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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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Radoslaw Zielinski updated SOLR-5725:
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Attachment: SOLR-5725-master.patch
I've altered the patch to be applicable on the current master branch. I had to
do this by hand because there were to many changes.
I've applied Mikhail suggestions as well. Can you please look at this?
What is done:
* renamed the faceting method to {{enumprobing}}
* switched to conditional code branching inside {{getFacetTermEnumCounts()}}
method
* covered {{else}} branch of \{\{if (df >= minDfFilterCache) \}\}
* throw an exception if combined with {{mincount=2}} or more
* handled per field faceting type setting
* handled distributed environment
* updated/added test to cover more use cases
> 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: Shalin Shekhar Mangar
> Fix For: 6.0
>
> Attachments: SOLR-5725-5x.patch, SOLR-5725-master.patch,
> SOLR-5725.patch
>
>
> 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.
> 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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