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https://issues.apache.org/jira/browse/FLINK-7208?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16709707#comment-16709707
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ASF GitHub Bot commented on FLINK-7208:
---------------------------------------

twalthr commented on a change in pull request #7201: [FLINK-7208] [table] 
Optimize Min/MaxWithRetractAggFunction with DataView
URL: https://github.com/apache/flink/pull/7201#discussion_r238959968
 
 

 ##########
 File path: 
flink-libraries/flink-table/src/test/scala/org/apache/flink/table/runtime/stream/table/AggregateITCase.scala
 ##########
 @@ -203,13 +203,13 @@ class AggregateITCase extends StreamingWithStateTestBase 
{
       .groupBy('b)
       .select('a.count as 'cnt, 'b)
       .groupBy('cnt)
-      .select('cnt, 'b.count as 'freq)
+      .select('cnt, 'b.count as 'freq, 'b.min as 'min, 'b.max as 'max)
 
     val results = t.toRetractStream[Row](queryConfig)
 
     results.addSink(new RetractingSink)
     env.execute()
-    val expected = List("1,1", "2,1", "3,1", "4,1", "5,1", "6,1")
+    val expected = List("1,1,1,1", "2,1,2,2", "3,1,3,3", "4,1,4,4", "5,1,5,5", 
"6,1,6,6")
 
 Review comment:
   Yes we can also do this in another PR. In general we definitely need more 
harness tests. For example, FLINK-10674 could have never been found without 
proper unit tests. It was luck that the distinct accumulator threw a 
NullPointerException.

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> Refactor build-in agg(MaxWithRetractAccumulator and 
> MinWithRetractAccumulator) using the DataView
> -------------------------------------------------------------------------------------------------
>
>                 Key: FLINK-7208
>                 URL: https://issues.apache.org/jira/browse/FLINK-7208
>             Project: Flink
>          Issue Type: Sub-task
>          Components: Table API & SQL
>            Reporter: kaibo.zhou
>            Assignee: Dian Fu
>            Priority: Major
>              Labels: pull-request-available
>
> Refactor build-in agg(MaxWithRetractAccumulator and 
> MinWithRetractAccumulator) using the DataView.



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