hvanhovell commented on code in PR #40129:
URL: https://github.com/apache/spark/pull/40129#discussion_r1115162635
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connector/connect/client/jvm/src/main/scala/org/apache/spark/sql/RelationalGroupedDataset.scala:
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@@ -37,16 +37,25 @@ import org.apache.spark.connect.proto
*/
class RelationalGroupedDataset protected[sql] (
private[sql] val df: DataFrame,
- private[sql] val groupingExprs: Seq[proto.Expression]) {
+ private[sql] val groupingExprs: Seq[proto.Expression],
+ groupType: RelationalGroupedDataset.GroupType) {
private[this] def toDF(aggExprs: Seq[Column]): DataFrame = {
- // TODO: support other GroupByType such as Rollup, Cube, Pivot.
df.session.newDataset { builder =>
builder.getAggregateBuilder
- .setGroupType(proto.Aggregate.GroupType.GROUP_TYPE_GROUPBY)
.setInput(df.plan.getRoot)
.addAllGroupingExpressions(groupingExprs.asJava)
.addAllAggregateExpressions(aggExprs.map(e => e.expr).asJava)
+
+ // TODO: support Pivot.
+ groupType match {
+ case RelationalGroupedDataset.RollupType =>
+
builder.getAggregateBuilder.setGroupType(proto.Aggregate.GroupType.GROUP_TYPE_ROLLUP)
+ case RelationalGroupedDataset.CubeType =>
+
builder.getAggregateBuilder.setGroupType(proto.Aggregate.GroupType.GROUP_TYPE_CUBE)
+ case _ =>
Review Comment:
A bit of an OCD point. Please match the actual case instead of assuming
nothing else is possible.
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