AngersZhuuuu commented on a change in pull request #30144:
URL: https://github.com/apache/spark/pull/30144#discussion_r611112158
##########
File path:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/grouping.scala
##########
@@ -231,3 +235,34 @@ object GroupingID {
if (SQLConf.get.integerGroupingIdEnabled) IntegerType else LongType
}
}
+
+object GroupingAnalytics {
+ def unapply(exprs: Seq[Expression])
+ : Option[(Seq[Seq[Expression]], Seq[Expression])] = {
+ if (!exprs.exists(_.isInstanceOf[BaseGroupingSets])) {
+ None
+ } else {
+ val resolved = exprs.forall {
+ case gs: BaseGroupingSets => gs.childrenResolved
+ case other => other.resolved
+ }
+ if (!resolved) {
+ None
+ } else {
+ val groups = exprs.flatMap {
+ case gs: BaseGroupingSets => gs.groupByExprs
+ case other: Expression => other :: Nil
+ }
+ val unmergedSelectedGroupByExprs = exprs.map {
+ case gs: BaseGroupingSets => gs.selectedGroupByExprs
+ case other: Expression => Seq(Seq(other))
+ }
+ val selectedGroupByExprs = unmergedSelectedGroupByExprs.init
+ .foldLeft(unmergedSelectedGroupByExprs.last) { (x, y) =>
Review comment:
Done
##########
File path: docs/sql-ref-syntax-qry-select-groupby.md
##########
@@ -24,7 +24,9 @@ license: |
The `GROUP BY` clause is used to group the rows based on a set of specified
grouping expressions and compute aggregations on
the group of rows based on one or more specified aggregate functions. Spark
also supports advanced aggregations to do multiple
aggregations for the same input record set via `GROUPING SETS`, `CUBE`,
`ROLLUP` clauses.
-When a FILTER clause is attached to an aggregate function, only the matching
rows are passed to that function.
+The grouping expressions and advanced aggregations can be mixed in the `GROUP
BY` clause.
+See more details in the `Mixed Grouping Analytics` section. When a FILTER
clause is attached to
+an aggregate function, only the matching.
Review comment:
Done
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