cloud-fan commented on a change in pull request #26509: [SPARK-29427][SQL] Add
API to convert RelationalGroupedDataset to KeyValueGroupedDataset
URL: https://github.com/apache/spark/pull/26509#discussion_r347716019
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File path:
sql/core/src/main/scala/org/apache/spark/sql/RelationalGroupedDataset.scala
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@@ -129,6 +132,32 @@ class RelationalGroupedDataset protected[sql](
(inputExpr: Expression) => exprToFunc(inputExpr)
}
+ /**
+ * Returns a `KeyValueGroupedDataset` where the data is grouped by the
grouping expressions
+ * of current `RelationalGroupedDataset`.
+ *
+ * @since 3.0.0
+ */
+ def keyAs[U : Encoder]: KeyValueGroupedDataset[U, T] = {
+ val keyEncoder = encoderFor[U]
+ val aliasedGrps = groupingExprs.map { g =>
+ g.transformDown {
+ case u: UnresolvedAttribute => df.resolve(u.name)
+ }
+ }.map(alias)
+ val additionalCols = aliasedGrps.filter(g =>
!df.logicalPlan.outputSet.contains(g.toAttribute))
+ val qe = Dataset.ofRows(
+ df.sparkSession,
+ Project(df.logicalPlan.output ++ additionalCols,
df.logicalPlan)).queryExecution
Review comment:
We can make `MapGroupsExec` follow aggregate, to calculate grouping columns
ahead and put it in the buffer row, then run key/value deserializer on buffer
row.
But I admit that it's a big change, we can do it in the future.
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