Hi Guozhang, I totally missed the total invocation count metric in the javadoc. Which brings me to a follow-up question. Should the names of the methods reflect the included total invocation count? We have to rename them anyways. One option would be to simply add `Total` to the method names, i.e., `addLatencyAndRateAndTotalSensor` and `addRateAndTotalSensor` (alternatively without the `And`s). Since those sensors record exclusively invocations, another option would be `addInvocationSensor` and `addInvocationSensorWithoutLatency`.
As far as I can see, we have sensors to record invocations but none to record amounts. Is that intentional? No need to add it to this KIP, I am just curious. Best, Bruno On Tue, Aug 20, 2019 at 1:13 AM Guozhang Wang <wangg...@gmail.com> wrote: > > Hi Bruno, > > Just realized that for `addRateSensor` and `addLatencyAndRateSensor` we've > actually added the total invocation metric already. > > > Guozhang > > On Mon, Aug 19, 2019 at 4:11 PM Guozhang Wang <wangg...@gmail.com> wrote: > > > Hi Bruno, > > > > > > On Tue, Aug 6, 2019 at 1:51 AM Bruno Cadonna <br...@confluent.io> wrote: > > > >> Hi Guozhang, > >> > >> I left my comments inline. > >> > >> On Thu, Jul 18, 2019 at 8:28 PM Guozhang Wang <wangg...@gmail.com> wrote: > >> > > >> > Hello Bruno, > >> > > >> > Thanks for the feedbacks, replied inline. > >> > > >> > On Mon, Jul 1, 2019 at 7:08 AM Bruno Cadonna <br...@confluent.io> > >> wrote: > >> > > >> > > Hi Guozhang, > >> > > > >> > > Thank you for the KIP. > >> > > > >> > > 1) As far as I understand, the StreamsMetrics interface is there for > >> > > user-defined processors. Would it make sense to also add a method to > >> > > the interface to specify a sensor that records skipped records? > >> > > > >> > > Not sure I follow.. if users want to add a specific skipped records > >> > sensor, she can still do that as a "throughput" sensor via " > >> > addThroughputSensor" and then "record" right? > >> > > >> > As an after-thought, maybe it's better to rename `throughput` to `rate` > >> in > >> > the public APIs since it is really meant for the latter semantics. I did > >> > not change it just to make less API changes / deprecate fewer functions. > >> > But if we feel it is important we can change it as well. > >> > > >> > >> I see now that a user can record the rate of skipped records. However, > >> I was referring to the total number of skipped records. Maybe my > >> question should be more general: should we allow the user to also > >> specify sensors for totals or combinations of rate and totals? > >> > >> Sounds good to me, I will add it to the wiki page as well for > > StreamsMetrics. > > > > > > > >> Regarding the naming, I like `rate` more than `throughput`, but I > >> would not fight for it. > >> > >> > > >> > > 2) What are the semantics of active-task-process and > >> standby-task-process > >> > > > >> > > Ah good catch, I think I made it in the wrong column. Just some > >> > explanations here: Within a thread's looped iterations, it will first > >> try > >> > to process some records from the active tasks, and then see if there are > >> > any standby-tasks that can be processed as well (i.e. just reading from > >> the > >> > restore consumer and apply to the local stores). The ratio metrics are > >> for > >> > indicating 1) what tasks (active or standby) does this thread own so > >> far, > >> > and 2) how much time in percentage does it spend on each of them. > >> > > >> > But this metric should really be a task-level one that includes both the > >> > thread-id and task-id, and upon task migrations they will be dynamically > >> > deleted / (re)-created. For each task-id it may be owned by multiple > >> > threads as one active and others standby, and hence the separation of > >> > active / standby seems still necessary. > >> > > >> > >> Makes sense. > >> > >> > >> > > >> > > >> > > 3) How do dropped-late-records and expired-window-record-drop relate > >> > > to each other? I guess the former is for records that fall outside the > >> > > grace period and the latter is for records that are processed after > >> > > the retention period of the window. Is this correct? > >> > > > >> > > Yes, that's correct. The names are indeed a bit confusing since they > >> are > >> > added at different releases historically.. > >> > > >> > More precisely, the `grace period` is a notion of the operator (hence > >> the > >> > metric is node-level, though it would only be used for DSL operators) > >> while > >> > the `retention` is a notion of the store (hence the metric is > >> store-level). > >> > Usually grace period will be smaller than store retention though. > >> > > >> > Processor node is aware of `grace period` and when received a record > >> that > >> > is older than grace deadline, it will be dropped immediately; otherwise > >> it > >> > will still be processed a maybe a new update is "put" into the store. > >> The > >> > store is aware of its `retention period` and then upon a "put" call if > >> it > >> > realized it is older than the retention deadline, that put call would be > >> > ignored and metric is recorded. > >> > > >> > We have to separate them here since the window store can be used in both > >> > DSL and PAPI, and for the former case it would likely to be already > >> ignored > >> > at the processor node level due to the grace period which is usually > >> > smaller than retention; but for PAPI there's no grace period and hence > >> the > >> > processor would likely still process and call "put" on the store. > >> > > >> > >> Alright! Got it! > >> > >> > > >> > > 4) Is there an actual difference between skipped and dropped records? > >> > > If not, shall we unify the terminology? > >> > > > >> > > > >> > There is. Dropped records are only due to lateness; where as skipped > >> > records can be due to serde errors (and user's error handling indicate > >> > "skip and continue"), timestamp errors, etc. > >> > > >> > I've considered maybe a better (more extensible) way would be defining a > >> > single metric name, say skipped-records, but use different tags to > >> indicate > >> > if its skipping reason (errors, windowing semantics, etc). But there's > >> > still a tricky difference: for serde caused skipping for example, they > >> will > >> > be skipped at the very beginning and there's no effects taken at all. > >> For > >> > some others e.g. null-key / value at the reduce operator, it is only > >> > skipped at the middle of the processing, i.e. some effects may have > >> already > >> > been taken in up-stream sub-topologies. And that's why for > >> skipped-records > >> > I've defined it on both task-level and node-level and the aggregate of > >> the > >> > latter may still be smaller than the former, whereas for > >> dropped-records it > >> > is only for node-level. > >> > > >> > So how about an even more significant change then: we enlarge the > >> > `dropped-late-records` to `dropped-records` which is node-level only, > >> but > >> > includes reasons form lateness to semantics (like null-key) as well; and > >> > then we have a task-level-only `skipped-records` which only record those > >> > dropped at the very beginning and did not make it at all to the > >> processing > >> > topology. I feel this is a clearer distinguishment but also a bigger > >> change > >> > to users. > >> > > >> > >> I like the way you dropped-records and skipped-records are now > >> defined. My follow-up question is whether we should give names to > >> those metrics that better describe their semantics, like: > >> > >> dropped-records-at-source and dropped-records-at-processor > >> > >> or > >> > >> records-dropped-at-source and records-dropped-at-processor > >> > >> or > >> > >> source-dropped-records and processor-dropped-records > >> > >> or alternatively with skipped. However, I would use the same term as > >> in expired-window-record-drop > >> > >> Maybe, we should also consider to rename expired-window-record-drop to > >> expired-window-record-dropped to be consistent. > >> > >> WDYT? > >> > >> I was not considering "expired-window-record-drop" before since it is a > > store-level metric, and I was only considering task-level (skipped-records) > > and processor-node-level (dropped-records) metrics, and I'm using different > > terms deliberately to hint users that they are different leveled metrics. > > > > I still feel that using `skip` for task-level metrics indicating that this > > record was not processed at all, and using `drop` for processor-level > > metrics that this record is only dropped at this stage of the topology is a > > better one; but I'm also okay with some finer grained metrics so that we > > can align the processor-level with store-level (they are on the same > > granularity any ways), like: > > > > `dropped-records-null-field`: at processor nodes > > > > `dropped-records-too-late`: at processor nodes > > > > `dropped-records-expired-window`: at window-stores > > > > > >> > > >> > > 5) What happens with removed metrics when the user sets the version of > >> > > "built.in.metrics.version" to 2.2- > >> > > > >> > > I think for those redundant ones like ""forward-rate" and > >> "destroy-rate" > >> > we can still remove them with 2.2- as well; for other ones that are > >> removed > >> > / replaced like thread-level skipped-records we should still maintain > >> them. > >> > > >> > >> Could you add this comment about removal of redundant metrics to the > >> KIP such that is documented somewhere? > >> > >> Yes, for sure. > > > > > >> > >> Best, > >> Bruno > >> > > > > I've also decided to remove the rebalance-related metrics from the > > instance-level and move it to consumer itself as part of KIP-429. > > > > > > -- > > -- Guozhang > > > > > -- > -- Guozhang
