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