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From "Sylvain Lebresne (JIRA)" <j...@apache.org>
Subject [jira] [Created] (CASSANDRA-2841) Always use even distribution for merkle tree with RandomPartitionner
Date Wed, 29 Jun 2011 19:04:28 GMT
Always use even distribution for merkle tree with RandomPartitionner
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                 Key: CASSANDRA-2841
                 URL: https://issues.apache.org/jira/browse/CASSANDRA-2841
             Project: Cassandra
          Issue Type: Improvement
          Components: Core
    Affects Versions: 0.7.0
            Reporter: Sylvain Lebresne
            Assignee: Sylvain Lebresne
            Priority: Trivial
             Fix For: 0.7.7, 0.8.2
         Attachments: 2841.patch

When creating the initial merkle tree, repair tries to be (too) smart and use the key samples
to "guide" the tree splitting. While this is a good idea for OPP where there is a good change
the data distribution is uneven, you can't beat an even distribution for the RandomPartitionner.
And a quick experiment even shows that the method used is significantly less efficient than
an even distribution for the ranges of the merkle tree (that is, an even distribution gives
a much better of distribution of the number of keys by range of the tree).

Thus let's switch to an even distribution for RandomPartitionner. That 3 lines change alone
amounts for a significant improvement of repair's precision.

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