maryannxue commented on a change in pull request #27833: [SPARK-31070][SQL]
make skew join split skewed partitions more evenly
URL: https://github.com/apache/spark/pull/27833#discussion_r389688165
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File path:
sql/core/src/main/scala/org/apache/spark/sql/execution/adaptive/OptimizeSkewedJoin.scala
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@@ -115,18 +115,32 @@ case class OptimizeSkewedJoin(conf: SQLConf) extends
Rule[SparkPlan] {
partitionStartIndices += 0
var i = 0
var postMapPartitionSize = 0L
+ var lastPackagedPartitionSize = -1L
while (i < mapPartitionSizes.length) {
val nextMapPartitionSize = mapPartitionSizes(i)
if (i > 0 && postMapPartitionSize + nextMapPartitionSize > targetSize) {
partitionStartIndices += i
+ lastPackagedPartitionSize = postMapPartitionSize
postMapPartitionSize = nextMapPartitionSize
} else {
postMapPartitionSize += nextMapPartitionSize
}
i += 1
}
- partitionStartIndices.toArray
+ if (lastPackagedPartitionSize > -1) {
+ val lastPartitionDiff = math.abs(targetSize - postMapPartitionSize)
+ val diffIfMergeLastPartition = math.abs(
+ lastPackagedPartitionSize + postMapPartitionSize - targetSize)
+ // If the last partition is very small, we should merge it to the
previous partition.
+ if (lastPartitionDiff > diffIfMergeLastPartition * 2) {
Review comment:
Yes, this would work for extreme cases where you could have a very small
split in between two large splits very close to the target size.
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