Github user fhueske commented on a diff in the pull request:
https://github.com/apache/flink/pull/3266#discussion_r101014879
--- Diff:
flink-libraries/flink-table/src/main/scala/org/apache/flink/table/plan/nodes/dataset/DataSetWindowAggregate.scala
---
@@ -294,18 +319,29 @@ class DataSetWindowAggregate(
namedProperties)
mappedInput.groupBy(groupingKeys: _*)
- .sortGroup(rowTimeFieldPos, Order.ASCENDING)
- .reduceGroup(groupReduceFunction)
- .returns(rowTypeInfo)
- .name(aggregateOperatorName)
- .asInstanceOf[DataSet[Any]]
+ .sortGroup(rowTimeFieldPos, Order.ASCENDING)
+ .reduceGroup(groupReduceFunction)
+ .returns(rowTypeInfo)
+ .name(aggregateOperatorName)
+ .asInstanceOf[DataSet[Any]]
+
+ } else {
+ // non-grouping window
+ val mapPartitionFunction =
createDataSetWindowAggregationMapPartitionFunction(
+ window,
+ namedAggregates,
+ inputType,
+ rowRelDataType,
+ namedProperties,
+ isPreMapPartition = false)
+
+ mappedInput.sortPartition(rowTimeFieldPos,
Order.ASCENDING).setParallelism(1)
+ .mapPartition(mapPartitionFunction).setParallelism(1)
--- End diff --
I think we can also use `.reduceGroup()` and a `GroupReduceFunction` here.
Without `groupBy`, the `GroupReduceFunction` will be executed with parallelism
1.
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