[jira] [Commented] (LUCENE-4198) Allow codecs to index term impacts

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[jira] [Commented] (LUCENE-4198) Allow codecs to index term impacts

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    [ https://issues.apache.org/jira/browse/LUCENE-4198?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16324250#comment-16324250 ]

Robert Muir commented on LUCENE-4198:

There are a lot of approaches for getting the same benefits with facets, such as returning fast top-N search results immediately, then do exact facet search as a separate query. this can be asynchronous from a user interface perspective so it still reduces latency to the user. There is also the idea of approximate facet counts which i think has been explored a bit with lucene facets module. But we have to start somewhere.

> Allow codecs to index term impacts
> ----------------------------------
>                 Key: LUCENE-4198
>                 URL: https://issues.apache.org/jira/browse/LUCENE-4198
>             Project: Lucene - Core
>          Issue Type: Sub-task
>          Components: core/index
>            Reporter: Robert Muir
>         Attachments: LUCENE-4198.patch, LUCENE-4198.patch, LUCENE-4198.patch, LUCENE-4198.patch, LUCENE-4198_flush.patch
> Subtask of LUCENE-4100.
> Thats an example of something similar to impact indexing (though, his implementation currently stores a max for the entire term, the problem is the same).
> We can imagine other similar algorithms too: I think the codec API should be able to support these.
> Currently it really doesnt: Stefan worked around the problem by providing a tool to 'rewrite' your index, he passes the IndexReader and Similarity to it. But it would be better if we fixed the codec API.
> One problem is that the Postings writer needs to have access to the Similarity. Another problem is that it needs access to the term and collection statistics up front, rather than after the fact.
> This might have some cost (hopefully minimal), so I'm thinking to experiment in a branch with these changes and see if we can make it work well.

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