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https://issues.apache.org/jira/browse/CASSANDRA-1608?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13071857#comment-13071857
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Ryan King commented on CASSANDRA-1608:
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bq. bq. Is it even worth keeping bloom filters around with such a drastic
reduction in worst-case number of sstables to check (for read path too)?
bq. I think they are absolutely worth keeping around for unleveled sstables,
but for leveled sstables the value is certainly questionable. Perhaps having
some kind of LRU cache where we have an upper bound on the number of bloom
filters we keep in memory would be wise. Is it possible that we could move
these off-heap?
I admit that I probably don't fully understand this change, but we have at
least one workload where keeping BFs would probably be necessary– the vast
majority of the traffic on that workload is for keys that don't exist anywhere.
Even small bumps in BF false positive rates greatly effect the read performance.
> 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-v2.txt, 1608-v8.txt, 1609-v10.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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