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Posted to dev@lucene.apache.org by "Ben Manes (JIRA)" <ji...@apache.org> on 2016/02/08 09:25:39 UTC
[jira] [Commented] (SOLR-8241) Evaluate W-TinyLfu cache
[ https://issues.apache.org/jira/browse/SOLR-8241?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15136695#comment-15136695 ]
Ben Manes commented on SOLR-8241:
---------------------------------
Attached a patch that includes a new SolrCache implementation based on Caffeine (version 2.1.0). This was based on the LruCache, trimmed extensively to match the requirements in the SolrCaching wiki page.
This passes the "ant precommit" check, but due to a lack of familiarity with Solr I didn't run the server to test it. Due to the simplicity of the change I think this should be a relatively good prototype to start from. Hopefully there isn't much work required to complete this task and see if the cache is beneficial. Based on my limited understanding of Solr's existing caches, I expect this new one to be both faster and have a higher hit rate.
Shawn, can you please take a look? Thanks!
> 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-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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