> ===============================================
> /class BoundedStreamInternalStateBackend<K> implements
> KeyedStateBackend<K>,
> SnapshotStrategy<SnapshotResult<KeyedStateHandle>>,
> Closeable,
> CheckpointListener {/
> ===============================================/
> /
The problem is that I could not use this "state backend" in a
StreamOperator. The goal of this effort is that it is mostly transparent
to all the implementations of StreamOperator(s). Right now
StreamOperator retrieves AbstractKeyedStateBackend through
StreamOperatorContext which instantiates it in StreamTaskInitializer
etc. The problem is that a big chunk of the current code base uses the
AbstractKeyedStateBackend, whereas it really just needs an interface not
that particular implementation. The change is really only about
separating the contract (InternalKeyedStateBackend) from the
implementation (AbstractKeyedStateBackend). My thinking is that it is
only an approach to fix a mistake of the past that StateBackend returns
a particular implementation rather than a contract.I do agree I don't need the `SnapshotStrategy` and `CheckpointListener` interfaces. The thing though is that the runtime expects those contracts from an AbstractKeyedStateBackend. BTW, If you'd like to see how does this change really looks like you can check the PR I already opened for it: https://github.com/apache/flink/pull/13405/files > Checking the FLIP more closely I found below description: "With a high > number of keys it (HeapStateBackend) suffers a significant penalty and > becomes even less performant for that particular case than the sorting > approach", does it mean "HeapStateBackend" outperformed > "SingleKeyStateBackend" when the number of keys is relatively small Correct, the goal though is not to outperform the HeapStateBackend. The single key state backend requires sorted inputs which come with a price. The main goal is to outperform RocksDBStateBackend, which is necessary for large states. > Thanks for the summary. I think it's more specific and could help > readers to better understand why we cannot use HeapKeyedStateBackend > directly, than the single line description "when the StateBackend > observes a new incoming key it will reset all acquired state objects > so far". What do you think? Sure, I can add it to the document. Best, Dawid On 18/09/2020 14:29, Yu Li wrote: > Thanks for the clarification Dawid. Some of my thoughts: > > /bq. The results are times for end-to-end execution of a job. > Therefore the sorting part is included. The actual target of the > replacement is RocksDB, which does the serialization and key bytes > comparison as well./ > I see. Checking the FLIP more closely I found below description: "With > a high number of keys it (HeapStateBackend) suffers a significant > penalty and becomes even less performant for that particular case than > the sorting approach", does it mean "HeapStateBackend" outperformed > "SingleKeyStateBackend" when the number of keys is relatively small? > The micro-benchmark of ValueState removes the key shuffling phase, so > its result could be self-explained. > > About `InternalKeyedStateBackend`, let me rephrase my question: why > don't we add the new state backend like below instead of adding a new > interface (and IMHO there's no need to implement the > `SnapshotStrategy` and `CheckpointListener` interfaces since it > doesn't support checkpoint)? Reserved for adding more internal state > backends in future? > =============================================== > /class BoundedStreamInternalStateBackend<K> implements > KeyedStateBackend<K>, > SnapshotStrategy<SnapshotResult<KeyedStateHandle>>, > Closeable, > CheckpointListener {/ > ===============================================/ > / > > /bq. Let me though quickly summarize and if you find it useful I can > add it to the FLIP itself./ > Thanks for the summary. I think it's more specific and could help > readers to better understand why we cannot use HeapKeyedStateBackend > directly, than the single line description "when the StateBackend > observes a new incoming key it will reset all acquired state objects > so far". What do you think? > > Thanks. > > Best Regards, > Yu > > > On Thu, 17 Sep 2020 at 23:38, Dawid Wysakowicz <dwysakow...@apache.org > <mailto:dwysakow...@apache.org>> wrote: > > Thanks for the comments Yu. > > > First of all, for the performance testing result, I'm wondering > whether the > > sorting cost is counted in the result for both DataSet and refined > > DataStream implementations. I could think of the saving of hash > computation > > and final iteration to emit the word-count result (processing a > key at a > > time could save such iteration), but not sure whether these cost > savings > > are at the same grade of comparing the key bytes. > The results are times for end-to-end execution of a job. Therefore the > sorting part is included. The actual target of the replacement is > RocksDB, which does the serialization and key bytes comparison as > well. > On top of that it adds all the RocksDB bookkeeping. > > > However, I'm not fully convinced to introduce a new > > `InternalKeyedStateBackend` interface. I agree that we don't > need to take > > the overhead of `AbstractKeyedStateBackend` since we don't plan > to support > > checkpoint for now, but why don't we directly write a state backend > > implementation for bounded stream? Or are we planning to > introduce more > > internal state backends in future? What's more, the current > design of > > `InternalKeyedStateBackend` in the FLIP document seems to be > extending as > > many interfaces as `AbstractedKeyedStateBackend` implements, > which I guess > > is a typo. > Maybe I was not clear enough about the change. This change does not > "strip" the AbstractKeyedStateBackend of any functionalities. My > intent > is not to remove any methods of the AbstractKeyedStateBackend. The > problem here is that the AbstractKeyedStateBackend is an abstract > class > (duh ;)), which does have some predefined implementation. Moreover it > requires objects such as InternalKeyContex, CloseableRegistry etc. > to be > constructed, which we don't need/want e.g. in the single key state > backend. My intention here is to make the StateBackend return only > pure > interfaces. (AbstractKeyedStateBackend is the only non-interface that > StateBackend returns). In other words I just want to make > AbstractKeyedStateBackend a proper interface. It is not a typo that > InternalKeyedStateBackend extends the same interfaces as > AbstractKeyedStateBackend does. > > > Thirdly, I suggest we name the special state backend as > > `BoundedStreamInternalStateBackend`. And from our existing > javadoc of > > `StateBackend` it actually cannot be called a complete state > backend...: "A > > State Backend defines how the state of a streaming application > is stored > > and checkpointed". > Thanks for the suggestion. Sure I can use that name. Yes I do agree it > is not a full fledged StateBackend. I do want it to be an internal > class, that is never used explicitly by users. > > > Lastly, I didn't find a detailed design of the > "SingleKeyStateBackend" in > > the FLIP, > I did not put it into the design, because 1) I found it internal. It > does not touch any public facing interfaces. 2) It is rather > straightforward. Let me though quickly summarize and if you find it > useful I can add it to the FLIP itself. > > > as how to detect the key switching > That is rather straightforwad. The state backend works only with the > assumption that the keys are sorted/grouped together. We keep the > current key and in the setCurrentKey we check if the new key is > different then the current one. Side note: yes, custom user operators > which call setCurrentKey explicitly might not work in this setup. > > > remove the data (especially in the non-windowing > > case), etc. > We only ever keep a single value for a state object. Therefore > ValueState is a very thin wrapper for a value, MapState for a HashMap, > ListState for a List etc. When the key changes we simply set the > wrapped > value/map/state to null. > > I hope this clarifies a few things. Let me know if you have any > questions. > > Best, > > Dawid > > On 17/09/2020 15:28, Yu Li wrote: > > Hi all, > > > > Sorry for being late to the discussion, but I just noticed there > are some > > state backend related changes proposed in this FLIP, so would > like to share > > my two cents. > > > > First of all, for the performance testing result, I'm wondering > whether the > > sorting cost is counted in the result for both DataSet and refined > > DataStream implementations. I could think of the saving of hash > computation > > and final iteration to emit the word-count result (processing a > key at a > > time could save such iteration), but not sure whether these cost > savings > > are at the same grade of comparing the key bytes. > > > > Regardless of the performance result, I agree that the capability of > > removing the data after processing a key could prominently > reduce the space > > required by state, so introducing a new state backend for > bounded stream > > makes sense. > > > > However, I'm not fully convinced to introduce a new > > `InternalKeyedStateBackend` interface. I agree that we don't > need to take > > the overhead of `AbstractKeyedStateBackend` since we don't plan > to support > > checkpoint for now, but why don't we directly write a state backend > > implementation for bounded stream? Or are we planning to > introduce more > > internal state backends in future? What's more, the current > design of > > `InternalKeyedStateBackend` in the FLIP document seems to be > extending as > > many interfaces as `AbstractedKeyedStateBackend` implements, > which I guess > > is a typo. > > > > Thirdly, I suggest we name the special state backend as > > `BoundedStreamInternalStateBackend`. And from our existing > javadoc of > > `StateBackend` it actually cannot be called a complete state > backend...: "A > > State Backend defines how the state of a streaming application > is stored > > and checkpointed". > > > > Lastly, I didn't find a detailed design of the > "SingleKeyStateBackend" in > > the FLIP, and suggest we write the key design down, such as how > to detect > > the key switching and remove the data (especially in the > non-windowing > > case), etc. > > > > Thanks. > > > > Best Regards, > > Yu > > > > > > On Wed, 9 Sep 2020 at 17:18, Kurt Young <ykt...@gmail.com > <mailto:ykt...@gmail.com>> wrote: > > > >> Yes, I didn't intend to block this FLIP, and some of the > comments are > >> actually implementation details. > >> And all of them are handled internally, not visible to users, > thus we can > >> also change or improve them > >> in the future. > >> > >> Best, > >> Kurt > >> > >> > >> On Wed, Sep 9, 2020 at 5:03 PM Aljoscha Krettek > <aljos...@apache.org <mailto:aljos...@apache.org>> > >> wrote: > >> > >>> I think Kurts concerns/comments are very valid and we need to > implement > >>> such things in the future. However, I also think that we need > to get > >>> started somewhere and I think what's proposed in this FLIP is > a good > >>> starting point that we can build on. So we should not get > paralyzed by > >>> thinking too far ahead into the future. Does that make sense? > >>> > >>> Best, > >>> Aljoscha > >>> > >>> On 08.09.20 16:59, Dawid Wysakowicz wrote: > >>>> Ad. 1 > >>>> > >>>> Yes, you are right in principle. > >>>> > >>>> Let me though clarify my proposal a bit. The proposed sort-style > >>>> execution aims at a generic KeyedProcessFunction were all the > >>>> "aggregations" are actually performed in the user code. It > tries to > >>>> improve the performance by actually removing the need to use > RocksDB > >>> e.g.: > >>>> private static final class Summer<K> > >>>> extends KeyedProcessFunction<K, Tuple2<K, Integer>, > >>>> Tuple2<K, Integer>> { > >>>> > >>>> .... > >>>> > >>>> @Override > >>>> public void processElement( > >>>> Tuple2<K, Integer> value, > >>>> Context ctx, > >>>> Collector<Tuple2<K, Integer>> out) throws > Exception { > >>>> if (!Objects.equals(timerRegistered.value(), > >> Boolean.TRUE)) > >>> { > >>> ctx.timerService().registerEventTimeTimer(Long.MAX_VALUE); > >>>> timerRegistered.update(true); > >>>> } > >>>> Integer v = counter.value(); > >>>> Integer incomingValue = value.f1; > >>>> if (v != null) { > >>>> v += incomingValue; > >>>> } else { > >>>> v = incomingValue; > >>>> } > >>>> counter.update(v); > >>>> } > >>>> > >>>> .... > >>>> > >>>> } > >>>> > >>>> Therefore I don't think the first part of your reply with > separating > >> the > >>>> write and read workload applies here. We do not aim to create a > >>>> competing API with the Table API. We think operations such as > joins or > >>>> analytical aggregations should be performed in Table API. > >>>> > >>>> As for the second part I agree it would be nice to fall back > to the > >>>> sorting approach only if a certain threshold of memory in a State > >>>> Backend is used. This has some problems though. We would need > a way to > >>>> estimate the size of the occupied memory to tell when the > threshold is > >>>> reached. That is not easily doable by default e.g. in a > >>>> MemoryStateBackend, as we do not serialize the values in the > state > >>>> backend by default. We would have to add that, but this would > add the > >>>> overhead of the serialization. > >>>> > >>>> This proposal aims at the cases where we do have a large > state that > >> will > >>>> not fit into the memory and without the change users are > forced to use > >>>> RocksDB. If the state fits in memory I agree it will be > better to do > >>>> hash-based aggregations e.g. using the MemoryStateBackend. > Therefore I > >>>> think it is important to give users the choice to use one or > the other > >>>> approach. We might discuss which approach should be the > default for > >>>> RuntimeMode.BATCH proposed in FLIP-134. Should it be > hash-based with > >>>> user configured state backend or sorting-based with a single > key at a > >>>> time backend. Moreover we could think if we should let users > choose the > >>>> sort vs hash "state backend" per operator. Would that suffice? > >>>> > >>>> Ad. 2 > >>>> > >>>> I still think we can just use the first X bytes of the > serialized form > >>>> as the normalized key and fallback to comparing full keys on > clashes. > >> It > >>>> is because we are actually not interested in a logical order, > but we > >>>> care only about the "grouping" aspect of the sorting. > Therefore I think > >>>> its enough to compare only parts of the full key as the > normalized key. > >>>> > >>>> Thanks again for the really nice and thorough feedback! > >>>> > >>>> Best, > >>>> > >>>> Dawid > >>>> > >>>> On 08/09/2020 14:47, Kurt Young wrote: > >>>>> Regarding #1, yes the state backend is definitely hash-based > >> execution. > >>>>> However there are some differences between > >>>>> batch hash-based execution. The key difference is *random > access & > >>>>> read/write mixed workload". For example, by using > >>>>> state backend in streaming execution, one have to mix the > read and > >> write > >>>>> operations and all of them are actually random > >>>>> access. But in a batch hash execution, we could divide the > phases into > >>>>> write and read. For example, we can build the > >>>>> hash table first, with only write operations. And once the > build is > >>> done, > >>>>> we can start to read and trigger the user codes. > >>>>> Take hash aggregation which blink planner implemented as an > example, > >>> during > >>>>> building phase, as long as the hash map > >>>>> could fit into memory, we will update the accumulators > directly in the > >>> hash > >>>>> map. And once we are running out of memory, > >>>>> we then fall back to sort based execution. It improves the > >> performance a > >>>>> lot if the incoming data can be processed in > >>>>> memory. > >>>>> > >>>>> Regarding #2, IIUC you are actually describing a binary > format of key, > >>> not > >>>>> normalized key which is used in DataSet. I will > >>>>> take String for example. If we have lots of keys with length all > >> greater > >>>>> than, let's say 20. In your proposal, you will encode > >>>>> the whole string in the prefix of your composed data ( <key> + > >>> <timestamp> > >>>>> + <record> ). And when you compare > >>>>> records, you will actually compare the *whole* key of the > record. For > >>>>> normalized key, it's fixed-length in this case, IIRC it will > >>>>> take 8 bytes to represent the string. And the sorter will > store the > >>>>> normalized key and offset in a dedicated array. When doing > >>>>> the sorting, it only sorts this *small* array. If the > normalized keys > >>> are > >>>>> different, you could immediately tell which is greater from > >>>>> normalized keys. You only have to compare the full keys if the > >>> normalized > >>>>> keys are equal and you know in this case the normalized > >>>>> key couldn't represent the full key. The reason why Dataset > is doing > >>> this > >>>>> is it's super cache efficient by sorting the *small* array. > >>>>> The idea is borrowed from this paper [1]. Let me know if I > missed or > >>>>> misunderstood anything. > >>>>> > >>>>> [1] https://dl.acm.org/doi/10.5555/615232.615237 (AlphaSort: a > >>>>> cache-sensitive parallel external sort) > >>>>> > >>>>> Best, > >>>>> Kurt > >>>>> > >>>>> > >>>>> On Tue, Sep 8, 2020 at 5:05 PM Dawid Wysakowicz < > >> dwysakow...@apache.org <mailto:dwysakow...@apache.org> > >>>>> wrote: > >>>>> > >>>>>> Hey Kurt, > >>>>>> > >>>>>> Thank you for comments! > >>>>>> > >>>>>> Ad. 1 I might have missed something here, but as far as I > see it is > >>> that > >>>>>> using the current execution stack with regular state backends > >> (RocksDB > >>>>>> in particular if we want to have spilling capabilities) is > equivalent > >>> to > >>>>>> hash-based execution. I can see a different spilling state > backend > >>>>>> implementation in the future, but I think it is not batch > specifc. Or > >>> am > >>>>>> I missing something? > >>>>>> > >>>>>> Ad. 2 Totally agree that normalized keys are important to the > >>>>>> performance. I think though TypeComparators are not a > necessity to > >> have > >>>>>> that. Actually this proposal is heading towards only ever > performing > >>>>>> "normalized keys" comparison. I have not included in the > proposal the > >>>>>> binary format which we will use for sorting (partially > because I > >>> forgot, > >>>>>> and partially because I thought it was too much of an > implementation > >>>>>> detail). Let me include it here though, as it might clear the > >> situation > >>>>>> a bit here. > >>>>>> > >>>>>> In DataSet, at times we have KeySelectors which extract > keys based on > >>>>>> field indices or names. This allows in certain situation to > extract > >> the > >>>>>> key from serialized records. Compared to DataSet, in > DataStream, the > >>> key > >>>>>> is always described with a black-box KeySelector, or > differently > >> with a > >>>>>> function which extracts a key from a deserialized record. > In turn > >>> there > >>>>>> is no way to create a comparator that could compare records by > >>>>>> extracting the key from a serialized record (neither with, nor > >> without > >>>>>> key normalization). We suggest that the input for the > sorter will be > >>>>>> > >>>>>> <key> + <timestamp> + <record> > >>>>>> > >>>>>> Without having the key prepended we would have to > deserialize the > >>> record > >>>>>> for every key comparison. > >>>>>> > >>>>>> Therefore if we agree that we perform binary comparison for > keys > >> (which > >>>>>> are always prepended), it is actually equivalent to a > DataSet with > >>>>>> TypeComparators that support key normalization. > >>>>>> > >>>>>> Let me know if that is clear, or I have missed something here. > >>>>>> > >>>>>> Best, > >>>>>> > >>>>>> Dawid > >>>>>> > >>>>>> On 08/09/2020 03:39, Kurt Young wrote: > >>>>>>> Hi Dawid, thanks for bringing this up, it's really > exciting to see > >>> that > >>>>>>> batch execution is introduced in DataStream. From the > flip, it seems > >>>>>>> we are sticking with sort based execution mode (at least > for now), > >>> which > >>>>>>> will sort the whole input data before any *keyed* operation is > >>>>>>> executed. I have two comments here: > >>>>>>> > >>>>>>> 1. Do we want to introduce hash-based execution in the > future? Sort > >>> is a > >>>>>>> safe choice but not the best in lots of cases. IIUC we > only need > >>>>>>> to make sure that before the framework finishes dealing > with one > >> key, > >>> the > >>>>>>> operator doesn't see any data belonging to other keys, thus > >>>>>>> hash-based execution would also do the trick. Oon tricky > thing the > >>>>>>> framework might need to deal with is memory constraint and > spilling > >>>>>>> in the hash map, but Flink also has some good knowledge > about these > >>>>>> stuff. > >>>>>>> 2. Going back to sort-based execution and how to sort > keys. From my > >>>>>>> experience, the performance of sorting would be one the most > >> important > >>>>>>> things if we want to achieve good performance of batch > execution. > >> And > >>>>>>> normalized keys are actually the key of the performance of > sorting. > >>>>>>> If we want to get rid of TypeComparator, I think we still > need to > >>> find a > >>>>>>> way to introduce this back. > >>>>>>> > >>>>>>> Best, > >>>>>>> Kurt > >>>>>>> > >>>>>>> > >>>>>>> On Tue, Sep 8, 2020 at 3:04 AM Aljoscha Krettek < > >> aljos...@apache.org <mailto:aljos...@apache.org>> > >>>>>> wrote: > >>>>>>>> Yes, I think we can address the problem of indeterminacy in a > >>> separate > >>>>>>>> FLIP because we're already in it. > >>>>>>>> > >>>>>>>> Aljoscha > >>>>>>>> > >>>>>>>> On 07.09.20 17:00, Dawid Wysakowicz wrote: > >>>>>>>>> @Seth That's a very good point. I agree that RocksDB has > the same > >>>>>>>>> problem. I think we can use the same approach for the sorted > >>> shuffles > >>>>>>>>> then. @Aljoscha I agree we should think about making it more > >>> resilient, > >>>>>>>>> as I guess users might have problems already if they use > keys with > >>>>>>>>> non-deterministic binary representation. How do you feel > about > >>>>>>>>> addressing that separately purely to limit the scope of > this FLIP? > >>>>>>>>> > >>>>>>>>> @Aljoscha I tend to agree with you that the best place > to actually > >>>>>> place > >>>>>>>>> the sorting would be in the InputProcessor(s). If there > are no > >> more > >>>>>>>>> suggestions in respect to that issue. I'll put this > proposal for > >>>>>> voting. > >>>>>>>>> @all Thank you for the feedback so far. I'd like to > start a voting > >>>>>>>>> thread on the proposal tomorrow. Therefore I'd > appreciate if you > >>>>>> comment > >>>>>>>>> before that, if you still have some outstanding ideas. > >>>>>>>>> > >>>>>>>>> Best, > >>>>>>>>> > >>>>>>>>> Dawid > >>>>>>>>> > >>>>>>>>> On 04/09/2020 17:13, Aljoscha Krettek wrote: > >>>>>>>>>> Seth is right, I was just about to write that as well. > There is a > >>>>>>>>>> problem, though, because some of our TypeSerializers > are not > >>>>>>>>>> deterministic even though we use them as if they were. Beam > >>> excludes > >>>>>>>>>> the FloatCoder, for example, and the AvroCoder in > certain cases. > >>> I'm > >>>>>>>>>> pretty sure there is also weirdness going on in our > >> KryoSerializer. > >>>>>>>>>> On 04.09.20 14:59, Seth Wiesman wrote: > >>>>>>>>>>> There is already an implicit assumption the > TypeSerializer for > >>> keys > >>>>>> is > >>>>>>>>>>> stable/deterministic, RocksDB compares keys using their > >> serialized > >>>>>> byte > >>>>>>>>>>> strings. I think this is a non-issue (or at least it's not > >>> changing > >>>>>> the > >>>>>>>>>>> status quo). > >>>>>>>>>>> > >>>>>>>>>>> On Fri, Sep 4, 2020 at 6:39 AM Timo Walther > <twal...@apache.org <mailto:twal...@apache.org> > >>>>>>>> wrote: > >>>>>>>>>>>> +1 for getting rid of the TypeComparator interface > and rely on > >>> the > >>>>>>>>>>>> serialized representation for grouping. > >>>>>>>>>>>> > >>>>>>>>>>>> Adding a new type to DataStream API is quite > difficult at the > >>> moment > >>>>>>>>>>>> due > >>>>>>>>>>>> to too many components that are required: TypeInformation > >> (tries > >>> to > >>>>>>>>>>>> deal > >>>>>>>>>>>> with logical fields for TypeComparators), > TypeSerializer (incl. > >>> it's > >>>>>>>>>>>> snapshot interfaces), and TypeComparator (with many > methods and > >>>>>>>>>>>> internals such normalized keys etc.). > >>>>>>>>>>>> > >>>>>>>>>>>> If necessary, we can add more simple > comparison-related methods > >>> to > >>>>>> the > >>>>>>>>>>>> TypeSerializer interface itself in the future (like > >>>>>>>>>>>> TypeSerializer.isDeterministic). > >>>>>>>>>>>> > >>>>>>>>>>>> Regards, > >>>>>>>>>>>> Timo > >>>>>>>>>>>> > >>>>>>>>>>>> > >>>>>>>>>>>> On 04.09.20 11:48, Aljoscha Krettek wrote: > >>>>>>>>>>>>> Thanks for publishing the FLIP! > >>>>>>>>>>>>> > >>>>>>>>>>>>> On 2020/09/01 06:49:06, Dawid Wysakowicz < > >>> dwysakow...@apache.org <mailto:dwysakow...@apache.org>> > >>>>>>>>>>>>> wrote: > >>>>>>>>>>>>>> 1. How to sort/group keys? What representation > of the > >> key > >>>>>>>>>>>>>> should we > >>>>>>>>>>>>>> use? Should we sort on the binary form or > should we > >>> depend > >>>>>> on > >>>>>>>>>>>>>> Comparators being available. > >>>>>>>>>>>>> Initially, I suggested to Dawid (in private) to do the > >>>>>>>>>>>>> sorting/grouping > >>>>>>>>>>>> by using the binary representation. Then my opinion > switched > >> and > >>> I > >>>>>>>>>>>> thought > >>>>>>>>>>>> we should use TypeComparator/Comparator because > that's what the > >>>>>>>>>>>> DataSet API > >>>>>>>>>>>> uses. After talking to Stephan, I'm again encouraged > in my > >>> opinion > >>>>>>>>>>>> to use > >>>>>>>>>>>> the binary representation because it means we can > eventually > >> get > >>> rid > >>>>>>>>>>>> of the > >>>>>>>>>>>> TypeComparator interface, which is a bit complicated, and > >>> because we > >>>>>>>>>>>> don't > >>>>>>>>>>>> need any good order in our sort, we only need the > grouping. > >>>>>>>>>>>>> This comes with some problems, though: we need to > ensure that > >>> the > >>>>>>>>>>>> TypeSerializer of the type we're sorting is > >> stable/deterministic. > >>>>>>>>>>>> Beam has > >>>>>>>>>>>> infrastructure for this in the form of > >>> Coder.verifyDeterministic() > >>>>>> [1] > >>>>>>>>>>>> which we don't have right now and should add if we go > down this > >>>>>> path. > >>>>>>>>>>>>>> 2. Where in the stack should we apply the > sorting (this > >>>>>> rather a > >>>>>>>>>>>>>> discussion about internals) > >>>>>>>>>>>>> Here, I'm gravitating towards the third option of > implementing > >>> it > >>>>>>>>>>>>> in the > >>>>>>>>>>>> layer of the StreamTask, which probably means > implementing a > >>> custom > >>>>>>>>>>>> InputProcessor. I think it's best to do it in this layer > >> because > >>> we > >>>>>>>>>>>> would > >>>>>>>>>>>> not mix concerns of different layers as we would if we > >>> implemented > >>>>>>>>>>>> this as > >>>>>>>>>>>> a custom StreamOperator. I think this solution is > also best > >> when > >>> it > >>>>>>>>>>>> comes > >>>>>>>>>>>> to multi-input operators. > >>>>>>>>>>>>>> 3. How should we deal with custom > implementations of > >>>>>>>>>>>>>> StreamOperators > >>>>>>>>>>>>> I think the cleanest solution would be to go through the > >>> complete > >>>>>>>>>>>> operator lifecycle for every key, because then the > watermark > >>> would > >>>>>> not > >>>>>>>>>>>> oscillate between -Inf and +Inf and we would not > break the > >>>>>> semantical > >>>>>>>>>>>> guarantees that we gave to operators so far, in that the > >>> watermark > >>>>>> is > >>>>>>>>>>>> strictly monotonically increasing. However, I don't > think this > >>>>>>>>>>>> solution is > >>>>>>>>>>>> feasible because it would come with too much overhead. We > >> should > >>>>>>>>>>>> solve this > >>>>>>>>>>>> problem via documentation and maybe educate people to > not query > >>> the > >>>>>>>>>>>> current > >>>>>>>>>>>> watermark or not rely on the watermark being > monotonically > >>>>>>>>>>>> increasing in > >>>>>>>>>>>> operator implementations to allow the framework more > freedoms > >> in > >>> how > >>>>>>>>>>>> user > >>>>>>>>>>>> programs are executed. > >>>>>>>>>>>>> Aljoscha > >>>>>>>>>>>>> > >>>>>>>>>>>>> [1] > >> > > https://github.com/apache/beam/blob/master/sdks/java/core/src/main/java/org/apache/beam/sdk/coders/Coder.java#L184 > >>> >
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