cloud-fan commented on a change in pull request #28226:
URL: https://github.com/apache/spark/pull/28226#discussion_r411102045
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File path:
sql/core/src/main/scala/org/apache/spark/sql/execution/adaptive/OptimizeSkewedJoin.scala
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@@ -88,9 +88,11 @@ case class OptimizeSkewedJoin(conf: SQLConf) extends
Rule[SparkPlan] {
private def targetSize(sizes: Seq[Long], medianSize: Long): Long = {
val advisorySize = conf.getConf(SQLConf.ADVISORY_PARTITION_SIZE_IN_BYTES)
val nonSkewSizes = sizes.filterNot(isSkewed(_, medianSize))
- // It's impossible that all the partitions are skewed, as we use median
size to define skew.
- assert(nonSkewSizes.nonEmpty)
- math.max(advisorySize, nonSkewSizes.sum / nonSkewSizes.length)
+ if (nonSkewSizes.isEmpty) {
Review comment:
because we calculate the median size based on the original map stats,
but the input partitions are coalesced. It's possible all partitions (after
coalesce) are skewed.
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