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From rtudoran <...@git.apache.org>
Subject [GitHub] flink pull request #3590: [FLINK-5654] - Add processing time OVER RANGE BETW...
Date Wed, 22 Mar 2017 12:33:05 GMT
Github user rtudoran commented on a diff in the pull request:

    https://github.com/apache/flink/pull/3590#discussion_r107401146
  
    --- Diff: flink-libraries/flink-table/src/main/scala/org/apache/flink/table/plan/nodes/datastream/DataStreamOverAggregate.scala
---
    @@ -119,6 +150,57 @@ class DataStreamOverAggregate(
     
       }
     
    +  def createTimeBoundedProcessingTimeOverWindow(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
    +
    +    val index = overWindow.lowerBound.getOffset.asInstanceOf[RexInputRef].getIndex
    +    val count = input.getRowType().getFieldCount()
    +    val lowerboundIndex = index - count
    +    
    +    
    +    val time_boundary = logicWindow.constants.get(lowerboundIndex).getValue2 match {
    +      case _: java.math.BigDecimal => logicWindow.constants.get(lowerboundIndex)
    +         .getValue2.asInstanceOf[java.math.BigDecimal].longValue()
    +      case _ => throw new TableException("OVER Window boundaries must be numeric")
    +    }
    +
    +     // get the output types
    +    val rowTypeInfo = FlinkTypeFactory.toInternalRowTypeInfo(getRowType).asInstanceOf[RowTypeInfo]
    +         
    +    val result: DataStream[Row] =
    +        // partitioned aggregation
    +        if (partitionKeys.nonEmpty) {
    +          
    +          val processFunction = AggregateUtil.CreateTimeBoundedProcessingOverProcessFunction(
    +            namedAggregates,
    +            inputType,
    +            time_boundary)
    +          
    +          inputDS
    +          .keyBy(partitionKeys: _*)
    +          .process(processFunction)
    +          .returns(rowTypeInfo)
    +          .name(aggOpName)
    +          .asInstanceOf[DataStream[Row]]
    +        } else { // non-partitioned aggregation
    +          val processFunction = AggregateUtil.CreateTimeBoundedProcessingOverProcessFunction(
    --- End diff --
    
    @fhueske - i would be fine with me to do that. However when we discussed this issue on
the initial design and i proposed this solution for the JIRA,  you said that is not worth
consuming extra resources  - and i agree with this ( it is work paying the price of having
2 function at compiling time to get less resource usage...IMHO)
    Also - if you look on what is in the code base for unbound window it is the same - shouldn't
we have the same?
    @sunjincheng121 


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