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? >> >>>> > >>>> >> >>>> > >>> >> >>>> >
