Github user fhueske commented on a diff in the pull request: https://github.com/apache/flink/pull/3585#discussion_r107866801 --- Diff: flink-libraries/flink-table/src/main/scala/org/apache/flink/table/plan/nodes/datastream/DataStreamOverAggregate.scala --- @@ -130,32 +169,76 @@ class DataStreamOverAggregate( val rowTypeInfo = FlinkTypeFactory.toInternalRowTypeInfo(getRowType).asInstanceOf[RowTypeInfo] val result: DataStream[Row] = - // partitioned aggregation - if (partitionKeys.nonEmpty) { - val processFunction = AggregateUtil.CreateUnboundedProcessingOverProcessFunction( - namedAggregates, - inputType) + // partitioned aggregation + if (partitionKeys.nonEmpty) { + val processFunction = AggregateUtil.createUnboundedProcessingOverProcessFunction( + namedAggregates, + inputType) - inputDS + inputDS .keyBy(partitionKeys: _*) .process(processFunction) .returns(rowTypeInfo) .name(aggOpName) .asInstanceOf[DataStream[Row]] - } - // non-partitioned aggregation - else { - val processFunction = AggregateUtil.CreateUnboundedProcessingOverProcessFunction( - namedAggregates, - inputType, - false) - - inputDS - .process(processFunction).setParallelism(1).setMaxParallelism(1) + } + // non-partitioned aggregation + else { + val processFunction = AggregateUtil.createUnboundedProcessingOverProcessFunction( + namedAggregates, + inputType, + false) + + inputDS + .process(processFunction).setParallelism(1).setMaxParallelism(1) + .returns(rowTypeInfo) + .name(aggOpName) + .asInstanceOf[DataStream[Row]] + } + result + } + + def createRowsClauseBoundedAndCurrentRowOverWindow( + inputDS: DataStream[Row], + isRowTimeType: Boolean = false): DataStream[Row] = { + + val overWindow: Group = logicWindow.groups.get(0) + val partitionKeys: Array[Int] = overWindow.keys.toArray + val namedAggregates: Seq[CalcitePair[AggregateCall, String]] = generateNamedAggregates + val inputFields = (0 until inputType.getFieldCount).toArray + + val precedingOffset = + getLowerBoundary(logicWindow, overWindow, getInput()) + 1 + + // get the output types + val rowTypeInfo = FlinkTypeFactory.toInternalRowTypeInfo(getRowType).asInstanceOf[RowTypeInfo] + + val processFunction = AggregateUtil.createRowsClauseBoundedOverProcessFunction( + namedAggregates, + inputType, + inputFields, + precedingOffset, + isRowTimeType + ) + val result: DataStream[Row] = + // partitioned aggregation + if (partitionKeys.nonEmpty) { + inputDS + .keyBy(partitionKeys: _*) + .process(processFunction) .returns(rowTypeInfo) .name(aggOpName) .asInstanceOf[DataStream[Row]] - } + } + // non-partitioned aggregation + else { + inputDS + .keyBy(new NullByteKeySelector[Row]) + .process(processFunction) --- End diff -- `setParallelism()` and `setMaxParallelism()`
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