Github user viirya commented on a diff in the pull request: https://github.com/apache/spark/pull/21564#discussion_r195420136 --- Diff: sql/core/src/main/scala/org/apache/spark/sql/execution/columnar/InMemoryTableScanExec.scala --- @@ -170,6 +170,8 @@ case class InMemoryTableScanExec( override def outputPartitioning: Partitioning = { relation.cachedPlan.outputPartitioning match { case h: HashPartitioning => updateAttribute(h).asInstanceOf[HashPartitioning] + case r: RangePartitioning => + r.copy(ordering = r.ordering.map(updateAttribute(_).asInstanceOf[SortOrder])) --- End diff -- Hmm, `HashPartitioning` and `RangePartitioning` can affect later sorting and shuffle. But for `BroadcastPartitioning`, seems to me no such benefit.
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