[
https://issues.apache.org/jira/browse/FLINK-4937?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15661167#comment-15661167
]
ASF GitHub Bot commented on FLINK-4937:
---------------------------------------
Github user wuchong commented on a diff in the pull request:
https://github.com/apache/flink/pull/2792#discussion_r87708469
--- Diff:
flink-libraries/flink-table/src/main/scala/org/apache/flink/api/table/runtime/aggregate/AggregateUtil.scala
---
@@ -61,25 +61,108 @@ object AggregateUtil {
* }}}
*
*/
- def createOperatorFunctionsForAggregates(
+ def createOperatorFunctionsForAggregates(
--- End diff --
It is a little confused that what's the difference between these two
`createOperatorFunctionsForAggregates` .
Could we remove the first one, and call `transformToAggregateFunctions`
explicitly before `createOperatorFunctionsForAggregates` in DataSetAggregate ?
> Add incremental group window aggregation for streaming Table API
> ----------------------------------------------------------------
>
> Key: FLINK-4937
> URL: https://issues.apache.org/jira/browse/FLINK-4937
> Project: Flink
> Issue Type: Sub-task
> Components: Table API & SQL
> Affects Versions: 1.2.0
> Reporter: Fabian Hueske
> Assignee: sunjincheng
>
> Group-window aggregates for streaming tables are currently not done in an
> incremental fashion. This means that the window collects all records and
> performs the aggregation when the window is closed instead of eagerly
> updating a partial aggregate for every added record. Since records are
> buffered, non-incremental aggregation requires more storage space than
> incremental aggregation.
> The DataStream API which is used under the hood of the streaming Table API
> features [incremental
> aggregation|https://ci.apache.org/projects/flink/flink-docs-release-1.2/dev/windows.html#windowfunction-with-incremental-aggregation]
> using a {{ReduceFunction}}.
> We should add support for incremental aggregation in group-windows.
> This is a follow-up task of FLINK-4691.
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
