peter-toth commented on a change in pull request #30203:
URL: https://github.com/apache/spark/pull/30203#discussion_r516836683
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File path:
sql/core/src/main/scala/org/apache/spark/sql/execution/python/ExtractPythonUDFs.scala
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@@ -218,13 +218,22 @@ object ExtractPythonUDFs extends Rule[LogicalPlan] with
PredicateHelper {
}
}
+ private def canonicalizeDeterministic(u: PythonUDF) = {
Review comment:
I think @cloud-fan was referring to that if we changed the default to
non-deterministic then it means that some of the optimization rules would not
handle those UDF expressions and would leave them untouched. E.g.
`PushDownPredicates` would not push them down, which could cause performance
regression.
IMHO, it is the user's responsibility to set the deterministic flag right
regardless what is the default. And if a UDF is flagged deterministic we should
do the optimizations.
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