Hi Feng, Thanks for the feedback. Yes, you can configure the execution.checkpointing.interval-during-backlog to effectively disable checkpoint during backlog.
Prior to your comment, the FLIP allows users to do this by setting the config value to something large (e.g. 365 day). After thinking about this more, we think it is more usable to allow users to achieve this goal by setting the config value to 0. This is consistent with the existing behavior of execution.checkpointing.interval -- the checkpoint is disabled if user set execution.checkpointing.interval to 0. We have updated the description of execution.checkpointing.interval-during-backlog to say the following: ... it is not null, the value must either be 0, which means the checkpoint is disabled during backlog, or be larger than or equal to execution.checkpointing.interval. Does this address your need? Best, Dong On Thu, Jun 29, 2023 at 9:23 AM feng xiangyu <xiangyu...@gmail.com> wrote: > Hi Dong and Yunfeng, > > Thanks for the proposal, your flip sounds very useful from my perspective. > In our business, when we using hybrid source in production we also met the > problem described in your flip. > In our solution, we tend to skip making any checkpoints before all batch > tasks have finished and resume the periodic checkpoint only in streaming > phrase. Within this flip, we can solve our problem in a more generic way. > > However, I am wondering if we still want to skip making any checkpoints > during historical phrase, can we set this configuration > "execution.checkpointing.interval-during-backlog" equals "-1" to cover this > case? > > Best, > Xiangyu > > Hang Ruan <ruanhang1...@gmail.com> 于2023年6月28日周三 16:30写道： > > > Thanks for Dong and Yunfeng's work. > > > > The FLIP looks good to me. This new version is clearer to understand. > > > > Best, > > Hang > > > > Dong Lin <lindon...@gmail.com> 于2023年6月27日周二 16:53写道： > > > > > Thanks Jack, Jingsong, and Zhu for the review! > > > > > > Thanks Zhu for the suggestion. I have updated the configuration name as > > > suggested. > > > > > > On Tue, Jun 27, 2023 at 4:45 PM Zhu Zhu <reed...@gmail.com> wrote: > > > > > > > Thanks Dong and Yunfeng for creating this FLIP and driving this > > > discussion. > > > > > > > > The new design looks generally good to me. Increasing the checkpoint > > > > interval when the job is processing backlogs is easier for users to > > > > understand and can help in more scenarios. > > > > > > > > I have one comment about the new configuration. > > > > Naming the new configuration > > > > "execution.checkpointing.interval-during-backlog" would be better > > > > according to Flink config naming convention. > > > > It is also because that nested config keys should be avoided. See > > > > FLINK-29372 for more details. > > > > > > > > Thanks, > > > > Zhu > > > > > > > > Jingsong Li <jingsongl...@gmail.com> 于2023年6月27日周二 15:45写道： > > > > > > > > > > Looks good to me! > > > > > > > > > > Thanks Dong, Yunfeng and all for your discussion and design. > > > > > > > > > > Best, > > > > > Jingsong > > > > > > > > > > On Tue, Jun 27, 2023 at 3:35 PM Jark Wu <imj...@gmail.com> wrote: > > > > > > > > > > > > Thank you Dong for driving this FLIP. > > > > > > > > > > > > The new design looks good to me! > > > > > > > > > > > > Best, > > > > > > Jark > > > > > > > > > > > > > 2023年6月27日 14:38，Dong Lin <lindon...@gmail.com> 写道： > > > > > > > > > > > > > > Thank you Leonard for the review! > > > > > > > > > > > > > > Hi Piotr, do you have any comments on the latest proposal? > > > > > > > > > > > > > > I am wondering if it is OK to start the voting thread this > week. > > > > > > > > > > > > > > On Mon, Jun 26, 2023 at 4:10 PM Leonard Xu <xbjt...@gmail.com> > > > > wrote: > > > > > > > > > > > > > >> Thanks Dong for driving this FLIP forward! > > > > > > >> > > > > > > >> Introducing `backlog status` concept for flink job makes > sense > > to > > > > me as > > > > > > >> following reasons: > > > > > > >> > > > > > > >> From concept/API design perspective, it’s more general and > > natural > > > > than > > > > > > >> above proposals as it can be used in HybridSource for bounded > > > > records, CDC > > > > > > >> Source for history snapshot and general sources like > KafkaSource > > > for > > > > > > >> historical messages. > > > > > > >> > > > > > > >> From user cases/requirements, I’ve seen many users manually to > > set > > > > larger > > > > > > >> checkpoint interval during backfilling and then set a shorter > > > > checkpoint > > > > > > >> interval for real-time processing in their production > > environments > > > > as a > > > > > > >> flink application optimization. Now, the flink framework can > > make > > > > this > > > > > > >> optimization no longer require the user to set the checkpoint > > > > interval and > > > > > > >> restart the job multiple times. > > > > > > >> > > > > > > >> Following supporting using larger checkpoint for job under > > backlog > > > > status > > > > > > >> in current FLIP, we can explore supporting larger > > > > parallelism/memory/cpu > > > > > > >> for job under backlog status in the future. > > > > > > >> > > > > > > >> In short, the updated FLIP looks good to me. > > > > > > >> > > > > > > >> > > > > > > >> Best, > > > > > > >> Leonard > > > > > > >> > > > > > > >> > > > > > > >>> On Jun 22, 2023, at 12:07 PM, Dong Lin <lindon...@gmail.com> > > > > wrote: > > > > > > >>> > > > > > > >>> Hi Piotr, > > > > > > >>> > > > > > > >>> Thanks again for proposing the isProcessingBacklog concept. > > > > > > >>> > > > > > > >>> After discussing with Becket Qin and thinking about this > more, > > I > > > > agree it > > > > > > >>> is a better idea to add a top-level concept to all source > > > > operators to > > > > > > >>> address the target use-case. > > > > > > >>> > > > > > > >>> The main reason that changed my mind is that > > isProcessingBacklog > > > > can be > > > > > > >>> described as an inherent/nature attribute of every source > > > instance > > > > and > > > > > > >> its > > > > > > >>> semantics does not need to depend on any specific > checkpointing > > > > policy. > > > > > > >>> Also, we can hardcode the isProcessingBacklog behavior for > the > > > > sources we > > > > > > >>> have considered so far (e.g. HybridSource and MySQL CDC > source) > > > > without > > > > > > >>> asking users to explicitly configure the per-source behavior, > > > which > > > > > > >> indeed > > > > > > >>> provides better user experience. > > > > > > >>> > > > > > > >>> I have updated the FLIP based on the latest suggestions. The > > > > latest FLIP > > > > > > >> no > > > > > > >>> longer introduces per-source config that can be used by > > > end-users. > > > > While > > > > > > >> I > > > > > > >>> agree with you that CheckpointTrigger can be a useful feature > > to > > > > address > > > > > > >>> additional use-cases, I am not sure it is necessary for the > > > > use-case > > > > > > >>> targeted by FLIP-309. Maybe we can introduce > CheckpointTrigger > > > > separately > > > > > > >>> in another FLIP? > > > > > > >>> > > > > > > >>> Can you help take another look at the updated FLIP? > > > > > > >>> > > > > > > >>> Best, > > > > > > >>> Dong > > > > > > >>> > > > > > > >>> > > > > > > >>> > > > > > > >>> On Fri, Jun 16, 2023 at 11:59 PM Piotr Nowojski < > > > > pnowoj...@apache.org> > > > > > > >>> wrote: > > > > > > >>> > > > > > > >>>> Hi Dong, > > > > > > >>>> > > > > > > >>>>> Suppose there are 1000 subtask and each subtask has 1% > chance > > > of > > > > being > > > > > > >>>>> "backpressured" at a given time (due to random traffic > > spikes). > > > > Then at > > > > > > >>>> any > > > > > > >>>>> given time, the chance of the job > > > > > > >>>>> being considered not-backpressured = (1-0.01)^1000. Since > we > > > > evaluate > > > > > > >> the > > > > > > >>>>> backpressure metric once a second, the estimated time for > the > > > job > > > > > > >>>>> to be considered not-backpressured is roughly 1 / > > > > ((1-0.01)^1000) = > > > > > > >> 23163 > > > > > > >>>>> sec = 6.4 hours. > > > > > > >>>>> > > > > > > >>>>> This means that the job will effectively always use the > > longer > > > > > > >>>>> checkpointing interval. It looks like a real concern, > right? > > > > > > >>>> > > > > > > >>>> Sorry I don't understand where you are getting those numbers > > > from. > > > > > > >>>> Instead of trying to find loophole after loophole, could you > > try > > > > to > > > > > > >> think > > > > > > >>>> how a given loophole could be improved/solved? > > > > > > >>>> > > > > > > >>>>> Hmm... I honestly think it will be useful to know the APIs > > due > > > > to the > > > > > > >>>>> following reasons. > > > > > > >>>> > > > > > > >>>> Please propose something. I don't think it's needed. > > > > > > >>>> > > > > > > >>>>> - For the use-case mentioned in FLIP-309 motivation > section, > > > > would the > > > > > > >>>> APIs > > > > > > >>>>> of this alternative approach be more or less usable? > > > > > > >>>> > > > > > > >>>> Everything that you originally wanted to achieve in > FLIP-309, > > > you > > > > could > > > > > > >> do > > > > > > >>>> as well in my proposal. > > > > > > >>>> Vide my many mentions of the "hacky solution". > > > > > > >>>> > > > > > > >>>>> - Can these APIs reliably address the extra use-case (e.g. > > > allow > > > > > > >>>>> checkpointing interval to change dynamically even during > the > > > > unbounded > > > > > > >>>>> phase) as it claims? > > > > > > >>>> > > > > > > >>>> I don't see why not. > > > > > > >>>> > > > > > > >>>>> - Can these APIs be decoupled from the APIs currently > > proposed > > > in > > > > > > >>>> FLIP-309? > > > > > > >>>> > > > > > > >>>> Yes > > > > > > >>>> > > > > > > >>>>> For example, if the APIs of this alternative approach can > be > > > > decoupled > > > > > > >>>> from > > > > > > >>>>> the APIs currently proposed in FLIP-309, then it might be > > > > reasonable to > > > > > > >>>>> work on this extra use-case with a more > advanced/complicated > > > > design > > > > > > >>>>> separately in a followup work. > > > > > > >>>> > > > > > > >>>> As I voiced my concerns previously, the current design of > > > > FLIP-309 would > > > > > > >>>> clog the public API and in the long run confuse the users. > IMO > > > > It's > > > > > > >>>> addressing the > > > > > > >>>> problem in the wrong place. > > > > > > >>>> > > > > > > >>>>> Hmm.. do you mean we can do the following: > > > > > > >>>>> - Have all source operators emit a metric named > > > > "processingBacklog". > > > > > > >>>>> - Add a job-level config that specifies "the checkpointing > > > > interval to > > > > > > >> be > > > > > > >>>>> used when any source is processing backlog". > > > > > > >>>>> - The JM collects the "processingBacklog" periodically from > > all > > > > source > > > > > > >>>>> operators and uses the newly added config value as > > appropriate. > > > > > > >>>> > > > > > > >>>> Yes. > > > > > > >>>> > > > > > > >>>>> The challenge with this approach is that we need to define > > the > > > > > > >> semantics > > > > > > >>>> of > > > > > > >>>>> this "processingBacklog" metric and have all source > operators > > > > > > >>>>> implement this metric. I am not sure we are able to do this > > yet > > > > without > > > > > > >>>>> having users explicitly provide this information on a > > > per-source > > > > basis. > > > > > > >>>>> > > > > > > >>>>> Suppose the job read from a bounded Kafka source, should it > > > emit > > > > > > >>>>> "processingBacklog=true"? If yes, then the job might use > long > > > > > > >>>> checkpointing > > > > > > >>>>> interval even > > > > > > >>>>> if the job is asked to process data starting from now to > the > > > > next 1 > > > > > > >> hour. > > > > > > >>>>> If no, then the job might use the short checkpointing > > interval > > > > > > >>>>> even if the job is asked to re-process data starting from 7 > > > days > > > > ago. > > > > > > >>>> > > > > > > >>>> Yes. The same can be said of your proposal. Your proposal > has > > > the > > > > very > > > > > > >> same > > > > > > >>>> issues > > > > > > >>>> that every source would have to implement it differently, > most > > > > sources > > > > > > >>>> would > > > > > > >>>> have no idea how to properly calculate the new requested > > > > checkpoint > > > > > > >>>> interval, > > > > > > >>>> for those that do know how to do that, user would have to > > > > configure > > > > > > >> every > > > > > > >>>> source > > > > > > >>>> individually and yet again we would end up with a system, > that > > > > works > > > > > > >> only > > > > > > >>>> partially in > > > > > > >>>> some special use cases (HybridSource), that's confusing the > > > users > > > > even > > > > > > >>>> more. > > > > > > >>>> > > > > > > >>>> That's why I think the more generic solution, working > > primarily > > > > on the > > > > > > >> same > > > > > > >>>> metrics that are used by various auto scaling solutions > (like > > > > Flink K8s > > > > > > >>>> operator's > > > > > > >>>> autosaler) would be better. The hacky solution I proposed > to: > > > > > > >>>> 1. show you that the generic solution is simply a superset > of > > > your > > > > > > >> proposal > > > > > > >>>> 2. if you are adamant that busyness/backpressured/records > > > > processing > > > > > > >>>> rate/pending records > > > > > > >>>> metrics wouldn't cover your use case sufficiently (imo > they > > > > can), > > > > > > >> then > > > > > > >>>> you can very easily > > > > > > >>>> enhance this algorithm with using some hints from the > > sources. > > > > Like > > > > > > >>>> "processingBacklog==true" > > > > > > >>>> to short circuit the main algorithm, if > `processingBacklog` > > is > > > > > > >>>> available. > > > > > > >>>> > > > > > > >>>> Best, > > > > > > >>>> Piotrek > > > > > > >>>> > > > > > > >>>> > > > > > > >>>> pt., 16 cze 2023 o 04:45 Dong Lin <lindon...@gmail.com> > > > > napisał(a): > > > > > > >>>> > > > > > > >>>>> Hi again Piotr, > > > > > > >>>>> > > > > > > >>>>> Thank you for the reply. Please see my reply inline. > > > > > > >>>>> > > > > > > >>>>> On Fri, Jun 16, 2023 at 12:11 AM Piotr Nowojski < > > > > > > >>>> piotr.nowoj...@gmail.com> > > > > > > >>>>> wrote: > > > > > > >>>>> > > > > > > >>>>>> Hi again Dong, > > > > > > >>>>>> > > > > > > >>>>>>> I understand that JM will get the backpressure-related > > > metrics > > > > every > > > > > > >>>>> time > > > > > > >>>>>>> the RestServerEndpoint receives the REST request to get > > these > > > > > > >>>> metrics. > > > > > > >>>>>> But > > > > > > >>>>>>> I am not sure if RestServerEndpoint is already always > > > > receiving the > > > > > > >>>>> REST > > > > > > >>>>>>> metrics at regular interval (suppose there is no human > > > manually > > > > > > >>>>>>> opening/clicking the Flink Web UI). And if it does, what > is > > > the > > > > > > >>>>> interval? > > > > > > >>>>>> > > > > > > >>>>>> Good catch, I've thought that metrics are pre-emptively > sent > > > to > > > > JM > > > > > > >>>> every > > > > > > >>>>> 10 > > > > > > >>>>>> seconds. > > > > > > >>>>>> Indeed that's not the case at the moment, and that would > > have > > > > to be > > > > > > >>>>>> improved. > > > > > > >>>>>> > > > > > > >>>>>>> I would be surprised if Flink is already paying this much > > > > overhead > > > > > > >>>> just > > > > > > >>>>>> for > > > > > > >>>>>>> metrics monitoring. That is the main reason I still doubt > > it > > > > is true. > > > > > > >>>>> Can > > > > > > >>>>>>> you show where this 100 ms is currently configured? > > > > > > >>>>>>> > > > > > > >>>>>>> Alternatively, maybe you mean that we should add extra > code > > > to > > > > invoke > > > > > > >>>>> the > > > > > > >>>>>>> REST API at 100 ms interval. Then that means we need to > > > > considerably > > > > > > >>>>>>> increase the network/cpu overhead at JM, where the > overhead > > > > will > > > > > > >>>>> increase > > > > > > >>>>>>> as the number of TM/slots increase, which may pose risk > to > > > the > > > > > > >>>>>> scalability > > > > > > >>>>>>> of the proposed design. I am not sure we should do this. > > What > > > > do you > > > > > > >>>>>> think? > > > > > > >>>>>> > > > > > > >>>>>> Sorry. I didn't mean metric should be reported every > 100ms. > > I > > > > meant > > > > > > >>>> that > > > > > > >>>>>> "backPressuredTimeMsPerSecond (metric) would report (a > value > > > of) > > > > > > >>>>> 100ms/s." > > > > > > >>>>>> once per metric interval (10s?). > > > > > > >>>>>> > > > > > > >>>>> > > > > > > >>>>> Suppose there are 1000 subtask and each subtask has 1% > chance > > > of > > > > being > > > > > > >>>>> "backpressured" at a given time (due to random traffic > > spikes). > > > > Then at > > > > > > >>>> any > > > > > > >>>>> given time, the chance of the job > > > > > > >>>>> being considered not-backpressured = (1-0.01)^1000. Since > we > > > > evaluate > > > > > > >> the > > > > > > >>>>> backpressure metric once a second, the estimated time for > the > > > job > > > > > > >>>>> to be considered not-backpressured is roughly 1 / > > > > ((1-0.01)^1000) = > > > > > > >> 23163 > > > > > > >>>>> sec = 6.4 hours. > > > > > > >>>>> > > > > > > >>>>> This means that the job will effectively always use the > > longer > > > > > > >>>>> checkpointing interval. It looks like a real concern, > right? > > > > > > >>>>> > > > > > > >>>>> > > > > > > >>>>>>> - What is the interface of this CheckpointTrigger? For > > > > example, are > > > > > > >>>> we > > > > > > >>>>>>> going to give CheckpointTrigger a context that it can use > > to > > > > fetch > > > > > > >>>>>>> arbitrary metric values? This can help us understand what > > > > information > > > > > > >>>>>> this > > > > > > >>>>>>> user-defined CheckpointTrigger can use to make the > > checkpoint > > > > > > >>>> decision. > > > > > > >>>>>> > > > > > > >>>>>> I honestly don't think this is important at this stage of > > the > > > > > > >>>> discussion. > > > > > > >>>>>> It could have > > > > > > >>>>>> whatever interface we would deem to be best. Required > > things: > > > > > > >>>>>> > > > > > > >>>>>> - access to at least a subset of metrics that the given > > > > > > >>>>> `CheckpointTrigger` > > > > > > >>>>>> requests, > > > > > > >>>>>> for example via some registration mechanism, so we don't > > have > > > to > > > > > > >>>> fetch > > > > > > >>>>>> all of the > > > > > > >>>>>> metrics all the time from TMs. > > > > > > >>>>>> - some way to influence `CheckpointCoordinator`. Either > via > > > > manually > > > > > > >>>>>> triggering > > > > > > >>>>>> checkpoints, and/or ability to change the checkpointing > > > > interval. > > > > > > >>>>>> > > > > > > >>>>> > > > > > > >>>>> Hmm... I honestly think it will be useful to know the APIs > > due > > > > to the > > > > > > >>>>> following reasons. > > > > > > >>>>> > > > > > > >>>>> We would need to know the concrete APIs to gauge the > > following: > > > > > > >>>>> - For the use-case mentioned in FLIP-309 motivation > section, > > > > would the > > > > > > >>>> APIs > > > > > > >>>>> of this alternative approach be more or less usable? > > > > > > >>>>> - Can these APIs reliably address the extra use-case (e.g. > > > allow > > > > > > >>>>> checkpointing interval to change dynamically even during > the > > > > unbounded > > > > > > >>>>> phase) as it claims? > > > > > > >>>>> - Can these APIs be decoupled from the APIs currently > > proposed > > > in > > > > > > >>>> FLIP-309? > > > > > > >>>>> > > > > > > >>>>> For example, if the APIs of this alternative approach can > be > > > > decoupled > > > > > > >>>> from > > > > > > >>>>> the APIs currently proposed in FLIP-309, then it might be > > > > reasonable to > > > > > > >>>>> work on this extra use-case with a more > advanced/complicated > > > > design > > > > > > >>>>> separately in a followup work. > > > > > > >>>>> > > > > > > >>>>> > > > > > > >>>>>>> - Where is this CheckpointTrigger running? For example, > is > > it > > > > going > > > > > > >>>> to > > > > > > >>>>>> run > > > > > > >>>>>>> on the subtask of every source operator? Or is it going > to > > > run > > > > on the > > > > > > >>>>> JM? > > > > > > >>>>>> > > > > > > >>>>>> IMO on the JM. > > > > > > >>>>>> > > > > > > >>>>>>> - Are we going to provide a default implementation of > this > > > > > > >>>>>>> CheckpointTrigger in Flink that implements the algorithm > > > > described > > > > > > >>>>> below, > > > > > > >>>>>>> or do we expect each source operator developer to > implement > > > > their own > > > > > > >>>>>>> CheckpointTrigger? > > > > > > >>>>>> > > > > > > >>>>>> As I mentioned before, I think we should provide at the > very > > > > least the > > > > > > >>>>>> implementation > > > > > > >>>>>> that replaces the current triggering mechanism (statically > > > > configured > > > > > > >>>>>> checkpointing interval) > > > > > > >>>>>> and it would be great to provide the backpressure > monitoring > > > > trigger > > > > > > >> as > > > > > > >>>>>> well. > > > > > > >>>>>> > > > > > > >>>>> > > > > > > >>>>> I agree that if there is a good use-case that can be > > addressed > > > > by the > > > > > > >>>>> proposed CheckpointTrigger, then it is reasonable > > > > > > >>>>> to add CheckpointTrigger and replace the current triggering > > > > mechanism > > > > > > >>>> with > > > > > > >>>>> it. > > > > > > >>>>> > > > > > > >>>>> I also agree that we will likely find such a use-case. For > > > > example, > > > > > > >>>> suppose > > > > > > >>>>> the source records have event timestamps, then it is likely > > > > > > >>>>> that we can use the trigger to dynamically control the > > > > checkpointing > > > > > > >>>>> interval based on the difference between the watermark and > > > > current > > > > > > >> system > > > > > > >>>>> time. > > > > > > >>>>> > > > > > > >>>>> But I am not sure the addition of this CheckpointTrigger > > should > > > > be > > > > > > >>>> coupled > > > > > > >>>>> with FLIP-309. Whether or not it is coupled probably > depends > > on > > > > the > > > > > > >>>>> concrete API design around CheckpointTrigger. > > > > > > >>>>> > > > > > > >>>>> If you would be adamant that the backpressure monitoring > > > doesn't > > > > cover > > > > > > >>>> well > > > > > > >>>>>> enough your use case, I would be ok to provide the hacky > > > > version that > > > > > > >> I > > > > > > >>>>>> also mentioned > > > > > > >>>>>> before: > > > > > > >>>>> > > > > > > >>>>> > > > > > > >>>>>> """ > > > > > > >>>>>> Especially that if my proposed algorithm wouldn't work > good > > > > enough, > > > > > > >>>> there > > > > > > >>>>>> is > > > > > > >>>>>> an obvious solution, that any source could add a metric, > > like > > > > let say > > > > > > >>>>>> "processingBacklog: true/false", and the > `CheckpointTrigger` > > > > > > >>>>>> could use this as an override to always switch to the > > > > > > >>>>>> "slowCheckpointInterval". I don't think we need it, but > > that's > > > > always > > > > > > >>>> an > > > > > > >>>>>> option > > > > > > >>>>>> that would be basically equivalent to your original > > proposal. > > > > > > >>>>>> """ > > > > > > >>>>>> > > > > > > >>>>> > > > > > > >>>>> Hmm.. do you mean we can do the following: > > > > > > >>>>> - Have all source operators emit a metric named > > > > "processingBacklog". > > > > > > >>>>> - Add a job-level config that specifies "the checkpointing > > > > interval to > > > > > > >> be > > > > > > >>>>> used when any source is processing backlog". > > > > > > >>>>> - The JM collects the "processingBacklog" periodically from > > all > > > > source > > > > > > >>>>> operators and uses the newly added config value as > > appropriate. > > > > > > >>>>> > > > > > > >>>>> The challenge with this approach is that we need to define > > the > > > > > > >> semantics > > > > > > >>>> of > > > > > > >>>>> this "processingBacklog" metric and have all source > operators > > > > > > >>>>> implement this metric. I am not sure we are able to do this > > yet > > > > without > > > > > > >>>>> having users explicitly provide this information on a > > > per-source > > > > basis. > > > > > > >>>>> > > > > > > >>>>> Suppose the job read from a bounded Kafka source, should it > > > emit > > > > > > >>>>> "processingBacklog=true"? If yes, then the job might use > long > > > > > > >>>> checkpointing > > > > > > >>>>> interval even > > > > > > >>>>> if the job is asked to process data starting from now to > the > > > > next 1 > > > > > > >> hour. > > > > > > >>>>> If no, then the job might use the short checkpointing > > interval > > > > > > >>>>> even if the job is asked to re-process data starting from 7 > > > days > > > > ago. > > > > > > >>>>> > > > > > > >>>>> > > > > > > >>>>>> > > > > > > >>>>>>> - How can users specify the > > > > > > >>>>>> fastCheckpointInterval/slowCheckpointInterval? > > > > > > >>>>>>> For example, will we provide APIs on the > CheckpointTrigger > > > that > > > > > > >>>>> end-users > > > > > > >>>>>>> can use to specify the checkpointing interval? What would > > > that > > > > look > > > > > > >>>>> like? > > > > > > >>>>>> > > > > > > >>>>>> Also as I mentioned before, just like metric reporters are > > > > configured: > > > > > > >>>>>> > > > > > > >>>>>> > > > > > > >>>>> > > > > > > >>>> > > > > > > >> > > > > > > > > > > https://nightlies.apache.org/flink/flink-docs-release-1.17/docs/deployment/metric_reporters/ > > > > > > >>>>>> Every CheckpointTrigger could have its own custom > > > configuration. > > > > > > >>>>>> > > > > > > >>>>>>> Overall, my gut feel is that the alternative approach > based > > > on > > > > > > >>>>>>> CheckpointTrigger is more complicated > > > > > > >>>>>> > > > > > > >>>>>> Yes, as usual, more generic things are more complicated, > but > > > > often > > > > > > >> more > > > > > > >>>>>> useful in the long run. > > > > > > >>>>>> > > > > > > >>>>>>> and harder to use. > > > > > > >>>>>> > > > > > > >>>>>> I don't agree. Why setting in config > > > > > > >>>>>> > > > > > > >>>>>> execution.checkpointing.trigger: > > > > > > >>>> BackPressureMonitoringCheckpointTrigger > > > > > > >>>>>> > > > > > > >>>>>> > > > > > > >>>>> > > > > > > >>>> > > > > > > >> > > > > > > > > > > execution.checkpointing.BackPressureMonitoringCheckpointTrigger.fast-interval: > > > > > > >>>>>> 1s > > > > > > >>>>>> > > > > > > >>>>>> > > > > > > >>>>> > > > > > > >>>> > > > > > > >> > > > > > > > > > > execution.checkpointing.BackPressureMonitoringCheckpointTrigger.slow-interval: > > > > > > >>>>>> 30s > > > > > > >>>>>> > > > > > > >>>>>> that we could even provide a shortcut to the above > construct > > > > via: > > > > > > >>>>>> > > > > > > >>>>>> execution.checkpointing.fast-interval: 1s > > > > > > >>>>>> execution.checkpointing.slow-interval: 30s > > > > > > >>>>>> > > > > > > >>>>>> is harder compared to setting two/three checkpoint > > intervals, > > > > one in > > > > > > >>>> the > > > > > > >>>>>> config/or via `env.enableCheckpointing(x)`, > > > > > > >>>>>> secondly passing one/two (fast/slow) values on the source > > > > itself? > > > > > > >>>>>> > > > > > > >>>>> > > > > > > >>>>> If we can address the use-case by providing just the two > > > > job-level > > > > > > >> config > > > > > > >>>>> as described above, I agree it will indeed be simpler. > > > > > > >>>>> > > > > > > >>>>> I have tried to achieve this goal. But the caveat is that > it > > > > requires > > > > > > >>>> much > > > > > > >>>>> more work than described above in order to give the configs > > > > > > >> well-defined > > > > > > >>>>> semantics. So I find it simpler to just use the approach in > > > > FLIP-309. > > > > > > >>>>> > > > > > > >>>>> Let me explain my concern below. It will be great if you or > > > > someone > > > > > > >> else > > > > > > >>>>> can help provide a solution. > > > > > > >>>>> > > > > > > >>>>> 1) We need to clearly document when the fast-interval and > > > > slow-interval > > > > > > >>>>> will be used so that users can derive the expected behavior > > of > > > > the job > > > > > > >>>> and > > > > > > >>>>> be able to config these values. > > > > > > >>>>> > > > > > > >>>>> 2) The trigger of fast/slow interval depends on the > behavior > > of > > > > the > > > > > > >>>> source > > > > > > >>>>> (e.g. MySQL CDC, HybridSource). However, no existing > concepts > > > of > > > > source > > > > > > >>>>> operator (e.g. boundedness) can describe the target > behavior. > > > For > > > > > > >>>> example, > > > > > > >>>>> MySQL CDC internally has two phases, namely snapshot phase > > and > > > > binlog > > > > > > >>>>> phase, which are not explicitly exposed to its users via > > source > > > > > > >> operator > > > > > > >>>>> API. And we probably should not enumerate all internal > phases > > > of > > > > all > > > > > > >>>> source > > > > > > >>>>> operators that are affected by fast/slow interval. > > > > > > >>>>> > > > > > > >>>>> 3) An alternative approach might be to define a new concept > > > (e.g. > > > > > > >>>>> processingBacklog) that is applied to all source operators. > > > Then > > > > the > > > > > > >>>>> fast/slow interval's documentation can depend on this > > concept. > > > > That > > > > > > >> means > > > > > > >>>>> we have to add a top-level concept (similar to source > > > > boundedness) and > > > > > > >>>>> require all source operators to specify how they enforce > this > > > > concept > > > > > > >>>> (e.g. > > > > > > >>>>> FileSystemSource always emits processingBacklog=true). And > > > there > > > > might > > > > > > >> be > > > > > > >>>>> cases where the source itself (e.g. a bounded Kafka Source) > > can > > > > not > > > > > > >>>>> automatically derive the value of this concept, in which > case > > > we > > > > need > > > > > > >> to > > > > > > >>>>> provide option for users to explicitly specify the value > for > > > this > > > > > > >> concept > > > > > > >>>>> on a per-source basis. > > > > > > >>>>> > > > > > > >>>>> > > > > > > >>>>> > > > > > > >>>>>>> And it probably also has the issues of "having two places > > to > > > > > > >>>> configure > > > > > > >>>>>> checkpointing > > > > > > >>>>>>> interval" and "giving flexibility for every source to > > > > implement a > > > > > > >>>>>> different > > > > > > >>>>>>> API" (as mentioned below). > > > > > > >>>>>> > > > > > > >>>>>> No, it doesn't. > > > > > > >>>>>> > > > > > > >>>>>>> IMO, it is a hard-requirement for the user-facing API to > be > > > > > > >>>>>>> clearly defined and users should be able to use the API > > > without > > > > > > >>>> concern > > > > > > >>>>>> of > > > > > > >>>>>>> regression. And this requirement is more important than > the > > > > other > > > > > > >>>> goals > > > > > > >>>>>>> discussed above because it is related to the > > > > stability/performance of > > > > > > >>>>> the > > > > > > >>>>>>> production job. What do you think? > > > > > > >>>>>> > > > > > > >>>>>> I don't agree with this. There are many things that work > > > > something in > > > > > > >>>>>> between perfectly and well enough > > > > > > >>>>>> in some fraction of use cases (maybe in 99%, maybe 95% or > > > maybe > > > > 60%), > > > > > > >>>>> while > > > > > > >>>>>> still being very useful. > > > > > > >>>>>> Good examples are: selection of state backend, unaligned > > > > checkpoints, > > > > > > >>>>>> buffer debloating but frankly if I go > > > > > > >>>>>> through list of currently available config options, > > something > > > > like > > > > > > >> half > > > > > > >>>>> of > > > > > > >>>>>> them can cause regressions. Heck, > > > > > > >>>>>> even Flink itself doesn't work perfectly in 100% of the > use > > > > cases, due > > > > > > >>>>> to a > > > > > > >>>>>> variety of design choices. Of > > > > > > >>>>>> course, the more use cases are fine with said feature, the > > > > better, but > > > > > > >>>> we > > > > > > >>>>>> shouldn't fixate to perfectly cover > > > > > > >>>>>> 100% of the cases, as that's impossible. > > > > > > >>>>>> > > > > > > >>>>>> In this particular case, if back pressure monitoring > > trigger > > > > can work > > > > > > >>>>> well > > > > > > >>>>>> enough in 95% of cases, I would > > > > > > >>>>>> say that's already better than the originally proposed > > > > alternative, > > > > > > >>>> which > > > > > > >>>>>> doesn't work at all if user has a large > > > > > > >>>>>> backlog to reprocess from Kafka, including when using > > > > HybridSource > > > > > > >>>> AFTER > > > > > > >>>>>> the switch to Kafka has > > > > > > >>>>>> happened. For the remaining 5%, we should try to improve > the > > > > behaviour > > > > > > >>>>> over > > > > > > >>>>>> time, but ultimately, users can > > > > > > >>>>>> decide to just run a fixed checkpoint interval (or at > worst > > > use > > > > the > > > > > > >>>> hacky > > > > > > >>>>>> checkpoint trigger that I mentioned > > > > > > >>>>>> before a couple of times). > > > > > > >>>>>> > > > > > > >>>>>> Also to be pedantic, if a user naively selects > slow-interval > > > in > > > > your > > > > > > >>>>>> proposal to 30 minutes, when that user's > > > > > > >>>>>> job fails on average every 15-20minutes, his job can end > up > > in > > > > a state > > > > > > >>>>> that > > > > > > >>>>>> it can not make any progress, > > > > > > >>>>>> this arguably is quite serious regression. > > > > > > >>>>>> > > > > > > >>>>> > > > > > > >>>>> I probably should not say it is "hard requirement". After > all > > > > there are > > > > > > >>>>> pros/cons. We will need to consider implementation > > complexity, > > > > > > >> usability, > > > > > > >>>>> extensibility etc. > > > > > > >>>>> > > > > > > >>>>> I just don't think we should take it for granted to > introduce > > > > > > >> regression > > > > > > >>>>> for one use-case in order to support another use-case. If > we > > > can > > > > not > > > > > > >> find > > > > > > >>>>> an algorithm/solution that addresses > > > > > > >>>>> both use-case well, I hope we can be open to tackle them > > > > separately so > > > > > > >>>> that > > > > > > >>>>> users can choose the option that best fits their needs. > > > > > > >>>>> > > > > > > >>>>> All things else being equal, I think it is preferred for > > > > user-facing > > > > > > >> API > > > > > > >>>> to > > > > > > >>>>> be clearly defined and let users should be able to use the > > API > > > > without > > > > > > >>>>> concern of regression. > > > > > > >>>>> > > > > > > >>>>> Maybe we can list pros/cons for the alternative approaches > we > > > > have been > > > > > > >>>>> discussing and see choose the best approach. And maybe we > > will > > > > end up > > > > > > >>>>> finding that use-case > > > > > > >>>>> which needs CheckpointTrigger can be tackled separately > from > > > the > > > > > > >> use-case > > > > > > >>>>> in FLIP-309. > > > > > > >>>>> > > > > > > >>>>> > > > > > > >>>>>>> I am not sure if there is a typo. Because if > > > > > > >>>>> backPressuredTimeMsPerSecond > > > > > > >>>>>> = > > > > > > >>>>>>> 0, then maxRecordsConsumedWithoutBackpressure = > > > > > > >>>> numRecordsInPerSecond / > > > > > > >>>>>>> 1000 * metricsUpdateInterval according to the above > > > algorithm. > > > > > > >>>>>>> > > > > > > >>>>>>> Do you mean "maxRecordsConsumedWithoutBackpressure = > > > > > > >>>>>> (numRecordsInPerSecond > > > > > > >>>>>>> / (1 - backPressuredTimeMsPerSecond / 1000)) * > > > > > > >>>> metricsUpdateInterval"? > > > > > > >>>>>> > > > > > > >>>>>> It looks like there is indeed some mistake in my proposal > > > > above. Yours > > > > > > >>>>> look > > > > > > >>>>>> more correct, it probably > > > > > > >>>>>> still needs some safeguard/special handling if > > > > > > >>>>>> `backPressuredTimeMsPerSecond > 950` > > > > > > >>>>>> > > > > > > >>>>>>> The only information it can access is the backlog. > > > > > > >>>>>> > > > > > > >>>>>> Again no. It can access whatever we want to provide to it. > > > > > > >>>>>> > > > > > > >>>>>> Regarding the rest of your concerns. It's a matter of > > tweaking > > > > the > > > > > > >>>>>> parameters and the algorithm itself, > > > > > > >>>>>> and how much safety-net do we want to have. Ultimately, > I'm > > > > pretty > > > > > > >> sure > > > > > > >>>>>> that's a (for 95-99% of cases) > > > > > > >>>>>> solvable problem. If not, there is always the hacky > > solution, > > > > that > > > > > > >>>> could > > > > > > >>>>> be > > > > > > >>>>>> even integrated into this above > > > > > > >>>>>> mentioned algorithm as a short circuit to always reach > > > > > > >> `slow-interval`. > > > > > > >>>>>> > > > > > > >>>>>> Apart of that, you picked 3 minutes as the checkpointing > > > > interval in > > > > > > >>>> your > > > > > > >>>>>> counter example. In most cases > > > > > > >>>>>> any interval above 1 minute would inflict pretty > negligible > > > > overheads, > > > > > > >>>> so > > > > > > >>>>>> all in all, I would doubt there is > > > > > > >>>>>> a significant benefit (in most cases) of increasing 3 > minute > > > > > > >> checkpoint > > > > > > >>>>>> interval to anything more, let alone > > > > > > >>>>>> 30 minutes. > > > > > > >>>>>> > > > > > > >>>>> > > > > > > >>>>> I am not sure we should design the algorithm with the > > > assumption > > > > that > > > > > > >> the > > > > > > >>>>> short checkpointing interval will always be higher than 1 > > > minute > > > > etc. > > > > > > >>>>> > > > > > > >>>>> I agree the proposed algorithm can solve most cases where > the > > > > resource > > > > > > >> is > > > > > > >>>>> sufficient and there is always no backlog in source > subtasks. > > > On > > > > the > > > > > > >>>> other > > > > > > >>>>> hand, what makes SRE > > > > > > >>>>> life hard is probably the remaining 1-5% cases where the > > > traffic > > > > is > > > > > > >> spiky > > > > > > >>>>> and the cluster is reaching its capacity limit. The ability > > to > > > > predict > > > > > > >>>> and > > > > > > >>>>> control Flink job's behavior (including checkpointing > > interval) > > > > can > > > > > > >>>>> considerably reduce the burden of manging Flink jobs. > > > > > > >>>>> > > > > > > >>>>> Best, > > > > > > >>>>> Dong > > > > > > >>>>> > > > > > > >>>>> > > > > > > >>>>>> > > > > > > >>>>>> Best, > > > > > > >>>>>> Piotrek > > > > > > >>>>>> > > > > > > >>>>>> > > > > > > >>>>>> > > > > > > >>>>>> > > > > > > >>>>>> > > > > > > >>>>>> sob., 3 cze 2023 o 05:44 Dong Lin <lindon...@gmail.com> > > > > napisał(a): > > > > > > >>>>>> > > > > > > >>>>>>> Hi Piotr, > > > > > > >>>>>>> > > > > > > >>>>>>> Thanks for the explanations. I have some followup > questions > > > > below. > > > > > > >>>>>>> > > > > > > >>>>>>> On Fri, Jun 2, 2023 at 10:55 PM Piotr Nowojski < > > > > pnowoj...@apache.org > > > > > > >>>>> > > > > > > >>>>>>> wrote: > > > > > > >>>>>>> > > > > > > >>>>>>>> Hi All, > > > > > > >>>>>>>> > > > > > > >>>>>>>> Thanks for chipping in the discussion Ahmed! > > > > > > >>>>>>>> > > > > > > >>>>>>>> Regarding using the REST API. Currently I'm leaning > > towards > > > > > > >>>>>> implementing > > > > > > >>>>>>>> this feature inside the Flink itself, via some pluggable > > > > interface. > > > > > > >>>>>>>> REST API solution would be tempting, but I guess not > > > everyone > > > > is > > > > > > >>>>> using > > > > > > >>>>>>>> Flink Kubernetes Operator. > > > > > > >>>>>>>> > > > > > > >>>>>>>> @Dong > > > > > > >>>>>>>> > > > > > > >>>>>>>>> I am not sure metrics such as isBackPressured are > already > > > > sent to > > > > > > >>>>> JM. > > > > > > >>>>>>>> > > > > > > >>>>>>>> Fetching code path on the JM: > > > > > > >>>>>>>> > > > > > > >>>>>>>> > > > > > > >>>>>>> > > > > > > >>>>>> > > > > > > >>>>> > > > > > > >>>> > > > > > > >> > > > > > > > > > > org.apache.flink.runtime.rest.handler.legacy.metrics.MetricFetcherImpl#queryTmMetricsFuture > > > > > > >>>>>>>> > > > > > > >>>> > > > > org.apache.flink.runtime.rest.handler.legacy.metrics.MetricStore#add > > > > > > >>>>>>>> > > > > > > >>>>>>>> Example code path accessing Task level metrics via JM > > using > > > > the > > > > > > >>>>>>>> `MetricStore`: > > > > > > >>>>>>>> > > > > > > >>>>>>>> > > > > > > >>>>>>> > > > > > > >>>>>> > > > > > > >>>>> > > > > > > >>>> > > > > > > >> > > > > > > > > > > org.apache.flink.runtime.rest.handler.job.metrics.AggregatingSubtasksMetricsHandler > > > > > > >>>>>>>> > > > > > > >>>>>>> > > > > > > >>>>>>> Thanks for the code reference. I checked the code that > > > invoked > > > > these > > > > > > >>>>> two > > > > > > >>>>>>> classes and found the following information: > > > > > > >>>>>>> > > > > > > >>>>>>> - AggregatingSubtasksMetricsHandler#getStoresis currently > > > > invoked > > > > > > >>>> only > > > > > > >>>>>>> when AggregatingJobsMetricsHandler is invoked. > > > > > > >>>>>>> - AggregatingJobsMetricsHandler is only instantiated and > > > > returned by > > > > > > >>>>>>> WebMonitorEndpoint#initializeHandlers > > > > > > >>>>>>> - WebMonitorEndpoint#initializeHandlers is only used by > > > > > > >>>>>> RestServerEndpoint. > > > > > > >>>>>>> And RestServerEndpoint invokes these handlers in response > > to > > > > external > > > > > > >>>>>> REST > > > > > > >>>>>>> request. > > > > > > >>>>>>> > > > > > > >>>>>>> I understand that JM will get the backpressure-related > > > metrics > > > > every > > > > > > >>>>> time > > > > > > >>>>>>> the RestServerEndpoint receives the REST request to get > > these > > > > > > >>>> metrics. > > > > > > >>>>>> But > > > > > > >>>>>>> I am not sure if RestServerEndpoint is already always > > > > receiving the > > > > > > >>>>> REST > > > > > > >>>>>>> metrics at regular interval (suppose there is no human > > > manually > > > > > > >>>>>>> opening/clicking the Flink Web UI). And if it does, what > is > > > the > > > > > > >>>>> interval? > > > > > > >>>>>>> > > > > > > >>>>>>> > > > > > > >>>>>>> > > > > > > >>>>>>>>> For example, let's say every source operator subtask > > > reports > > > > this > > > > > > >>>>>>> metric > > > > > > >>>>>>>> to > > > > > > >>>>>>>>> JM once every 10 seconds. There are 100 source > subtasks. > > > And > > > > each > > > > > > >>>>>>> subtask > > > > > > >>>>>>>>> is backpressured roughly 10% of the total time due to > > > traffic > > > > > > >>>>> spikes > > > > > > >>>>>>> (and > > > > > > >>>>>>>>> limited buffer). Then at any given time, there are 1 - > > > > 0.9^100 = > > > > > > >>>>>>> 99.997% > > > > > > >>>>>>>>> chance that there is at least one subtask that is > > > > backpressured. > > > > > > >>>>> Then > > > > > > >>>>>>> we > > > > > > >>>>>>>>> have to wait for at least 10 seconds to check again. > > > > > > >>>>>>>> > > > > > > >>>>>>>> backPressuredTimeMsPerSecond and other related metrics > > (like > > > > > > >>>>>>>> busyTimeMsPerSecond) are not subject to that problem. > > > > > > >>>>>>>> They are recalculated once every metric fetching > interval, > > > > and they > > > > > > >>>>>>> report > > > > > > >>>>>>>> accurately on average the given subtask spent > > > > > > >>>>>> busy/idling/backpressured. > > > > > > >>>>>>>> In your example, backPressuredTimeMsPerSecond would > report > > > > 100ms/s. > > > > > > >>>>>>> > > > > > > >>>>>>> > > > > > > >>>>>>> Suppose every subtask is already reporting > > > > > > >>>> backPressuredTimeMsPerSecond > > > > > > >>>>>> to > > > > > > >>>>>>> JM once every 100 ms. If a job has 10 operators (that are > > not > > > > > > >>>> chained) > > > > > > >>>>>> and > > > > > > >>>>>>> each operator has 100 subtasks, then JM would need to > > handle > > > > 10000 > > > > > > >>>>>> requests > > > > > > >>>>>>> per second to receive metrics from these 1000 subtasks. > It > > > > seems > > > > > > >>>> like a > > > > > > >>>>>>> non-trivial overhead for medium-to-large sized jobs and > can > > > > make JM > > > > > > >>>> the > > > > > > >>>>>>> performance bottleneck during job execution. > > > > > > >>>>>>> > > > > > > >>>>>>> I would be surprised if Flink is already paying this much > > > > overhead > > > > > > >>>> just > > > > > > >>>>>> for > > > > > > >>>>>>> metrics monitoring. That is the main reason I still doubt > > it > > > > is true. > > > > > > >>>>> Can > > > > > > >>>>>>> you show where this 100 ms is currently configured? > > > > > > >>>>>>> > > > > > > >>>>>>> Alternatively, maybe you mean that we should add extra > code > > > to > > > > invoke > > > > > > >>>>> the > > > > > > >>>>>>> REST API at 100 ms interval. Then that means we need to > > > > considerably > > > > > > >>>>>>> increase the network/cpu overhead at JM, where the > overhead > > > > will > > > > > > >>>>> increase > > > > > > >>>>>>> as the number of TM/slots increase, which may pose risk > to > > > the > > > > > > >>>>>> scalability > > > > > > >>>>>>> of the proposed design. I am not sure we should do this. > > What > > > > do you > > > > > > >>>>>> think? > > > > > > >>>>>>> > > > > > > >>>>>>> > > > > > > >>>>>>>> > > > > > > >>>>>>>>> While it will be nice to support additional use-cases > > > > > > >>>>>>>>> with one proposal, it is probably also reasonable to > make > > > > > > >>>>> incremental > > > > > > >>>>>>>>> progress and support the low-hanging-fruit use-case > > first. > > > > The > > > > > > >>>>> choice > > > > > > >>>>>>>>> really depends on the complexity and the importance of > > > > supporting > > > > > > >>>>> the > > > > > > >>>>>>>> extra > > > > > > >>>>>>>>> use-cases. > > > > > > >>>>>>>> > > > > > > >>>>>>>> That would be true, if that was a private implementation > > > > detail or > > > > > > >>>> if > > > > > > >>>>>> the > > > > > > >>>>>>>> low-hanging-fruit-solution would be on the direct path > to > > > the > > > > final > > > > > > >>>>>>>> solution. > > > > > > >>>>>>>> That's unfortunately not the case here. This will add > > public > > > > facing > > > > > > >>>>>> API, > > > > > > >>>>>>>> that we will later need to maintain, no matter what the > > > final > > > > > > >>>>> solution > > > > > > >>>>>>> will > > > > > > >>>>>>>> be, > > > > > > >>>>>>>> and at the moment at least I don't see it being related > > to a > > > > > > >>>>> "perfect" > > > > > > >>>>>>>> solution. > > > > > > >>>>>>> > > > > > > >>>>>>> > > > > > > >>>>>>> Sure. Then let's decide the final solution first. > > > > > > >>>>>>> > > > > > > >>>>>>> > > > > > > >>>>>>>>> I guess the point is that the suggested approach, which > > > > > > >>>> dynamically > > > > > > >>>>>>>>> determines the checkpointing interval based on the > > > > backpressure, > > > > > > >>>>> may > > > > > > >>>>>>>> cause > > > > > > >>>>>>>>> regression when the checkpointing interval is > relatively > > > low. > > > > > > >>>> This > > > > > > >>>>>>> makes > > > > > > >>>>>>>> it > > > > > > >>>>>>>>> hard for users to enable this feature in production. It > > is > > > > like > > > > > > >>>> an > > > > > > >>>>>>>>> auto-driving system that is not guaranteed to work > > > > > > >>>>>>>> > > > > > > >>>>>>>> Yes, creating a more generic solution that would require > > > less > > > > > > >>>>>>> configuration > > > > > > >>>>>>>> is usually more difficult then static configurations. > > > > > > >>>>>>>> It doesn't mean we shouldn't try to do that. Especially > > that > > > > if my > > > > > > >>>>>>> proposed > > > > > > >>>>>>>> algorithm wouldn't work good enough, there is > > > > > > >>>>>>>> an obvious solution, that any source could add a metric, > > > like > > > > let > > > > > > >>>> say > > > > > > >>>>>>>> "processingBacklog: true/false", and the > > `CheckpointTrigger` > > > > > > >>>>>>>> could use this as an override to always switch to the > > > > > > >>>>>>>> "slowCheckpointInterval". I don't think we need it, but > > > that's > > > > > > >>>> always > > > > > > >>>>>> an > > > > > > >>>>>>>> option > > > > > > >>>>>>>> that would be basically equivalent to your original > > > proposal. > > > > Or > > > > > > >>>> even > > > > > > >>>>>>>> source could add "suggestedCheckpointInterval : int", > and > > > > > > >>>>>>>> `CheckpointTrigger` could use that value if present as a > > > hint > > > > in > > > > > > >>>> one > > > > > > >>>>>> way > > > > > > >>>>>>> or > > > > > > >>>>>>>> another. > > > > > > >>>>>>>> > > > > > > >>>>>>> > > > > > > >>>>>>> So far we have talked about the possibility of using > > > > > > >>>> CheckpointTrigger > > > > > > >>>>>> and > > > > > > >>>>>>> mentioned the CheckpointTrigger > > > > > > >>>>>>> and read metric values. > > > > > > >>>>>>> > > > > > > >>>>>>> Can you help answer the following questions so that I can > > > > understand > > > > > > >>>>> the > > > > > > >>>>>>> alternative solution more concretely: > > > > > > >>>>>>> > > > > > > >>>>>>> - What is the interface of this CheckpointTrigger? For > > > > example, are > > > > > > >>>> we > > > > > > >>>>>>> going to give CheckpointTrigger a context that it can use > > to > > > > fetch > > > > > > >>>>>>> arbitrary metric values? This can help us understand what > > > > information > > > > > > >>>>>> this > > > > > > >>>>>>> user-defined CheckpointTrigger can use to make the > > checkpoint > > > > > > >>>> decision. > > > > > > >>>>>>> - Where is this CheckpointTrigger running? For example, > is > > it > > > > going > > > > > > >>>> to > > > > > > >>>>>> run > > > > > > >>>>>>> on the subtask of every source operator? Or is it going > to > > > run > > > > on the > > > > > > >>>>> JM? > > > > > > >>>>>>> - Are we going to provide a default implementation of > this > > > > > > >>>>>>> CheckpointTrigger in Flink that implements the algorithm > > > > described > > > > > > >>>>> below, > > > > > > >>>>>>> or do we expect each source operator developer to > implement > > > > their own > > > > > > >>>>>>> CheckpointTrigger? > > > > > > >>>>>>> - How can users specify the > > > > > > >>>>>> fastCheckpointInterval/slowCheckpointInterval? > > > > > > >>>>>>> For example, will we provide APIs on the > CheckpointTrigger > > > that > > > > > > >>>>> end-users > > > > > > >>>>>>> can use to specify the checkpointing interval? What would > > > that > > > > look > > > > > > >>>>> like? > > > > > > >>>>>>> > > > > > > >>>>>>> Overall, my gut feel is that the alternative approach > based > > > on > > > > > > >>>>>>> CheckpointTrigger is more complicated and harder to use. > > And > > > it > > > > > > >>>>> probably > > > > > > >>>>>>> also has the issues of "having two places to configure > > > > checkpointing > > > > > > >>>>>>> interval" and "giving flexibility for every source to > > > > implement a > > > > > > >>>>>> different > > > > > > >>>>>>> API" (as mentioned below). > > > > > > >>>>>>> > > > > > > >>>>>>> Maybe we can evaluate it more after knowing the answers > to > > > the > > > > above > > > > > > >>>>>>> questions. > > > > > > >>>>>>> > > > > > > >>>>>>> > > > > > > >>>>>>> > > > > > > >>>>>>>> > > > > > > >>>>>>>>> On the other hand, the approach currently proposed in > the > > > > FLIP is > > > > > > >>>>>> much > > > > > > >>>>>>>>> simpler as it does not depend on backpressure. Users > > > specify > > > > the > > > > > > >>>>>> extra > > > > > > >>>>>>>>> interval requirement on the specific sources (e.g. > > > > HybridSource, > > > > > > >>>>>> MySQL > > > > > > >>>>>>>> CDC > > > > > > >>>>>>>>> Source) and can easily know the checkpointing interval > > will > > > > be > > > > > > >>>> used > > > > > > >>>>>> on > > > > > > >>>>>>>> the > > > > > > >>>>>>>>> continuous phase of the corresponding source. This is > > > pretty > > > > much > > > > > > >>>>>> same > > > > > > >>>>>>> as > > > > > > >>>>>>>>> how users use the existing > > execution.checkpointing.interval > > > > > > >>>> config. > > > > > > >>>>>> So > > > > > > >>>>>>>>> there is no extra concern of regression caused by this > > > > approach. > > > > > > >>>>>>>> > > > > > > >>>>>>>> To an extent, but as I have already previously > mentioned I > > > > really > > > > > > >>>>>> really > > > > > > >>>>>>> do > > > > > > >>>>>>>> not like idea of: > > > > > > >>>>>>>> - having two places to configure checkpointing interval > > > > (config > > > > > > >>>>> file > > > > > > >>>>>>> and > > > > > > >>>>>>>> in the Source builders) > > > > > > >>>>>>>> - giving flexibility for every source to implement a > > > different > > > > > > >>>> API > > > > > > >>>>>> for > > > > > > >>>>>>>> that purpose > > > > > > >>>>>>>> - creating a solution that is not generic enough, so > that > > we > > > > will > > > > > > >>>>>> need > > > > > > >>>>>>> a > > > > > > >>>>>>>> completely different mechanism in the future anyway > > > > > > >>>>>>>> > > > > > > >>>>>>> > > > > > > >>>>>>> Yeah, I understand different developers might have > > different > > > > > > >>>>>>> concerns/tastes for these APIs. Ultimately, there might > not > > > be > > > > a > > > > > > >>>>> perfect > > > > > > >>>>>>> solution and we have to choose based on the pros/cons of > > > these > > > > > > >>>>> solutions. > > > > > > >>>>>>> > > > > > > >>>>>>> I agree with you that, all things being equal, it is > > > > preferable to 1) > > > > > > >>>>>> have > > > > > > >>>>>>> one place to configure checkpointing intervals, 2) have > all > > > > source > > > > > > >>>>>>> operators use the same API, and 3) create a solution that > > is > > > > generic > > > > > > >>>>> and > > > > > > >>>>>>> last lasting. Note that these three goals affects the > > > > usability and > > > > > > >>>>>>> extensibility of the API, but not necessarily the > > > > > > >>>> stability/performance > > > > > > >>>>>> of > > > > > > >>>>>>> the production job. > > > > > > >>>>>>> > > > > > > >>>>>>> BTW, there are also other preferrable goals. For example, > > it > > > > is very > > > > > > >>>>>> useful > > > > > > >>>>>>> for the job's behavior to be predictable and > interpretable > > so > > > > that > > > > > > >>>> SRE > > > > > > >>>>>> can > > > > > > >>>>>>> operator/debug the Flink in an easier way. We can list > > these > > > > > > >>>> pros/cons > > > > > > >>>>>>> altogether later. > > > > > > >>>>>>> > > > > > > >>>>>>> I am wondering if we can first agree on the priority of > > goals > > > > we want > > > > > > >>>>> to > > > > > > >>>>>>> achieve. IMO, it is a hard-requirement for the > user-facing > > > API > > > > to be > > > > > > >>>>>>> clearly defined and users should be able to use the API > > > without > > > > > > >>>> concern > > > > > > >>>>>> of > > > > > > >>>>>>> regression. And this requirement is more important than > the > > > > other > > > > > > >>>> goals > > > > > > >>>>>>> discussed above because it is related to the > > > > stability/performance of > > > > > > >>>>> the > > > > > > >>>>>>> production job. What do you think? > > > > > > >>>>>>> > > > > > > >>>>>>> > > > > > > >>>>>>>> > > > > > > >>>>>>>>> Sounds good. Looking forward to learning more ideas. > > > > > > >>>>>>>> > > > > > > >>>>>>>> I have thought about this a bit more, and I think we > don't > > > > need to > > > > > > >>>>>> check > > > > > > >>>>>>>> for the backpressure status, or how much overloaded all > of > > > the > > > > > > >>>>>> operators > > > > > > >>>>>>>> are. > > > > > > >>>>>>>> We could just check three things for source operators: > > > > > > >>>>>>>> 1. pendingRecords (backlog length) > > > > > > >>>>>>>> 2. numRecordsInPerSecond > > > > > > >>>>>>>> 3. backPressuredTimeMsPerSecond > > > > > > >>>>>>>> > > > > > > >>>>>>>> // int metricsUpdateInterval = 10s // obtained from > config > > > > > > >>>>>>>> // Next line calculates how many records can we consume > > from > > > > the > > > > > > >>>>>> backlog, > > > > > > >>>>>>>> assuming > > > > > > >>>>>>>> // that magically the reason behind a backpressure > > vanishes. > > > > We > > > > > > >>>> will > > > > > > >>>>>> use > > > > > > >>>>>>>> this only as > > > > > > >>>>>>>> // a safeguard against scenarios like for example if > > > > backpressure > > > > > > >>>>> was > > > > > > >>>>>>>> caused by some > > > > > > >>>>>>>> // intermittent failure/performance degradation. > > > > > > >>>>>>>> maxRecordsConsumedWithoutBackpressure = > > > > (numRecordsInPerSecond / > > > > > > >>>>> (1000 > > > > > > >>>>>>>> - backPressuredTimeMsPerSecond / 1000)) * > > > > metricsUpdateInterval > > > > > > >>>>>>>> > > > > > > >>>>>>> > > > > > > >>>>>>> I am not sure if there is a typo. Because if > > > > > > >>>>>> backPressuredTimeMsPerSecond = > > > > > > >>>>>>> 0, then maxRecordsConsumedWithoutBackpressure = > > > > > > >>>> numRecordsInPerSecond / > > > > > > >>>>>>> 1000 * metricsUpdateInterval according to the above > > > algorithm. > > > > > > >>>>>>> > > > > > > >>>>>>> Do you mean "maxRecordsConsumedWithoutBackpressure = > > > > > > >>>>>> (numRecordsInPerSecond > > > > > > >>>>>>> / (1 - backPressuredTimeMsPerSecond / 1000)) * > > > > > > >>>> metricsUpdateInterval"? > > > > > > >>>>>>> > > > > > > >>>>>>> > > > > > > >>>>>>>> > > > > > > >>>>>>>> // we are excluding > maxRecordsConsumedWithoutBackpressure > > > > from the > > > > > > >>>>>>> backlog > > > > > > >>>>>>>> as > > > > > > >>>>>>>> // a safeguard against an intermittent back pressure > > > > problems, so > > > > > > >>>>> that > > > > > > >>>>>> we > > > > > > >>>>>>>> don't > > > > > > >>>>>>>> // calculate next checkpoint interval far far in the > > future, > > > > while > > > > > > >>>>> the > > > > > > >>>>>>>> backpressure > > > > > > >>>>>>>> // goes away before we will recalculate metrics and new > > > > > > >>>> checkpointing > > > > > > >>>>>>>> interval > > > > > > >>>>>>>> timeToConsumeBacklog = (pendingRecords - > > > > > > >>>>>>>> maxRecordsConsumedWithoutBackpressure) / > > > numRecordsInPerSecond > > > > > > >>>>>>>> > > > > > > >>>>>>>> > > > > > > >>>>>>>> Then we can use those numbers to calculate desired > > > > checkpointed > > > > > > >>>>>> interval > > > > > > >>>>>>>> for example like this: > > > > > > >>>>>>>> > > > > > > >>>>>>>> long calculatedCheckpointInterval = > timeToConsumeBacklog / > > > 10; > > > > > > >>>> //this > > > > > > >>>>>> may > > > > > > >>>>>>>> need some refining > > > > > > >>>>>>>> long nextCheckpointInterval = > > > min(max(fastCheckpointInterval, > > > > > > >>>>>>>> calculatedCheckpointInterval), slowCheckpointInterval); > > > > > > >>>>>>>> long nextCheckpointTs = lastCheckpointTs + > > > > nextCheckpointInterval; > > > > > > >>>>>>>> > > > > > > >>>>>>>> WDYT? > > > > > > >>>>>>> > > > > > > >>>>>>> > > > > > > >>>>>>> I think the idea of the above algorithm is to incline to > > use > > > > the > > > > > > >>>>>>> fastCheckpointInterval unless we are very sure the > backlog > > > > will take > > > > > > >>>> a > > > > > > >>>>>> long > > > > > > >>>>>>> time to process. This can alleviate the concern of > > regression > > > > during > > > > > > >>>>> the > > > > > > >>>>>>> continuous_bounded phase since we are more likely to use > > the > > > > > > >>>>>>> fastCheckpointInterval. However, it can cause regression > > > > during the > > > > > > >>>>>> bounded > > > > > > >>>>>>> phase. > > > > > > >>>>>>> > > > > > > >>>>>>> I will use a concrete example to explain the risk of > > > > regression: > > > > > > >>>>>>> - The user is using HybridSource to read from HDFS > followed > > > by > > > > Kafka. > > > > > > >>>>> The > > > > > > >>>>>>> data in HDFS is old and there is no need for data > freshness > > > > for the > > > > > > >>>>> data > > > > > > >>>>>> in > > > > > > >>>>>>> HDFS. > > > > > > >>>>>>> - The user configures the job as below: > > > > > > >>>>>>> - fastCheckpointInterval = 3 minutes > > > > > > >>>>>>> - slowCheckpointInterval = 30 minutes > > > > > > >>>>>>> - metricsUpdateInterval = 100 ms > > > > > > >>>>>>> > > > > > > >>>>>>> Using the above formulate, we can know that once > > > pendingRecords > > > > > > >>>>>>> <= numRecordsInPerSecond * 30-minutes, then > > > > > > >>>>> calculatedCheckpointInterval > > > > > > >>>>>> <= > > > > > > >>>>>>> 3 minutes, meaning that we will use > slowCheckpointInterval > > as > > > > the > > > > > > >>>>>>> checkpointing interval. Then in the last 30 minutes of > the > > > > bounded > > > > > > >>>>> phase, > > > > > > >>>>>>> the checkpointing frequency will be 10X higher than what > > the > > > > user > > > > > > >>>>> wants. > > > > > > >>>>>>> > > > > > > >>>>>>> Also note that the same issue would also considerably > limit > > > the > > > > > > >>>>> benefits > > > > > > >>>>>> of > > > > > > >>>>>>> the algorithm. For example, during the continuous phase, > > the > > > > > > >>>> algorithm > > > > > > >>>>>> will > > > > > > >>>>>>> only be better than the approach in FLIP-309 when there > is > > at > > > > least > > > > > > >>>>>>> 30-minutes worth of backlog in the source. > > > > > > >>>>>>> > > > > > > >>>>>>> Sure, having a slower checkpointing interval in this > > extreme > > > > case > > > > > > >>>>> (where > > > > > > >>>>>>> there is 30-minutes backlog in the continous-unbounded > > phase) > > > > is > > > > > > >>>> still > > > > > > >>>>>>> useful when this happens. But since this is the un-common > > > > case, and > > > > > > >>>> the > > > > > > >>>>>>> right solution is probably to do capacity planning to > avoid > > > > this from > > > > > > >>>>>>> happening in the first place, I am not sure it is worth > > > > optimizing > > > > > > >>>> for > > > > > > >>>>>> this > > > > > > >>>>>>> case at the cost of regression in the bounded phase and > the > > > > reduced > > > > > > >>>>>>> operational predictability for users (e.g. what > > checkpointing > > > > > > >>>> interval > > > > > > >>>>>>> should I expect at this stage of the job). > > > > > > >>>>>>> > > > > > > >>>>>>> I think the fundamental issue with this algorithm is that > > it > > > is > > > > > > >>>> applied > > > > > > >>>>>> to > > > > > > >>>>>>> both the bounded phases and the continous_unbounded > phases > > > > without > > > > > > >>>>>> knowing > > > > > > >>>>>>> which phase the job is running at. The only information > it > > > can > > > > access > > > > > > >>>>> is > > > > > > >>>>>>> the backlog. But two sources with the same amount of > > backlog > > > > do not > > > > > > >>>>>>> necessarily mean they have the same data freshness > > > requirement. > > > > > > >>>>>>> > > > > > > >>>>>>> In this particular example, users know that the data in > > HDFS > > > > is very > > > > > > >>>>> old > > > > > > >>>>>>> and there is no need for data freshness. Users can > express > > > > signals > > > > > > >>>> via > > > > > > >>>>>> the > > > > > > >>>>>>> per-source API proposed in the FLIP. This is why the > > current > > > > approach > > > > > > >>>>> in > > > > > > >>>>>>> FLIP-309 can be better in this case. > > > > > > >>>>>>> > > > > > > >>>>>>> What do you think? > > > > > > >>>>>>> > > > > > > >>>>>>> Best, > > > > > > >>>>>>> Dong > > > > > > >>>>>>> > > > > > > >>>>>>> > > > > > > >>>>>>>> > > > > > > >>>>>>>> Best, > > > > > > >>>>>>>> Piotrek > > > > > > >>>>>>>> > > > > > > >>>>>>>> > > > > > > >>>>>>> > > > > > > >>>>>> > > > > > > >>>>> > > > > > > >>>> > > > > > > >> > > > > > > >> > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > >
