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https://issues.apache.org/jira/browse/FLINK-5990?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15938642#comment-15938642
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ASF GitHub Bot commented on FLINK-5990:
---------------------------------------

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

    https://github.com/apache/flink/pull/3585#discussion_r107706443
  
    --- Diff: 
flink-libraries/flink-table/src/test/scala/org/apache/flink/table/api/scala/stream/sql/SqlITCase.scala
 ---
    @@ -293,6 +297,82 @@ class SqlITCase extends StreamingWithStateTestBase {
         assertEquals(expected.sorted, StreamITCase.testResults.sorted)
       }
     
    +  @Test
    +  def testBoundPartitionedEventTimeWindowWithRow(): Unit = {
    +    val env = StreamExecutionEnvironment.getExecutionEnvironment
    +    env.setStreamTimeCharacteristic(TimeCharacteristic.EventTime)
    +    env.setStateBackend(getStateBackend)
    +    val tEnv = TableEnvironment.getTableEnvironment(env)
    +    StreamITCase.clear
    +
    +    val t1 = env.fromCollection(data)
    +      .assignTimestampsAndWatermarks(new TimestampWithLatenessWatermark(0))
    --- End diff --
    
    I would suggest to implement a utility `SourceFunction` similar to the ones 
which are defined inline in PR #3386.
    The `SourceFunction` could have a `Seq[Either[(Long, Tuple), Long]]` as 
input, i.e., either tuples with timestamp or a watermark timestamp. 
    
    This would be useful for many more event-time tests.


> Add [partitioned] event time OVER ROWS BETWEEN x PRECEDING aggregation to SQL
> -----------------------------------------------------------------------------
>
>                 Key: FLINK-5990
>                 URL: https://issues.apache.org/jira/browse/FLINK-5990
>             Project: Flink
>          Issue Type: Sub-task
>          Components: Table API & SQL
>            Reporter: sunjincheng
>            Assignee: sunjincheng
>
> The goal of this issue is to add support for OVER ROWS aggregations on event 
> 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 rowTime() ROWS BETWEEN 2 PRECEDING AND 
> CURRENT ROW) AS sumB,
>   MIN(b) OVER (PARTITION BY c ORDER BY rowTime() 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 required
> - The ORDER BY clause may only have rowTime() as parameter. rowTime() is a 
> parameterless scalar function that just indicates event time mode.
> - UNBOUNDED PRECEDING is not supported (see FLINK-5803)
> - 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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