cloud-fan commented on a change in pull request #25215:
[SPARK-28445][SQL][Python] Fix error when PythonUDF is used in both group by
and aggregate expression
URL: https://github.com/apache/spark/pull/25215#discussion_r310002712
##########
File path:
sql/core/src/main/scala/org/apache/spark/sql/execution/python/ExtractPythonUDFs.scala
##########
@@ -81,6 +81,69 @@ object ExtractPythonUDFFromAggregate extends
Rule[LogicalPlan] {
}
}
+/**
+ * Extracts PythonUDFs in logical aggregate, which are used in grouping keys,
evaluate them
+ * before aggregate.
+ * This must be executed after `ExtractPythonUDFFromAggregate` rule and before
`ExtractPythonUDFs`.
+ */
+object ExtractGroupingPythonUDFFromAggregate extends Rule[LogicalPlan] {
+ private def hasScalarPythonUDF(e: Expression): Boolean = {
+ e.find(PythonUDF.isScalarPythonUDF).isDefined
+ }
+
+ private def extract(agg: Aggregate): LogicalPlan = {
+ val projList = new ArrayBuffer[NamedExpression]()
+ val groupingExpr = new ArrayBuffer[Expression]()
+ val attributeMap = mutable.HashMap[PythonUDF, NamedExpression]()
+
+ agg.groupingExpressions.foreach { expr =>
+ if (hasScalarPythonUDF(expr)) {
+ val newE = expr transformDown {
+ case p: PythonUDF =>
+ // This is just a sanity check, the rule PullOutNondeterministic
should
+ // already pull out those nondeterministic expressions.
+ assert(p.udfDeterministic, "Non-determinstic PythonUDFs should not
appear " +
+ "in grouping expression")
+ val canonicalized = p.canonicalized.asInstanceOf[PythonUDF]
+ if (attributeMap.contains(canonicalized)) {
+ attributeMap(canonicalized)
+ } else {
+ val alias = Alias(p, "groupingPythonUDF")()
+ projList += alias
+ attributeMap += ((canonicalized, alias.toAttribute))
+ alias.toAttribute
+ }
+ }
+ groupingExpr += newE
+ } else {
+ groupingExpr += expr
+ }
+ }
+ val aggExpr = agg.aggregateExpressions.map { expr =>
+ expr.transformUp {
+ // PythonUDF over aggregate was pull out by
ExtractPythonUDFFromAggregate.
+ // PythonUDF here should be either
+ // 1. Argument of an aggregate function.
+ // CheckAnalysis guarantees the arguments are deterministic.
+ // 2. PythonUDF in grouping key. Grouping key must be deterministic.
+ // 3. PythonUDF not in grouping key. It is either no arguments or with
grouping key
+ // in its arguments. Such PythonUDF was pull out by
ExtractPythonUDFFromAggregate, too.
+ case p: PythonUDF if p.udfDeterministic =>
+ val canonicalized = p.canonicalized.asInstanceOf[PythonUDF]
+ attributeMap.getOrElse(canonicalized, p)
Review comment:
nit: if we can't replace python udf here, we can't run the query. Maybe it's
better to do `attributeMap.get(...).getOrElse(fail)`?
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