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From "Shawn Heisey (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SOLR-8241) Evaluate W-TinyLfu cache
Date Thu, 05 Jan 2017 17:47:58 GMT

    [ https://issues.apache.org/jira/browse/SOLR-8241?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15802010#comment-15802010
] 

Shawn Heisey commented on SOLR-8241:
------------------------------------

This issue was filed by the author of Caffeine (Ben Manes) and does include upgrading the
caffeine dependency already present.  I haven't checked yet, but presumably all the Solr tests
still pass with the upgrade.

> Evaluate W-TinyLfu cache
> ------------------------
>
>                 Key: SOLR-8241
>                 URL: https://issues.apache.org/jira/browse/SOLR-8241
>             Project: Solr
>          Issue Type: Wish
>          Components: search
>            Reporter: Ben Manes
>            Priority: Minor
>         Attachments: SOLR-8241.patch, SOLR-8241.patch, SOLR-8241.patch, proposal.patch
>
>
> SOLR-2906 introduced an LFU cache and in-progress SOLR-3393 makes it O(1). The discussions
seem to indicate that the higher hit rate (vs LRU) is offset by the slower performance of
the implementation. An original goal appeared to be to introduce ARC, a patented algorithm
that uses ghost entries to retain history information.
> My analysis of Window TinyLfu indicates that it may be a better option. It uses a frequency
sketch to compactly estimate an entry's popularity. It uses LRU to capture recency and operate
in O(1) time. When using available academic traces the policy provides a near optimal hit
rate regardless of the workload.
> I'm getting ready to release the policy in Caffeine, which Solr already has a dependency
on. But, the code is fairly straightforward and a port into Solr's caches instead is a pragmatic
alternative. More interesting is what the impact would be in Solr's workloads and feedback
on the policy's design.
> https://github.com/ben-manes/caffeine/wiki/Efficiency



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