Github user sddyljsx commented on a diff in the pull request:
https://github.com/apache/spark/pull/21859#discussion_r209417551
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/exchange/ShuffleExchangeExec.scala
---
@@ -294,7 +296,12 @@ object ShuffleExchangeExec {
sorter.sort(iter.asInstanceOf[Iterator[UnsafeRow]])
}
} else {
- rdd
+ part match {
+ case partitioner: RangePartitioner[InternalRow @unchecked, _]
+ if partitioner.getSampledArray != null =>
+ sparkContext.parallelize(partitioner.getSampledArray.toSeq,
rdd.getNumPartitions)
--- End diff --
```
part match {
case partitioner: RangePartitioner[InternalRow @unchecked, _]
if partitioner.getSampledArray != null =>
sparkContext.parallelize(partitioner.getSampledArray.toSeq,
rdd.getNumPartitions)
case _ => rdd
}
```
When the optimization works, It will return the parallelized sampled data
instead of the rdd. So I keep the number of the partitions same as the rdd's
here
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