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From "Benedict (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (CASSANDRA-9060) Anticompaction hangs on bloom filter bitset serialization
Date Wed, 06 May 2015 10:22:00 GMT

    [ https://issues.apache.org/jira/browse/CASSANDRA-9060?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14530295#comment-14530295
] 

Benedict commented on CASSANDRA-9060:
-------------------------------------

[~grddev] apologies for dropping the ball on this. it's a busy time as we ramp up to 3.0,
and my workflow ignores tickets I'm reviewing that aren't marked 'Patch Available'. I'll see
if we can get this integrated in the near future; it's a shame we missed 2.1.5.

> Anticompaction hangs on bloom filter bitset serialization 
> ----------------------------------------------------------
>
>                 Key: CASSANDRA-9060
>                 URL: https://issues.apache.org/jira/browse/CASSANDRA-9060
>             Project: Cassandra
>          Issue Type: Bug
>            Reporter: Gustav Munkby
>            Assignee: Gustav Munkby
>            Priority: Minor
>             Fix For: 2.1.x
>
>         Attachments: 0001-another-tweak-to-9060.patch, 2.1-9060-simple.patch, trunk-9060.patch
>
>
> I tried running an incremental repair against a 15-node vnode-cluster with roughly 500GB
data running on 2.1.3-SNAPSHOT, without performing the suggested migration steps. I manually
chose a small range for the repair (using --start/end-token). The actual repair part took
almost no time at all, but the anticompactions took a lot of time (not surprisingly).
> Obviously, this might not be the ideal way to run incremental repairs, but I wanted to
look into what made the whole process so slow. The results were rather surprising. The majority
of the time was spent serializing bloom filters.
> The reason seemed to be two-fold. First, the bloom-filters generated were huge (probably
because the original SSTables were large). With a proper migration to incremental repairs,
I'm guessing this would not happen. Secondly, however, the bloom filters were being written
to the output one byte at a time (with quite a few type-conversions on the way) to transform
the little-endian in-memory representation to the big-endian on-disk representation.
> I have implemented a solution where big-endian is used in-memory as well as on-disk,
which obviously makes de-/serialization much, much faster. This introduces some slight overhead
when checking the bloom filter, but I can't see how that would be problematic. An obvious
alternative would be to still perform the serialization/deserialization using a byte array,
but perform the byte-order swap there.



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