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https://issues.apache.org/jira/browse/SOLR-5725?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Mikhail Khludnev resolved SOLR-5725.
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    Resolution: Fixed

> Efficient facets without counts for enum method
> -----------------------------------------------
>
>                 Key: SOLR-5725
>                 URL: https://issues.apache.org/jira/browse/SOLR-5725
>             Project: Solr
>          Issue Type: Improvement
>          Components: search
>            Reporter: Alexey Kozhemiakin
>            Assignee: Mikhail Khludnev
>             Fix For: 6.3, master (7.0)
>
>         Attachments: SOLR-5725-5x.patch, SOLR-5725-master.patch, 
> SOLR-5725.patch, SOLR-5725.patch, SOLR-5725.patch, SOLR-5725.patch, 
> SOLR-5725.patch, SOLR-5725.patch, SOLR-5725.patch, 
> facet.limit=0&facet.missing=true discrepancy between cloud and non-distr.txt
>
>
> h1. UPD: Specification
> To cap facet counts by 1 specify {{facet.exists=true}}. It can be used with 
> {{facet.method=enum}} or when it's omitted. It can be used only on non-trie 
> fields i.e. strings. It may speed up facet counting on large indices and/or 
> high-cardinality facet values..  
> h3. Shot version:
> This improves performance for facet.method=enum when it's enough to know that 
> facet count>0, for example when you it's when you dynamically populate 
> filters on search form. New method checks if two bitsets intersect instead of 
> counting intersection size.
> h3.Long version:
> We have a dataset containing hundreds of millions of records, we facet by 
> dozens of fields with many of facet-excludes and have relatively small number 
> of unique values in fields, around thousands.
> Before executing search, users work with "advanced search" form, our  goal is 
> to populate dozens of filters with values which are applicable with other 
> selected values, so basically this is a use case for facets with mincount=1, 
> but without need in actual counts.
> Our performance tests showed that facet.method=enum works much better than 
> fc\fcs, probably due to a specific ratio of "docset"\"unique terms count". 
> For example average execution of query time with method fc=1500ms, fcs=2600ms 
> and with enum=280ms. Profiling indicated the majority time for enum was spent 
> on intersecting docsets.
> Hers's a patch that introduces an extension to facet calculation for 
> method=enum. Basically it uses docSetA.intersects(docSetB) instead of 
> docSetA. intersectionSize (docSetB).
> As a result we were able to reduce our average query time from 280ms to 60ms.



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