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Sylvain Lebresne commented on CASSANDRA-2901:
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bq. Well, I changed the semantics of maxInMemorySize.
Oups, missed that, sorry. Nevermind then.
Patch lgtm, +1. I would deactivate the use of parallel compaction for the test
by default before committing though, as it is not what we care the more for.
About Stu remarks, the goal is to speed up a given compaction. It is clearly
for people having SSDs, so the goal is imho more about having compactions done
as quickly as possible (to have the more consistent possible reads in
particular) rather than the catching up of compactions being behind (which
CASSANDRA-2191 solves indeed). Even without triggering major compaction, you
can have a minor compaction that takes time. If you have the I/O capacity and
the idle cpu, why not having those get done more quickly ?
As you mentioned, it is also useful for things like repair for which, let's be
honest, the "other efforts underway to make the tasks less like a major
compaction" are only idea at this point (not that they are bad idea or
anything, let's not just consider them as done).
For CASSANDRA-1608, I admit it is less clear how useful exactly that will be
with leveled compaction. However, it is not clear that will be useless either
and again, leveled compaction is not the default compaction yet.
Anyway, I have to admit that it is not the ticket I care the more for, and it
will likely not be useful for everyone. However it's done, the complexity is
really all in ParallelCompactionIterable (the rest of this patch being mostly
trivial refactorings), and that last one is completely optional, so I don't see
a good reason not to add this.
> 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-compaction.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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