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From "Wei Deng (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (CASSANDRA-12464) Investigate the potential improvement of parallelism on higher level compactions in LCS
Date Tue, 16 Aug 2016 03:06:22 GMT

     [ https://issues.apache.org/jira/browse/CASSANDRA-12464?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Wei Deng updated CASSANDRA-12464:
---------------------------------
    Labels: lcs performance  (was: )

> Investigate the potential improvement of parallelism on higher level compactions in LCS
> ---------------------------------------------------------------------------------------
>
>                 Key: CASSANDRA-12464
>                 URL: https://issues.apache.org/jira/browse/CASSANDRA-12464
>             Project: Cassandra
>          Issue Type: Improvement
>          Components: Compaction
>            Reporter: Wei Deng
>              Labels: lcs, performance
>
> According to LevelDB's design doc [here|https://github.com/google/leveldb/blob/master/doc/impl.html#L115-L116],
"A compaction merges the contents of the picked files to produce a
> sequence of level-(L+1) files", it will "switch to producing a new
> level-(L+1) file after the current output file has reached the target
> file size" (in our case 160MB), it will also "switch to a new output file when the key
range of the current output file has grown enough to overlap more than ten level-(L+2) files".
This is to ensure "that a later compaction
> of a level-(L+1) file will not pick up too much data from level-(L+2)."
> Our current code in LeveledCompactionStrategy doesn't implement this last rule, but we
might be able to quickly implement it and see how much a compaction throughput improvement
it can deliver. Potentially we can create a scenario where a number of large L0 SSTables are
present (e.g. 200GB after switching from STCS) and let it to create thousands of L1 SSTables
overflow, and see how fast LCS can digest this much data from L1 and properly upper-level
them to completion.



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