Github user marmbrus commented on a diff in the pull request:
https://github.com/apache/spark/pull/9858#discussion_r46209620
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/Exchange.scala ---
@@ -488,6 +488,12 @@ private[sql] case class EnsureRequirements(sqlContext:
SQLContext) extends Rule[
}
def apply(plan: SparkPlan): SparkPlan = plan.transformUp {
+ case operator @ Exchange(partitioning, child, _) =>
+ child.children match {
+ case Exchange(childPartitioning, baseChild, _)::Nil =>
--- End diff --
The key difference about putting it in the planner instead of in the
optimizer is that you can actually plan the child first and check its actual
output ordering instead of doing this specific check for `Aggregate`.
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