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https://issues.apache.org/jira/browse/FLINK-8689?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16449240#comment-16449240
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ASF GitHub Bot commented on FLINK-8689:
---------------------------------------

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

    https://github.com/apache/flink/pull/5555#discussion_r183222267
  
    --- Diff: 
flink-libraries/flink-table/src/main/scala/org/apache/flink/table/codegen/AggregationCodeGenerator.scala
 ---
    @@ -151,8 +157,15 @@ class AggregationCodeGenerator(
           }
         }
     
    -    // initialize and create data views
    -    addReusableDataViews()
    +    // get distinct filter of acc fields for each aggregate functions
    +    val distinctAccType = s"${classOf[DistinctAccumulator[_, _]].getName}"
    +    val isDistinctAggs = distinctAggs.map(_.nonEmpty)
    --- End diff --
    
    Hmm I tried to generate MapViewSpec in codegen but 
`AggregationCodeGenerator.generateAggregations` call signature seems to miss 
the typeinfo for accumulator (`accTypes` only shows the accumulator type, not 
the `PojoField` info). 
    
    I can certainly changed to a more simple: `DistinctAccumulator[Object, 
Long]` but I think there's pros and cons, also making a `MapTypeInfo` for plain 
`Object` seems funny to me. How about we leave it to the future optimization.


> Add runtime support of distinct filter using MapView 
> -----------------------------------------------------
>
>                 Key: FLINK-8689
>                 URL: https://issues.apache.org/jira/browse/FLINK-8689
>             Project: Flink
>          Issue Type: Sub-task
>            Reporter: Rong Rong
>            Assignee: Rong Rong
>            Priority: Major
>
> This ticket should cover distinct aggregate function support to codegen for 
> *AggregateCall*, where *isDistinct* fields is set to true.
> This can be verified using the following SQL, which is not currently 
> producing correct results.
> {code:java}
> SELECT
>   a,
>   SUM(b) OVER (PARTITION BY a ORDER BY proctime ROWS BETWEEN 5 PRECEDING AND 
> CURRENT ROW)
> FROM
>   MyTable{code}
>  
>  



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