndices.clear()
}
}
}
- logDebug(s"number of skewed partitions is ${skewedPartitions.size}")
- if (skewedPartitions.nonEmpty) {
- val optimizedSmj = smj.copy(
- left = s1.copy(child = PartialShuffleReaderExec(left,
skewedPartitions.toSet)),
- right = s2.copy(child = PartialShuffleReaderExec(right,
skewedPartitions.toSet)),
- isPartial = true)
- subJoins += optimizedSmj
- UnionExec(subJoins)
+
+ logDebug("number of skewed partitions: " +
+ s"left ${leftSkewDesc.numPartitions}, right
${rightSkewDesc.numPartitions}")
+ if (leftSkewDesc.numPartitions > 0 || rightSkewDesc.numPartitions > 0) {
+ val newLeft = SkewJoinShuffleReaderExec(
+ left, leftSidePartitions.toArray, leftSkewDesc.toString)
+ val newRight = SkewJoinShuffleReaderExec(
+ right, rightSidePartitions.toArray, rightSkewDesc.toString)
+ smj.copy(
+ left = s1.copy(child = newLeft), right = s2.copy(child = newRight),
isSkewJoin = true)
} else {
smj
}
}
+ private def createNonSkewPartitions(
+ leftStats: MapOutputStatistics,
+ rightStats: MapOutputStatistics,
+ nonSkewPartitionIndices: Seq[Int]): Seq[ShufflePartitionSpec] = {
+ assert(nonSkewPartitionIndices.nonEmpty)
+ if (nonSkewPartitionIndices.length == 1) {
+ Seq(NormalPartitionSpec(nonSkewPartitionIndices.head))
+ } else {
+ val startIndices = ShufflePartitionsCoalescer.coalescePartitions(
Review comment:
This is pretty neat.
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