flink-issues mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (FLINK-5653) Add processing time OVER ROWS BETWEEN x PRECEDING aggregation to SQL
Date Thu, 16 Mar 2017 05:48:41 GMT

    [ https://issues.apache.org/jira/browse/FLINK-5653?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15927536#comment-15927536
] 

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

Github user sunjincheng121 commented on a diff in the pull request:

    https://github.com/apache/flink/pull/3547#discussion_r106343179
  
    --- Diff: flink-libraries/flink-table/src/main/scala/org/apache/flink/table/plan/nodes/datastream/DataStreamOverAggregate.scala
---
    @@ -130,32 +142,76 @@ 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)
    -            .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]
    +
    +    val lowerbound: Int = AggregateUtil.getLowerBoundary(
    +      logicWindow.constants,
    +      overWindow.lowerBound,
    +      getInput())
    +
    +    val result: DataStream[Row] =
    +      // partitioned aggregation
    +      if (partitionKeys.nonEmpty) {
    +        val windowFunction = AggregateUtil.CreateBoundedProcessingOverWindowFunction(
    +          namedAggregates,
    +          inputType)
    +        inputDS
    +          .keyBy(partitionKeys: _*)
    +          .countWindow(lowerbound,1)
    --- End diff --
    
    `lowerbound -> (lowerbound+1)`


> 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).



--
This message was sent by Atlassian JIRA
(v6.3.15#6346)

Mime
View raw message