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From Erick Erickson <erickerick...@gmail.com>
Subject Re: [jira] [Updated] (LUCENE-1812) Static index pruning by in-document term frequency (Carmel pruning)
Date Mon, 29 Aug 2011 11:36:16 GMT
You download the regular source code, then apply the
patch, compile and test. Here's a guide for patches:

http://wiki.apache.org/solr/HowToContribute#Working_With_Patches


and the rest of the page will help you too!

Best
Erick

On Mon, Aug 29, 2011 at 4:29 AM, luo (JIRA) <jira@apache.org> wrote:
>
>     [ https://issues.apache.org/jira/browse/LUCENE-1812?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
>
> luo updated LUCENE-1812:
> ------------------------
>
>    Comment: was deleted
>
> (was: where can i download the codes of version 1812?)
>
>> Static index pruning by in-document term frequency (Carmel pruning)
>> -------------------------------------------------------------------
>>
>>                 Key: LUCENE-1812
>>                 URL: https://issues.apache.org/jira/browse/LUCENE-1812
>>             Project: Lucene - Java
>>          Issue Type: New Feature
>>          Components: modules/other
>>            Reporter: Andrzej Bialecki
>>            Assignee: Doron Cohen
>>             Fix For: 3.4, 4.0
>>
>>         Attachments: pruning.patch, pruning.patch, pruning.patch, pruning.patch
>>
>>
>> This module provides tools to produce a subset of input indexes by removing postings
data for those terms where their in-document frequency is below a specified threshold. The
net effect of this processing is a much smaller index that for common types of queries returns
nearly identical top-N results as compared with the original index, but with increased performance.
>> Optionally, stored values and term vectors can also be removed. This functionality
is largely independent, so it can be used without term pruning (when term freq. threshold
is set to 1).
>> As the threshold value increases, the total size of the index decreases, search performance
increases, and recall decreases (i.e. search quality deteriorates). NOTE: especially phrase
recall deteriorates significantly at higher threshold values.
>> Primary purpose of this class is to produce small first-tier indexes that fit completely
in RAM, and store these indexes using IndexWriter.addIndexes(IndexReader[]). Usually the performance
of this class will not be sufficient to use the resulting index view for on-the-fly pruning
and searching.
>> NOTE: If the input index is optimized (i.e. doesn't contain deletions) then the index
produced via IndexWriter.addIndexes(IndexReader[]) will preserve internal document id-s so
that they are in sync with the original index. This means that all other auxiliary information
not necessary for first-tier processing, such as some stored fields, can also be removed,
to be quickly retrieved on-demand from the original index using the same internal document
id.
>> Threshold values can be specified globally (for terms in all fields) using defaultThreshold
parameter, and can be overriden using per-field or per-term values supplied in a thresholds
map. Keys in this map are either field names, or terms in field:text format. The precedence
of these values is the following: first a per-term threshold is used if present, then per-field
threshold if present, and finally the default threshold.
>> A command-line tool (PruningTool) is provided for convenience. At this moment it
doesn't support all functionality available through API.
>
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