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https://issues.apache.org/jira/browse/LUCENE-4227?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13419129#comment-13419129
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Michael McCandless commented on LUCENE-4227:
--------------------------------------------

bq. I do think maybe this class needs some more warnings, to me it seems it 
will use crazy amounts of RAM.

I'll add some scary warnings :)

bq. I also am not sure I like the name "Direct"... is it crazy to suggest 
"Instantiated"?

It is very much like the old instantiated (though I think its terms dict is 
faster than instantiated's)... but I didn't really like the name 
"Instanstiated"... I had picked Direct because it "directly" represents the 
postings ... but maybe we can find a better name.

I will update MIGRATE.txt to explain how "Direct" (or whatever we name it) is 
the closest match if you were previously using Instantiated...


                
> DirectPostingsFormat, storing postings as simple int[] in memory, if you have 
> tons of RAM
> -----------------------------------------------------------------------------------------
>
>                 Key: LUCENE-4227
>                 URL: https://issues.apache.org/jira/browse/LUCENE-4227
>             Project: Lucene - Java
>          Issue Type: Improvement
>            Reporter: Michael McCandless
>            Assignee: Michael McCandless
>         Attachments: LUCENE-4227.patch, LUCENE-4227.patch
>
>
> This postings format just wraps Lucene40 (on disk) but then at search
> time it loads (up front) all terms postings into RAM.
> You'd use this if you have insane amounts of RAM and want the fastest
> possible search performance.  The postings are not compressed: docIds,
> positions are stored as straight int[]s.
> The terms are stored as a skip list (array of byte[]), but I packed
> all terms together into a single long byte[]: I had started as actual
> separate byte[] per term but the added pointer deref and loss of
> locality was a lot (~2X) slower for terms-dict intensive queries like
> FuzzyQuery.
> Low frequency postings (docFreq <= 32 by default) store all docs, pos
> and offsets into a single int[].  High frequency postings store docs
> as int[], freqs as int[], and positions as int[][] parallel arrays.
> For skipping I just do a growing binary search.
> I also made specialized DirectTermScorer and DirectExactPhraseScorer
> for the high freq case that just pull the int[] and iterate
> themselves.
> All tests pass.

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