Hi Biao! Thanks for reviving this. I would like to join this discussion, but am quite occupied with the 1.9 release, so can we maybe pause this discussion for a week or so?
In the meantime I can share some suggestion based on prior experiments: How to do watermarks / timestamp extractors in a simpler and more flexible way. I think that part is quite promising should be part of the new source interface. https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/eventtime https://github.com/StephanEwen/flink/blob/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src/SourceOutput.java Some experiments on how to build the source reader and its library for common threading/split patterns: https://github.com/StephanEwen/flink/tree/source_interface/flink-core/src/main/java/org/apache/flink/api/common/src Best, Stephan On Thu, Jul 25, 2019 at 10:03 AM Biao Liu <mmyy1...@gmail.com> wrote: > Hi devs, > > Since 1.9 is nearly released, I think we could get back to FLIP-27. I > believe it should be included in 1.10. > > There are so many things mentioned in document of FLIP-27. [1] I think > we'd better discuss them separately. However the wiki is not a good place > to discuss. I wrote google doc about SplitReader API which misses some > details in the document. [2] > > 1. > https://cwiki.apache.org/confluence/display/FLINK/FLIP-27:+Refactor+Source+Interface > 2. > https://docs.google.com/document/d/1R1s_89T4S3CZwq7Tf31DciaMCqZwrLHGZFqPASu66oE/edit?usp=sharing > > CC Stephan, Aljoscha, Piotrek, Becket > > > On Thu, Mar 28, 2019 at 4:38 PM Biao Liu <mmyy1...@gmail.com> wrote: > >> Hi Steven, >> Thank you for the feedback. Please take a look at the document FLIP-27 >> <https://cwiki.apache.org/confluence/display/FLINK/FLIP-27%3A+Refactor+Source+Interface> >> which >> is updated recently. A lot of details of enumerator were added in this >> document. I think it would help. >> >> Steven Wu <stevenz...@gmail.com> 于2019年3月28日周四 下午12:52写道： >> >>> This proposal mentioned that SplitEnumerator might run on the JobManager >>> or >>> in a single task on a TaskManager. >>> >>> if enumerator is a single task on a taskmanager, then the job DAG can >>> never >>> been embarrassingly parallel anymore. That will nullify the leverage of >>> fine-grained recovery for embarrassingly parallel jobs. >>> >>> It's not clear to me what's the implication of running enumerator on the >>> jobmanager. So I will leave that out for now. >>> >>> On Mon, Jan 28, 2019 at 3:05 AM Biao Liu <mmyy1...@gmail.com> wrote: >>> >>> > Hi Stephan & Piotrek, >>> > >>> > Thank you for feedback. >>> > >>> > It seems that there are a lot of things to do in community. I am just >>> > afraid that this discussion may be forgotten since there so many >>> proposals >>> > recently. >>> > Anyway, wish to see the split topics soon :) >>> > >>> > Piotr Nowojski <pi...@da-platform.com> 于2019年1月24日周四 下午8:21写道： >>> > >>> > > Hi Biao! >>> > > >>> > > This discussion was stalled because of preparations for the open >>> sourcing >>> > > & merging Blink. I think before creating the tickets we should split >>> this >>> > > discussion into topics/areas outlined by Stephan and create Flips for >>> > that. >>> > > >>> > > I think there is no chance for this to be completed in couple of >>> > remaining >>> > > weeks/1 month before 1.8 feature freeze, however it would be good to >>> aim >>> > > with those changes for 1.9. >>> > > >>> > > Piotrek >>> > > >>> > > > On 20 Jan 2019, at 16:08, Biao Liu <mmyy1...@gmail.com> wrote: >>> > > > >>> > > > Hi community, >>> > > > The summary of Stephan makes a lot sense to me. It is much clearer >>> > indeed >>> > > > after splitting the complex topic into small ones. >>> > > > I was wondering is there any detail plan for next step? If not, I >>> would >>> > > > like to push this thing forward by creating some JIRA issues. >>> > > > Another question is that should version 1.8 include these features? >>> > > > >>> > > > Stephan Ewen <se...@apache.org> 于2018年12月1日周六 上午4:20写道： >>> > > > >>> > > >> Thanks everyone for the lively discussion. Let me try to summarize >>> > > where I >>> > > >> see convergence in the discussion and open issues. >>> > > >> I'll try to group this by design aspect of the source. Please let >>> me >>> > > know >>> > > >> if I got things wrong or missed something crucial here. >>> > > >> >>> > > >> For issues 1-3, if the below reflects the state of the >>> discussion, I >>> > > would >>> > > >> try and update the FLIP in the next days. >>> > > >> For the remaining ones we need more discussion. >>> > > >> >>> > > >> I would suggest to fork each of these aspects into a separate mail >>> > > thread, >>> > > >> or will loose sight of the individual aspects. >>> > > >> >>> > > >> *(1) Separation of Split Enumerator and Split Reader* >>> > > >> >>> > > >> - All seem to agree this is a good thing >>> > > >> - Split Enumerator could in the end live on JobManager (and >>> assign >>> > > splits >>> > > >> via RPC) or in a task (and assign splits via data streams) >>> > > >> - this discussion is orthogonal and should come later, when the >>> > > interface >>> > > >> is agreed upon. >>> > > >> >>> > > >> *(2) Split Readers for one or more splits* >>> > > >> >>> > > >> - Discussion seems to agree that we need to support one reader >>> that >>> > > >> possibly handles multiple splits concurrently. >>> > > >> - The requirement comes from sources where one poll()-style call >>> > > fetches >>> > > >> data from different splits / partitions >>> > > >> --> example sources that require that would be for example >>> Kafka, >>> > > >> Pravega, Pulsar >>> > > >> >>> > > >> - Could have one split reader per source, or multiple split >>> readers >>> > > that >>> > > >> share the "poll()" function >>> > > >> - To not make it too complicated, we can start with thinking >>> about >>> > one >>> > > >> split reader for all splits initially and see if that covers all >>> > > >> requirements >>> > > >> >>> > > >> *(3) Threading model of the Split Reader* >>> > > >> >>> > > >> - Most active part of the discussion ;-) >>> > > >> >>> > > >> - A non-blocking way for Flink's task code to interact with the >>> > source >>> > > is >>> > > >> needed in order to a task runtime code based on a >>> > > >> single-threaded/actor-style task design >>> > > >> --> I personally am a big proponent of that, it will help with >>> > > >> well-behaved checkpoints, efficiency, and simpler yet more robust >>> > > runtime >>> > > >> code >>> > > >> >>> > > >> - Users care about simple abstraction, so as a subclass of >>> > SplitReader >>> > > >> (non-blocking / async) we need to have a BlockingSplitReader which >>> > will >>> > > >> form the basis of most source implementations. BlockingSplitReader >>> > lets >>> > > >> users do blocking simple poll() calls. >>> > > >> - The BlockingSplitReader would spawn a thread (or more) and the >>> > > >> thread(s) can make blocking calls and hand over data buffers via a >>> > > blocking >>> > > >> queue >>> > > >> - This should allow us to cover both, a fully async runtime, and >>> a >>> > > simple >>> > > >> blocking interface for users. >>> > > >> - This is actually very similar to how the Kafka connectors work. >>> > Kafka >>> > > >> 9+ with one thread, Kafka 8 with multiple threads >>> > > >> >>> > > >> - On the base SplitReader (the async one), the non-blocking >>> method >>> > that >>> > > >> gets the next chunk of data would signal data availability via a >>> > > >> CompletableFuture, because that gives the best flexibility (can >>> await >>> > > >> completion or register notification handlers). >>> > > >> - The source task would register a "thenHandle()" (or similar) >>> on the >>> > > >> future to put a "take next data" task into the actor-style mailbox >>> > > >> >>> > > >> *(4) Split Enumeration and Assignment* >>> > > >> >>> > > >> - Splits may be generated lazily, both in cases where there is a >>> > > limited >>> > > >> number of splits (but very many), or splits are discovered over >>> time >>> > > >> - Assignment should also be lazy, to get better load balancing >>> > > >> - Assignment needs support locality preferences >>> > > >> >>> > > >> - Possible design based on discussion so far: >>> > > >> >>> > > >> --> SplitReader has a method "addSplits(SplitT...)" to add one >>> or >>> > > more >>> > > >> splits. Some split readers might assume they have only one split >>> ever, >>> > > >> concurrently, others assume multiple splits. (Note: idea behind >>> being >>> > > able >>> > > >> to add multiple splits at the same time is to ease startup where >>> > > multiple >>> > > >> splits may be assigned instantly.) >>> > > >> --> SplitReader has a context object on which it can call >>> indicate >>> > > when >>> > > >> splits are completed. The enumerator gets that notification and >>> can >>> > use >>> > > to >>> > > >> decide when to assign new splits. This should help both in cases >>> of >>> > > sources >>> > > >> that take splits lazily (file readers) and in case the source >>> needs to >>> > > >> preserve a partial order between splits (Kinesis, Pravega, Pulsar >>> may >>> > > need >>> > > >> that). >>> > > >> --> SplitEnumerator gets notification when SplitReaders start >>> and >>> > > when >>> > > >> they finish splits. They can decide at that moment to push more >>> splits >>> > > to >>> > > >> that reader >>> > > >> --> The SplitEnumerator should probably be aware of the source >>> > > >> parallelism, to build its initial distribution. >>> > > >> >>> > > >> - Open question: Should the source expose something like "host >>> > > >> preferences", so that yarn/mesos/k8s can take this into account >>> when >>> > > >> selecting a node to start a TM on? >>> > > >> >>> > > >> *(5) Watermarks and event time alignment* >>> > > >> >>> > > >> - Watermark generation, as well as idleness, needs to be per >>> split >>> > > (like >>> > > >> currently in the Kafka Source, per partition) >>> > > >> - It is desirable to support optional event-time-alignment, >>> meaning >>> > > that >>> > > >> splits that are ahead are back-pressured or temporarily >>> unsubscribed >>> > > >> >>> > > >> - I think i would be desirable to encapsulate watermark >>> generation >>> > > logic >>> > > >> in watermark generators, for a separation of concerns. The >>> watermark >>> > > >> generators should run per split. >>> > > >> - Using watermark generators would also help with another >>> problem of >>> > > the >>> > > >> suggested interface, namely supporting non-periodic watermarks >>> > > efficiently. >>> > > >> >>> > > >> - Need a way to "dispatch" next record to different watermark >>> > > generators >>> > > >> - Need a way to tell SplitReader to "suspend" a split until a >>> certain >>> > > >> watermark is reached (event time backpressure) >>> > > >> - This would in fact be not needed (and thus simpler) if we had a >>> > > >> SplitReader per split and may be a reason to re-open that >>> discussion >>> > > >> >>> > > >> *(6) Watermarks across splits and in the Split Enumerator* >>> > > >> >>> > > >> - The split enumerator may need some watermark awareness, which >>> > should >>> > > be >>> > > >> purely based on split metadata (like create timestamp of file >>> splits) >>> > > >> - If there are still more splits with overlapping event time >>> range >>> > for >>> > > a >>> > > >> split reader, then that split reader should not advance the >>> watermark >>> > > >> within the split beyond the overlap boundary. Otherwise future >>> splits >>> > > will >>> > > >> produce late data. >>> > > >> >>> > > >> - One way to approach this could be that the split enumerator may >>> > send >>> > > >> watermarks to the readers, and the readers cannot emit watermarks >>> > beyond >>> > > >> that received watermark. >>> > > >> - Many split enumerators would simply immediately send Long.MAX >>> out >>> > and >>> > > >> leave the progress purely to the split readers. >>> > > >> >>> > > >> - For event-time alignment / split back pressure, this begs the >>> > > question >>> > > >> how we can avoid deadlocks that may arise when splits are >>> suspended >>> > for >>> > > >> event time back pressure, >>> > > >> >>> > > >> *(7) Batch and streaming Unification* >>> > > >> >>> > > >> - Functionality wise, the above design should support both >>> > > >> - Batch often (mostly) does not care about reading "in order" and >>> > > >> generating watermarks >>> > > >> --> Might use different enumerator logic that is more locality >>> > aware >>> > > >> and ignores event time order >>> > > >> --> Does not generate watermarks >>> > > >> - Would be great if bounded sources could be identified at >>> compile >>> > > time, >>> > > >> so that "env.addBoundedSource(...)" is type safe and can return a >>> > > >> "BoundedDataStream". >>> > > >> - Possible to defer this discussion until later >>> > > >> >>> > > >> *Miscellaneous Comments* >>> > > >> >>> > > >> - Should the source have a TypeInformation for the produced type, >>> > > instead >>> > > >> of a serializer? We need a type information in the stream >>> anyways, and >>> > > can >>> > > >> derive the serializer from that. Plus, creating the serializer >>> should >>> > > >> respect the ExecutionConfig. >>> > > >> >>> > > >> - The TypeSerializer interface is very powerful but also not >>> easy to >>> > > >> implement. Its purpose is to handle data super efficiently, >>> support >>> > > >> flexible ways of evolution, etc. >>> > > >> For metadata I would suggest to look at the >>> SimpleVersionedSerializer >>> > > >> instead, which is used for example for checkpoint master hooks, >>> or for >>> > > the >>> > > >> streaming file sink. I think that is is a good match for cases >>> where >>> > we >>> > > do >>> > > >> not need more than ser/deser (no copy, etc.) and don't need to >>> push >>> > > >> versioning out of the serialization paths for best performance >>> (as in >>> > > the >>> > > >> TypeSerializer) >>> > > >> >>> > > >> >>> > > >> On Tue, Nov 27, 2018 at 11:45 AM Kostas Kloudas < >>> > > >> k.klou...@data-artisans.com> >>> > > >> wrote: >>> > > >> >>> > > >>> Hi Biao, >>> > > >>> >>> > > >>> Thanks for the answer! >>> > > >>> >>> > > >>> So given the multi-threaded readers, now we have as open >>> questions: >>> > > >>> >>> > > >>> 1) How do we let the checkpoints pass through our multi-threaded >>> > reader >>> > > >>> operator? >>> > > >>> >>> > > >>> 2) Do we have separate reader and source operators or not? In the >>> > > >> strategy >>> > > >>> that has a separate source, the source operator has a >>> parallelism of >>> > 1 >>> > > >> and >>> > > >>> is responsible for split recovery only. >>> > > >>> >>> > > >>> For the first one, given also the constraints (blocking, finite >>> > queues, >>> > > >>> etc), I do not have an answer yet. >>> > > >>> >>> > > >>> For the 2nd, I think that we should go with separate operators >>> for >>> > the >>> > > >>> source and the readers, for the following reasons: >>> > > >>> >>> > > >>> 1) This is more aligned with a potential future improvement >>> where the >>> > > >> split >>> > > >>> discovery becomes a responsibility of the JobManager and readers >>> are >>> > > >>> pooling more work from the JM. >>> > > >>> >>> > > >>> 2) The source is going to be the "single point of truth". It will >>> > know >>> > > >> what >>> > > >>> has been processed and what not. If the source and the readers >>> are a >>> > > >> single >>> > > >>> operator with parallelism > 1, or in general, if the split >>> discovery >>> > is >>> > > >>> done by each task individually, then: >>> > > >>> i) we have to have a deterministic scheme for each reader to >>> assign >>> > > >>> splits to itself (e.g. mod subtaskId). This is not necessarily >>> > trivial >>> > > >> for >>> > > >>> all sources. >>> > > >>> ii) each reader would have to keep a copy of all its processed >>> > slpits >>> > > >>> iii) the state has to be a union state with a non-trivial >>> merging >>> > > >> logic >>> > > >>> in order to support rescaling. >>> > > >>> >>> > > >>> Two additional points that you raised above: >>> > > >>> >>> > > >>> i) The point that you raised that we need to keep all splits >>> > (processed >>> > > >> and >>> > > >>> not-processed) I think is a bit of a strong requirement. This >>> would >>> > > imply >>> > > >>> that for infinite sources the state will grow indefinitely. This >>> is >>> > > >> problem >>> > > >>> is even more pronounced if we do not have a single source that >>> > assigns >>> > > >>> splits to readers, as each reader will have its own copy of the >>> > state. >>> > > >>> >>> > > >>> ii) it is true that for finite sources we need to somehow not >>> close >>> > the >>> > > >>> readers when the source/split discoverer finishes. The >>> > > >>> ContinuousFileReaderOperator has a work-around for that. It is >>> not >>> > > >> elegant, >>> > > >>> and checkpoints are not emitted after closing the source, but >>> this, I >>> > > >>> believe, is a bigger problem which requires more changes than >>> just >>> > > >>> refactoring the source interface. >>> > > >>> >>> > > >>> Cheers, >>> > > >>> Kostas >>> > > >>> >>> > > >> >>> > > >>> > > >>> > >>> >>
