The influence of checkpointing on the output of the results should be minimal in particular for Direct Runner. It seems what Steve reports here seems to be something different. Jan have you or others already checked the influence of this on Flink who is now using this new translation path?
I think the argument that the Direct runner is mostly about testing and not about performance is an argument that is playing bad on Beam, one should not necessarily exclude the other. Direct runner is our most used runner, basically every Beam user relies on the direct runners so every regression or improvement on it affects everyone, but well that's a subject worth its own thread. On Thu, Dec 17, 2020 at 10:55 AM Jan Lukavský <je...@seznam.cz> wrote: > > Hi, > > from my point of view the number in DirectRunner are set correctly. Primary > purpose of DirectRunner is testing, not performance, so DirectRunner makes > intentionally frequent checkpoints to easily exercise potential bugs in user > code. It might be possible to make the frequency configurable, though. > > Jan > > On 12/17/20 12:20 AM, Boyuan Zhang wrote: > > It's not a portable execution on DirectRunner so I would expect that outputs > from OutputAndTimeBoundedSplittableProcessElementInvoker should be emitted > immediately. For SDF execution on DirectRunner, the overhead could come from > the SDF expansion, SDF wrapper and the invoker. > > Steve, based on your findings, it seems like it takes more time for the SDF > pipeline to actually start to read from PubSub and more time to output > records. Are you able to tell how much time each part is taking? > > On Wed, Dec 16, 2020 at 1:53 PM Robert Bradshaw <rober...@google.com> wrote: >> >> If all it takes is bumping these numbers up a bit, that seems like a >> reasonable thing to do ASAP. (I would argue that perhaps they shouldn't be >> static, e.g. it might be preferable to start emitting results right away, >> but use larger batches for the steady state if there are performance >> benefits.) >> >> That being said, it sounds like there's something deeper going on here. We >> should also verify that this performance impact is limited to the direct >> runner. >> >> On Wed, Dec 16, 2020 at 1:36 PM Steve Niemitz <sniem...@apache.org> wrote: >>> >>> I tried changing my build locally to 10 seconds and 10,000 elements but it >>> didn't seem to make much of a difference, it still takes a few minutes for >>> elements to begin actually showing up to downstream stages from the Pubsub >>> read. I can see elements being emitted from >>> OutputAndTimeBoundedSplittableProcessElementInvoker, and bundles being >>> committed by ParDoEvaluator.finishBundle, but after that, they seem to just >>> kind of disappear somewhere. >>> >>> On Wed, Dec 16, 2020 at 4:18 PM Boyuan Zhang <boyu...@google.com> wrote: >>>> >>>> Making it as the PipelineOptions was my another proposal but it might take >>>> some time to do so. On the other hand, tuning the number into something >>>> acceptable is low-hanging fruit. >>>> >>>> On Wed, Dec 16, 2020 at 12:48 PM Ismaël Mejía <ieme...@gmail.com> wrote: >>>>> >>>>> It sounds reasonable. I am wondering also on the consequence of these >>>>> parameters for other runners (where it is every 10 seconds or 10000 >>>>> elements) + their own configuration e.g. checkpointInterval, >>>>> checkpointTimeoutMillis and minPauseBetweenCheckpoints for Flink. It >>>>> is not clear for me what would be chosen now in this case. >>>>> >>>>> I know we are a bit anti knobs but maybe it makes sense to make this >>>>> configurable via PipelineOptions at least for Direct runner. >>>>> >>>>> On Wed, Dec 16, 2020 at 7:29 PM Boyuan Zhang <boyu...@google.com> wrote: >>>>> > >>>>> > I agree, Ismael. >>>>> > >>>>> > From my current investigation, the performance overhead should majorly >>>>> > come from the frequency of checkpoint in >>>>> > OutputAndTimeBoundedSplittableProcessElementinvoker[1], which is >>>>> > hardcoded in the DirectRunner(every 1 seconds or 100 elements)[2]. I >>>>> > believe configuring these numbers on DirectRunner should improve >>>>> > reported cases so far. My last proposal was to change the number to >>>>> > every 5 seconds or 10000 elements. What do you think? >>>>> > >>>>> > [1] >>>>> > https://github.com/apache/beam/blob/master/runners/core-java/src/main/java/org/apache/beam/runners/core/OutputAndTimeBoundedSplittableProcessElementInvoker.java >>>>> > [2] >>>>> > https://github.com/apache/beam/blob/3bb232fb098700de408f574585dfe74bbaff7230/runners/direct-java/src/main/java/org/apache/beam/runners/direct/SplittableProcessElementsEvaluatorFactory.java#L178-L181 >>>>> > >>>>> > On Wed, Dec 16, 2020 at 9:02 AM Ismaël Mejía <ieme...@gmail.com> wrote: >>>>> >> >>>>> >> I can guess that the same issues mentioned here probably will affect >>>>> >> the usability for people trying Beam's interactive SQL on Unbounded IO >>>>> >> too. >>>>> >> >>>>> >> We should really take into account that the performance of the SDF >>>>> >> based path should be as good or better than the previous version >>>>> >> before considering its removal (--experiments=use_deprecated_read) and >>>>> >> probably have consensus when this happens. >>>>> >> >>>>> >> >>>>> >> On Fri, Dec 11, 2020 at 11:33 PM Boyuan Zhang <boyu...@google.com> >>>>> >> wrote: >>>>> >> > >>>>> >> > > From what I've seen, the direct runner initiates a checkpoint >>>>> >> > > after every element output. >>>>> >> > That seems like the 1 second limit kicks in before the output >>>>> >> > reaches 100 elements. >>>>> >> > >>>>> >> > I think the original purpose for DirectRunner to use a small limit >>>>> >> > on issuing checkpoint requests is for exercising SDF better in a >>>>> >> > small data set. But it brings overhead on a larger set owing to too >>>>> >> > many checkpoints. It would be ideal to make this limit configurable >>>>> >> > from pipeline but the easiest approach is that we figure out a >>>>> >> > number for most common cases. Do you think we raise the limit to >>>>> >> > 1000 elements or every 5 seconds will help? >>>>> >> > >>>>> >> > On Fri, Dec 11, 2020 at 2:22 PM Steve Niemitz <sniem...@apache.org> >>>>> >> > wrote: >>>>> >> >> >>>>> >> >> From what I've seen, the direct runner initiates a checkpoint after >>>>> >> >> every element output. >>>>> >> >> >>>>> >> >> On Fri, Dec 11, 2020 at 5:19 PM Boyuan Zhang <boyu...@google.com> >>>>> >> >> wrote: >>>>> >> >>> >>>>> >> >>> Hi Antonio, >>>>> >> >>> >>>>> >> >>> Thanks for the details! Which version of Beam SDK are you using? >>>>> >> >>> And are you using --experiments=beam_fn_api with DirectRunner to >>>>> >> >>> launch your pipeline? >>>>> >> >>> >>>>> >> >>> For ReadFromKafkaDoFn.processElement(), it will take a Kafka >>>>> >> >>> topic+partition as input element and a KafkaConsumer will be >>>>> >> >>> assigned to this topic+partition then poll records continuously. >>>>> >> >>> The Kafka consumer will resume reading and return from the process >>>>> >> >>> fn when >>>>> >> >>> >>>>> >> >>> There are no available records currently(this is a feature of SDF >>>>> >> >>> which calls SDF self-initiated checkpoint) >>>>> >> >>> The OutputAndTimeBoundedSplittableProcessElementInvoker issues >>>>> >> >>> checkpoint request to ReadFromKafkaDoFn for getting partial >>>>> >> >>> results. The checkpoint frequency for DirectRunner is every 100 >>>>> >> >>> output records or every 1 seconds. >>>>> >> >>> >>>>> >> >>> It seems like either the self-initiated checkpoint or DirectRunner >>>>> >> >>> issued checkpoint gives you the performance regression since there >>>>> >> >>> is overhead when rescheduling residuals. In your case, it's more >>>>> >> >>> like that the checkpoint behavior of >>>>> >> >>> OutputAndTimeBoundedSplittableProcessElementInvoker gives you 200 >>>>> >> >>> elements a batch. I want to understand what kind of performance >>>>> >> >>> regression you are noticing? Is it slower to output the same >>>>> >> >>> amount of records? >>>>> >> >>> >>>>> >> >>> On Fri, Dec 11, 2020 at 1:31 PM Antonio Si <antonio...@gmail.com> >>>>> >> >>> wrote: >>>>> >> >>>> >>>>> >> >>>> Hi Boyuan, >>>>> >> >>>> >>>>> >> >>>> This is Antonio. I reported the KafkaIO.read() performance issue >>>>> >> >>>> on the slack channel a few days ago. >>>>> >> >>>> >>>>> >> >>>> I am not sure if this is helpful, but I have been doing some >>>>> >> >>>> debugging on the SDK KafkaIO performance issue for our pipeline >>>>> >> >>>> and I would like to provide some observations. >>>>> >> >>>> >>>>> >> >>>> It looks like in my case the ReadFromKafkaDoFn.processElement() >>>>> >> >>>> was invoked within the same thread and every time >>>>> >> >>>> kafaconsumer.poll() is called, it returns some records, from 1 up >>>>> >> >>>> to 200 records. So, it will proceed to run the pipeline steps. >>>>> >> >>>> Each kafkaconsumer.poll() takes about 0.8ms. So, in this case, >>>>> >> >>>> the polling and running of the pipeline are executed sequentially >>>>> >> >>>> within a single thread. So, after processing a batch of records, >>>>> >> >>>> it will need to wait for 0.8ms before it can process the next >>>>> >> >>>> batch of records again. >>>>> >> >>>> >>>>> >> >>>> Any suggestions would be appreciated. >>>>> >> >>>> >>>>> >> >>>> Hope that helps. >>>>> >> >>>> >>>>> >> >>>> Thanks and regards, >>>>> >> >>>> >>>>> >> >>>> Antonio. >>>>> >> >>>> >>>>> >> >>>> On 2020/12/04 19:17:46, Boyuan Zhang <boyu...@google.com> wrote: >>>>> >> >>>> > Opened https://issues.apache.org/jira/browse/BEAM-11403 for >>>>> >> >>>> > tracking. >>>>> >> >>>> > >>>>> >> >>>> > On Fri, Dec 4, 2020 at 10:52 AM Boyuan Zhang >>>>> >> >>>> > <boyu...@google.com> wrote: >>>>> >> >>>> > >>>>> >> >>>> > > Thanks for the pointer, Steve! I'll check it out. The >>>>> >> >>>> > > execution paths for >>>>> >> >>>> > > UnboundedSource and SDF wrapper are different. It's highly >>>>> >> >>>> > > possible that >>>>> >> >>>> > > the regression either comes from the invocation path for SDF >>>>> >> >>>> > > wrapper, or >>>>> >> >>>> > > the implementation of SDF wrapper itself. >>>>> >> >>>> > > >>>>> >> >>>> > > On Fri, Dec 4, 2020 at 6:33 AM Steve Niemitz >>>>> >> >>>> > > <sniem...@apache.org> wrote: >>>>> >> >>>> > > >>>>> >> >>>> > >> Coincidentally, someone else in the ASF slack mentioned [1] >>>>> >> >>>> > >> yesterday >>>>> >> >>>> > >> that they were seeing significantly reduced performance >>>>> >> >>>> > >> using KafkaIO.Read >>>>> >> >>>> > >> w/ the SDF wrapper vs the unbounded source. They mentioned >>>>> >> >>>> > >> they were using >>>>> >> >>>> > >> flink 1.9. >>>>> >> >>>> > >> >>>>> >> >>>> > >> https://the-asf.slack.com/archives/C9H0YNP3P/p1607057900393900 >>>>> >> >>>> > >> >>>>> >> >>>> > >> On Thu, Dec 3, 2020 at 1:56 PM Boyuan Zhang >>>>> >> >>>> > >> <boyu...@google.com> wrote: >>>>> >> >>>> > >> >>>>> >> >>>> > >>> Hi Steve, >>>>> >> >>>> > >>> >>>>> >> >>>> > >>> I think the major performance regression comes from >>>>> >> >>>> > >>> OutputAndTimeBoundedSplittableProcessElementInvoker[1], >>>>> >> >>>> > >>> which will >>>>> >> >>>> > >>> checkpoint the DoFn based on time/output limit and use >>>>> >> >>>> > >>> timers/state to >>>>> >> >>>> > >>> reschedule works. >>>>> >> >>>> > >>> >>>>> >> >>>> > >>> [1] >>>>> >> >>>> > >>> https://github.com/apache/beam/blob/master/runners/core-java/src/main/java/org/apache/beam/runners/core/OutputAndTimeBoundedSplittableProcessElementInvoker.java >>>>> >> >>>> > >>> >>>>> >> >>>> > >>> On Thu, Dec 3, 2020 at 9:40 AM Steve Niemitz >>>>> >> >>>> > >>> <sniem...@apache.org> >>>>> >> >>>> > >>> wrote: >>>>> >> >>>> > >>> >>>>> >> >>>> > >>>> I have a pipeline that reads from pubsub, does some >>>>> >> >>>> > >>>> aggregation, and >>>>> >> >>>> > >>>> writes to various places. Previously, in older versions >>>>> >> >>>> > >>>> of beam, when >>>>> >> >>>> > >>>> running this in the DirectRunner, messages would go >>>>> >> >>>> > >>>> through the pipeline >>>>> >> >>>> > >>>> almost instantly, making it very easy to debug locally, >>>>> >> >>>> > >>>> etc. >>>>> >> >>>> > >>>> >>>>> >> >>>> > >>>> However, after upgrading to beam 2.25, I noticed that it >>>>> >> >>>> > >>>> could take on >>>>> >> >>>> > >>>> the order of 5-10 minutes for messages to get from the >>>>> >> >>>> > >>>> pubsub read step to >>>>> >> >>>> > >>>> the next step in the pipeline (deserializing them, etc). >>>>> >> >>>> > >>>> The subscription >>>>> >> >>>> > >>>> being read from has on the order of 100,000 elements/sec >>>>> >> >>>> > >>>> arriving in it. >>>>> >> >>>> > >>>> >>>>> >> >>>> > >>>> Setting --experiments=use_deprecated_read fixes it, and >>>>> >> >>>> > >>>> makes the >>>>> >> >>>> > >>>> pipeline behave as it did before. >>>>> >> >>>> > >>>> >>>>> >> >>>> > >>>> It seems like the SDF implementation in the DirectRunner >>>>> >> >>>> > >>>> here is >>>>> >> >>>> > >>>> causing some kind of issue, either buffering a very large >>>>> >> >>>> > >>>> amount of data >>>>> >> >>>> > >>>> before emitting it in a bundle, or something else. Has >>>>> >> >>>> > >>>> anyone else run >>>>> >> >>>> > >>>> into this? >>>>> >> >>>> > >>>> >>>>> >> >>>> > >>> >>>>> >> >>>> >
