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Ben Manes commented on CASSANDRA-10855:
---------------------------------------
[2.1.0|https://github.com/ben-manes/caffeine/releases/tag/v2.1.0] was released
which includes the above mentioned optimizations. So the cache should seem
artificially better for an artificial workload =)
I haven't had a chance to try to add more workload profiles to the Cassandra
tool. It would be nice if we knew what real-world distributions were like, as
Zipf-like is what researchers published. From the traces I've experimented
with, I am fairly confident in a net positive result.
P.S. An
[article|http://highscalability.com/blog/2016/1/25/design-of-a-modern-cache.html]
on HighScalability describes the overall design.
> Use Caffeine (W-TinyLFU) for on-heap caches
> -------------------------------------------
>
> Key: CASSANDRA-10855
> URL: https://issues.apache.org/jira/browse/CASSANDRA-10855
> Project: Cassandra
> Issue Type: Improvement
> Reporter: Ben Manes
> Labels: performance
>
> Cassandra currently uses
> [ConcurrentLinkedHashMap|https://code.google.com/p/concurrentlinkedhashmap]
> for performance critical caches (key, counter) and Guava's cache for
> non-critical (auth, metrics, security). All of these usages have been
> replaced by [Caffeine|https://github.com/ben-manes/caffeine], written by the
> author of the previously mentioned libraries.
> The primary incentive is to switch from LRU policy to W-TinyLFU, which
> provides [near optimal|https://github.com/ben-manes/caffeine/wiki/Efficiency]
> hit rates. It performs particularly well in database and search traces, is
> scan resistant, and as adds a very small time/space overhead to LRU.
> Secondarily, Guava's caches never obtained similar
> [performance|https://github.com/ben-manes/caffeine/wiki/Benchmarks] to CLHM
> due to some optimizations not being ported over. This change results in
> faster reads and not creating garbage as a side-effect.
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