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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