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From "Toby Cole (JIRA)" <j...@apache.org>
Subject [jira] Commented: (SOLR-711) SimpleFacets: Performance Boost for Tokenized Fields for smaller DocSet using Term Vectors
Date Wed, 20 Aug 2008 10:20:47 GMT

    [ https://issues.apache.org/jira/browse/SOLR-711?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12623950#action_12623950
] 

Toby Cole commented on SOLR-711:
--------------------------------

We've seen this problem with our dataset, we have around 10m small records and were trying
to facet on several multi-valued strings. Two of which had over 40k unique values (around
10 values per record).
If we can come up with a plan I don't mind volunteering to implement it.

> SimpleFacets: Performance Boost for Tokenized Fields for smaller DocSet using Term Vectors
> ------------------------------------------------------------------------------------------
>
>                 Key: SOLR-711
>                 URL: https://issues.apache.org/jira/browse/SOLR-711
>             Project: Solr
>          Issue Type: Improvement
>          Components: search
>    Affects Versions: 1.3
>            Reporter: Fuad Efendi
>             Fix For: 1.4
>
>   Original Estimate: 1680h
>  Remaining Estimate: 1680h
>
> From [http://www.nabble.com/SimpleFacets%3A-Performance-Boost-for-Tokenized-Fields-td19033760.html]:
> Scenario:
> - 10,000,000 documents in the index; 
> - 5-10 terms per document; 
> - 200,000 unique terms for a tokenized field. 
> _Obviously calculating sizes of 200,000 intersections with FilterCache is 100 times slower
than traversing 10 - 20,000 documents for smaller DocSets and counting frequencies of Terms._
> Not applicable if size of DocSet is close to total number of unique tokens (200,000 in
our scenario).
> See   SimpleFacets.java:
> {code}
> public NamedList getFacetTermEnumCounts(
>   SolrIndexSearcher searcher, 
>   DocSet docs, ...
> {code}

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