Hi again everyone, It’s been a while, so first of all happy new year :)
I was revisiting this discussion and started looking at the code. However, it seems that all of the overloads of ConnectedStreams#process expect a CoProcessFunction or the Keyed counterpart, so I don’t think I can inject a custom TwoInputStreamOperator. After a quick glance at the joining documentation, I wonder if I could accomplish what I want with a window/interval join of streams. If so, I might be able to avoid using state in the join function, but if I can’t avoid it, is it possible to use managed state in a (Process)JoinFunction? The join needs keys, but I don’t know if the resulting stream counts as keyed from the state’s point of view. Regards, Alexis. From: Piotr Nowojski <pnowoj...@apache.org> Sent: Montag, 6. Dezember 2021 08:43 To: David Morávek <d...@apache.org> Cc: Alexis Sarda-Espinosa <alexis.sarda-espin...@microfocus.com>; user@flink.apache.org Subject: Re: Buffering when connecting streams Hi Alexis and David, This actually can not happen. There are mechanisms in the code to make sure none of the input is starved IF there is some data to be read. The only time when input can be blocked is during the alignment phase of aligned checkpoints under back pressure. If there was a back pressure in your job it could have easily happened that checkpoint barriers would flow through the job graph to the CoProcessKeyedCoProcessFunction on one of the paths much quicker then the other, causing this faster path to be blocked until the other side catched up. But that would happen only during the alignment phase of the checkpoint, so without a backpressure for a very short period of time. Piotrek czw., 2 gru 2021 o 18:23 David Morávek <d...@apache.org<mailto:d...@apache.org>> napisał(a): I think this could happen, but I have a very limited knowledge about how the input gates work internally. @Piotr could definitely provide some more insight here. D. On Thu, Dec 2, 2021 at 5:54 PM Alexis Sarda-Espinosa <alexis.sarda-espin...@microfocus.com<mailto:alexis.sarda-espin...@microfocus.com>> wrote: I do have some logic with timers today, but it’s indeed not ideal. I guess I’ll have a look at TwoInputStreamOperator, but I do have related questions. You mentioned a sample scenario of "processing backlog" where windows fire very quickly; could it happen that, in such a situation, the framework calls the operator’s processElement1 continuously (even for several minutes) before calling processElement2 a single time? How does the framework decide when to switch the stream processing when the streams are connected? Regards, Alexis. From: David Morávek <d...@apache.org<mailto:d...@apache.org>> Sent: Donnerstag, 2. Dezember 2021 17:18 To: Alexis Sarda-Espinosa <alexis.sarda-espin...@microfocus.com<mailto:alexis.sarda-espin...@microfocus.com>> Cc: user@flink.apache.org<mailto:user@flink.apache.org> Subject: Re: Buffering when connecting streams Even with the TwoInputStreamOperator you can not "halt" the processing. You need to buffer these elements for example in the ListState for later processing. At the time the watermark of the second stream arrives, you can process all buffered elements that satisfy the condition. You could probably also implement a similar (less optimized) solution with KeyedCoProcessFunction using event time timers. Best, D. On Thu, Dec 2, 2021 at 5:12 PM Alexis Sarda-Espinosa <alexis.sarda-espin...@microfocus.com<mailto:alexis.sarda-espin...@microfocus.com>> wrote: Yes, that sounds right, but with my current KeyedCoProcessFunction I can’t tell Flink to "halt" processElement1 and switch to the other stream depending on watermarks. I could look into TwoInputStreamOperator if you think that’s the best approach. Regards, Alexis. From: David Morávek <d...@apache.org<mailto:d...@apache.org>> Sent: Donnerstag, 2. Dezember 2021 16:59 To: Alexis Sarda-Espinosa <alexis.sarda-espin...@microfocus.com<mailto:alexis.sarda-espin...@microfocus.com>> Cc: user@flink.apache.org<mailto:user@flink.apache.org> Subject: Re: Buffering when connecting streams I think this would require using lower level API and implementing a custom `TwoInputStreamOperator`. Then you can hook to `processWatemark{1,2}` methods. Let's also make sure we're on the same page on what the watermark is. You can think of the watermark as event time clock. It basically gives you an information, that no more events with timestamp lower than the watermark should appear in your stream. You simply delay emitting of the window result from your "connect" operator, until watermark from the second (side output) stream passes the window's max timestamp (maximum timestamp that is included in the window). Does that make sense? Best, D. On Thu, Dec 2, 2021 at 4:25 PM Alexis Sarda-Espinosa <alexis.sarda-espin...@microfocus.com<mailto:alexis.sarda-espin...@microfocus.com>> wrote: Could you elaborate on what you mean with synchronize? Buffering in the state would be fine, but I haven’t been able to come up with a good way of ensuring that all data from the side stream for a given minute is processed by processElement2 before all data for the same (windowed) minute reaches processElement1, even when considering watermarks. Regards, Alexis. From: David Morávek <d...@apache.org<mailto:d...@apache.org>> Sent: Donnerstag, 2. Dezember 2021 15:45 To: Alexis Sarda-Espinosa <alexis.sarda-espin...@microfocus.com<mailto:alexis.sarda-espin...@microfocus.com>> Cc: user@flink.apache.org<mailto:user@flink.apache.org> Subject: Re: Buffering when connecting streams You can not rely on order of the two streams that easily. In case you are for example processing backlog and the windows fire quickly, it can happen that it's actually faster than the second branch which has less work to do. This will make the pipeline non-deterministic. What you can do is to "synchronize" watermarks of both streams in your "connect" operator, but that of course involves buffering events in the state. Best, D. On Thu, Dec 2, 2021 at 3:02 PM Alexis Sarda-Espinosa <alexis.sarda-espin...@microfocus.com<mailto:alexis.sarda-espin...@microfocus.com>> wrote: Hi David, A watermark step simply refers to assigning timestamps and watermarks, my source doesn’t do that. I have a test system with only a couple of data points per day, so there’s definitely no back pressure. I basically have a browser where I can see the results from the sink, and I found one result that should have been discarded but wasn’t, which makes me think that the operator processed the "open" state but waited too long and didn’t process the "close" state before the window fired. I can also see that the closure (going from open to close) triggered on second 17, and my windows are evaluated every minute, so it wasn’t a race condition. Regards, Alexis. From: David Morávek <d...@apache.org<mailto:d...@apache.org>> Sent: Donnerstag, 2. Dezember 2021 14:52 To: Alexis Sarda-Espinosa <alexis.sarda-espin...@microfocus.com<mailto:alexis.sarda-espin...@microfocus.com>> Cc: user@flink.apache.org<mailto:user@flink.apache.org> Subject: Re: Buffering when connecting streams Hi Alexis, I'm not sure what "watermark" step refers to in you graph, but in general I'd say your intuition is correct. For the "buffering" part, each sub-task needs to send data via data exchange (last operator in chain) has an output buffer and the operator that consumes this data (maybe on different machine) has an input buffer (buffer de-bloating feature can help to mitigate excessive buffering in case of back-pressure). but I’m not sure if this actually happens How are you trying to verify this? Also can you check whether the operators are not back-pressured? Best, D. On Thu, Dec 2, 2021 at 12:27 PM Alexis Sarda-Espinosa <alexis.sarda-espin...@microfocus.com<mailto:alexis.sarda-espin...@microfocus.com>> wrote: Hello, I have a use case with event-time processing that ends up with a DAG roughly like this: source -> filter -> keyBy -> watermark -> window -> process -> keyBy_2 -> connect (KeyedCoProcessFunction) -> sink | / (side output) -> keyBy -> watermark --------------------------------/ (In case the text gets mangled in the e-mail, the side output comes from the filter and joins back with the connect operation) The filter takes all data and its main output is all _valid_ data with state "open"; the side output is all _valid_ data regardless of state. The goal of the KeyedCoProcessFunction is to check the results of the (sliding) window. The window only receives open states, but KeyedCoProcessFunction receives all valid data and should discard results from the main stream if states changed from "open" to something else before the window was evaluated. I would have expected all data from the side output to be processed roughly immediately in KeyedCoProcessFunction’s processElement2 because there’s no windowing in the side stream, but I’m not sure if this actually happens, maybe the side stream (or both streams) buffers some data before passing it to the connected stream? If yes, is there any way I could tune this? Regards, Alexis.
