Hi and thank you for this thread, I'm also experimenting the same valid bug/limitation when connecting streams.
I had a quick look in the annoucments but couldn't find any more information: Would it be planned to propagate the Idle stream status to the operator in the upcoming Flink minor versions/releases? If not, would there be a way around it other than emitting beats in the idle stream? Best, Pierre Aljoscha Krettek wrote > I can only agree with Dawid, who explained it better than me... 😅 > > Aljoscha > > On 31.08.20 12:10, Dawid Wysakowicz wrote: >> Hey Arvid, >> >> The problem is that the StreamStatus.IDLE is set on the Task level. It >> is not propagated to the operator. Combining of the Watermark for a >> TwoInputStreamOperator happens in the AbstractStreamOperator: >> >>    public void processWatermark(Watermark mark) throws Exception { >>       if (timeServiceManager != null) { >>          timeServiceManager.advanceWatermark(mark); >>       } >>       output.emitWatermark(mark); >>    } >> >>    public void processWatermark1(Watermark mark) throws Exception { >>       input1Watermark = mark.getTimestamp(); >>       long newMin = Math.min(input1Watermark, input2Watermark); >>       if (newMin > combinedWatermark) { >>          combinedWatermark = newMin; >>          processWatermark(new Watermark(combinedWatermark)); >>       } >>    } >> >>    public void processWatermark2(Watermark mark) throws Exception { >>       input2Watermark = mark.getTimestamp(); >>       long newMin = Math.min(input1Watermark, input2Watermark); >>       if (newMin > combinedWatermark) { >>          combinedWatermark = newMin; >>          processWatermark(new Watermark(combinedWatermark)); >>       } >>    } >> >> There we do not know that e.g. the whole input 1 is idle. Therefore if >> we do not receive any Watermarks from it (it became IDLE) we do not >> progress the Watermark starting from any two input operator. We are >> missing similar handling of the IDLE status from the task level which >> works well for one input operators and multiple parallel upstream >> instances. >> >> Best, >> >> Dawid >> >> -- Sent from: http://apache-flink-user-mailing-list-archive.2336050.n4.nabble.com/