Github user hvanhovell commented on a diff in the pull request: https://github.com/apache/spark/pull/15238#discussion_r80802568 --- Diff: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/planning/patterns.scala --- @@ -191,25 +191,34 @@ object ExtractFiltersAndInnerJoins extends PredicateHelper { /** * A pattern that collects all adjacent unions and returns their children as a Seq. + * If the top union is wrapped in a [[Distinct]], then the [[Distinct]] in the adjacent unions, if + * any, will be eliminated. */ object Unions { - def unapply(plan: LogicalPlan): Option[Seq[LogicalPlan]] = plan match { - case u: Union => Some(collectUnionChildren(mutable.Stack(u), Seq.empty[LogicalPlan])) + def unapply(plan: LogicalPlan): Option[(Seq[LogicalPlan], Boolean)] = plan match { + case u: Union => + Some(collectUnionChildren(mutable.Stack(u), Seq.empty[LogicalPlan], false), false) + case Distinct(u: Union) => + Some(collectUnionChildren(mutable.Stack(u), Seq.empty[LogicalPlan], true), true) case _ => None } // Doing a depth-first tree traversal to combine all the union children. @tailrec private def collectUnionChildren( plans: mutable.Stack[LogicalPlan], - children: Seq[LogicalPlan]): Seq[LogicalPlan] = { + children: Seq[LogicalPlan], + dedupDistinct: Boolean): Seq[LogicalPlan] = { --- End diff -- Ok, so I took a longer look. The current approach uses tail recursion with a bunch of state. I tried rewriting this as a tail recursive function without that much state, but that proved to be very painful. So it seems simpler to just use a purely imperative function: ```scala private def flattenUnion(union: Union, flattenDistinct: Boolean): Union = { val stack = mutable.Stack[LogicalPlan](union) val flattened = mutable.ArrayBuffer.empty[LogicalPlan] while (stack.nonEmpty) { stack.pop() match { case Distinct(Union(children)) if flattenDistinct => stack.pushAll(children) case Union(children) => stack.pushAll(children) case child => flattened += child } } Union(flattened) } ``` @gatorsmile why did you use `reverseMap`?
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