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https://issues.apache.org/jira/browse/LUCENE-2588?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12895438#action_12895438
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Yonik Seeley commented on LUCENE-2588:
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Ah sweet, nice idea!

> 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
>
>
> 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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