[jira] [Work logged] (BEAM-6766) Sort Merge Bucket Join support in Beam

["ASF GitHub Bot (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/BEAM-6766?focusedWorklogId=337372&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-337372 ]

ASF GitHub Bot logged work on BEAM-6766:
----------------------------------------

                Author: ASF GitHub Bot
            Created on: 01/Nov/19 15:01
            Start Date: 01/Nov/19 15:01
    Worklog Time Spent: 10m 
      Work Description: stale[bot] commented on pull request #8823: [BEAM-6766] Metadata file implementation for Sort Merge Bucket source/sink
URL: https://github.com/apache/beam/pull/8823
 
 
   
 
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Issue Time Tracking
-------------------

    Worklog Id:     (was: 337372)
    Time Spent: 7.5h  (was: 7h 20m)

> Sort Merge Bucket Join support in Beam
> --------------------------------------
>
>                 Key: BEAM-6766
>                 URL: https://issues.apache.org/jira/browse/BEAM-6766
>             Project: Beam
>          Issue Type: Improvement
>          Components: extensions-java-join-library, io-ideas
>            Reporter: Claire McGinty
>            Assignee: Claire McGinty
>            Priority: Major
>          Time Spent: 7.5h
>  Remaining Estimate: 0h
>
> Design doc: https://docs.google.com/document/d/1AQlonN8t4YJrARcWzepyP7mWHTxHAd6WIECwk1s3LQQ/edit#
> Hi! Spotify has been internally prototyping and testing an implementation of the sort merge join using Beam primitives and we're interested in contributing it open-source – probably to Beam's extensions package in its own `smb` module or as part of the joins module?
> We've tested this with Avro files using Avro's GenericDatumWriter/Reader directly (although this could theoretically be expanded to other serialization formats). We'd add two transforms*, an SMB write and an SMB join. 
> SMB write would take in one PCollection and a # of buckets and:
> 1) Apply a partitioning function to the input to assign each record to one bucket. (the user code would have to statically specify a # of buckets... hard to see a way to do this dynamically.)
> 2) Group by that bucket ID and within each bucket perform an in-memory sort on join key. If the grouped records are too large to fit in memory, fall back to an external sort (although if this happens, user should probably increase bucket size so every group fits in memory).
> 3) Directly write the contents of bucket to a sequentially named file.
> 4) Write a metadata file to the same output path with info about hash algorithm/# buckets.
> SMB join would take in the input paths for 2 or more Sources, all of which are written in a bucketed and partitioned way, and :
> 1) Verify that the metadata files have compatible bucket # and hash algorithm.
> 2) Expand the input paths to enumerate the `ResourceIds` of every file in the paths. Group all inputs with the same bucket ID.
> 3) Within each group, open a file reader on all `ResourceIds`. Sequentially read files one record at a time, outputting tuples of all record pairs with matching join key.
>  \* These could be implemented either directly as `PTransforms` with the writer being a `DoFn` but I semantically do like the idea of extending `FileBasedSource`/`Sink` with abstract classes like `SortedBucketSink`/`SortedBucketSource`... if we represent the elements in a sink as KV pairs of <Bucket #, <Sorted Iterable of Records>>>, so that the # of elements in the PCollection == # of buckets == # of output files, we could just implement something like `SortedBucketSink` extending `FileBasedSink` with a dynamic file naming function. I'd like to be able to take advantage of the existing write/read implementation logic in the `io` package as much as possible although I guess some of those are package private. 
> –
> From our internal testing, we've seen some substantial performance improvements using the right bucket size--not only by avoiding a shuffle during the join step, but also in storage costs, since we're getting better compression in Avro by storing sorted records.
> Please let us know what you think/any concerns we can address! Our implementation isn't quite production-ready yet, but we'd like to start a discussion about it early.



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