[GitHub] flink pull request #3646: [FLINK-6216] [table] DataStream unbounded groupby ...

[fhueske <gi...@git.apache.org>]

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

    https://github.com/apache/flink/pull/3646#discussion_r110041174
  
    --- Diff: flink-libraries/flink-table/src/test/scala/org/apache/flink/table/api/scala/stream/sql/WindowAggregateTest.scala ---
    @@ -299,27 +299,6 @@ class WindowAggregateTest extends TableTestBase {
       }
     
       @Test
    -  def testGroupWithFloorExpression() = {
    -    val sql = "SELECT COUNT(*) FROM MyTable GROUP BY FLOOR(localTimestamp TO HOUR)"
    --- End diff --
    
    I think we need to discuss with the community how to distinguish non-windowed and windowed group aggregates. At the moment `GROUP BY FLOOR(rowtime() TO HOUR)` is translated into a tumbling event time window. By adding support for non-windows aggregates, it could also be executed as a such, i.e., with early firing and late update instead of a final result when the window is closed. The final result should be the same, but the behavior during execution would be different.
    
    I think a good approach would be to only translate group window functions (TUMBLE, HOP, SESSION) into group windows and treat everything else as non-windowed aggregation. 
    We should move this discussion to the mailing list though. I don't think we have to wait for a decision for this issue to continue.


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