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From "Benedict (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (CASSANDRA-9060) Anticompaction hangs on bloom filter bitset serialization
Date Sun, 29 Mar 2015 15:07:52 GMT

    [ https://issues.apache.org/jira/browse/CASSANDRA-9060?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14385804#comment-14385804
] 

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

bq. I think the immediate problem is that they are created to allow room for all keys in all
anticompacted tables, whereas anticompactions process one table at a time

Thanks. You're right., and this is definitely something to fix in 2.1

In this instance we don't use HLL cardinality estimators, but the index summary, which isn't
probabilistic. What it is, however, is only accurate to a certain granularity. As a first
patch your approach reduces the problem to the one I initially assumed it was, i.e. a doubling
of required space (instead of \*N), but with a small amount of TLC the estimatedKeysForRanges()
method could be modified to give a lower bound for the size of both resultant tables (at the
moment it can significantly over estimate in some scenarios, but also cannot easily estimate
the cardinality of the negation of the range - so we would have to subtract the overestimation,
giving an underestimate which is much worse).

Your patch looks to me to significantly improve the status quo, so I will commit it now, and
we can address a slightly improved patch for perhaps 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: Marcus Eriksson
>            Priority: Minor
>             Fix For: 3.0
>
>         Attachments: 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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