Github user yhuai commented on a diff in the pull request:
https://github.com/apache/spark/pull/11583#discussion_r57541319
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/Analyzer.scala
---
@@ -309,38 +309,64 @@ class Analyzer(
object ResolvePivot extends Rule[LogicalPlan] {
def apply(plan: LogicalPlan): LogicalPlan = plan transform {
- case p: Pivot if !p.childrenResolved |
!p.aggregates.forall(_.resolved) => p
+ case p: Pivot if !p.childrenResolved |
!p.aggregates.forall(_.resolved)
+ | !p.groupByExprs.forall(_.resolved) | !p.pivotColumn.resolved => p
case Pivot(groupByExprs, pivotColumn, pivotValues, aggregates,
child) =>
val singleAgg = aggregates.size == 1
- val pivotAggregates: Seq[NamedExpression] = pivotValues.flatMap {
value =>
- def ifExpr(expr: Expression) = {
- If(EqualTo(pivotColumn, value), expr, Literal(null))
+ def outputName(value: Literal, aggregate: Expression): String = {
+ if (singleAgg) value.toString else value + "_" + aggregate.sql
+ }
+ if (pivotValues.length >= 10
+ && aggregates.forall(a =>
PivotFirst.supportsDataType(a.dataType))) {
--- End diff --
Will it better if we remove `pivotValues.length` and just keep
`aggregates.forall(a => PivotFirst.supportsDataType(a.dataType))`? Also, which
data types does the new code path not support?
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