Hi all, I am writing to describe where I got with the issue.
The next thing I wanted to do was to check topics if they contain records with mixed timestamps in single partition that could cause the warning "Skipping record for expired segment" - meaning, timestamp of incoming record is behind observed stream time and out-of a join window. I did the check. They do have the mixed timestamps. The input topics of the streaming app have timestamps in order. But I need to do repartitioning to introduce key needed for the join. And the repartition topics have mixed timestamps in single partition. It doesn't happen during continues run of the streaming application. It happens when I stop the streaming application for several minutes or more. The stream app is deployed in 10 instances. My theory is, that stream tasks doesn't start at the same time or doesn't process records at the same speed. So it can happen that one task is writing records with different timestamps than other task is writing to a given partition of the repartition topic. And so they get mixed. I am not aware of mechanism in Kafka Streams that could prevent mixing timestamps in repartition topics. If there is one, or if there is a configuration or something that could mitigate it, please let me know. So, in light of it, I think the warning is definitely a good thing. I have increased join-window duration to handle 2 hours pauses in stream processing (2 hour out-of-order records) which should do it for most cases. Increasing window duration has memory and cpu impact, I still wonder if there is more efficient way how to resolve it. Best Regards, Jiri On Tue, Feb 11, 2020 at 6:45 PM John Roesler <vvcep...@apache.org> wrote: > Hi Jiří, > > Hmm, that is a mystery indeed. to inspect the log, you could try > kafka-dump-log (I've never used it). > > What I have done before is use kafka-console-consumer, with the > following option specified: > --property <String: prop> > properties include: > > print.timestamp=true|false > > Which version of Streams are you running? This is bringing up a > vague memory of when I refactored the retention time logic a while > back, and added logic to skip writing changelog records upon restore > when we detect that they would already be expired according to the > current stream time. Previously, we would go ahead and write them > and then have to rotate store segments later on during the restoration > when we reach the current stream time. This is a pretty heavy and > completely avoidable I/O operation. If this is what's happening, then > it's just an unforseen consequence of the new log level. We might > need to follow up with a change to suppress the warnings specifically > in this circumstance. > > Feel free to open a bug ticket with all the relevant version info, repro, > logs etc., you've collected if you feel like the above might be what's > happening. > > For clarity, this wouldn't be a correctness problem at all, just a > misleading > and troubling log message we shouldn't be producing. > > Thanks, > -John > > On Tue, Feb 11, 2020, at 11:21, Samek, Jiří wrote: > > Hi Bruno, John and Sophie, > > > > thank you very much for quick responses, you are the best. After thinking > > about it a little bit more, it seems fishy. > > > > From logs, I see that it is not happening when application is running > > normally. > > > > I have checked timestamps (windowStartTimestamp) - connecting local > > instance in debug mode to Kafka cluster. And they are mixed up. Not > always, > > there can be a day with good sequence and then a time interval with mixed > > up timestamps, like these (store retention is 20.6 minutes): > > StreamThread-1.task.1_57, 2020-02-07T13:05:46.550Z > > StreamThread-1.task.1_57, 2020-02-07T13:12:07.870Z > > StreamThread-1.task.1_57, 2020-02-07T13:10:49.980Z > > StreamThread-1.task.1_57, 2020-02-07T13:12:55.909Z > > StreamThread-1.task.1_57, 2020-02-07T13:09:02.662Z > > StreamThread-1.task.1_57, 2020-02-07T13:13:08.651Z > > StreamThread-1.task.1_57, 2020-02-07T13:06:53.946Z > > StreamThread-1.task.1_57, 2020-02-07T13:11:58.188Z > > StreamThread-1.task.1_57, 2020-02-07T12:59:42.884Z > > StreamThread-1.task.1_57, 2020-02-07T13:07:30.412Z > > StreamThread-1.task.1_57, 2020-02-07T12:55:53.328Z > > StreamThread-1.task.1_57, 2020-02-07T12:44:51.912Z > > StreamThread-1.task.1_57, 2020-02-07T12:59:27.364Z > > StreamThread-1.task.1_57, 2020-02-07T13:01:34.313Z > > StreamThread-1.task.1_57, 2020-02-07T13:07:56.379Z > > StreamThread-1.task.1_57, 2020-02-07T12:45:32.984Z > > StreamThread-1.task.1_57, 2020-02-07T12:45:44.232Z > > StreamThread-1.task.1_57, 2020-02-07T12:45:59.594Z > > StreamThread-1.task.1_57, 2020-02-07T12:46:02.860Z > > StreamThread-1.task.1_57, 2020-02-07T13:02:17.658Z > > StreamThread-1.task.1_57, 2020-02-07T12:46:25.125Z > > StreamThread-1.task.1_57, 2020-02-07T12:46:44.864Z > > StreamThread-1.task.1_57, 2020-02-07T12:44:44.074Z > > StreamThread-1.task.1_57, 2020-02-07T13:03:36.221Z > > StreamThread-1.task.1_57, 2020-02-07T13:12:16.691Z > > StreamThread-1.task.1_57, 2020-02-07T12:56:55.214Z > > > > Picking a few of these, the stack trace was like: > > put:134, InMemoryWindowStore (org.apache.kafka.streams.state.internals) > > lambda$init$0:112, InMemoryWindowStore > > (org.apache.kafka.streams.state.internals) > > restore:-1, 69348804 > > > (org.apache.kafka.streams.state.internals.InMemoryWindowStore$$Lambda$270) > > lambda$adapt$1:47, StateRestoreCallbackAdapter > > (org.apache.kafka.streams.processor.internals) > > restoreBatch:-1, 791473363 > > > (org.apache.kafka.streams.processor.internals.StateRestoreCallbackAdapter$$Lambda$269) > > restoreBatch:89, CompositeRestoreListener > > (org.apache.kafka.streams.processor.internals) > > restore:92, StateRestorer (org.apache.kafka.streams.processor.internals) > > processNext:349, StoreChangelogReader > > (org.apache.kafka.streams.processor.internals) > > restore:93, StoreChangelogReader > > (org.apache.kafka.streams.processor.internals) > > updateNewAndRestoringTasks:389, TaskManager > > (org.apache.kafka.streams.processor.internals) > > runOnce:769, StreamThread (org.apache.kafka.streams.processor.internals) > > runLoop:698, StreamThread (org.apache.kafka.streams.processor.internals) > > run:671, StreamThread (org.apache.kafka.streams.processor.internals) > > > > So I believe it happens on stream restoration phase. And it's restoring > > state from internal changelog topic. It's all task.1_57 so I expect that > it > > is a single partition. > > > > Thinking about it, I don't understand how such a case can even > > theoretically happen. I expect that a window, in order to be written to > the > > changelog topic, first needs to go through "put"; so even if it's mixed > on > > the input side, it should be skipped if expired at the moment of "put" > > (relatively to observedStreamTime) and on restoration everything should > be > > fine. > > > > As the next step, I would like to list/inspect records and their > timestamps > > from given partition of the changelog topic via a command line tool (or > in > > some other way) - to confirm if they are really stored this way. If you > > have a tip on how to do it, please let me know. > > > > That is all I have for now. I would like to resolve it. I will post it > here > > if I come up with something new. > > > > Thank you > > Jiri > > > > > > > > On Mon, Feb 10, 2020 at 10:14 PM John Roesler <vvcep...@apache.org> > wrote: > > > > > > Hey all, > > > > > > Sorry for the confusion. Bruno set me straight offline. > > > > > > Previously, we had metrics for each reason for skipping records, and > the > > > rationale was that you would monitor the metrics and only turn to the > logs > > > if you needed to *debug* unexpected record skipping. Note that skipping > > > records by itself isn't a cause for concern, since this is exactly what > > Streams > > > is designed to do in a number of situations. > > > > > > However, during the KIP-444 discussion, the decision was reversed, and > we > > > decided to just log one "roll-up" metric for all skips and increase the > > log > > > messages to warning level for debuggability. This particularly makes > sense > > > because you otherwise would have to restart the application to change > the > > > log level if you needed to figure out why the single skipped-record > metric > > > is non-zero. And then you may not even observe it again. > > > > > > I either missed the memo on that discussion, or participated in it and > > then > > > forgot it even happened. I'm not sure I want to look back at the > thread to > > > find out. > > > > > > Anyway, I've closed the PR I opened to move it back to debug. We should > > > still try to help figure out the root cause of this particular email > > thread, > > > though. > > > > > > Thanks, > > > -John > > > > > > On Mon, Feb 10, 2020, at 12:20, Sophie Blee-Goldman wrote: > > > > While I agree that seems like it was probably a refactoring mistake, > I'm > > > > not > > > > convinced it isn't the right thing to do. John, can you reiterate the > > > > argument > > > > for setting it to debug way back when? > > > > > > > > I would actually present this exact situation as an argument for > > keeping it > > > > as > > > > warn, since something indeed seems fishy here that was only surfaced > > > > through this warning. That said, maybe the metric is the more > > appropriate > > > > way to bring attention to this: not sure if it's info or debug level > > > > though, or > > > > how likely it is that anyone really pays attention to it? > > > > > > > > On Mon, Feb 10, 2020 at 9:53 AM John Roesler <j...@vvcephei.org> > wrote: > > > > > > > > > Hi, > > > > > > > > > > I’m sorry for the trouble. It looks like it was a mistake during > > > > > > > > > > https://github.com/apache/kafka/pull/6521 > > > > > > > > > > Specifically, while addressing code review comments to change a > bunch > > of > > > > > other logs from debugs to warnings, that one seems to have been > > included by > > > > > accident: > > > > > > > > https://github.com/apache/kafka/commit/ac27e8578f69d60a56ba28232d7e96c76957f66c > > > > > > > > > > I’ll see if I can fix it today. > > > > > > > > > > Regarding Bruno's thoughts, there was a pretty old decision to > > capture the > > > > > "skipped records" as a metric for visibility and log it at the > debug > > level > > > > > for debuggability. We decided that "warning" wasn't the right level > > because > > > > > Streams is operating completely as specified. > > > > > > > > > > However, I do agree that it doesn't seem right to see more skipped > > records > > > > > during start-up; I would expect to see exactly the same records > > skipped > > > > > during start-up as during regular processing, since the skipping > > logic is > > > > > completely deterministic and based on the sequence of timestamps > your > > > > > records have in the topic. Maybe you just notice it more during > > startup? > > > > > I.e., if there are 1000 warning logs spread over a few months, then > > you > > > > > don't notice it, but when you see them all together at start-up, > it's > > more > > > > > concerning? > > > > > > > > > > Thanks, > > > > > -John > > > > > > > > > > > > > > > On Mon, Feb 10, 2020, at 10:15, Bruno Cadonna wrote: > > > > > > Hi, > > > > > > > > > > > > I am pretty sure this was intentional. All skipped records log > > > > > > messages are on WARN level. > > > > > > > > > > > > If a lot of your records are skipped on app restart with this log > > > > > > message on WARN-level, they were also skipped with the log > message > > on > > > > > > DEBUG-level. You simply did not know about it before. With an > > > > > > in-memory window store, this message is logged when a window > with a > > > > > > start time older than the current stream time minus the retention > > > > > > period is put into the window store, i.e., the window is NOT > > inserted > > > > > > into the window stroe. If you get a lot of them on app restart, > you > > > > > > should have a look at the timestamps of your records and the > > retention > > > > > > of your window store. If those values do not explain the > behavior, > > > > > > please try to find a minimal example that shows the issue and > post > > it > > > > > > here on the mailing list. > > > > > > > > > > > > On Mon, Feb 10, 2020 at 2:27 PM Samek, Jiří > <sa...@avast.com.invalid > > > > > > > > wrote: > > > > > > > > > > > > > > Hi, > > > > > > > > > > > > > > in > > > > > > > > > > > > > > > https://github.com/apache/kafka/commit/9f5a69a4c2d6ac812ab6134e64839602a0840b87#diff-a5cfe68a5931441eff5f00261653dd10R134 > > > > > > > > > > > > > > log level of "Skipping record for expired segment" was changed > > from > > > > > debug > > > > > > > to warn. Was it intentional change? Should it be somehow > handled > > by > > > > > user? > > > > > > > How can user handle it? I am getting a lot of these on app > > restart. > > > > > > > > > > > > > > > > > > > > > > > -- > > > > Jiří Samek | Software Developer > > > > AVAST Software s.r.o. | Pikrtova 1737/1a | 140 00 Praha 4 > > > > M +420 734 524 549 | E sa...@avast.com | W www.avast.com > > > -- *Jiří Samek * <sa...@avast.com>| *Software Developer* *AVAST Software s.r.o.* | Pikrtova 1737/1a | 140 00 Praha 4 *M* +420 734 524 549 | *E* sa...@avast.com | *W* www.avast.com
