Forking this thread to discuss action items regarding the change. We can keep technical discussion in the original thread.
Background: our SMB POC showed promising performance & cost saving improvements and we'd like to adopt it for production soon (by EOY). We want to contribute it to Beam so it's better generalized and maintained. We also want to avoid divergence between our internal version and the PR while it's in progress, specifically any breaking change in the produced SMB data. To achieve that I'd like to propose a few action items. 1. Reach a consensus about bucket and shard strategy, key handling, bucket file and metadata format, etc., anything that affect produced SMB data. 2. Revise the existing PR according to #1 3. Reduce duplicate file IO logic by reusing FileIO.Sink, Compression, etc., but keep the existing file level abstraction 4. (Optional) Merge code into extensions::smb but mark clearly as @experimental 5. Incorporate ideas from the discussion, e.g. ShardingFn, GroupByKeyAndSortValues, FileIO generalization, key URN, etc. #1-4 gives us something usable in the short term, while #1 guarantees that production data produced today are usable when #5 lands on master. #4 also gives early adopters a chance to give feedback. Due to the scope of #5, it might take much longer and a couple of big PRs to achieve, which we can keep iterating on. What are your thoughts on this? On Thu, Jul 18, 2019 at 5:32 AM Robert Bradshaw <rober...@google.com> wrote: > On Wed, Jul 17, 2019 at 9:12 PM Gleb Kanterov <g...@spotify.com> wrote: > >> > >> Suppose one assigns a sharding function to a PCollection. Is it lazy, > >> or does it induce a reshuffle right at that point? In either case, > >> once the ShardingFn has been applied, how long does it remain in > >> effect? Does it prohibit the runner (or user) from doing subsequent > >> resharding (including dynamic load balancing)? What happens when one > >> has a DoFn that changes the value? (Including the DoFns in our sinks > >> that assign random keys.) > > > > > > What if we would reason about sharding in the same way as we reason > about timestamps? > > > > Please correct me if I am wrong, as I know, in Beam, timestamps exist > for each element. You can get timestamp by using Reify.timestamps. If there > are timestamped values, and they go through ParDo, timestamps are preserved. > > That is correct. > > > We can think of the same with sharding, where Reify.shards would be > PTransform<PCollection<T>, ShardedValue<T>> and ShardedValue<?> would > contain shard and a grouping key. > > Meaning the shard that the PCollection is currently sharded by, or the > one that it should be sharded by in the future. (Your use case is a > bit strange in that a single key may be spread across multiple shards, > as long as they're part of the same "bucket.") > > > ParDo wouldn't change sharding and would propagate ShardingFn. > > The ShardingFn may not be applicable to downstream (mutated) elements. > > FYI, internally this is handled by having annotations on DoFns as > being key-preserving, and only reasoning about operations separated by > such DoFns. > > > CoGroupByKey on such PTransforms would reify grouping key, and do > regular CoGroupByKey, or be rewritten to a regular ParDo if sharding of > inputs is compatible. > > > > As you mentioned, it requires dynamic work rebalancing to preserve > sharding. What if we do dynamic work rebalancing for each shard > independently, as, I guess, it's done today for fixed windows. > > Currently, the unit of colocation is by key. Generally sharding > introduces a notion of colocation where multiple keys (or mulitple > elements, I suppose it need not be keyed) are promised to be processed > by the same machine. This is both to constraining (wrt dynamic > reshrading) and not needed (with respect to SMB, as your "colocation" > is per bucket, but buckets themselves can be processed in a > distributed manner). > > > When we do a split, we would split one shard into two. It should be > possible to do consistently if values within buckets are sorted, in this > case, we would split ranges of possible values. > > I'm not quite following here. Suppose one processes element a, m, and > z. Then one decides to split the bundle, but there's not a "range" we > can pick for the "other" as this bundle already spans the whole range. > But maybe I'm just off in the weeds here. > > > On Wed, Jul 17, 2019 at 6:37 PM Robert Bradshaw <rober...@google.com> > wrote: > >> > >> On Wed, Jul 17, 2019 at 4:26 PM Gleb Kanterov <g...@spotify.com> wrote: > >> > > >> > I find there is an interesting point in the comments brought by Ahmed > Eleryan. Similar to WindowFn, having a concept of ShardingFn, that enables > users to implement a class for sharding data. Each Beam node can have > ShardingFn set, similar to WindowFn (or WindowingStrategy). Sinks and > sources are aware of that and preserve this information. Using that it's > possible to do optimization on Beam graph, removing redundant CoGroupByKey, > and it would be transparent to users. > >> > > >> > It feels like a nice addition to the Beam model, or possibly we can > implement it using existing windowing mechanics. There are people on the > list with strong experience in the area, I'm wondering what do you think? > >> > >> I've actually thought about this some, though it's been quite a while. > >> At the time it seemed hard to work it into a cohesive part of the > >> model (even ignoring the fact that sharding is primarily an execution, > >> rather than logical, property). > >> > >> Suppose one assigns a sharding function to a PCollection. Is it lazy, > >> or does it induce a reshuffle right at that point? In either case, > >> once the ShardingFn has been applied, how long does it remain in > >> effect? Does it prohibit the runner (or user) from doing subsequent > >> resharding (including dynamic load balancing)? What happens when one > >> has a DoFn that changes the value? (Including the DoFns in our sinks > >> that assign random keys.) > >> > >> Right now one can get most of the semantics of sharding by keying by > >> the shard id and doing a GBK, where the resulting value set (which is > >> allowed to be arbitrarily big) is the (indivisible) shard (e.g. for > >> writing to a single file.) > >> > >> I think sharding (like ordering, the two are quite related) is a > >> property that a PCollection can have, and could be leveraged by the > >> optimizer, but it's difficult to see how it's propagated through > >> transforms. The most sane way to reason about it IMHO is similar to > >> sink triggers, where one specifies that one wants a sharding at some > >> point, and the runner arranges things upstream such that it is so, and > >> some operations can declare that they happen to produce data sharded > >> in some way (though again, PCollection to PCollection one needs a > >> consistent notion of key to have a consistent notion of sharding). > >> > >> > Gleb > >> > > >> > On Tue, Jul 16, 2019 at 11:34 PM Eugene Kirpichov < > kirpic...@google.com> wrote: > >> >> > >> >> I'd like to reiterate the request to not build anything on top of > FileBasedSource/Reader. > >> >> If the design requires having some interface for representing a > function from a filename to a stream of records, better introduce a new > interface for that. > >> >> If it requires interoperability with other IOs that read files, > better change them to use the new interface. > >> >> > >> >> On Tue, Jul 16, 2019 at 9:08 AM Chamikara Jayalath < > chamik...@google.com> wrote: > >> >>> > >> >>> Thanks this clarifies a lot. > >> >>> > >> >>> For writer, I think it's great if you can utilize existing > FileIO.Sink implementations even if you have to reimplement some of the > logic (for example compression, temp file handling) that is already > implemented in Beam FileIO/WriteFiles transforms in your SMB sink transform. > >> >>> > >> >>> For reader, you are right that there's no FileIO.Read. What we have > are various implementations of FileBasedSource/FileBasedReader classes that > are currently intentionally hidden since Beam IO transforms are expected to > be the intended public interface for users. If you can expose and re-use > these classes with slight modifications (keeping backwards compatibility) > I'm OK with it. Otherwise you'll have to write your own reader > implementations. > >> >>> > >> >>> In general, seems like SMB has very strong requirements related to > sharding/hot-key management that are not easily achievable by implementing > SMB source/sink as a composite transform that utilizes existing source/sink > transforms. This forces you to implement this logic in your own DoFns and > existing Beam primitives are not easily re-usable in this context. > >> >>> > >> >>> Thanks, > >> >>> Cham > >> >>> > >> >>> On Tue, Jul 16, 2019 at 8:26 AM Neville Li <neville....@gmail.com> > wrote: > >> >>>> > >> >>>> A little clarification of the IO requirement and my understanding > of the current state of IO. > >> >>>> > >> >>>> tl;dr: not sure if there're reusable bits for the reader. It's > possible to reuse some for the writer but with heavy refactoring. > >> >>>> > >> >>>> Reader > >> >>>> > >> >>>> For each bucket (containing the same key partition, sorted) across > multiple input data sets, we stream records from bucket files and merge > sort. > >> >>>> We open the files in a DoFn, and emit KV<K, CoGbkResult> where the > CGBKR encapsulates Iterable<V> from each input. > >> >>>> Basically we need a simple API like ResourceId -> Iterator<T>, > i.e. sequential read, no block/offset/split requirement. > >> >>>> FileBasedSource.FileBasedReader seems the closest fit but they're > nested & decoupled. > >> >>>> There's no FileIO.Read, only a ReadMatches[1], which can be used > with ReadAllViaFileBasedSource<T>. But that's not the granularity we need, > since we lose ordering of the input records, and can't merge 2+ sources. > >> >>>> > >> >>>> Writer > >> >>>> > >> >>>> We get a `PCollection<BucketShardId, Iterable<T>>` after bucket > and and sort, where Iterable<T> is the records sorted by key and > BucketShardId is used to produce filename, e.g. > bucket-00001-shard-00002.avro. > >> >>>> We write each Iterable<T> to a temp file and move to final > destination when done. Both should ideally reuse existing code. > >> >>>> Looks like FileIO.Sink (and impls in AvroIO, TextIO, TFRecordIO) > supports record writing into a WritableByteChannel, but some logic like > compression is handled in FileIO through ViaFileBasedSink which extends > FileBasedSink. > >> >>>> FileIO uses WriteFiles[3] to shard and write of PCollection<T>. > Again we lose ordering of the output records or custom file naming scheme. > However, WriteShardsIntoTempFilesFn[4] and FinalizeTempFileBundles[5] in > WriteFiles seem closest to our need but would have to be split out and > generalized. > >> >>>> > >> >>>> Note on reader block/offset/split requirement > >> >>>> > >> >>>> Because of the merge sort, we can't split or offset seek a bucket > file. Because without persisting the offset index of a key group somewhere, > we can't efficiently skip to a key group without exhausting the previous > ones. Furthermore we need to merge sort and align keys from multiple > sources, which may not have the same key distribution. It might be possible > to binary search for matching keys but that's extra complication. IMO the > reader work distribution is better solved by better bucket/shard strategy > in upstream writer. > >> >>>> > >> >>>> References > >> >>>> > >> >>>> ReadMatches extends PTransform<PCollection<MatchResult.Metadata>, > PCollection<ReadableFile>> > >> >>>> ReadAllViaFileBasedSource<T> extends > PTransform<PCollection<ReadableFile>, PCollection<T>> > >> >>>> WriteFiles<UserT, DestinationT, OutputT> extends > PTransform<PCollection<UserT>, WriteFilesResult<DestinationT>> > >> >>>> WriteShardsIntoTempFilesFn extends DoFn<KV<ShardedKey<Integer>, > Iterable<UserT>>, FileResult<DestinationT>> > >> >>>> FinalizeTempFileBundles extends PTransform< > PCollection<List<FileResult<DestinationT>>>, WriteFilesResult<DestinationT>> > >> >>>> > >> >>>> > >> >>>> On Tue, Jul 16, 2019 at 5:15 AM Robert Bradshaw < > rober...@google.com> wrote: > >> >>>>> > >> >>>>> On Mon, Jul 15, 2019 at 7:03 PM Eugene Kirpichov < > kirpic...@google.com> wrote: > >> >>>>> > > >> >>>>> > Quick note: I didn't look through the document, but please do > not build on either FileBasedSink or FileBasedReader. They are both > remnants of the old, non-composable IO world; and in fact much of the > composable IO work emerged from frustration with their limitations and > recognizing that many other IOs were suffering from the same limitations. > >> >>>>> > Instead of FileBasedSink, build on FileIO.write; instead of > FileBasedReader, build on FileIO.read. > >> >>>>> > >> >>>>> +1 > >> >>>>> > >> >>>>> I think the sink could be written atop FileIO.write, possibly > using > >> >>>>> dynamic destinations. At the very least the FileSink interface, > which > >> >>>>> handles the details of writing a single shard, would be an ideal > way > >> >>>>> to parameterize an SMB sink. It seems that none of our existing > IOs > >> >>>>> (publically?) expose FileSink implementations. > >> >>>>> > >> >>>>> FileIO.read is not flexible enough to do the merging. Eugene, is > there > >> >>>>> a composable analogue to FileSink, for sources, i.e. something > that > >> >>>>> can turn a file handle (possibly with offsets) into a set of > records > >> >>>>> other than FileBasedReader? > >> >>>>> > >> >>>>> > On Mon, Jul 15, 2019 at 9:01 AM Gleb Kanterov <g...@spotify.com> > wrote: > >> >>>>> >> > >> >>>>> >> I share the same concern with Robert regarding re-implementing > parts of IO. At the same time, in the past, I worked on internal libraries > that try to re-use code from existing IO, and it's hardly possible because > it feels like it wasn't designed for re-use. There are a lot of classes > that are nested (non-static) or non-public. I can understand why they were > made non-public, it's a hard abstraction to design well and keep > compatibility. As Neville mentioned, decoupling readers and writers would > not only benefit for this proposal but for any other use-case that has to > deal with low-level API such as FileSystem API, that is hardly possible > today without copy-pasting, > >> >>>>> >> > >> >>>>> >> > >> >>>>> >> > >> >>>>> >> > >> >>>>> >> > >> >>>>> >> On Mon, Jul 15, 2019 at 5:05 PM Neville Li < > neville....@gmail.com> wrote: > >> >>>>> >>> > >> >>>>> >>> Re: avoiding mirroring IO functionality, what about: > >> >>>>> >>> > >> >>>>> >>> - Decouple the nested FileBasedSink.Writer and > FileBasedSource.FileBasedReader, make them top level and remove references > to parent classes. > >> >>>>> >>> - Simplify the interfaces, while maintaining support for > block/offset read & sequential write. > >> >>>>> >>> - As a bonus, the refactored IO classes can be used > standalone in case when the user wants to perform custom IO in a DoFn, i.e. > a PTransform<PCollection<URI>, PCollection<KV<URI, GenericRecord>>>. Today > this requires a lot of copy-pasted Avro boilerplate. > >> >>>>> >>> - For compatibility, we can delegate to the new classes from > the old ones and remove them in the next breaking release. > >> >>>>> >>> > >> >>>>> >>> Re: WriteFiles logic, I'm not sure about generalizing it, but > what about splitting the part handling writing temp files into a new > PTransform<PCollection<KV<ResourceId, Iterable<UserT>>>, > PCollection<WriteFilesResult<DestinationT>>>? That splits the bucket-shard > logic from actual file IO. > >> >>>>> >>> > >> >>>>> >>> On Mon, Jul 15, 2019 at 10:27 AM Robert Bradshaw < > rober...@google.com> wrote: > >> >>>>> >>>> > >> >>>>> >>>> I agree that generalizing the existing FileIO may not be the > right > >> >>>>> >>>> path forward, and I'd only make their innards public with > great care. > >> >>>>> >>>> (Would this be used like like > >> >>>>> >>>> SmbSink(MyFileIO.sink(parameters).getWriter[Factory]())?) > SMB is a bit > >> >>>>> >>>> unique that the source and sink are much more coupled than > other > >> >>>>> >>>> sources and sinks (which happen to be completely > independent, if > >> >>>>> >>>> complementary implementations, whereas SMB attempts to be a > kind of > >> >>>>> >>>> pipe where one half is instanciated in each pipeline). > >> >>>>> >>>> > >> >>>>> >>>> In short, an SMB source/sink that is parameterized by an > arbitrary, > >> >>>>> >>>> existing IO would be ideal (but possibly not feasible (per > existing > >> >>>>> >>>> prioritizations)), or an SMB source/sink that works as a > pair. What > >> >>>>> >>>> I'd like to avoid is a set of parallel SMB IO classes that > (partially, > >> >>>>> >>>> and incompletely) mirror the existing IO ones (from an API > >> >>>>> >>>> perspective--how much implementation it makes sense to share > is an > >> >>>>> >>>> orthogonal issue that I'm sure can be worked out.) > >> >>>>> >>>> > >> >>>>> >>>> On Mon, Jul 15, 2019 at 4:18 PM Neville Li < > neville....@gmail.com> wrote: > >> >>>>> >>>> > > >> >>>>> >>>> > Hi Robert, > >> >>>>> >>>> > > >> >>>>> >>>> > I agree, it'd be nice to reuse FileIO logic of different > file types. But given the current code structure of FileIO & scope of the > change, I feel it's better left for future refactor PRs. > >> >>>>> >>>> > > >> >>>>> >>>> > Some thoughts: > >> >>>>> >>>> > - SMB file operation is simple single file sequential > reads/writes, which already exists as Writer & FileBasedReader but are > private inner classes, and have references to the parent Sink/Source > instance. > >> >>>>> >>>> > - The readers also have extra offset/split logic but that > can be worked around. > >> >>>>> >>>> > - It'll be nice to not duplicate temp->destination file > logic but again WriteFiles is assuming a single integer shard key, so it'll > take some refactoring to reuse it. > >> >>>>> >>>> > > >> >>>>> >>>> > All of these can be done in backwards compatible way. OTOH > generalizing the existing components too much (esp. WriteFiles, which is > already complex) might lead to two logic paths, one specialized for the SMB > case. It might be easier to decouple some of them for better reuse. But > again I feel it's a separate discussion. > >> >>>>> >>>> > > >> >>>>> >>>> > On Mon, Jul 15, 2019 at 9:45 AM Claire McGinty < > claire.d.mcgi...@gmail.com> wrote: > >> >>>>> >>>> >> > >> >>>>> >>>> >> Thanks Robert! > >> >>>>> >>>> >> > >> >>>>> >>>> >> We'd definitely like to be able to re-use existing I/O > components--for example the Writer<DestinationT, > OutputT>/FileBasedReader<T> (since they operate on a > WritableByteChannel/ReadableByteChannel, which is the level of granularity > we need) but the Writers, at least, seem to be mostly private-access. Do > you foresee them being made public at any point? > >> >>>>> >>>> >> > >> >>>>> >>>> >> - Claire > >> >>>>> >>>> >> > >> >>>>> >>>> >> On Mon, Jul 15, 2019 at 9:31 AM Robert Bradshaw < > rober...@google.com> wrote: > >> >>>>> >>>> >>> > >> >>>>> >>>> >>> I left some comments on the doc. > >> >>>>> >>>> >>> > >> >>>>> >>>> >>> I think the general idea is sound, but one thing that > worries me is > >> >>>>> >>>> >>> the introduction of a parallel set of IOs that mirrors > the (existing) > >> >>>>> >>>> >>> FileIOs. I would suggest either (1) incorporate this > functionality > >> >>>>> >>>> >>> into the generic FileIO infrastructure, or let it be > parameterized by > >> >>>>> >>>> >>> arbitrary IO (which I'm not sure is possible, especially > for the Read > >> >>>>> >>>> >>> side (and better would be the capability of supporting > arbitrary > >> >>>>> >>>> >>> sources, aka an optional "as-sharded-source" operation > that returns a > >> >>>>> >>>> >>> PTransform<..., KV<shard-id, Iterable<KV<K, V>>> where > the iterable is > >> >>>>> >>>> >>> promised to be in key order)) or support a single SMB aka > >> >>>>> >>>> >>> "PreGrouping" source/sink pair that's aways used > together (and whose > >> >>>>> >>>> >>> underlying format is not necessarily public). > >> >>>>> >>>> >>> > >> >>>>> >>>> >>> On Sat, Jul 13, 2019 at 3:19 PM Neville Li < > neville....@gmail.com> wrote: > >> >>>>> >>>> >>> > > >> >>>>> >>>> >>> > 4 people have commented but mostly clarifying details > and not much on the overall design. > >> >>>>> >>>> >>> > > >> >>>>> >>>> >>> > It'd be great to have thumbs up/down on the design, > specifically metadata, bucket & shard strategy, etc., since that affects > backwards compatibility of output files. > >> >>>>> >>>> >>> > Some breaking changes, e.g. dynamic # of shards, are > out of scope for V1 unless someone feels strongly about it. The current > scope should cover all our use cases and leave room for optimization. > >> >>>>> >>>> >>> > > >> >>>>> >>>> >>> > Once green lighted we can start adopting internally, > ironing out rough edges while iterating on the PRs in parallel. > >> >>>>> >>>> >>> > > >> >>>>> >>>> >>> > Most of the implementation is self-contained in the > extensions:smb module, except making a few core classes/methods public for > reuse. So despite the amount of work it's still fairly low risk to the code > base. There're some proposed optimization & refactoring involving core (see > appendix) but IMO they're better left for followup PRs. > >> >>>>> >>>> >>> > > >> >>>>> >>>> >>> > On Fri, Jul 12, 2019 at 11:34 PM Kenneth Knowles < > k...@apache.org> wrote: > >> >>>>> >>>> >>> >> > >> >>>>> >>>> >>> >> I've seen some discussion on the doc. I cannot tell > whether the questions are resolved or what the status of review is. Would > you mind looping this thread with a quick summary? This is such a major > piece of work I don't want it to sit with everyone thinking they are > waiting on someone else, or any such thing. (not saying this is happening, > just pinging to be sure) > >> >>>>> >>>> >>> >> > >> >>>>> >>>> >>> >> Kenn > >> >>>>> >>>> >>> >> > >> >>>>> >>>> >>> >> On Mon, Jul 1, 2019 at 1:09 PM Neville Li < > neville....@gmail.com> wrote: > >> >>>>> >>>> >>> >>> > >> >>>>> >>>> >>> >>> Updated the doc a bit with more future work > (appendix). IMO most of them are non-breaking and better done in separate > PRs later since some involve pretty big refactoring and are outside the > scope of MVP. > >> >>>>> >>>> >>> >>> > >> >>>>> >>>> >>> >>> For now we'd really like to get feedback on some > fundamental design decisions and find a way to move forward. > >> >>>>> >>>> >>> >>> > >> >>>>> >>>> >>> >>> On Thu, Jun 27, 2019 at 4:39 PM Neville Li < > neville....@gmail.com> wrote: > >> >>>>> >>>> >>> >>>> > >> >>>>> >>>> >>> >>>> Thanks. I responded to comments in the doc. More > inline. > >> >>>>> >>>> >>> >>>> > >> >>>>> >>>> >>> >>>> On Thu, Jun 27, 2019 at 2:44 PM Chamikara Jayalath < > chamik...@google.com> wrote: > >> >>>>> >>>> >>> >>>>> > >> >>>>> >>>> >>> >>>>> Thanks added few comments. > >> >>>>> >>>> >>> >>>>> > >> >>>>> >>>> >>> >>>>> If I understood correctly, you basically assign > elements with keys to different buckets which are written to unique files > and merge files for the same key while reading ? > >> >>>>> >>>> >>> >>>>> > >> >>>>> >>>> >>> >>>>> Some of my concerns are. > >> >>>>> >>>> >>> >>>>> > >> >>>>> >>>> >>> >>>>> (1) Seems like you rely on an in-memory sorting > of buckets. Will this end up limiting the size of a PCollection you can > process ? > >> >>>>> >>>> >>> >>>> > >> >>>>> >>>> >>> >>>> The sorter transform we're using supports spilling > and external sort. We can break up large key groups further by sharding, > similar to fan out in some GBK transforms. > >> >>>>> >>>> >>> >>>> > >> >>>>> >>>> >>> >>>>> (2) Seems like you rely on > Reshuffle.viaRandomKey() which is actually implemented using a shuffle > (which you try to replace with this proposal). > >> >>>>> >>>> >>> >>>> > >> >>>>> >>>> >>> >>>> That's for distributing task metadata, so that each > DoFn thread picks up a random bucket and sort merge key-values. It's not > shuffling actual data. > >> >>>>> >>>> >>> >>>> > >> >>>>> >>>> >>> >>>>> > >> >>>>> >>>> >>> >>>>> (3) I think (at least some of the) shuffle > implementations are implemented in ways similar to this (writing to files > and merging). So I'm wondering if the performance benefits you see are for > a very specific case and may limit the functionality in other ways. > >> >>>>> >>>> >>> >>>> > >> >>>>> >>>> >>> >>>> This is for the common pattern of few core data > producer pipelines and many downstream consumer pipelines. It's not > intended to replace shuffle/join within a single pipeline. On the producer > side, by pre-grouping/sorting data and writing to bucket/shard output > files, the consumer can sort/merge matching ones without a CoGBK. > Essentially we're paying the shuffle cost upfront to avoid them repeatedly > in each consumer pipeline that wants to join data. > >> >>>>> >>>> >>> >>>> > >> >>>>> >>>> >>> >>>>> > >> >>>>> >>>> >>> >>>>> Thanks, > >> >>>>> >>>> >>> >>>>> Cham > >> >>>>> >>>> >>> >>>>> > >> >>>>> >>>> >>> >>>>> > >> >>>>> >>>> >>> >>>>> On Thu, Jun 27, 2019 at 8:12 AM Neville Li < > neville....@gmail.com> wrote: > >> >>>>> >>>> >>> >>>>>> > >> >>>>> >>>> >>> >>>>>> Ping again. Any chance someone takes a look to > get this thing going? It's just a design doc and basic metadata/IO impl. > We're not talking about actual source/sink code yet (already done but saved > for future PRs). > >> >>>>> >>>> >>> >>>>>> > >> >>>>> >>>> >>> >>>>>> On Fri, Jun 21, 2019 at 1:38 PM Ahmet Altay < > al...@google.com> wrote: > >> >>>>> >>>> >>> >>>>>>> > >> >>>>> >>>> >>> >>>>>>> Thank you Claire, this looks promising. > Explicitly adding a few folks that might have feedback: +Ismaël Mejía > +Robert Bradshaw +Lukasz Cwik +Chamikara Jayalath > >> >>>>> >>>> >>> >>>>>>> > >> >>>>> >>>> >>> >>>>>>> On Mon, Jun 17, 2019 at 2:12 PM Claire McGinty < > claire.d.mcgi...@gmail.com> wrote: > >> >>>>> >>>> >>> >>>>>>>> > >> >>>>> >>>> >>> >>>>>>>> Hey dev@! > >> >>>>> >>>> >>> >>>>>>>> > >> >>>>> >>>> >>> >>>>>>>> Myself and a few other Spotify data engineers > have put together a design doc for SMB Join support in Beam, and have a > working Java implementation we've started to put up for PR ([0], [1], [2]). > There's more detailed information in the document, but the tl;dr is that > SMB is a strategy to optimize joins for file-based sources by modifying the > initial write operation to write records in sorted buckets based on the > desired join key. This means that subsequent joins of datasets written in > this way are only sequential file reads, no shuffling involved. We've seen > some pretty substantial performance speedups with our implementation and > would love to get it checked in to Beam's Java SDK. > >> >>>>> >>>> >>> >>>>>>>> > >> >>>>> >>>> >>> >>>>>>>> We'd appreciate any suggestions or feedback on > our proposal--the design doc should be public to comment on. > >> >>>>> >>>> >>> >>>>>>>> > >> >>>>> >>>> >>> >>>>>>>> Thanks! > >> >>>>> >>>> >>> >>>>>>>> Claire / Neville > >> >>>>> >> > >> >>>>> >> > >> >>>>> >> > >> >>>>> >> -- > >> >>>>> >> Cheers, > >> >>>>> >> Gleb > >> > > >> > > >> > > >> > -- > >> > Cheers, > >> > Gleb > > > > > > > > -- > > Cheers, > > Gleb >
