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https://issues.apache.org/jira/browse/LUCENE-1812?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13192101#comment-13192101
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Doron Cohen commented on LUCENE-1812:
-------------------------------------
I ran 'javadocs' under 3x/lucene/contrib/pruning and 'javadocs-all' under
3x/lucene.
The latter failed due to multiple package.html under o.a.l.index - in core and
under contrib/pruning.
Entirely renaming the package to o.a.l.pruning.index won't work because
PruningReader accesses package protected SegmentTermVector.
I can move the other classes to that new package and keep only PruningReader in
that "index friend" package. (Unless there are javadoc/ant tricks that will
avoid this error and still generate valid javadocs in both cases).
> 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: 3.6, 4.0
>
> Attachments: pruning.patch, 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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