Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/18861#discussion_r131766593
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/plans/logical/basicLogicalOperators.scala
---
@@ -746,8 +746,20 @@ abstract class RepartitionOperation extends UnaryNode {
* [[RepartitionByExpression]] as this method is called directly by
DataFrame's, because the user
* asked for `coalesce` or `repartition`. [[RepartitionByExpression]] is
used when the consumer
* of the output requires some specific ordering or distribution of the
data.
+ *
+ * If `shuffle` = false (`coalesce` cases), this logical plan can have an
user-specified strategy
+ * to coalesce input partitions.
+ *
+ * @param numPartitions How many partitions to use in the output RDD
+ * @param shuffle Whether to shuffle when repartitioning
+ * @param child the LogicalPlan
+ * @param coalescer Optional coalescer that an user specifies
*/
-case class Repartition(numPartitions: Int, shuffle: Boolean, child:
LogicalPlan)
+case class Repartition(
+ numPartitions: Int,
+ shuffle: Boolean,
+ child: LogicalPlan,
+ coalescer: Option[PartitionCoalescer] = None)
extends RepartitionOperation {
require(numPartitions > 0, s"Number of partitions ($numPartitions) must
be positive.")
--- End diff --
Add a new require here?
```
require(!shuffle || coalescer.isEmpty, "Custom coalescer is not allowed for
repartition(shuffle=true)")
```
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