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From "Michael McCandless (JIRA)" <>
Subject [jira] Commented: (LUCENE-2362) Add support for slow filters with batch processing
Date Sat, 03 Apr 2010 09:47:27 GMT


Michael McCandless commented on LUCENE-2362:

I think in general Lucene should do a better job managing whether the filter is cheap or expensive,
random access or not (LUCENE-1536), and tune the matching/scoring appropriately.

But one issue with this patch: how is scoring done?  It looks like in first pass you gather
bit set, then you filter it w/ batch filter, then you iterate again in 2nd pass to collect
the docs.  But that 2nd pass won't in general have enough info to do scoring?

> Add support for slow filters with batch processing
> --------------------------------------------------
>                 Key: LUCENE-2362
>                 URL:
>             Project: Lucene - Java
>          Issue Type: Improvement
>          Components: Search
>    Affects Versions: 3.0.1
>            Reporter: Sergey Vladimirov
>         Attachments:,
> 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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