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From "Simon Willnauer (JIRA)" <j...@apache.org>
Subject [jira] Updated: (LUCENE-2588) terms index should not store useless suffixes
Date Sun, 19 Sep 2010 12:48:36 GMT

     [ https://issues.apache.org/jira/browse/LUCENE-2588?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Simon Willnauer updated LUCENE-2588:
------------------------------------

    Attachment: LUCENE-2588.patch

attached nit-picky iteration. Both failures from LUCENE-2622 pass now - I will commit soon
if nobody objects

> terms index should not store useless suffixes
> ---------------------------------------------
>
>                 Key: LUCENE-2588
>                 URL: https://issues.apache.org/jira/browse/LUCENE-2588
>             Project: Lucene - Java
>          Issue Type: Improvement
>          Components: Index
>            Reporter: Michael McCandless
>            Assignee: Michael McCandless
>             Fix For: 4.0
>
>         Attachments: LUCENE-2588.patch, LUCENE-2588.patch, LUCENE-2588.patch, LUCENE-2588.patch
>
>
> This idea came up when discussing w/ Robert how to improve our terms index...
> The terms dict index today simply grabs whatever term was at a 0 mod 128 index (by default).
> But this is wasteful because you often don't need the suffix of the term at that point.
> EG if the 127th term is aa and the 128th (indexed) term is abcd123456789, instead of
storing that full term you only need to store ab.  The suffix is useless, and uses up RAM
since we load the terms index into RAM.
> The patch is very simple.  The optimization is particularly easy because terms are now
byte[] and we sort in binary order.
> I tested on first 10M 1KB Wikipedia docs, and this reduces the terms index (tii) file
from 3.9 MB -> 3.3 MB = 16% smaller (using StandardAnalyzer, indexing body field tokenized
but title / date fields untokenized).  I expect on noisier terms dicts, especially ones w/
bad terms accidentally indexed, that the savings will be even more.
> In the future we could do crazier things.  EG there's no real reason why the indexed
terms must be regular (every N terms), so, we could instead pick terms more carefully, say
"approximately" every N, but favor terms that have a smaller net prefix.  We can also index
more sparsely in regions where the net docFreq is lowish, since we can afford somewhat higher
seek+scan time to these terms since enuming their docs will be much faster.

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