Hi Gyula Thanks for the clarification!
Best Rui Fan On Fri, Nov 25, 2022 at 1:50 PM Gyula Fóra <gyula.f...@gmail.com> wrote: > Rui, Prasanna: > > I am afraid that creating a completely independent autoscaler process that > works with any type of Flink clusters is out of scope right now due to the > following reasons: > > If we were to create a new general process, we would have to implement high > availability and a pluggable mechanism to durably store metadata etc. The > process itself would also have to run somewhere so we would have to provide > integrations. > > It would also not be able to scale clusters easily without adding > Kubernetes-operator-like functionality to it, and if the user has to do it > manually most of the value is already lost. > > Last but not least this would have the potential of interfering with other > actions the user might be currently doing, making the autoscaler itself > complex and more unreliable. > > These are all prohibitive reasons at this point. We already have a > prototype that tackle these smoothly as part of the Kubernetes operator. > > Instead of trying to put the autoscaler somewhere else we might also > consider supporting different cluster types within the Kubernetes operator. > While that might sound silly at first, it is of similar scope to your > suggestions and could help the problem. > > As for the new config question, we could collectively decide to backport > this feature to enable the autoscaler as it is a very minor change. > > Gyula > > On Fri, 25 Nov 2022 at 06:21, John Roesler <vvcep...@apache.org> wrote: > > > Thanks for this answer, Gyula! > > -John > > > > On Thu, Nov 24, 2022, at 14:53, Gyula Fóra wrote: > > > Hi John! > > > > > > Thank you for the excellent question. > > > > > > There are few reasons why we felt that the operator is the right place > > for > > > this component: > > > > > > - Ideally the autoscaler is a separate process (an outside observer) , > > and > > > the jobmanager is very much tied to the lifecycle of the job. The > > operator > > > is a perfect example of such an external process that lives beyond > > > individual jobs. > > > - Scaling itself might need some external resource management (for > > > standalone clusters) that the jobmanager is not capable of, and the > logic > > > is already in the operator > > > - Adding this to the operator allows us to integrate this fully in the > > > lifecycle management of the application. This guarantees that scaling > > > decisions do not interfere with upgrades, suspends etc. > > > - By adding it to the operator, the autoscaler can potentially work on > > > older Flink versions as well > > > - The jobmanager is a component designed to handle Flink individual > jobs, > > > but the autoscaler component needs to work on a higher abstraction > layer > > to > > > be able to integrate with user job upgrades etc. > > > > > > These are some of the main things that come to my mind :) > > > > > > Having it in the operator ties this logic to Kubernetes itself but we > > feel > > > that an autoscaler is mostly relevant in an elastic cloud environment > > > anyways. > > > > > > Cheers, > > > Gyula > > > > > > On Thu, Nov 24, 2022 at 9:40 PM John Roesler <vvcep...@apache.org> > > wrote: > > > > > >> Hi Max, > > >> > > >> Thanks for the FLIP! > > >> > > >> I’ve been curious about one one point. I can imagine some good reasons > > for > > >> it but wonder what you have in mind. What’s the reason to add auto > > scaling > > >> to the Operator instead of to the JobManager? > > >> > > >> It seems like adding that capability to the JobManager would be a > bigger > > >> project, but it also would create some interesting opportunities. > > >> > > >> This is certainly not a suggestion, just a question. > > >> > > >> Thanks! > > >> John > > >> > > >> On Wed, Nov 23, 2022, at 10:12, Maximilian Michels wrote: > > >> > Thanks for your comments @Dong and @Chen. It is true that not all > the > > >> > details are contained in the FLIP. The document is meant as a > general > > >> > design concept. > > >> > > > >> > As for the rescaling time, this is going to be a configurable > setting > > for > > >> > now but it is foreseeable that we will provide auto-tuning of this > > >> > configuration value by observing the job restart time. Same goes for > > the > > >> > scaling decision itself which can learn from previous decisions. But > > we > > >> > want to keep it simple for the first version. > > >> > > > >> > For sources that do not support the pendingRecords metric, we are > > >> planning > > >> > to either give the user the choice to set a manual target rate, or > > scale > > >> it > > >> > purely based on its utilization as reported via busyTimeMsPerSecond. > > In > > >> > case of legacy sources, we will skip scaling these branches entirely > > >> > because they support neither of these metrics. > > >> > > > >> > -Max > > >> > > > >> > On Mon, Nov 21, 2022 at 11:27 AM Maximilian Michels <m...@apache.org > > > > >> wrote: > > >> > > > >> >> >Do we think the scaler could be a plugin or hard coded ? > > >> >> > > >> >> +1 For pluggable scaling logic. > > >> >> > > >> >> On Mon, Nov 21, 2022 at 3:38 AM Chen Qin <qinnc...@gmail.com> > wrote: > > >> >> > > >> >>> On Sun, Nov 20, 2022 at 7:25 AM Gyula Fóra <gyula.f...@gmail.com> > > >> wrote: > > >> >>> > > >> >>> > Hi Chen! > > >> >>> > > > >> >>> > I think in the long term it makes sense to provide some > pluggable > > >> >>> > mechanisms but it's not completely trivial where exactly you > would > > >> plug > > >> >>> in > > >> >>> > your custom logic at this point. > > >> >>> > > > >> >>> sounds good, more specifically would be great if it can accept > input > > >> >>> features > > >> >>> (including previous scaling decisions) and output decisions. > > >> >>> Folks might keep their own secret sauce and avoid patching oss > fork. > > >> >>> > > >> >>> > > > >> >>> > In any case the problems you mentioned should be solved robustly > > by > > >> the > > >> >>> > algorithm itself without any customization: > > >> >>> > - We need to be able to detect ineffective scaling decisions, > > let\s > > >> >>> say we > > >> >>> > scaled up (expecting better throughput with a higher > parallelism) > > >> but we > > >> >>> > did not get a better processing capacity (this would be the > > external > > >> >>> > service bottleneck) > > >> >>> > > > >> >>> sounds good, so we would at least try restart job once (optimistic > > >> path) > > >> >>> as > > >> >>> design choice. > > >> >>> > > >> >>> > - We are evaluating metrics in windows, and we have some > flexible > > >> >>> > boundaries to avoid scaling on minor load spikes > > >> >>> > > > >> >>> yes, would be great if user can feed in throughput changes over > > >> different > > >> >>> time buckets (last 10s, 30s, 1 min,5 mins) as input features > > >> >>> > > >> >>> > > > >> >>> > Regards, > > >> >>> > Gyula > > >> >>> > > > >> >>> > On Sun, Nov 20, 2022 at 12:28 AM Chen Qin <qinnc...@gmail.com> > > >> wrote: > > >> >>> > > > >> >>> > > Hi Gyula, > > >> >>> > > > > >> >>> > > Do we think the scaler could be a plugin or hard coded ? > > >> >>> > > We observed some cases scaler can't address (e.g async io > > >> dependency > > >> >>> > > service degradation or small spike that doesn't worth > restarting > > >> job) > > >> >>> > > > > >> >>> > > Thanks, > > >> >>> > > Chen > > >> >>> > > > > >> >>> > > On Fri, Nov 18, 2022 at 1:03 AM Gyula Fóra < > > gyula.f...@gmail.com> > > >> >>> wrote: > > >> >>> > > > > >> >>> > > > Hi Dong! > > >> >>> > > > > > >> >>> > > > Could you please confirm that your main concerns have been > > >> >>> addressed? > > >> >>> > > > > > >> >>> > > > Some other minor details that might not have been fully > > >> clarified: > > >> >>> > > > - The prototype has been validated on some production > > workloads > > >> yes > > >> >>> > > > - We are only planning to use metrics that are generally > > >> available > > >> >>> and > > >> >>> > > are > > >> >>> > > > previously accepted to be standardized connector metrics > (not > > >> Kafka > > >> >>> > > > specific). This is actually specified in the FLIP > > >> >>> > > > - Even if some metrics (such as pendingRecords) are not > > >> accessible > > >> >>> the > > >> >>> > > > scaling algorithm works and can be used. For source scaling > > >> based on > > >> >>> > > > utilization alone we still need some trivial modifications > on > > the > > >> >>> > > > implementation side. > > >> >>> > > > > > >> >>> > > > Cheers, > > >> >>> > > > Gyula > > >> >>> > > > > > >> >>> > > > On Thu, Nov 17, 2022 at 5:22 PM Gyula Fóra < > > gyula.f...@gmail.com > > >> > > > >> >>> > wrote: > > >> >>> > > > > > >> >>> > > > > Hi Dong! > > >> >>> > > > > > > >> >>> > > > > This is not an experimental feature proposal. The > > >> implementation > > >> >>> of > > >> >>> > the > > >> >>> > > > > prototype is still in an experimental phase but by the > time > > the > > >> >>> FLIP, > > >> >>> > > > > initial prototype and review is done, this should be in a > > good > > >> >>> stable > > >> >>> > > > first > > >> >>> > > > > version. > > >> >>> > > > > This proposal is pretty general as autoscalers/tuners get > as > > >> far > > >> >>> as I > > >> >>> > > > > understand and there is no history of any alternative > effort > > >> that > > >> >>> > even > > >> >>> > > > > comes close to the applicability of this solution. > > >> >>> > > > > > > >> >>> > > > > Any large features that were added to Flink in the past > have > > >> gone > > >> >>> > > through > > >> >>> > > > > several iterations over the years and the APIs have > evolved > > as > > >> >>> they > > >> >>> > > > matured. > > >> >>> > > > > Something like the autoscaler can only be successful if > > there > > >> is > > >> >>> > enough > > >> >>> > > > > user exposure and feedback to make it good, putting it in > an > > >> >>> external > > >> >>> > > > repo > > >> >>> > > > > will not get us anywhere. > > >> >>> > > > > > > >> >>> > > > > We have a prototype implementation ready that works well > and > > >> it is > > >> >>> > more > > >> >>> > > > or > > >> >>> > > > > less feature complete. We proposed this FLIP based on > > something > > >> >>> that > > >> >>> > we > > >> >>> > > > see > > >> >>> > > > > as a working solution, please do not underestimate the > > effort > > >> that > > >> >>> > went > > >> >>> > > > > into this proposal and the validation of the ideas. So in > > this > > >> >>> sense > > >> >>> > > our > > >> >>> > > > > approach here is the same as with the Table Store and > > >> Kubernetes > > >> >>> > > Operator > > >> >>> > > > > and other big components of the past. On the other hand > it's > > >> >>> > impossible > > >> >>> > > > to > > >> >>> > > > > sufficiently explain all the technical > depth/implementation > > >> >>> details > > >> >>> > of > > >> >>> > > > such > > >> >>> > > > > complex components in FLIPs to 100%, I feel we have a good > > >> >>> overview > > >> >>> > of > > >> >>> > > > the > > >> >>> > > > > algorithm in the FLIP and the implementation should cover > > all > > >> >>> > remaining > > >> >>> > > > > questions. We will have an extended code review phase > > following > > >> >>> the > > >> >>> > > FLIP > > >> >>> > > > > vote before this make it into the project. > > >> >>> > > > > > > >> >>> > > > > I understand your concern regarding the stability of Flink > > >> >>> Kubernetes > > >> >>> > > > > Operator config and metric names. We have decided to not > > >> provide > > >> >>> > > > guarantees > > >> >>> > > > > there yet but if you feel that it's time for the operator > to > > >> >>> support > > >> >>> > > such > > >> >>> > > > > guarantees please open a separate discussion on that > topic, > > I > > >> >>> don't > > >> >>> > > want > > >> >>> > > > to > > >> >>> > > > > mix the two problems here. > > >> >>> > > > > > > >> >>> > > > > Regards, > > >> >>> > > > > Gyula > > >> >>> > > > > > > >> >>> > > > > On Thu, Nov 17, 2022 at 5:07 PM Dong Lin < > > lindon...@gmail.com> > > >> >>> > wrote: > > >> >>> > > > > > > >> >>> > > > >> Hi Gyula, > > >> >>> > > > >> > > >> >>> > > > >> If I understand correctly, this autopilot proposal is an > > >> >>> > experimental > > >> >>> > > > >> feature and its configs/metrics are not mature enough to > > >> provide > > >> >>> > > > backward > > >> >>> > > > >> compatibility yet. And the proposal provides high-level > > ideas > > >> of > > >> >>> the > > >> >>> > > > >> algorithm but it is probably too complicated to explain > it > > >> >>> > end-to-end. > > >> >>> > > > >> > > >> >>> > > > >> On the one hand, I do agree that having an auto-tuning > > >> prototype, > > >> >>> > even > > >> >>> > > > if > > >> >>> > > > >> not mature, is better than nothing for Flink users. On > the > > >> other > > >> >>> > > hand, I > > >> >>> > > > >> am > > >> >>> > > > >> concerned that this FLIP seems a bit too experimental, > and > > >> >>> starting > > >> >>> > > with > > >> >>> > > > >> an > > >> >>> > > > >> immature design might make it harder for us to reach a > > >> >>> > > production-ready > > >> >>> > > > >> and > > >> >>> > > > >> generally applicable auto-tuner in the future. And > > introducing > > >> >>> too > > >> >>> > > > >> backward > > >> >>> > > > >> incompatible changes generally hurts users' trust in the > > Flink > > >> >>> > > project. > > >> >>> > > > >> > > >> >>> > > > >> One alternative might be to develop and experiment with > > this > > >> >>> feature > > >> >>> > > in > > >> >>> > > > a > > >> >>> > > > >> non-Flink repo. You can iterate fast without worrying > about > > >> >>> > typically > > >> >>> > > > >> backward compatibility requirement as required for most > > Flink > > >> >>> public > > >> >>> > > > >> features. And once the feature is reasonably evaluated > and > > >> mature > > >> >>> > > > enough, > > >> >>> > > > >> it will be much easier to explain the design and address > > all > > >> the > > >> >>> > > issues > > >> >>> > > > >> mentioned above. For example, Jingsong implemented a > Flink > > >> Table > > >> >>> > Store > > >> >>> > > > >> prototype > > >> >>> > > > >> < > > >> >>> > https://github.com/JingsongLi/flink/tree/table_storage/flink-table > > >> >>> > > > > >> >>> > > > >> before > > >> >>> > > > >> proposing FLIP-188 in this thread > > >> >>> > > > >> < > > >> >>> https://lists.apache.org/thread/dlhspjpms007j2ynymsg44fxcx6fm064 > >. > > >> >>> > > > >> > > >> >>> > > > >> I don't intend to block your progress. Just my two cents. > > It > > >> >>> will be > > >> >>> > > > great > > >> >>> > > > >> to hear more from other developers (e.g. in the voting > > >> thread). > > >> >>> > > > >> > > >> >>> > > > >> Thanks, > > >> >>> > > > >> Dong > > >> >>> > > > >> > > >> >>> > > > >> > > >> >>> > > > >> On Thu, Nov 17, 2022 at 1:24 AM Gyula Fóra < > > >> gyula.f...@gmail.com > > >> >>> > > > >> >>> > > > wrote: > > >> >>> > > > >> > > >> >>> > > > >> > Hi Dong, > > >> >>> > > > >> > > > >> >>> > > > >> > Let me address your comments. > > >> >>> > > > >> > > > >> >>> > > > >> > Time for scale / backlog processing time derivation: > > >> >>> > > > >> > We can add some more details to the Flip but at this > > point > > >> the > > >> >>> > > > >> > implementation is actually much simpler than the > > algorithm > > >> to > > >> >>> > > describe > > >> >>> > > > >> it. > > >> >>> > > > >> > I would not like to add more equations etc because it > > just > > >> >>> > > > >> overcomplicates > > >> >>> > > > >> > something relatively simple in practice. > > >> >>> > > > >> > > > >> >>> > > > >> > In a nutshell: Time to recover == lag / > > >> >>> > > > processing-rate-after-scaleup. > > >> >>> > > > >> > It's fairly easy to see where this is going, but best > to > > >> see in > > >> >>> > > code. > > >> >>> > > > >> > > > >> >>> > > > >> > Using pendingRecords and alternative mechanisms: > > >> >>> > > > >> > True that the current algorithm relies on pending > > records to > > >> >>> > > > effectively > > >> >>> > > > >> > compute the target source processing rates and > therefore > > >> scale > > >> >>> > > > sources. > > >> >>> > > > >> > This is available for Kafka which is by far the most > > common > > >> >>> > > streaming > > >> >>> > > > >> > source and is used by the majority of streaming > > applications > > >> >>> > > > currently. > > >> >>> > > > >> > It would be very easy to add alternative purely > > utilization > > >> >>> based > > >> >>> > > > >> scaling > > >> >>> > > > >> > to the sources. We can start with the current proposal > > and > > >> add > > >> >>> > this > > >> >>> > > > >> along > > >> >>> > > > >> > the way before the first version. > > >> >>> > > > >> > > > >> >>> > > > >> > Metrics, Configs and Public API: > > >> >>> > > > >> > The autoscaler feature is proposed for the Flink > > Kubernetes > > >> >>> > Operator > > >> >>> > > > >> which > > >> >>> > > > >> > does not have the same API/config maturity and thus > does > > not > > >> >>> > provide > > >> >>> > > > the > > >> >>> > > > >> > same guarantees. > > >> >>> > > > >> > We currently support backward compatibilty for the CRD > > >> itself > > >> >>> and > > >> >>> > > not > > >> >>> > > > >> the > > >> >>> > > > >> > configs or metrics. This does not mean that we do not > > aim to > > >> >>> do so > > >> >>> > > but > > >> >>> > > > >> at > > >> >>> > > > >> > this stage we still have to clean up the details of the > > >> newly > > >> >>> > added > > >> >>> > > > >> > components. In practice this means that if we manage to > > get > > >> the > > >> >>> > > > metrics > > >> >>> > > > >> / > > >> >>> > > > >> > configs right at the first try we will keep them and > > provide > > >> >>> > > > >> compatibility, > > >> >>> > > > >> > but if we feel that we missed something or we don't > need > > >> >>> something > > >> >>> > > we > > >> >>> > > > >> can > > >> >>> > > > >> > still remove it. It's a more pragmatic approach for > such > > a > > >> >>> > component > > >> >>> > > > >> that > > >> >>> > > > >> > is likely to evolve than setting everything in stone > > >> >>> immediately. > > >> >>> > > > >> > > > >> >>> > > > >> > Cheers, > > >> >>> > > > >> > Gyula > > >> >>> > > > >> > > > >> >>> > > > >> > > > >> >>> > > > >> > > > >> >>> > > > >> > On Wed, Nov 16, 2022 at 6:07 PM Dong Lin < > > >> lindon...@gmail.com> > > >> >>> > > wrote: > > >> >>> > > > >> > > > >> >>> > > > >> > > Thanks for the update! Please see comments inline. > > >> >>> > > > >> > > > > >> >>> > > > >> > > On Tue, Nov 15, 2022 at 11:46 PM Maximilian Michels < > > >> >>> > > m...@apache.org > > >> >>> > > > > > > >> >>> > > > >> > > wrote: > > >> >>> > > > >> > > > > >> >>> > > > >> > > > Of course! Let me know if your concerns are > > addressed. > > >> The > > >> >>> > wiki > > >> >>> > > > page > > >> >>> > > > >> > has > > >> >>> > > > >> > > > been updated. > > >> >>> > > > >> > > > > > >> >>> > > > >> > > > >It will be great to add this in the FLIP so that > > >> reviewers > > >> >>> > can > > >> >>> > > > >> > > understand > > >> >>> > > > >> > > > how the source parallelisms are computed and how > the > > >> >>> algorithm > > >> >>> > > > works > > >> >>> > > > >> > > > end-to-end. > > >> >>> > > > >> > > > > > >> >>> > > > >> > > > I've updated the FLIP page to add more details on > how > > >> the > > >> >>> > > > >> backlog-based > > >> >>> > > > >> > > > scaling works (2). > > >> >>> > > > >> > > > > > >> >>> > > > >> > > > > >> >>> > > > >> > > The algorithm is much more informative now. The > > algorithm > > >> >>> > > currently > > >> >>> > > > >> uses > > >> >>> > > > >> > > "Estimated time for rescale" to derive new source > > >> >>> parallelism. > > >> >>> > > Could > > >> >>> > > > >> we > > >> >>> > > > >> > > also specify in the FLIP how this value is derived? > > >> >>> > > > >> > > > > >> >>> > > > >> > > The algorithm currently uses pendingRecords to derive > > >> source > > >> >>> > > > >> parallelism. > > >> >>> > > > >> > > It is an optional metric and KafkaSource currently > > reports > > >> >>> this > > >> >>> > > > >> metric. > > >> >>> > > > >> > So > > >> >>> > > > >> > > it means that only the proposed algorithm currently > > only > > >> >>> works > > >> >>> > > when > > >> >>> > > > >> all > > >> >>> > > > >> > > sources of the job are KafkaSource, right? > > >> >>> > > > >> > > > > >> >>> > > > >> > > This issue considerably limits the applicability of > > this > > >> >>> FLIP. > > >> >>> > Do > > >> >>> > > > you > > >> >>> > > > >> > think > > >> >>> > > > >> > > most (if not all) streaming source will report this > > >> metric? > > >> >>> > > > >> > Alternatively, > > >> >>> > > > >> > > any chance we can have a fallback solution to > evaluate > > the > > >> >>> > source > > >> >>> > > > >> > > parallelism based on e.g. cpu or idle ratio for cases > > >> where > > >> >>> this > > >> >>> > > > >> metric > > >> >>> > > > >> > is > > >> >>> > > > >> > > not available? > > >> >>> > > > >> > > > > >> >>> > > > >> > > > > >> >>> > > > >> > > > >These metrics and configs are public API and need > > to be > > >> >>> > stable > > >> >>> > > > >> across > > >> >>> > > > >> > > > minor versions, could we document them before > > finalizing > > >> >>> the > > >> >>> > > FLIP? > > >> >>> > > > >> > > > > > >> >>> > > > >> > > > Metrics and config changes are not strictly part of > > the > > >> >>> public > > >> >>> > > API > > >> >>> > > > >> but > > >> >>> > > > >> > > > Gyula has added a section. > > >> >>> > > > >> > > > > > >> >>> > > > >> > > > > >> >>> > > > >> > > Hmm... if metrics are not public API, then it might > > happen > > >> >>> that > > >> >>> > we > > >> >>> > > > >> change > > >> >>> > > > >> > > the mbean path in a minor release and break users' > > >> monitoring > > >> >>> > > tool. > > >> >>> > > > >> > > Similarly, we might change configs in a minor release > > that > > >> >>> break > > >> >>> > > > >> user's > > >> >>> > > > >> > job > > >> >>> > > > >> > > behavior. We probably want to avoid these breaking > > >> changes in > > >> >>> > > minor > > >> >>> > > > >> > > releases. > > >> >>> > > > >> > > > > >> >>> > > > >> > > It is documented here > > >> >>> > > > >> > > < > > >> >>> > > > >> > > > > >> >>> > > > >> > > > >> >>> > > > >> > > >> >>> > > > > > >> >>> > > > > >> >>> > > > >> >>> > > >> > > > https://cwiki.apache.org/confluence/display/FLINK/Flink+Improvement+Proposals > > >> >>> > > > >> > > > > > >> >>> > > > >> > > that > > >> >>> > > > >> > > "Exposed monitoring information" and "Configuration > > >> settings" > > >> >>> > are > > >> >>> > > > >> public > > >> >>> > > > >> > > interfaces of the project. > > >> >>> > > > >> > > > > >> >>> > > > >> > > Maybe we should also specify the metric here so that > > users > > >> >>> can > > >> >>> > > > safely > > >> >>> > > > >> > setup > > >> >>> > > > >> > > dashboards and tools to track how the autopilot is > > >> working, > > >> >>> > > similar > > >> >>> > > > to > > >> >>> > > > >> > how > > >> >>> > > > >> > > metrics are documented in FLIP-33 > > >> >>> > > > >> > > < > > >> >>> > > > >> > > > > >> >>> > > > >> > > > >> >>> > > > >> > > >> >>> > > > > > >> >>> > > > > >> >>> > > > >> >>> > > >> > > > https://cwiki.apache.org/confluence/display/FLINK/FLIP-33%3A+Standardize+Connector+Metrics > > >> >>> > > > >> > > > > > >> >>> > > > >> > > ? > > >> >>> > > > >> > > > > >> >>> > > > >> > > > > >> >>> > > > >> > > > -Max > > >> >>> > > > >> > > > > > >> >>> > > > >> > > > On Tue, Nov 15, 2022 at 3:01 PM Dong Lin < > > >> >>> lindon...@gmail.com > > >> >>> > > > > >> >>> > > > >> wrote: > > >> >>> > > > >> > > > > > >> >>> > > > >> > > > > Hi Maximilian, > > >> >>> > > > >> > > > > > > >> >>> > > > >> > > > > It seems that the following comments from the > > previous > > >> >>> > > > discussions > > >> >>> > > > >> > have > > >> >>> > > > >> > > > not > > >> >>> > > > >> > > > > been addressed yet. Any chance we can have them > > >> addressed > > >> >>> > > before > > >> >>> > > > >> > > starting > > >> >>> > > > >> > > > > the voting thread? > > >> >>> > > > >> > > > > > > >> >>> > > > >> > > > > Thanks, > > >> >>> > > > >> > > > > Dong > > >> >>> > > > >> > > > > > > >> >>> > > > >> > > > > On Mon, Nov 7, 2022 at 2:33 AM Gyula Fóra < > > >> >>> > > gyula.f...@gmail.com > > >> >>> > > > > > > >> >>> > > > >> > > wrote: > > >> >>> > > > >> > > > > > > >> >>> > > > >> > > > > > Hi Dong! > > >> >>> > > > >> > > > > > > > >> >>> > > > >> > > > > > Let me try to answer the questions :) > > >> >>> > > > >> > > > > > > > >> >>> > > > >> > > > > > 1 : busyTimeMsPerSecond is not specific for > CPU, > > it > > >> >>> > measures > > >> >>> > > > the > > >> >>> > > > >> > time > > >> >>> > > > >> > > > > > spent in the main record processing loop for an > > >> >>> operator > > >> >>> > if > > >> >>> > > I > > >> >>> > > > >> > > > > > understand correctly. This includes IO > operations > > >> too. > > >> >>> > > > >> > > > > > > > >> >>> > > > >> > > > > > 2: We should add this to the FLIP I agree. It > > would > > >> be > > >> >>> a > > >> >>> > > > >> Duration > > >> >>> > > > >> > > > config > > >> >>> > > > >> > > > > > with the expected catch up time after rescaling > > >> (let's > > >> >>> > say 5 > > >> >>> > > > >> > > minutes). > > >> >>> > > > >> > > > It > > >> >>> > > > >> > > > > > could be computed based on the current data > rate > > and > > >> >>> the > > >> >>> > > > >> calculated > > >> >>> > > > >> > > max > > >> >>> > > > >> > > > > > processing rate after the rescale. > > >> >>> > > > >> > > > > > > > >> >>> > > > >> > > > > > > >> >>> > > > >> > > > > It will be great to add this in the FLIP so that > > >> >>> reviewers > > >> >>> > can > > >> >>> > > > >> > > understand > > >> >>> > > > >> > > > > how the source parallelisms are computed and how > > the > > >> >>> > algorithm > > >> >>> > > > >> works > > >> >>> > > > >> > > > > end-to-end. > > >> >>> > > > >> > > > > > > >> >>> > > > >> > > > > > > >> >>> > > > >> > > > > > 3: In the current proposal we don't have per > > >> operator > > >> >>> > > configs. > > >> >>> > > > >> > Target > > >> >>> > > > >> > > > > > utilization would apply to all operators > > uniformly. > > >> >>> > > > >> > > > > > > > >> >>> > > > >> > > > > > 4: It should be configurable, yes. > > >> >>> > > > >> > > > > > > > >> >>> > > > >> > > > > > > >> >>> > > > >> > > > > Since this config is a public API, could we > update > > the > > >> >>> FLIP > > >> >>> > > > >> > accordingly > > >> >>> > > > >> > > > to > > >> >>> > > > >> > > > > provide this config? > > >> >>> > > > >> > > > > > > >> >>> > > > >> > > > > > > >> >>> > > > >> > > > > > > > >> >>> > > > >> > > > > > 5,6: The names haven't been finalized but I > think > > >> these > > >> >>> > are > > >> >>> > > > >> minor > > >> >>> > > > >> > > > > details. > > >> >>> > > > >> > > > > > We could add concrete names to the FLIP :) > > >> >>> > > > >> > > > > > > > >> >>> > > > >> > > > > > > >> >>> > > > >> > > > > These metrics and configs are public API and need > > to > > >> be > > >> >>> > stable > > >> >>> > > > >> across > > >> >>> > > > >> > > > minor > > >> >>> > > > >> > > > > versions, could we document them before > finalizing > > the > > >> >>> FLIP? > > >> >>> > > > >> > > > > > > >> >>> > > > >> > > > > > > >> >>> > > > >> > > > > > > > >> >>> > > > >> > > > > > Cheers, > > >> >>> > > > >> > > > > > Gyula > > >> >>> > > > >> > > > > > > > >> >>> > > > >> > > > > > > > >> >>> > > > >> > > > > > On Sun, Nov 6, 2022 at 5:19 PM Dong Lin < > > >> >>> > > lindon...@gmail.com> > > >> >>> > > > >> > wrote: > > >> >>> > > > >> > > > > > > > >> >>> > > > >> > > > > >> Hi Max, > > >> >>> > > > >> > > > > >> > > >> >>> > > > >> > > > > >> Thank you for the proposal. The proposal > > tackles a > > >> >>> very > > >> >>> > > > >> important > > >> >>> > > > >> > > > issue > > >> >>> > > > >> > > > > >> for Flink users and the design looks promising > > >> >>> overall! > > >> >>> > > > >> > > > > >> > > >> >>> > > > >> > > > > >> I have some questions to better understand the > > >> >>> proposed > > >> >>> > > > public > > >> >>> > > > >> > > > > interfaces > > >> >>> > > > >> > > > > >> and the algorithm. > > >> >>> > > > >> > > > > >> > > >> >>> > > > >> > > > > >> 1) The proposal seems to assume that the > > operator's > > >> >>> > > > >> > > > busyTimeMsPerSecond > > >> >>> > > > >> > > > > >> could reach 1 sec. I believe this is mostly > true > > >> for > > >> >>> > > > cpu-bound > > >> >>> > > > >> > > > > operators. > > >> >>> > > > >> > > > > >> Could you confirm that this can also be true > for > > >> >>> io-bound > > >> >>> > > > >> > operators > > >> >>> > > > >> > > > > such as > > >> >>> > > > >> > > > > >> sinks? For example, suppose a Kafka Sink > subtask > > >> has > > >> >>> > > reached > > >> >>> > > > >> I/O > > >> >>> > > > >> > > > > bottleneck > > >> >>> > > > >> > > > > >> when flushing data out to the Kafka clusters, > > will > > >> >>> > > > >> > > busyTimeMsPerSecond > > >> >>> > > > >> > > > > >> reach 1 sec? > > >> >>> > > > >> > > > > >> > > >> >>> > > > >> > > > > >> 2) It is said that "users can configure a > > maximum > > >> >>> time to > > >> >>> > > > fully > > >> >>> > > > >> > > > process > > >> >>> > > > >> > > > > >> the backlog". The configuration section does > not > > >> seem > > >> >>> to > > >> >>> > > > >> provide > > >> >>> > > > >> > > this > > >> >>> > > > >> > > > > >> config. Could you specify this? And any chance > > this > > >> >>> > > proposal > > >> >>> > > > >> can > > >> >>> > > > >> > > > provide > > >> >>> > > > >> > > > > >> the formula for calculating the new processing > > >> rate? > > >> >>> > > > >> > > > > >> > > >> >>> > > > >> > > > > >> 3) How are users expected to specify the > > >> per-operator > > >> >>> > > configs > > >> >>> > > > >> > (e.g. > > >> >>> > > > >> > > > > >> target utilization)? For example, should users > > >> >>> specify it > > >> >>> > > > >> > > > > programmatically > > >> >>> > > > >> > > > > >> in a DataStream/Table/SQL API? > > >> >>> > > > >> > > > > >> > > >> >>> > > > >> > > > > >> 4) How often will the Flink Kubernetes > operator > > >> query > > >> >>> > > metrics > > >> >>> > > > >> from > > >> >>> > > > >> > > > > >> JobManager? Is this configurable? > > >> >>> > > > >> > > > > >> > > >> >>> > > > >> > > > > >> 5) Could you specify the config name and > default > > >> value > > >> >>> > for > > >> >>> > > > the > > >> >>> > > > >> > > > proposed > > >> >>> > > > >> > > > > >> configs? > > >> >>> > > > >> > > > > >> > > >> >>> > > > >> > > > > >> 6) Could you add the name/mbean/type for the > > >> proposed > > >> >>> > > > metrics? > > >> >>> > > > >> > > > > >> > > >> >>> > > > >> > > > > >> > > >> >>> > > > >> > > > > >> Cheers, > > >> >>> > > > >> > > > > >> Dong > > >> >>> > > > >> > > > > >> > > >> >>> > > > >> > > > > >> > > >> >>> > > > >> > > > > >> > > >> >>> > > > >> > > > > > > >> >>> > > > >> > > > > > >> >>> > > > >> > > > > >> >>> > > > >> > > > >> >>> > > > >> > > >> >>> > > > > > > >> >>> > > > > > >> >>> > > > > >> >>> > > > >> >>> > > >> >> > > >> > > >
