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From "Robert Muir (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (LUCENE-4481) AnalyzingSuggester may fail to return correct topN suggestions
Date Fri, 19 Oct 2012 19:58:16 GMT

    [ https://issues.apache.org/jira/browse/LUCENE-4481?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13480327#comment-13480327
] 

Robert Muir commented on LUCENE-4481:
-------------------------------------

Though this is a pretty big hit (i look at prefixes 2-4), lets commit the fix 
for the bug first and then go back around to optimizations. 
                
> AnalyzingSuggester may fail to return correct topN suggestions
> --------------------------------------------------------------
>
>                 Key: LUCENE-4481
>                 URL: https://issues.apache.org/jira/browse/LUCENE-4481
>             Project: Lucene - Core
>          Issue Type: Bug
>            Reporter: Michael McCandless
>            Assignee: Michael McCandless
>             Fix For: 4.1, 5.0
>
>         Attachments: LUCENE-4481.patch, LUCENE-4481.patch, LUCENE-4481.patch
>
>
> I hit this when working on LUCENE-4480.
> Because AnalyzingSuggester may prune some of the topN paths found by FST's Util.TopNSearcher,
this means the queue size limit of topN makes the overall search inadmissible, ie it may incorrectly
prune paths that would have lead to a competitive path.
> However, such pruning is rare: it happens only for graph token streams, and even then
only when competitive analyzed forms share the same surface forms.
> The simplest way to fix this is to make the queue unbounded but this is likely a sizable
performance hit ... I haven't tested yet.  It's even possible the way the dups happen (always
at the "end" of the suggestion, because we tack on 0 byte followed by ord dedup byte) prevent
this bug from even occurring and so this could all be a false alarm!  I have to try to make
a test case showing it ...
> A cop-out solution would be to expose a separate queueSize or queueMultiplier (over the
topN) so that if users are affected by this they could crank up the queue size or multiplier.

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