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Yun Gao commented on FLINK-22587: --------------------------------- Hi, sorry for forgetting to update here, with some more try we found that it works to use an event-time window that assigns all the records to the same window [0, +Inf):[https://github.com/apache/flink-ml/blob/master/flink-ml-core/src/main/java/org/apache/flink/ml/common/datastream/EndOfStreamWindows.java] And the join works with source1.join(source2) .where(a -> a.f0) .equalTo(b -> b.f0) .window(new EndOfStreamWindows()) .apply(xx) for both bounded streaming processing and batch processing. It does not require the records to have event-time and watermark, since the assignment does not rely on event-time, and the window will be triggered by the Long.MAX_VALUE inserted at the end of stream. But we'll still try to propose a proper fix for this issue. One option is that we does not force to set a window in this case, if the window is not set, we'll by default mark it all the records. > Support aggregations in batch mode with DataStream API > ------------------------------------------------------ > > Key: FLINK-22587 > URL: https://issues.apache.org/jira/browse/FLINK-22587 > Project: Flink > Issue Type: Bug > Components: API / DataStream > Affects Versions: 1.12.0, 1.13.0 > Reporter: Etienne Chauchot > Priority: Major > > A pipeline like this *in batch mode* would output no data > {code:java} > stream.join(otherStream) > .where(<KeySelector>) > .equalTo(<KeySelector>) > .window(GlobalWindows.create()) > .apply(<JoinFunction>) > {code} > Indeed the default trigger for GlobalWindow is NeverTrigger which never > fires. If we set a _EventTimeTrigger_ it will fire with every element as the > watermark will be set to +INF (batch mode) and will pass the end of the > global window with each new element. A _ProcessingTimeTrigger_ never fires > either and all elapsed time or delta based triggers would not be suited for > batch. > Same goes for _reduce()_ instead of join(). > So I guess we miss something for batch support with DataStream. -- This message was sent by Atlassian Jira (v8.20.10#820010)