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Date: Mon, 20 Mar 2017 20:15:42 +0000 (UTC)
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Subject: [jira] [Commented] (FLINK-5653) Add processing time OVER ROWS
 BETWEEN x PRECEDING aggregation to SQL
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archived-at: Mon, 20 Mar 2017 20:15:49 -0000


    [ https://issues.apache.org/jira/browse/FLINK-5653?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15933453#comment-15933453 ] 

ASF GitHub Bot commented on FLINK-5653:
---------------------------------------

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

    https://github.com/apache/flink/pull/3574#discussion_r106963715
  
    --- Diff: flink-libraries/flink-table/src/main/scala/org/apache/flink/table/plan/nodes/datastream/DataStreamOverAggregate.scala ---
    @@ -150,12 +160,71 @@ class DataStreamOverAggregate(
                 inputType,
                 false)
     
    -          inputDS
    -            .process(processFunction).setParallelism(1).setMaxParallelism(1)
    -            .returns(rowTypeInfo)
    -            .name(aggOpName)
    -            .asInstanceOf[DataStream[Row]]
    -        }
    +        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 (aggFunction, accumulatorRowType, aggResultRowType) =
    --- End diff --
    
    `aggResultRowType` and `rowTypeInfo` should be the same. Please add a safety check for this.


> Add processing time OVER ROWS BETWEEN x PRECEDING aggregation to SQL
> --------------------------------------------------------------------
>
>                 Key: FLINK-5653
>                 URL: https://issues.apache.org/jira/browse/FLINK-5653
>             Project: Flink
>          Issue Type: Sub-task
>          Components: Table API & SQL
>            Reporter: Fabian Hueske
>            Assignee: Stefano Bortoli
>
> The goal of this issue is to add support for OVER ROWS aggregations on processing time streams to the SQL interface.
> Queries similar to the following should be supported:
> {code}
> SELECT 
>   a, 
>   SUM(b) OVER (PARTITION BY c ORDER BY procTime() ROWS BETWEEN 2 PRECEDING AND CURRENT ROW) AS sumB,
>   MIN(b) OVER (PARTITION BY c ORDER BY procTime() ROWS BETWEEN 2 PRECEDING AND CURRENT ROW) AS minB
> FROM myStream
> {code}
> The following restrictions should initially apply:
> - All OVER clauses in the same SELECT clause must be exactly the same.
> - The PARTITION BY clause is optional (no partitioning results in single threaded execution).
> - The ORDER BY clause may only have procTime() as parameter. procTime() is a parameterless scalar function that just indicates processing time mode.
> - UNBOUNDED PRECEDING is not supported (see FLINK-5656)
> - FOLLOWING is not supported.
> The restrictions will be resolved in follow up issues. If we find that some of the restrictions are trivial to address, we can add the functionality in this issue as well.
> This issue includes:
> - Design of the DataStream operator to compute OVER ROW aggregates
> - Translation from Calcite's RelNode representation (LogicalProject with RexOver expression).


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