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https://issues.apache.org/jira/browse/CASSANDRA-1608?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12980654#action_12980654
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David Boxenhorn commented on CASSANDRA-1608:
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> Partitioning by token ranges is functionally equivalent to virtual nodes, no? 
> Which in the OPP case means you now have to deal with intra-node load 
> balancing. 

I don't see any reason why OPP has to be used within a node just because it is 
used between nodes. I think RP should always be used within a node, and the 
number of partitions should be chosen to keep SST size optimal. 

> 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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