Github user nsyca commented on a diff in the pull request:
https://github.com/apache/spark/pull/17186#discussion_r106169573
--- Diff:
sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/PruneFiltersSuite.scala
---
@@ -133,4 +146,28 @@ class PruneFiltersSuite extends PlanTest {
val correctAnswer = testRelation.where(Rand(10) > 5).where(Rand(10) >
5).select('a).analyze
comparePlans(optimized, correctAnswer)
}
+
+ test("No pruning when constraint propagation is disabled") {
+ val tr1 = LocalRelation('a.int, 'b.int, 'c.int).subquery('tr1)
+ val tr2 = LocalRelation('a.int, 'd.int, 'e.int).subquery('tr2)
+
+ val query = tr1
+ .where("tr1.a".attr > 10 || "tr1.c".attr < 10)
+ .join(tr2.where('d.attr < 100), Inner, Some("tr1.a".attr ===
"tr2.a".attr))
+
+ val queryWithUselessFilter =
+ query.where(
+ ("tr1.a".attr > 10 || "tr1.c".attr < 10) &&
+ 'd.attr < 100)
+
+ val optimized =
OptimizeDisableConstraintPropagation.execute(queryWithUselessFilter.analyze)
+ // When constraint propagation is disabled, the useless filter won't
be pruned.
+ // It gets pushed down. Because the rule `CombineFilters` runs only
once, there are redundant
+ // and duplicate filters.
--- End diff --
I am aware of it. My point is when users turn on this setting in hope of
alleviating a lengthy compilation time, they will get this "unintentional" side
effect that could lengthen the execution time of evaluating the same predicate
twice.
Overall, I agree with your approach but the point I raised could be a
followup work.
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