Github user HyukjinKwon commented on a diff in the pull request: https://github.com/apache/spark/pull/21650#discussion_r205061160 --- Diff: sql/core/src/main/scala/org/apache/spark/sql/execution/python/ExtractPythonUDFs.scala --- @@ -94,36 +95,59 @@ object ExtractPythonUDFFromAggregate extends Rule[LogicalPlan] { */ object ExtractPythonUDFs extends Rule[SparkPlan] with PredicateHelper { - private def hasPythonUDF(e: Expression): Boolean = { + private def hasScalarPythonUDF(e: Expression): Boolean = { e.find(PythonUDF.isScalarPythonUDF).isDefined } - private def canEvaluateInPython(e: PythonUDF): Boolean = { - e.children match { - // single PythonUDF child could be chained and evaluated in Python - case Seq(u: PythonUDF) => canEvaluateInPython(u) - // Python UDF can't be evaluated directly in JVM - case children => !children.exists(hasPythonUDF) + private def canEvaluateInPython(e: PythonUDF, evalType: Int): Boolean = { + if (e.evalType != evalType) { --- End diff -- Can we rename this function or write a comment since Scalar both Vectorized UDF and normal UDF can be evaluated in Python each but it returns `false` in this case?
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