Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/16193#discussion_r91630688
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/python/ExtractPythonUDFs.scala
---
@@ -165,4 +167,31 @@ object ExtractPythonUDFs extends Rule[SparkPlan] {
}
}
}
+
+ // Split the original FilterExec to two FilterExecs. The upper
FilterExec only contains
+ // Python UDF and non-deterministic predicates.
+ private def trySplitFilter(plan: SparkPlan): SparkPlan = {
+ plan match {
+ case filter: FilterExec =>
+ // Only push down the predicates that is deterministic and all the
referenced attributes
+ // come from child.
+ val (candidates, containingNonDeterministic) =
+
splitConjunctivePredicates(filter.condition).span(_.deterministic)
+ val (pushDown, rest) = candidates.partition(!hasPythonUDF(_))
--- End diff --
This will change the semantics. `span` and `partition` have different
semantics. Thus, we still have to keep the existing behavior.
Let me write a comment to explain `PythonUDF` is always assumed to
deterministic.
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