Github user fhueske commented on a diff in the pull request:

    https://github.com/apache/flink/pull/3547#discussion_r106519460
  
    --- Diff: 
flink-libraries/flink-table/src/main/scala/org/apache/flink/table/plan/nodes/datastream/DataStreamOverAggregate.scala
 ---
    @@ -130,32 +142,77 @@ 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)
    -            .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)
    +          .returns(rowTypeInfo)
    +          .name(aggOpName)
    +          .asInstanceOf[DataStream[Row]]
    +      }
    +    result
    +  }
    +
    +  def createBoundedAndCurrentRowProcessingTimeOverWindow(
    +    inputDS: DataStream[Row]): DataStream[Row] = {
    +
    +    val overWindow: Group = logicWindow.groups.get(0)
    +    val partitionKeys: Array[Int] = overWindow.keys.toArray
    +    val namedAggregates: Seq[CalcitePair[AggregateCall, String]] = 
generateNamedAggregates
    +
    +    // get the output types
    +    val rowTypeInfo = 
FlinkTypeFactory.toInternalRowTypeInfo(getRowType).asInstanceOf[RowTypeInfo]
    +
    +    // window size is lowerbound +1 to comply with over semantics 
    +    val lowerbound: Int = AggregateUtil.getLowerBoundary(
    +      logicWindow.constants,
    +      overWindow.lowerBound,
    +      getInput()) + 1
    +
    +    val result: DataStream[Row] =
    +      // partitioned aggregation
    +      if (partitionKeys.nonEmpty) {
    +        val windowFunction = 
AggregateUtil.CreateBoundedProcessingOverWindowFunction(
    +          namedAggregates,
    +          inputType)
    +        inputDS
    +          .keyBy(partitionKeys: _*)
    +          .countWindow(lowerbound,1) 
    +          .apply(windowFunction)
    +          .returns(rowTypeInfo)
    +          .name(aggOpName)
    +          .asInstanceOf[DataStream[Row]]
    +      } // global non-partitioned aggregation
    +      else {
    +        val windowFunction = 
AggregateUtil.CreateBoundedProcessingOverGlobalWindowFunction(
    +          namedAggregates,
    +          inputType)
    +
    +        inputDS
    +          .countWindowAll(lowerbound,1)
    +          .apply(windowFunction)
    +          .setParallelism(1).setMaxParallelism(1)
    --- End diff --
    
    Parallelism 1 is already implied by `countWindowAll`


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