Hi Reuven, I noticed that there was an implementation of the in-memory OrderedListState introduced [1]. Where can I find out more regarding the plan and design? Is there a design doc? I'd like to know more details about the implementation to see if it fits my use case. I was hoping it would have a remove(TimestampedValue<T> e) method.
Thanks, -Tyson [1]: https://github.com/apache/beam/commit/9d0d0b0c4506b288164b155c5ce3a23d76db3c41 On 2020/08/03 21:41:46, Catlyn Kong <catl...@yelp.com> wrote: > Hey folks, > > Sry I'm late to this thread but this might be very helpful for the problem > we're dealing with. Do we have a design doc or a jira ticket I can follow? > > Cheers, > Catlyn > > On Thu, Jun 18, 2020 at 1:11 PM Jan Lukavský <je...@seznam.cz> wrote: > > > My questions were just an example. I fully agree there is a fundamental > > need for a sorted state (of some form, and I also think this links to > > efficient implementation of retrations) - I was reacting to Kenn's question > > about BIP. This one would be pretty nice example why it would be good to > > have such a "process" - not everything can be solved on ML and there are > > fundamental decisions that might need a closer attention. > > On 6/18/20 5:28 PM, Reuven Lax wrote: > > > > Jan - my proposal is exactly TimeSortedBagState (more accurately - > > TimeSortedListState), though I went a bit further and also proposed a way > > to have a dynamic number of tagged TimeSortedBagStates. > > > > You are correct that the runner doesn't really have to store the data time > > sorted - what's actually needed is the ability to fetch and remove > > timestamp ranges of data (though that does include fetching the entire > > list); TimeOrderedState is probably a more accurate name then > > TimeSortedState. I don't think we could get away with operations that only > > act on the smallest timestamp, however we could limit the API to only being > > able to fetch and remove prefixes of data (ordered by timestamp). However > > if we support prefixes, we might as well support arbitrary subranges. > > > > On Thu, Jun 18, 2020 at 7:26 AM Jan Lukavský <je...@seznam.cz> wrote: > > > >> Big +1 for a BIP, as this might really help clarify all the pros and cons > >> of all possibilities. There seem to be questions that need answering and > >> motivating use cases - do we need sorted map state or can we solve our use > >> cases by something simpler - e.g. the mentioned TimeSortedBagState? Does > >> that really have to be time-sorted structure, or does it "only" have to > >> have operations that can efficiently find and remove element with smallest > >> timestamp (like a PriorityQueue)? > >> > >> Jan > >> On 6/18/20 5:32 AM, Kenneth Knowles wrote: > >> > >> Zooming in from generic philosophy to be clear: adding time ordered > >> buffer to the Fn state API is *not* a shortcut.It has benefits that will > >> not be achieved by SDK-side implementation on top of either ordered or > >> unordered multimap. Are those benefits worth expanding the API? I don't > >> know. > >> > >> A change to allow a runner to have a specialized implementation for > >> time-buffered state would be one or more StateKey types, right? Reuven, > >> maybe put this and your Java API in a doc? A BIP? Seems like there's at > >> least the following to explore: > >> > >> - how that Java API would map to an SDK-side implementation on top of > >> multimap state key > >> - how that Java API would map to a new StateKey > >> - whether there's actually more than one relevant implementation of that > >> StateKey > >> - whether SDK-side implementation on some other state key would be > >> performant enough in all SDK languages (present and future) > >> > >> Zooming back out to generic philosophy: Proliferation of StateKey > >> types tuned by runners (which can very easily still share implementation) > >> is probably better than proliferation of complex SDK-side implementations > >> with varying completeness and performance. > >> > >> Kenn > >> > >> On Wed, Jun 17, 2020 at 3:24 PM Reuven Lax <re...@google.com> wrote: > >> > >>> It might help for me to describe what I have in mind. I'm still > >>> proposing that we build multimap, just not a globally-sorted multimap. > >>> > >>> My previous proposal was that we provide a Multimap<Key, Value> state > >>> type, sorted by key. this would have two additional operations - > >>> multimap.getRange(startKey, endKey) and multimap.deleteRange(startKey, > >>> endKey). The primary use case was timestamp sorting, but I felt that a > >>> sorted multimap provided a nice generalization - after all, you can simply > >>> key the multimap by timestamp to get timestamp sorting. > >>> > >>> This approach had some issues immediately that would take some work to > >>> solve. Since a multimap key can have any type and a runner will only be > >>> able to sort by encoded type, we would need to introduce a concept of > >>> order-preserving coders into Beam and plumb that through. Robert pointed > >>> out that even our existing standard coders for simple integral types don't > >>> preserve order, so there will likely be surprises here. > >>> > >>> My current proposal is for a multimap that is not sorted by key, but > >>> that can support.ordered values for a single key. Remember that a multimap > >>> maps K -> Iterable<V>, so this means that each individual Iterable<V> is > >>> ordered, but the keys have no specific order relative to each other. This > >>> is not too different from many multimap implementations where the keys are > >>> unordered, but the list of values for a single key at least has a stable > >>> order. > >>> > >>> The interface would look like this: > >>> > >>> public interface MultimapState<K, V> extends State { > >>> // Add a value with a default timestamp. > >>> void put(K key, V value); > >>> > >>> // Add a timestamped value. > >>> void put(K, key, TimestampedValue<V> value); > >>> > >>> // Remove all values for a key. > >>> void remove (K key); > >>> > >>> // Remove all values for a key with timestamps within the specified > >>> range. > >>> void removeRange(K key, Instant startTs, Instant endTs); > >>> > >>> // Get an Iterable of values for V. The Iterable will be returned > >>> sorted by timestamp. > >>> ReadableState<Iterable<TimestampedValue<V>>> get(K key); > >>> > >>> // Get an Iterable of values for V in the specified range. The > >>> Iterable will be returned sorted by timestamp. > >>> ReadableState<Iterable<TimestampedValue<V>>> getRange(K key, Instant > >>> startTs, Instant endTs); > >>> > >>> ReadableState<Iterable<K>> keys(); > >>> ReadableState<Iterable<TimestampedValue<V>>> values(); > >>> ReadableState<Iterable<Map.Entry<K, TimestampedValue<V>> entries; > >>> } > >>> > >>> We can of course provide helper functions that allow using MultimapState > >>> without deailing with TimestampValue for users who only want a multimap > >>> and > >>> don't want sorting. > >>> > >>> I think many users will only need a single sorted list - not a full > >>> multimap. It's worth offering this as well, and we can simply build it on > >>> top of MultimapState. It will look like an extension of BagState > >>> > >>> public interface TimestampSortedListState<T> extends State { > >>> void add(TimestampedValue<T> value); > >>> Iterable<TimestampedValue<T>> read(); > >>> Iterable<TimestampedValue<T>> readRange(Instant startTs, Instant > >>> endTs); > >>> void clearRange(Instant startTs, Instant endTs); > >>> } > >>> > >>> > >>> On Wed, Jun 17, 2020 at 2:47 PM Luke Cwik <lc...@google.com> wrote: > >>> > >>>> The portability layer is meant to live across multiple versions of Beam > >>>> and I don't think it should be treated by doing the simple and useful > >>>> thing > >>>> now since I believe it will lead to a proliferation of the API. > >>>> > >>>> On Wed, Jun 17, 2020 at 2:30 PM Kenneth Knowles <k...@apache.org> > >>>> wrote: > >>>> > >>>>> I have thoughts on the subject of whether to have APIs just for the > >>>>> lowest-level building blocks versus having APIs for higher-level > >>>>> constructs. Specifically this applies to providing only unsorted > >>>>> multimap > >>>>> vs what I will call "time-ordered buffer". TL;DR: I'd vote to focus on > >>>>> time-ordered buffer; if it turns out to be easy to go all the way to > >>>>> sorted > >>>>> multimap that's nice-to-have; if it turns out to be easy to implement on > >>>>> top of unsorted map state that should probably be under the hood > >>>>> > >>>>> Reasons to build low-level multimap in the runner & fn api and layer > >>>>> higher-level things in the SDK: > >>>>> > >>>>> - It is less implementation for runners if they have to only provide > >>>>> fewer lower-level building blocks like multimap state. > >>>>> - There are many more runners than SDKs (and will be even more and > >>>>> more) so this saves overall. > >>>>> > >>>>> Reasons to build higher-level constructs directly in the runner and fn > >>>>> api: > >>>>> > >>>>> - Having multiple higher-level state types may actually be less > >>>>> implementation than one complex state type, especially if they map to > >>>>> runner primitives. > >>>>> - The runner may have better specialized implementations, especially > >>>>> for something like a time-ordered buffer. > >>>>> - The particular access patterns in an SDK-based implementation may > >>>>> not be ideal for each runner's underlying implementation of the > >>>>> low-level > >>>>> building block. > >>>>> - There may be excessive gRPC overhead even for optimal access > >>>>> patterns. > >>>>> > >>>>> There are ways to have best of both worlds, like: > >>>>> > >>>>> 1. Define multiple state types according to fundamental access > >>>>> patterns, like we did this before portability. > >>>>> 2. If it is easy to layer one on top of the other, do that inside the > >>>>> runner. Provide shared code so for runners providing the lowest-level > >>>>> primitive they get all the types for free. > >>>>> > >>>>> I understand that this is an oversimplification. It still creates some > >>>>> more work. And APIs are a burden so it is good to introduce as few as > >>>>> possible for maintenance. But it has performance benefits and also > >>>>> unblocks > >>>>> "just doing the simple and useful thing now" which I always like to do > >>>>> as > >>>>> long as it is compatible with future changes. If the APIs are > >>>>> fundamental, > >>>>> like sets, maps, timestamp ordering, then it is safe to guess that they > >>>>> will change rarely and be useful forever. > >>>>> > >>>>> Kenn > >>>>> > >>>>> On Tue, Jun 16, 2020 at 2:54 PM Luke Cwik <lc...@google.com> wrote: > >>>>> > >>>>>> I would be glad to take a stab at how to provide sorting on top of > >>>>>> unsorted multimap state. > >>>>>> Based upon your description, you want integer keys representing > >>>>>> timestamps and arbitrary user value for the values, is that correct? > >>>>>> What kinds of operations do you need on the sorted map state in order > >>>>>> of efficiency requirements? > >>>>>> (e.g. Next(x), Previous(x), GetAll(Range[x, y)), ClearAll(Range[x, y)) > >>>>>> What kinds of operations do we expect the underlying unsorted map > >>>>>> state to be able to provide? > >>>>>> (at a minimum Get(K), Append(K), Clear(K) but what else e.g. > >>>>>> enumerate(K)?) > >>>>>> > >>>>>> I went through a similar exercise of how to provide a list like side > >>>>>> input view over a multimap[1] side input which efficiently allowed > >>>>>> computation of size and provided random access while only having > >>>>>> access to > >>>>>> get(K) and enumerate K's. > >>>>>> > >>>>>> 1: > >>>>>> https://github.com/lukecwik/incubator-beam/blob/ec8769f6163ca8a4daecc2fb29708bc1da430917/sdks/java/core/src/main/java/org/apache/beam/sdk/values/PCollectionViews.java#L568 > >>>>>> > >>>>>> On Tue, Jun 16, 2020 at 8:47 AM Reuven Lax <re...@google.com> wrote: > >>>>>> > >>>>>>> Bringing this subject up again, > >>>>>>> > >>>>>>> I've spent some time looking into implementing this for the Dataflow > >>>>>>> runner. I'm unable to find a way to implement the arbitrary sorted > >>>>>>> multimap > >>>>>>> efficiently for the case where there are large numbers of unique keys. > >>>>>>> Since the primary driving use case is timestamp ordering (i.e. key is > >>>>>>> event > >>>>>>> timestamp), you would expect to have nearly a new key per element. I > >>>>>>> considered Luke's suggestion above, but unfortunately it doesn't > >>>>>>> really > >>>>>>> solve this issue. > >>>>>>> > >>>>>>> The primary use case for sorting always seems to be sorting by > >>>>>>> timestamp. I want to propose that instead of building the > >>>>>>> fully-general > >>>>>>> sorted multimap, we instead focus on a state type where the sort key > >>>>>>> is an > >>>>>>> integral type (like a timestamp or an integer). There is still a > >>>>>>> valid use > >>>>>>> case for multimap, but we can provide that as an unordered state. At > >>>>>>> least > >>>>>>> for Dataflow, it will be much easier > >>>>>>> > >>>>>>> While my difficulties here may be specific to the Dataflow runner, > >>>>>>> any such support would have to be built into other runners as well, > >>>>>>> and > >>>>>>> limiting to integral sorting likely makes it easier for other runners > >>>>>>> to > >>>>>>> implement this. Also, if you look at this > >>>>>>> <https://github.com/apache/flink/blob/0ab1549f52f1f544e8492757c6b0d562bf50a061/flink-table/flink-table-planner/src/main/scala/org/apache/flink/table/runtime/join/TemporalRowtimeJoin.scala#L95> > >>>>>>> Flink > >>>>>>> comment pointed out by Aljoscha, for Flink the main use case > >>>>>>> identified was > >>>>>>> also timestamp sorting. This will also simplify the API design for > >>>>>>> this > >>>>>>> feature: Sorted multimap with arbitrary keys would require us to > >>>>>>> introduce > >>>>>>> a way of mapping natural ordering to encoded ordering (i.e. a new > >>>>>>> OrderPreservingCoder), but if we limit sort keys to integral types, > >>>>>>> the API > >>>>>>> design is simpler as integral types can be represented directly. > >>>>>>> > >>>>>>> Reuven > >>>>>>> > >>>>>>> On Sun, Jun 2, 2019 at 7:04 AM Reuven Lax <re...@google.com> wrote: > >>>>>>> > >>>>>>>> This sounds to me like a potential runner strategy. However if a > >>>>>>>> runner can natively support sorted maps (e.g. we expect the Dataflow > >>>>>>>> runner > >>>>>>>> to be able to do so, and I think it would be useful for other > >>>>>>>> runners as > >>>>>>>> well), then it's probably preferable to allow the runner to use its > >>>>>>>> native > >>>>>>>> capabilities. > >>>>>>>> > >>>>>>>> On Fri, May 24, 2019 at 11:05 AM Lukasz Cwik <lc...@google.com> > >>>>>>>> wrote: > >>>>>>>> > >>>>>>>>> For the API that you proposed, the map key is always "void" and > >>>>>>>>> the sort key == user key. So in my example of > >>>>>>>>> key: dummy value > >>>>>>>>> key.000: token, (0001, value4) > >>>>>>>>> key.001: token, (0010, value1), (0011, value2) > >>>>>>>>> key.01: token > >>>>>>>>> key.1: token, (1011, value3) > >>>>>>>>> you would have: > >>>>>>>>> "void": dummy value > >>>>>>>>> "void".000: token, (0001, value4) > >>>>>>>>> "void".001: token, (0010, value1), (0011, value2) > >>>>>>>>> "void".01: token > >>>>>>>>> "void".1: token, (1011, value3) > >>>>>>>>> > >>>>>>>>> Iterable<KV<K, V>> entriesUntil(K limit) translates into walking > >>>>>>>>> the the prefixes until you find a common prefix for K and then > >>>>>>>>> filter for > >>>>>>>>> values where they have a sort key <= K. Using the example above, to > >>>>>>>>> find > >>>>>>>>> entriesUntil(0010) you would: > >>>>>>>>> look for key."", miss > >>>>>>>>> look for key.0, miss > >>>>>>>>> look for key.00, miss > >>>>>>>>> look for key.000, hit, sort all contained values using secondary > >>>>>>>>> key, provide value4 to user > >>>>>>>>> look for key.001, hit, notice that 001 is a prefix of 0010 so we > >>>>>>>>> sort all contained values using secondary key, filter out value2 and > >>>>>>>>> provide value1 > >>>>>>>>> > >>>>>>>>> void removeUntil(K limit) also translates into walking the > >>>>>>>>> prefixes but instead we will clear them when we have a "hit" with > >>>>>>>>> some > >>>>>>>>> special logic for when the sort key is a prefix of the key. Used the > >>>>>>>>> example, to removeUntil(0010) you would: > >>>>>>>>> look for key."", miss > >>>>>>>>> look for key.0, miss > >>>>>>>>> look for key.00, miss > >>>>>>>>> look for key.000, hit, clear > >>>>>>>>> look for key.001, hit, notice that 001 is a prefix of 0010 so we > >>>>>>>>> sort all contained values using secondary key, store in memory all > >>>>>>>>> values > >>>>>>>>> that > 0010, clear and append values stored in memory. > >>>>>>>>> > >>>>>>>>> On Fri, May 24, 2019 at 10:36 AM Reuven Lax <re...@google.com> > >>>>>>>>> wrote: > >>>>>>>>> > >>>>>>>>>> Can you explain how fetching and deleting ranges of keys would > >>>>>>>>>> work with this data structure? > >>>>>>>>>> > >>>>>>>>>> On Fri, May 24, 2019 at 9:50 AM Lukasz Cwik <lc...@google.com> > >>>>>>>>>> wrote: > >>>>>>>>>> > >>>>>>>>>>> Reuven, for the example, I assume that we never want to store > >>>>>>>>>>> more then 2 values at a given sort key prefix, and if we do then > >>>>>>>>>>> we will > >>>>>>>>>>> create a new longer prefix splitting up the values based upon the > >>>>>>>>>>> sort key. > >>>>>>>>>>> > >>>>>>>>>>> Tuple representation in examples below is (key, sort key, value) > >>>>>>>>>>> and . is a character outside of the alphabet which can be > >>>>>>>>>>> represented by > >>>>>>>>>>> using an escaping encoding that wraps the key + sort key encoding. > >>>>>>>>>>> > >>>>>>>>>>> To insert (key, 0010, value1), we lookup "key" + all the > >>>>>>>>>>> prefixes of 0010 finding one that is not empty. In this case its > >>>>>>>>>>> 0, so we > >>>>>>>>>>> append value to the map at key.0 ending up with (we also set the > >>>>>>>>>>> key to any > >>>>>>>>>>> dummy value to know that it it contains values): > >>>>>>>>>>> key: dummy value > >>>>>>>>>>> key."": token, (0010, value1) > >>>>>>>>>>> Now we insert (key, 0011, value2), we again lookup "key" + all > >>>>>>>>>>> the prefixes of 0010, finding "", so we append value2 to key."" > >>>>>>>>>>> ending up > >>>>>>>>>>> with: > >>>>>>>>>>> key: dummy value > >>>>>>>>>>> key."": token, (0010, value1), (0011, value2) > >>>>>>>>>>> Now we insert (key, 1011, value3), we again lookup "key" + all > >>>>>>>>>>> the prefixes of 1011 finding "" but notice that it is full, so we > >>>>>>>>>>> partition > >>>>>>>>>>> all the values into two prefixes 0 and 1. We also clear the "" > >>>>>>>>>>> prefix > >>>>>>>>>>> ending up with: > >>>>>>>>>>> key: dummy value > >>>>>>>>>>> key.0: token, (0010, value1), (0011, value2) > >>>>>>>>>>> key.1: token, (1011, value3) > >>>>>>>>>>> Now we insert (key, 0001, value4), we again lookup "key" + all > >>>>>>>>>>> the prefixes of the value finding 0 but notice that it is full, > >>>>>>>>>>> so we > >>>>>>>>>>> partition all the values into two prefixes 00 and 01 but notice > >>>>>>>>>>> this > >>>>>>>>>>> doesn't help us since 00 will be too full so we split 00 again to > >>>>>>>>>>> 000, 001. > >>>>>>>>>>> We also clear the 0 prefix ending up with: > >>>>>>>>>>> key: dummy value > >>>>>>>>>>> key.000: token, (0001, value4) > >>>>>>>>>>> key.001: token, (0010, value1), (0011, value2) > >>>>>>>>>>> key.01: token > >>>>>>>>>>> key.1: token, (1011, value3) > >>>>>>>>>>> > >>>>>>>>>>> We are effectively building a trie[1] where we only have values > >>>>>>>>>>> at the leaves and control how full each leaf can be. There are > >>>>>>>>>>> other trie > >>>>>>>>>>> representations like a radix tree that may be better. > >>>>>>>>>>> > >>>>>>>>>>> Looking up the values in sorted order for "key" would go like > >>>>>>>>>>> this: > >>>>>>>>>>> Is key set, yes > >>>>>>>>>>> look for key."", miss > >>>>>>>>>>> look for key.0, miss > >>>>>>>>>>> look for key.00, miss > >>>>>>>>>>> look for key.000, hit, sort all contained values using secondary > >>>>>>>>>>> key, provide value4 to user > >>>>>>>>>>> look for key.001, hit, sort all contained values using secondary > >>>>>>>>>>> key, provide value1 followed by value2 to user > >>>>>>>>>>> look for key.01, hit, empty, return no values to user > >>>>>>>>>>> look for key.1, hit, sort all contained values using secondary > >>>>>>>>>>> key, provide value3 to user > >>>>>>>>>>> we have walked the entire prefix space, signal end of iterable > >>>>>>>>>>> > >>>>>>>>>>> Some notes for the above: > >>>>>>>>>>> * The dummy value is used to know that the key contains values > >>>>>>>>>>> and the token is to know whether there are any values deeper in > >>>>>>>>>>> the trie so > >>>>>>>>>>> when we know when to stop searching. > >>>>>>>>>>> * If we can recalculate the sort key from the combination of the > >>>>>>>>>>> key and value, then we don't need to store it. > >>>>>>>>>>> * Keys with lots of values will perform worse then keys with > >>>>>>>>>>> less values since we have to look up more keys but they will be > >>>>>>>>>>> empty > >>>>>>>>>>> reads. The number of misses can be controlled by how many > >>>>>>>>>>> elements we are > >>>>>>>>>>> willing to store at a given node before we subdivide. > >>>>>>>>>>> > >>>>>>>>>>> In reality you could build a lot of structures (e.g. red black > >>>>>>>>>>> tree, binary tree) using the sort key, the issue is the cost of > >>>>>>>>>>> rebalancing/re-organizing the structure in map form and whether > >>>>>>>>>>> it has a > >>>>>>>>>>> convenient pre-order traversal for lookups. > >>>>>>>>>>> > >>>>>>>>>>> > >>>>>>>>>>> > >>>>>>>>>>> On Fri, May 24, 2019 at 8:14 AM Reuven Lax <re...@google.com> > >>>>>>>>>>> wrote: > >>>>>>>>>>> > >>>>>>>>>>>> Some great comments! > >>>>>>>>>>>> > >>>>>>>>>>>> *Aljoscha*: absolutely this would have to be implemented by > >>>>>>>>>>>> runners to be efficient. We can of course provide a default > >>>>>>>>>>>> (inefficient) > >>>>>>>>>>>> implementation, but ideally runners would provide better ones. > >>>>>>>>>>>> > >>>>>>>>>>>> *Jan* Exactly. I think MapState can be dropped or backed by > >>>>>>>>>>>> this. E.g. > >>>>>>>>>>>> > >>>>>>>>>>>> *Robert* Great point about standard coders not satisfying > >>>>>>>>>>>> this. That's why I suggested that we provide a way to tag the > >>>>>>>>>>>> coders that > >>>>>>>>>>>> do preserve order, and only accept those as key coders > >>>>>>>>>>>> Alternatively we > >>>>>>>>>>>> could present a more limited API - e.g. only allowing a > >>>>>>>>>>>> hard-coded set of > >>>>>>>>>>>> types to be used as keys - but that seems counter to the > >>>>>>>>>>>> direction Beam > >>>>>>>>>>>> usually goes. So users will have two ways .of creating multimap > >>>>>>>>>>>> state specs: > >>>>>>>>>>>> > >>>>>>>>>>>> private final StateSpec<MultimapState<Long, String>> state = > >>>>>>>>>>>> StateSpecs.multimap(VarLongCoder.of(), StringUtf8Coder.of()); > >>>>>>>>>>>> > >>>>>>>>>>>> or > >>>>>>>>>>>> private final StateSpec<MultimapState<Long, String>> state = > >>>>>>>>>>>> StateSpecs.orderedMultimap(VarLongCoder.of(), > >>>>>>>>>>>> StringUtf8Coder.of()); > >>>>>>>>>>>> > >>>>>>>>>>>> The second one will validate that the key coder preserves > >>>>>>>>>>>> order, and fails otherwise (similar to coder determinism > >>>>>>>>>>>> checking in > >>>>>>>>>>>> GroupByKey). (BTW we would also have versions of these functions > >>>>>>>>>>>> that use > >>>>>>>>>>>> coder inference to "guess" the coder, but those will do the same > >>>>>>>>>>>> checking) > >>>>>>>>>>>> > >>>>>>>>>>>> Also the API I proposed did support random access! We could > >>>>>>>>>>>> separate out OrderedBagState again if we think the use cases are > >>>>>>>>>>>> fundamentally different. I merged the proposal into that of > >>>>>>>>>>>> MultimapState > >>>>>>>>>>>> because there seemed be 99% overlap. > >>>>>>>>>>>> > >>>>>>>>>>>> Reuven > >>>>>>>>>>>> > >>>>>>>>>>>> On Fri, May 24, 2019 at 6:19 AM Robert Bradshaw < > >>>>>>>>>>>> rober...@google.com> wrote: > >>>>>>>>>>>> > >>>>>>>>>>>>> On Fri, May 24, 2019 at 5:32 AM Reuven Lax <re...@google.com> > >>>>>>>>>>>>> wrote: > >>>>>>>>>>>>> > > >>>>>>>>>>>>> > On Thu, May 23, 2019 at 1:53 PM Ahmet Altay < > >>>>>>>>>>>>> al...@google.com> wrote: > >>>>>>>>>>>>> >> > >>>>>>>>>>>>> >> > >>>>>>>>>>>>> >> > >>>>>>>>>>>>> >> On Thu, May 23, 2019 at 1:38 PM Lukasz Cwik < > >>>>>>>>>>>>> lc...@google.com> wrote: > >>>>>>>>>>>>> >>> > >>>>>>>>>>>>> >>> > >>>>>>>>>>>>> >>> > >>>>>>>>>>>>> >>> On Thu, May 23, 2019 at 11:37 AM Rui Wang < > >>>>>>>>>>>>> ruw...@google.com> wrote: > >>>>>>>>>>>>> >>>>> > >>>>>>>>>>>>> >>>>> A few obvious problems with this code: > >>>>>>>>>>>>> >>>>> 1. Removing the elements already processed from the > >>>>>>>>>>>>> bag requires clearing and rewriting the entire bag. This is > >>>>>>>>>>>>> O(n^2) in the > >>>>>>>>>>>>> number of input trades. > >>>>>>>>>>>>> >>>> > >>>>>>>>>>>>> >>>> why it's not O(2 * n) to clearing and rewriting trade > >>>>>>>>>>>>> state? > >>>>>>>>>>>>> >>>> > >>>>>>>>>>>>> >>>>> > >>>>>>>>>>>>> >>>>> public interface SortedMultimapState<K, V> extends State > >>>>>>>>>>>>> { > >>>>>>>>>>>>> >>>>> // Add a value to the map. > >>>>>>>>>>>>> >>>>> void put(K key, V value); > >>>>>>>>>>>>> >>>>> // Get all values for a given key. > >>>>>>>>>>>>> >>>>> ReadableState<Iterable<V>> get(K key); > >>>>>>>>>>>>> >>>>> // Return all entries in the map. > >>>>>>>>>>>>> >>>>> ReadableState<Iterable<KV<K, V>>> allEntries(); > >>>>>>>>>>>>> >>>>> // Return all entries in the map with keys <= limit. > >>>>>>>>>>>>> returned elements are sorted by the key. > >>>>>>>>>>>>> >>>>> ReadableState<Iterable<KV<K, V>>> entriesUntil(K > >>>>>>>>>>>>> limit); > >>>>>>>>>>>>> >>>>> > >>>>>>>>>>>>> >>>>> // Remove all values with the given key; > >>>>>>>>>>>>> >>>>> void remove(K key); > >>>>>>>>>>>>> >>>>> // Remove all entries in the map with keys <= limit. > >>>>>>>>>>>>> >>>>> void removeUntil(K limit); > >>>>>>>>>>>>> >>>> > >>>>>>>>>>>>> >>>> Will removeUntilExcl(K limit) also useful? It will remove > >>>>>>>>>>>>> all entries in the map with keys < limit. > >>>>>>>>>>>>> >>>> > >>>>>>>>>>>>> >>>>> > >>>>>>>>>>>>> >>>>> Runners will sort based on the encoded value of the key. > >>>>>>>>>>>>> In order to make this easier for users, I propose that we > >>>>>>>>>>>>> introduce a new > >>>>>>>>>>>>> tag on Coders PreservesOrder. A Coder that contains this tag > >>>>>>>>>>>>> guarantees > >>>>>>>>>>>>> that the encoded value preserves the same ordering as the base > >>>>>>>>>>>>> Java type. > >>>>>>>>>>>>> >>>> > >>>>>>>>>>>>> >>>> > >>>>>>>>>>>>> >>>> Could you clarify what is "encoded value preserves the > >>>>>>>>>>>>> same ordering as the base Java type"? > >>>>>>>>>>>>> >>> > >>>>>>>>>>>>> >>> > >>>>>>>>>>>>> >>> Lets say A and B represent two different instances of the > >>>>>>>>>>>>> same Java type like a double, then A < B (using the languages > >>>>>>>>>>>>> comparison > >>>>>>>>>>>>> operator) iff encode(A) < encode(B) (note the encoded versions > >>>>>>>>>>>>> are compared > >>>>>>>>>>>>> lexicographically) > >>>>>>>>>>>>> >> > >>>>>>>>>>>>> >> > >>>>>>>>>>>>> >> Since coders are shared across SDKs, do we expect A < B iff > >>>>>>>>>>>>> e(A) < e(P) property to hold for all languages we support? What > >>>>>>>>>>>>> happens A, > >>>>>>>>>>>>> B sort differently in different languages? > >>>>>>>>>>>>> > > >>>>>>>>>>>>> > > >>>>>>>>>>>>> > That would have to be the property of the coder (which means > >>>>>>>>>>>>> that this property probably needs to be represented in the > >>>>>>>>>>>>> portability > >>>>>>>>>>>>> representation of the coder). I imagine the common use cases > >>>>>>>>>>>>> will be for > >>>>>>>>>>>>> simple coders like int, long, string, etc., which are likely to > >>>>>>>>>>>>> sort the > >>>>>>>>>>>>> same in most languages. > >>>>>>>>>>>>> > >>>>>>>>>>>>> The standard coders for both double and integral types do not > >>>>>>>>>>>>> respect > >>>>>>>>>>>>> the natural ordering (consider negative values). KV coders > >>>>>>>>>>>>> violate the > >>>>>>>>>>>>> "natural" lexicographic ordering on components as well. I think > >>>>>>>>>>>>> implicitly sorting on encoded value would yield many > >>>>>>>>>>>>> surprises. (The > >>>>>>>>>>>>> state, of course, could take a order-preserving, bytes > >>>>>>>>>>>>> (string?)-producing callable as a parameter of course). (As for > >>>>>>>>>>>>> naming, I'd probably call this OrderedBagState or something > >>>>>>>>>>>>> like > >>>>>>>>>>>>> that...rather than Map which tends to imply random access.) > >>>>>>>>>>>>> > >>>>>>>>>>>> >
