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Benjamin Coverston edited comment on CASSANDRA-1608 at 8/9/11 4:36 PM:
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We know the input and output keys, yes.
If we isolate the problem to concurrent compactions in the same level, and
staggered levels {L2, L3}, {L4, L5} it is certainly an easier problem.
was (Author: bcoverston):
We know the input and output keys, yes.
If we isolate the problem to concurrent compactions in the same level, and
staggered levels {L2, L3}, {L4, L5}.
> Redesigned Compaction
> ---------------------
>
> Key: CASSANDRA-1608
> URL: https://issues.apache.org/jira/browse/CASSANDRA-1608
> Project: Cassandra
> Issue Type: Improvement
> Components: Core
> Reporter: Chris Goffinet
> Assignee: Benjamin Coverston
> Attachments: 1608-v11.txt, 1608-v2.txt
>
>
> After seeing the I/O issues in CASSANDRA-1470, I've been doing some more
> thinking on this subject that I wanted to lay out.
> I propose we redo the concept of how compaction works in Cassandra. At the
> moment, compaction is kicked off based on a write access pattern, not read
> access pattern. In most cases, you want the opposite. You want to be able to
> track how well each SSTable is performing in the system. If we were to keep
> statistics in-memory of each SSTable, prioritize them based on most accessed,
> and bloom filter hit/miss ratios, we could intelligently group sstables that
> are being read most often and schedule them for compaction. We could also
> schedule lower priority maintenance on SSTable's not often accessed.
> I also propose we limit the size of each SSTable to a fix sized, that gives
> us the ability to better utilize our bloom filters in a predictable manner.
> At the moment after a certain size, the bloom filters become less reliable.
> This would also allow us to group data most accessed. Currently the size of
> an SSTable can grow to a point where large portions of the data might not
> actually be accessed as often.
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