Hi, Like I said I've only just started thinking about how this can be implemented (I'm currently still lacking a lot of knowledge). So at this point I do not yet see why solving this in the transport (like Kafka) is easier than solving it in the processing engine (like Flink). In the normal scenarios we have today all watermarks are (re)created in the processing engine so instinctively I would expect that to be the "right place".
Also as far as I can see right now in order to make this happen the watermarks must all be annotated with things like the applicationId (to handle multiple producers), the timestamp (duh), the taskId and the total number of tasks in the producing system: So the producers or the broker must attach this information to the watermarks. It should also be able to handle dynamic scaling of producing applications and handling the entering and leaving of producers into a topic is also a thing to consider. [Reading this back; is this the reason for it to be easier in the transport?] I do realize that even if this is implemented in the processing engine some constraints may be needed to allow this to work: Like having some kind of ordering guarantees per partition in a topic. Do you guys know of any article/blog/paper/mail discussion/... that describes/discusses this? Niels On Mon, Dec 20, 2021 at 4:35 PM Matthias J. Sax <mj...@mailbox.org.invalid> wrote: > I think this problem should be tackled inside Kafka, not Flink. > > Kafka already has internal control messages to write transaction > markers. Those could be extended to carry watermark information. It > would be best to generalize those as "user control messages" and > watermarks could just be one application. > > In addition, we might need something link a "producer group" to track > how many producers are writing into a partition: this would allow to > inform downstream consumer how many different watermarks they need to > track. > > It's not an easy problem to solve, but without integrating with the > storage layer, but trying to solve it at the processing layer, it's even > harder. > > -Matthias > > On 12/20/21 01:57, Niels Basjes wrote: > > I'm reading the Pulsar PIP and noticed another thing to take into > account: > > multiple applications (with each a different parallelism) that all write > > into the same topic. > > > > On Mon, 20 Dec 2021, 10:45 Niels Basjes, <ni...@basjes.nl> wrote: > > > >> Hi Till, > >> > >> This morning I also realized what you call an 'effective watermark' is > >> indeed what is needed. > >> I'm going to read up on what Pulsar has planned. > >> > >> What I realized is that the consuming application must be aware of the > >> parallelism of the producing application, which is independent of the > >> partitions in the intermediate transport. > >> > >> Assume I produce in parallel 2 and have 5 kafka partition which I then > >> read in parallel 3; then in the consuming (parallel 3) application I > must > >> wait for watermarks from each original input before I can continue: > which > >> is 2 > >> Also we must assume that those watermarks are created at different > >> timestamps. > >> So my current assessment is that the watermark records must include at > >> least the timestamp, the number of the thread for this watermark and the > >> total number of threads . > >> > >> Niels > >> > >> > >> On Mon, Dec 20, 2021 at 10:10 AM Till Rohrmann <trohrm...@apache.org> > >> wrote: > >> > >>> Hi Niels, > >>> > >>> if you have multiple inputs going into a single Kafka partition then > you > >>> have to calculate the effective watermark by looking at the min > watermark > >>> from all inputs. You could insert a Flink operator that takes care of > it > >>> and then writes to a set of partitions in 1:n relationship. > Alternatively, > >>> you could take a look at Pulsar that wants to support this > functionality > >>> out of the box [1]. > >>> > >>> [1] https://github.com/apache/pulsar/issues/12267 > >>> > >>> Cheers, > >>> Till > >>> > >>> On Sun, Dec 19, 2021 at 4:46 PM Niels Basjes <ni...@basjes.nl> wrote: > >>> > >>>> Hi, > >>>> > >>>> About a year ago I spoke at the Flink Forward conference ( > >>>> https://www.youtube.com/watch?v=wqRDyrE3dwg ) about handling > >>> development > >>>> problems regarding streaming applications and handling the lack of > >>> events > >>>> in a stream. > >>>> Something I spoke about towards the end of this talk was the idea to > >>> ship > >>>> the watermarks of a Flink topology into the intermediate transport > >>> between > >>>> applications so you wouldn't need to recreate them. > >>>> > >>>> At that time it was just an idea, today I'm actually trying to build > >>> that > >>>> and see if this idea is actually possible. > >>>> > >>>> So the class of applications I work on usually do a keyBy on something > >>> like > >>>> a SessionId, SensorId or IP address. > >>>> In low traffic scenarios this means that in Kafka some partitions are > >>>> completely idle which makes Windows/GroupBy type operations impossible > >>> (in > >>>> my talk I explain it a lot better). > >>>> > >>>> I have a test setup right now to play around with this and I'm running > >>> into > >>>> a bit of a conceptual hurdle for which I'm looking for help. > >>>> > >>>> My goal is to ship the watermarks from within a topology into Kafka > and > >>>> then let a follow up application extract those watermarks again and > >>> simply > >>>> continue. > >>>> The new SinkWriter interface has a void writeWatermark(Watermark > >>>> watermark) method > >>>> that seems intended for this kind of thing. > >>>> The basic operations like writing a watermark into Kafka, reading it > >>> again > >>>> and then recreating the watermark again works in my test setup (very > >>> messy > >>>> code but it works). > >>>> > >>>> My hurdle has to do with the combination of > >>>> - different parallelism numbers between Flink and Kafka (how do I > ship 2 > >>>> watermarks into 3 partitions) > >>>> - the fact that if you do a keyBy (both in Flink and Kafka) there is a > >>>> likely mismatch between the Flink 'partition' and the Kafka > `partition`. > >>>> - processing speed differences between various threads (like session > "A" > >>>> needs more CPU cycles/time/processing than session "B") will lead to > >>>> skewing of the progression between them. > >>>> - watermarks in separate threads in a single Flink topology are not > >>>> synchronized (they cannot and should not be). > >>>> > >>>> Has anyone any pointers on possible ways to handle this? > >>>> > >>>> Right now my only idea is to ship the watermark into all partitions > (as > >>>> they do not have a key!) and let the consuming application determine > the > >>>> "real watermark" based on the mix of watermarks coming in from the > >>> upstream > >>>> threads. > >>>> > >>>> All suggestions and ideas are appreciated. > >>>> > >>>> -- > >>>> Best regards / Met vriendelijke groeten, > >>>> > >>>> Niels Basjes > >>>> > >>> > >> > >> > >> -- > >> Best regards / Met vriendelijke groeten, > >> > >> Niels Basjes > >> > > > -- Best regards / Met vriendelijke groeten, Niels Basjes
