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From "Robert Muir (Assigned) (JIRA)" <j...@apache.org>
Subject [jira] [Assigned] (SOLR-3143) Supply a phrase-oriented QueryConverter for Suggesters
Date Mon, 20 Feb 2012 13:54:36 GMT

     [ https://issues.apache.org/jira/browse/SOLR-3143?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Robert Muir reassigned SOLR-3143:
---------------------------------

    Assignee: Robert Muir
    
> Supply a phrase-oriented QueryConverter for Suggesters
> ------------------------------------------------------
>
>                 Key: SOLR-3143
>                 URL: https://issues.apache.org/jira/browse/SOLR-3143
>             Project: Solr
>          Issue Type: New Feature
>          Components: spellchecker
>            Reporter: Robert Muir
>            Assignee: Robert Muir
>             Fix For: 3.6, 4.0
>
>
> The supplied QueryConverter makes sense for Spellcheckers:
> it tries to parse out the 'meat' of the query (using e.g. identifier rules), 
> and analyzes each parsed 'word' with the configured analyzer (separate tokenstream).
> {code}
> words[] = splitByIdentifierRules();
> for (each word) {
>  tokenstream ts = analyzer.tokenStream(word)
>  for (each analyzedWord from tokenstream) {
>    tokens.add(analyzedWord)
>  }
> }
> {code}
> However, for Suggesters this is not really optimal, because in the general
> case they do not work one word at a time: they aren't really suggesting 
> individual words but instead an entire 'query' that matches a prefix.
> so instead here, I think we just want a QueryConverter that creates a 
> single string containing all the 'meat', and we pass the whole thing to 
> the analyzer, then the suggester.
> The current workaround on the wiki to this problem, is to ask the user to write custom
> code (http://wiki.apache.org/solr/Suggester#Tips_and_tricks), I think thats not 
> great since this phrase-based suggesting is really the primary use case for
> suggesters.

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