Hi, Currently we only support removing a timestamp range. You can remove a single timestamp of course by removing [ts, ts+1), however if there are multiple elements with the same timestamp this will remove all of those elements.
Does this fit your use case? If not, I wonder if MapState is closer to what you are looking for? Reuven On Tue, Sep 15, 2020 at 2:33 PM Tyson Hamilton <tyso...@google.com> wrote: > 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.) > > >>>>>>>>>>>>> > > >>>>>>>>>>>> > > >
