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 <[email protected]> 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 <[email protected]> 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 <[email protected]> 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 <[email protected]> > 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 <[email protected]> > 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 <[email protected]> > 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 <[email protected]> > 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 <[email protected]> wrote: > >> >>>> > Opened https://issues.apache.org/jira/browse/BEAM-11403 for > tracking. > >> >>>> > > >> >>>> > On Fri, Dec 4, 2020 at 10:52 AM Boyuan Zhang <[email protected]> > 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 < > [email protected]> 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 < > [email protected]> 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 < > [email protected]> > >> >>>> > >>> 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? > >> >>>> > >>>> > >> >>>> > >>> > >> >>>> > >
