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ASF GitHub Bot commented on FLINK-5655: --------------------------------------- Github user fhueske commented on a diff in the pull request: https://github.com/apache/flink/pull/3629#discussion_r108470691 --- Diff: flink-libraries/flink-table/src/test/scala/org/apache/flink/table/api/scala/stream/sql/SqlITCase.scala --- @@ -411,6 +411,128 @@ class SqlITCase extends StreamingWithStateTestBase { assertEquals(expected.sorted, StreamITCase.testResults.sorted) } + @Test + def testBoundPartitionedEventTimeWindowWithRange(): Unit = { + val data = Seq( --- End diff -- I think a bit more diverse test data would be good to cover more corner cases. Basically check that each loop is correctly triggered (retract data of two (or more timestamps), emit different rows in one timestamp, etc. > Add event time OVER RANGE BETWEEN x PRECEDING aggregation to SQL > ---------------------------------------------------------------- > > Key: FLINK-5655 > URL: https://issues.apache.org/jira/browse/FLINK-5655 > Project: Flink > Issue Type: Sub-task > Components: Table API & SQL > Reporter: Fabian Hueske > Assignee: sunjincheng > > The goal of this issue is to add support for OVER RANGE 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() RANGE BETWEEN INTERVAL '1' > HOUR PRECEDING AND CURRENT ROW) AS sumB, > MIN(b) OVER (PARTITION BY c ORDER BY rowTime() RANGE BETWEEN INTERVAL '1' > HOUR 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 rowTime() as parameter. rowTime() is a > parameterless scalar function that just indicates processing time mode. > - UNBOUNDED PRECEDING is not supported (see FLINK-5658) > - 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)