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 > > >> > > >> > > >> > > >
