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https://issues.apache.org/jira/browse/CASSANDRA-2901?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13078591#comment-13078591
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Jonathan Ellis commented on CASSANDRA-2901:
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Split out some fixes to the SSTII bytes tracker getting out of sync w/ the
underlying stream, and did some cleanup to make the streamed/file versions less
divergent.
Also adds parallel compaction testing to LazilyCompactedRowTest.
CliTest and DefsTest generate compaction loads (in DefsTest's case, on the
Migrations CF -- haven't dug into CliTest as much) that break w/ parallel
enabled, although the test doesn't actually fail (argh).
Haven't figured out what's causing that, and haven't come up with a way to
reproduce in a "real" test yet. The DefsTest does mix lazy/nonlazy iteration
in the merge, which may be relevant.
bq. I'm also no proposing to complicate things.
You're right, poor choice of words on my part.
Latest gives the merge executor a SynchronousQueue. I think that's a better
way to cut worst-case, than the Deserializer, for the reason given previously.
bq. 'if...instanceof' business is a bit error prone/ugly
Agreed. Added getColumnCount + reset to ICountableColumnIterator sub-interface.
bq. say how multithreaded_compaction is different from concurrent_compactors
and that multithread_compaction is likely only useful for SSDs in cassandra.yaml
done
bq. The bytesRead "race" should also be fixed in CompactionIterable
done
bq. I would have put the code in CompactedRow.close() at the end of the
LCR.write() instead of adding a new method, as it avoids forgetting calling
close
I did consider that, but it feels weird to me to have write implicitly call
close. I guess we could just change the method name? :)
bq. We can make PreCompactedRow.removeDeletedAndOldShards a public method and
use it in PCI.MergeTask
done
> Allow taking advantage of multiple cores while compacting a single CF
> ---------------------------------------------------------------------
>
> Key: CASSANDRA-2901
> URL: https://issues.apache.org/jira/browse/CASSANDRA-2901
> Project: Cassandra
> Issue Type: Improvement
> Components: Core
> Reporter: Jonathan Ellis
> Assignee: Jonathan Ellis
> Priority: Minor
> Fix For: 0.8.4
>
> Attachments:
> 0001-fix-tracker-getting-out-of-sync-with-underlying-data-s.txt,
> 0002-parallel-compactions.txt
>
>
> Moved from CASSANDRA-1876:
> There are five stages: read, deserialize, merge, serialize, and write. We
> probably want to continue doing read+deserialize and serialize+write
> together, or you waste a lot copying to/from buffers.
> So, what I would suggest is: one thread per input sstable doing read +
> deserialize (a row at a time). A thread pool (one per core?) merging
> corresponding rows from each input sstable. One thread doing serialize +
> writing the output (this has to wait for the merge threads to complete
> in-order, obviously). This should take us from being CPU bound on SSDs (since
> only one core is compacting) to being I/O bound.
> This will require roughly 2x the memory, to allow the reader threads to work
> ahead of the merge stage. (I.e. for each input sstable you will have up to
> one row in a queue waiting to be merged, and the reader thread working on the
> next.) Seems quite reasonable on that front. You'll also want a small queue
> size for the serialize-merged-rows executor.
> Multithreaded compaction should be either on or off. It doesn't make sense to
> try to do things halfway (by doing the reads with a
> threadpool whose size you can grow/shrink, for instance): we still have
> compaction threads tuned to low priority, by default, so the impact on the
> rest of the system won't be very different. Nor do we expect to have so many
> input sstables that we lose a lot in context switching between reader threads.
> IMO it's acceptable to punt completely on rows that are larger than memory,
> and fall back to the old non-parallel code there. I don't see any sane way to
> parallelize large-row compactions.
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