No unfortunately it is not the case. The table record is written about 20 seconds before the stream record. I’ll crank up the time tomorrow and see what happens.
On Tue, Nov 2, 2021 at 6:24 PM Matthias J. Sax <mj...@apache.org> wrote: > Hard to tell, but as it seems that you can reproduce the issue, it might > be worth a try to increase the idle time further. > > I guess one corner case for stream-table join that is not resolved yet > is when stream and table record have the same timestamp... For this > case, the table record might not be processed first. > > Could you hit this case? > > > -Matthias > > On 11/2/21 3:13 PM, Chad Preisler wrote: > > Thank you for the information. We are using the Kafka 3.0 client library. > > We are able to reliably reproduce this issue in our test environment > now. I > > removed my timestamp extractor, and I set the max.task.idle.ms to 2000. > I > > also turned on trace logging for package > > org.apache.kafka.streams.processor.internals. > > > > To create the issue we stopped the application and ran enough data to > > create a lag of 400 messages. We saw 5 missed joins. > > > > From the stream-thread log messages we saw the event message, our stream > > missed the join, and then several milliseconds later we saw the > > stream-thread print out the status message. The stream-thread printed out > > our status message a total of 5 times. > > > > Given that only a few milliseconds passed between missing the join and > the > > stream-thread printing the status message, would increasing the > > max.task.idle.ms help? > > > > Thanks, > > Chad > > > > On Mon, Nov 1, 2021 at 10:03 PM Matthias J. Sax <mj...@apache.org> > wrote: > > > >> Timestamp synchronization is not perfect, and as a matter of fact, we > >> fixed a few gaps in 3.0.0 release. We actually hope, that we closed the > >> last gaps in 3.0.0... *fingers-crossed* :) > >> > >>> We are using a timestamp extractor that returns 0. > >> > >> You can do this, and it effectively "disables" timestamp synchronization > >> as records on the KTable side don't have a timeline any longer. As a > >> side effect it also allows you to "bootstrap" the table, as records with > >> timestamp zero will always be processed first (as they are smaller). Of > >> course, you also don't have time synchronization for "future" data and > >> your program becomes non-deterministic if you reprocess old data. > >> > >>> his seemed to be the only > >>> way to bootstrap enough records at startup to avoid the missed join. > >> > >> Using 3.0.0 and enabling timestamp synchronization via > >> `max.task.idle.ms` config, should allow you to get the correct behavior > >> without the zero-extractor (of course, your KTable data must have > >> smaller timestamps that your KStream data). > >> > >>> If I use "timestamp synchronization" do I have to remove the zero > >>> timestamp extractor? If I remove the zero timestamp extractor will > >>> timestamp synchronization take care of the missed join issue on > startup? > >> > >> To be more precise: timestamp synchronization is _always_ on. The > >> question is just how strict it is applied. By default, we do the weakest > >> from which is only best effort. > >> > >>> I'm guessing the issue here is that occasionally the poll request is > not > >>> returning the matching record for the KTable side of the join before > the > >>> task goes off and starts processing records. > >> > >> Yes, because of default best effort approach. That is why you should > >> increase `max.task.idle.ms` to detect this case and "skip" processing > >> and let KS do another poll() to get KTable data. > >> > >> 2.8 and earlier: > >> > >> max.task.idle.ms=0 -> best effort (no poll() retry) > >> max.task.idle.ms>0 -> try to do another poll() until data is there or > >> idle time passed > >> > >> Note: >0 might still "fail" even if there is data, because consumer > >> fetch behavior is not predictable. > >> > >> > >> 3.0: > >> > >> max.task.idle.ms=-1 -> best effort (no poll() retry) > >> max.task.idle.ms=0 -> if there is data broker side, repeat to poll() > >> until you get the data > >> max.task.idle.ms>0 -> even if there is not data broker side, wait until > >> data becomes available or the idle time passed > >> > >> > >> Hope this helps. > >> > >> > >> -Matthias > >> > >> On 11/1/21 4:29 PM, Guozhang Wang wrote: > >>> Hello Chad, > >>> > >>> From your earlier comment, you mentioned "In my scenario the records > >> were > >>> written to the KTable topic before the record was written to the > KStream > >>> topic." So I think Matthias and others have excluded this possibility > >> while > >>> trying to help investigate. > >>> > >>> If only the matching records from KStream are returned via a single a > >>> consumer poll call but not the other records from KTable, then you > would > >>> miss this matched join result. > >>> > >>> Guozhang > >>> > >>> > >>> On Sun, Oct 31, 2021 at 7:28 AM Chad Preisler <chad.preis...@gmail.com > > > >>> wrote: > >>> > >>>> Thank you for your response and the links to the presentations. > >>>> > >>>> > >>>> *However, this seems tobe orthogonal to your issue?* > >>>> > >>>> Yes. From what I see in the code it looks like you have a single > >> consumer > >>>> subscribed to multiple topics. Please correct me if I'm wrong. > >>>> > >>>> > >>>> *By default, timestamp synchronization is disabled. Maybeenabling it > >> would > >>>> help?* > >>>> > >>>> We are using a timestamp extractor that returns 0. We did that because > >> we > >>>> were almost always missing joins on startup, and this seemed to be the > >> only > >>>> way to bootstrap enough records at startup to avoid the missed join. > We > >>>> found a post that said doing that would make the KTable act like the > >>>> GlobalKTable at startup. So far this works great, we never miss a join > >> on a > >>>> startup. If I use "timestamp synchronization" do I have to remove the > >> zero > >>>> timestamp extractor? If I remove the zero timestamp extractor will > >>>> timestamp synchronization take care of the missed join issue on > startup? > >>>> > >>>> I'm guessing the issue here is that occasionally the poll request is > not > >>>> returning the matching record for the KTable side of the join before > the > >>>> task goes off and starts processing records. Later when we put the > same > >>>> record on the topic and the KTable has had a chance to load more > records > >>>> the join works and everything is good to go. Because of the way our > >> system > >>>> works no new status records have been written and so the new record > >> joins > >>>> against the correct status. > >>>> > >>>> Do you agree that the poll request is returning the KStream record but > >> not > >>>> returning the KTable record and therefore the join is getting missed? > If > >>>> you don't agree, what do you think is going on? Is there a way to > prove > >>>> this out? > >>>> > >>>> Thanks, > >>>> Chad > >>>> > >>>> On Sat, Oct 30, 2021 at 2:09 PM Matthias J. Sax <mj...@apache.org> > >> wrote: > >>>> > >>>>> Yes, a StreamThread has one consumer. The number of StreamThreads per > >>>>> instance is configurable via `num.stream.threads`. Partitions are > >>>>> assigned to threads similar to consumer is a plain consumer group. > >>>>> > >>>>> It seems you run with the default of one thread per instance. As you > >>>>> spin up 12 instances, it results in 12 threads for the application. > As > >>>>> you have 12 partitions, using more threads won't be useful as no > >>>>> partitions are left for them to process. > >>>>> > >>>>> For a stream-table joins, there will be one task per "partition pair" > >>>>> that computes the join for those partitions. So you get 12 tasks, and > >>>>> each thread processes one task in your setup. Ie, a thread consumer > is > >>>>> reading data for both input topics. > >>>>> > >>>>> Pausing happens on a per-partition bases: for joins there is two > >> buffers > >>>>> per task (one for each input topic partition). It's possible that one > >>>>> partition is paused while the other is processed. However, this seems > >> to > >>>>> be orthogonal to your issue? > >>>>> > >>>>> For a GlobalKTable, you get an additional GlobalThread that only > reads > >>>>> the data from the "global topic" to update the GlobalKTable. > Semantics > >>>>> of KStream-KTable and KStream-GlobalKTable joins are different: Cf > >>>>> > >>>>> > >>>> > >> > https://www.confluent.io/events/kafka-summit-europe-2021/temporal-joins-in-kafka-streams-and-ksqldb/ > >>>>> > >>>>> For the timestamp synchronization, you may checkout ` > max.task.idle.ms` > >>>>> config. By default, timestamp synchronization is disabled. Maybe > >>>>> enabling it would help? > >>>>> > >>>>> You may also check out slides 34-38: > >>>>> > >>>>> > >>>> > >> > https://www.confluent.io/kafka-summit-san-francisco-2019/whats-the-time-and-why/ > >>>>> > >>>>> There is one corner case: if two records with the same timestamp come > >>>>> it, it's not defined which one will be processed first. > >>>>> > >>>>> Hope this helps. > >>>>> > >>>>> > >>>>> -Matthias > >>>>> > >>>>> > >>>>> On 10/30/21 6:45 AM, Chad Preisler wrote: > >>>>>> Yes, this helped. I have some additional questions. > >>>>>> > >>>>>> Does StreamThread have one consumer? (Looks like it, but just want > to > >>>>>> confirm) > >>>>>> Is there a separate StreamThread for each topic including the > KTable? > >>>>>> If a KTable is a StreamThread and there is a StreamTask for that > >>>> KTable, > >>>>>> could my buffer be getting filled up, and the mainConsumer for the > >>>> KTable > >>>>>> be getting paused? I see this code in StreamTask#addRecords. > >>>>>> > >>>>>> // if after adding these records, its partition queue's buffered > size > >>>> has > >>>>>> been > >>>>>> // increased beyond the threshold, we can then pause the > >>>>>> consumption for this partition > >>>>>> if (newQueueSize > maxBufferedSize) { > >>>>>> mainConsumer.pause(singleton(partition)); > >>>>>> } > >>>>>> > >>>>>> Is there any specific logging that I can set to debug or trace that > >>>> would > >>>>>> help me troubleshoot? I'd prefer not to turn debug and/or trace on > for > >>>>>> every single class. > >>>>>> > >>>>>> Thanks, > >>>>>> Chad > >>>>>> > >>>>>> > >>>>>> > >>>>>> > >>>>>> > >>>>>> On Sat, Oct 30, 2021 at 5:20 AM Luke Chen <show...@gmail.com> > wrote: > >>>>>> > >>>>>>> Hi Chad, > >>>>>>>> I'm wondering if someone can point me to the Kafka streams > internal > >>>>> code > >>>>>>> that reads records for the join? > >>>>>>> --> You can check StreamThread#pollPhase, where stream thread (main > >>>>>>> consumer) periodically poll records. And then, it'll process each > >>>>> topology > >>>>>>> node with these polled records in stream tasks > (StreamTask#process). > >>>>>>> > >>>>>>> Hope that helps. > >>>>>>> > >>>>>>> Thanks. > >>>>>>> Luke > >>>>>>> > >>>>>>> > >>>>>>> On Sat, Oct 30, 2021 at 5:42 PM Gilles Philippart > >>>>>>> <gilles.philipp...@fundingcircle.com.invalid> wrote: > >>>>>>> > >>>>>>>> Hi Chad, this talk around 24:00 clearly explains what you’re > seeing > >>>>>>>> > >>>>>>> > >>>>> > >>>> > >> > https://www.confluent.io/events/kafka-summit-europe-2021/failing-to-cross-the-streams-lessons-learned-the-hard-way/ > >>>>>>>> < > >>>>>>>> > >>>>>>> > >>>>> > >>>> > >> > https://www.confluent.io/events/kafka-summit-europe-2021/failing-to-cross-the-streams-lessons-learned-the-hard-way/ > >>>>>>>>> > >>>>>>>> > >>>>>>>> Gilles > >>>>>>>> > >>>>>>>>> On 30 Oct 2021, at 04:02, Chad Preisler <chad.preis...@gmail.com > > > >>>>>>> wrote: > >>>>>>>>> > >>>>>>>>> Hello, > >>>>>>>>> > >>>>>>>>> I have a stream application that does a KStream to KTable left > >> join. > >>>>> We > >>>>>>>>> seem to be occasionally missing joins > <https://www.google.com/maps/search/%3E%3E%3E%3E%3E+seem+to+be+occasionally+missing+joins?entry=gmail&source=g> > (KTable side is null). > >>>>>>>>> > >>>>>>>>> I'm wondering if someone can point me to the Kafka streams > internal > >>>>>>> code > >>>>>>>>> that reads records for the join? I've poked around the Kafka code > >>>>> base, > >>>>>>>> but > >>>>>>>>> there is a lot there. I imagine there is some consumer poll for > >> each > >>>>>>> side > >>>>>>>>> of the join, and possibly a background thread for reading the > >> KTable > >>>>>>>> topic. > >>>>>>>>> > >>>>>>>>> I figure there are several possible causes of this issue, and > since > >>>>>>>> nothing > >>>>>>>>> is really jumping out in my code, I was going to start looking at > >>>> the > >>>>>>>> Kafka > >>>>>>>>> code to see if there is something I can do to fix this. > >>>>>>>>> > >>>>>>>>> Thanks, > >>>>>>>>> Chad > >>>>>>>> > >>>>>>>> > >>>>>>>> -- > >>>>>>>> > >>>>>>>> > >>>>>>>> > >>>>>>>> > >>>>>>>> Funding Circle Limited is authorised and regulated by the > Financial > >>>>>>>> Conduct Authority under firm registration number 722513. Funding > >>>> Circle > >>>>>>> is > >>>>>>>> not covered by the Financial Services Compensation Scheme. > >> Registered > >>>>> in > >>>>>>>> England (Co. No. 06968588) with registered office at 71 Queen > >>>> Victoria > >>>>>>>> Street, London EC4V 4AY. > >>>>>>>> > >>>>>>> > >>>>>> > >>>>> > >>>> > >>> > >>> > >> > > >
