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https://issues.apache.org/jira/browse/LUCENE-2362?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12853119#action_12853119
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Michael McCandless commented on LUCENE-2362:
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But that's a big problem -- most scorers can't score "after the fact". They
need to access things they have loaded for the one document being scored.
EG try running a TermQuery and compare the scores you get for docs with
Lucene's normal search vs with your patch.
> Add support for slow filters with batch processing
> --------------------------------------------------
>
> Key: LUCENE-2362
> URL: https://issues.apache.org/jira/browse/LUCENE-2362
> Project: Lucene - Java
> Issue Type: Improvement
> Components: Search
> Affects Versions: 3.0.1
> Reporter: Sergey Vladimirov
> Attachments: BatchFilter.java, IndexSearcherImpl.java
>
>
> Internal implementation of IndexSearch assumes that Filter and scorer has
> almost equal perfomance. But in our environment we have Filter implementation
> that is very expensive (in compare to scorer).
> if we have, let's say, 2k of termdocs selected by scorer (each ~250 docs) and
> 2k selected by filter, then 250k docs will be fastly checked (and filtered
> out) by scorer, and 250k docs will be slowly checked by our filter.
> Using straigthforward implementation makes search out of 60 seconds per query
> boundary, because each next() or advance() requires N queries to database PER
> CHECKED DOC. Using read ahead technique allows us to optimze it to 35 seconds
> per query. Still too slow.
> The solution to problem is firstly select all documents by scorer and filter
> them in batch by our filter. Example of implementation (with BitSet) in
> attachement. Currently it takes only ~300 millseconds per query.
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