[
https://issues.apache.org/jira/browse/FLINK-5990?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15939914#comment-15939914
]
ASF GitHub Bot commented on FLINK-5990:
---------------------------------------
Github user sunjincheng121 commented on a diff in the pull request:
https://github.com/apache/flink/pull/3585#discussion_r107842352
--- Diff:
flink-libraries/flink-table/src/main/scala/org/apache/flink/table/plan/nodes/datastream/DataStreamOverAggregate.scala
---
@@ -99,28 +100,64 @@ class DataStreamOverAggregate(
.getFieldList
.get(overWindow.orderKeys.getFieldCollations.get(0).getFieldIndex)
.getValue
-
timeType match {
case _: ProcTimeType =>
- // both ROWS and RANGE clause with UNBOUNDED PRECEDING and CURRENT
ROW condition.
- if (overWindow.lowerBound.isUnbounded &&
- overWindow.upperBound.isCurrentRow) {
+ // proc-time OVER window
+ if (overWindow.lowerBound.isUnbounded &&
overWindow.upperBound.isCurrentRow) {
+ // non-bounded OVER window
createUnboundedAndCurrentRowProcessingTimeOverWindow(inputDS)
+ } else if (
+ overWindow.lowerBound.isPreceding &&
!overWindow.lowerBound.isUnbounded &&
+ overWindow.upperBound.isCurrentRow) {
+ // bounded OVER window
+ if (overWindow.isRows) {
+ // ROWS clause bounded OVER window
+ createRowsClauseBoundedAndCurrentRowOverWindow(inputDS)
+ } else {
+ // RANGE clause bounded OVER window
+ throw new TableException(
+ "RANGE clause bounded proc-time OVER window no supported
yet.")
+ }
} else {
throw new TableException(
- "OVER window only support ProcessingTime UNBOUNDED PRECEDING
and CURRENT ROW " +
- "condition.")
+ "proc-time OVER window only support CURRENT ROW condition.")
}
case _: RowTimeType =>
- throw new TableException("OVER Window of the EventTime type is not
currently supported.")
+ // row-time OVER window
+ if (overWindow.lowerBound.isUnbounded &&
overWindow.upperBound.isCurrentRow) {
+ // non-bounded OVER window
+ if (overWindow.isRows) {
--- End diff --
No, row-time OVER rows / range have different semantics. I think this does
not affect the current JIRA. feature. Can I explain it in FLINK-5658 later
today?
> 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).
--
This message was sent by Atlassian JIRA
(v6.3.15#6346)
