Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/23248#discussion_r239686156
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/python/ExtractPythonUDFs.scala
---
@@ -131,8 +131,20 @@ object ExtractPythonUDFs extends Rule[LogicalPlan]
with PredicateHelper {
expressions.flatMap(collectEvaluableUDFs)
}
- def apply(plan: LogicalPlan): LogicalPlan = plan transformUp {
- case plan: LogicalPlan => extract(plan)
+ def apply(plan: LogicalPlan): LogicalPlan = plan match {
+ // SPARK-26293: A subquery will be rewritten into join later, and will
go through this rule
+ // eventually. Here we skip subquery, as Python UDF only needs to be
extracted once.
+ case _: Subquery => plan
--- End diff --
I agree it's a bit confusing, but that's how `Subquery` is designed to
work. See how `RemoveRedundantAliases` catches `Subquery`.
It's sufficient to make `ExtractPythonUDFs` idempotent, skip `Subquery` is
just for double safe, and may have a little bit perf improvement, since this
rule will be run less.
In general, I think we should skip `Subquery` here. This is why we create
`Subquery`: we expect rules that don't want to be executed on subquery to skip
it. I'll check more rules and see if they need to skip `Subquery` later.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org
For additional commands, e-mail: reviews-h...@spark.apache.org
