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https://issues.apache.org/jira/browse/CASSANDRA-1608?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12921900#action_12921900
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Peter Schuller commented on CASSANDRA-1608:
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Regarding superseding rows in sstables; what would be the criteria for picking
which rows to supersede for? A simple threshold would be easy and certainly
addresses extreme cases of rows being spread. But if one also expects to take
into account of often the rows are read, that would imply recenticity or
frequency tracking?
A simple threshold on sstable count would certainly help avoiding the extreme
cases of reads across many sstables.
But in terms of trying to keep frequently accessed data together with high
locality (as briefly alluded to in CASSANDRA-1625), would that require tracking
some information over time at row level granularity? (I'm concerned about the
overhead of such tracking.)
If so, an observation is that false positives are allowed for the stats. I.e.,
recenticity/frequency could be associated with something like
64-bit-hash-of-key rather than keys, meaning that some optimizations become
possible (e.g. smacking hash-of-key:counter pairs into large byte arrays).
> Redesigned Compaction
> ---------------------
>
> Key: CASSANDRA-1608
> URL: https://issues.apache.org/jira/browse/CASSANDRA-1608
> Project: Cassandra
> Issue Type: Improvement
> Components: Core
> Reporter: Chris Goffinet
> Fix For: 0.7.1
>
>
> 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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