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https://issues.apache.org/jira/browse/LUCENE-1195?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12573049#action_12573049
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Yonik Seeley commented on LUCENE-1195:
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{quote}
Here is the simple patch. The cache is only used in TermInfosReader.get(Term).

So if for example a RangeQuery gets a TermEnum from the IndexReader, then
enumerating the terms using the TermEnum will not replace the terms in the
cache.
{quote}

But for each term, TermDocs.seek() will be called, and that will do a 
TermInfosReader.get(Term), replacing items in the cache.
For SegmentReader, seek(TermEnum) actually doesn't call 
TermInfosReader.get(Term), but any kind of multi-reader does.


> Performance improvement for TermInfosReader
> -------------------------------------------
>
>                 Key: LUCENE-1195
>                 URL: https://issues.apache.org/jira/browse/LUCENE-1195
>             Project: Lucene - Java
>          Issue Type: Improvement
>          Components: Index
>            Reporter: Michael Busch
>            Assignee: Michael Busch
>            Priority: Minor
>             Fix For: 2.4
>
>         Attachments: lucene-1195.patch
>
>
> Currently we have a bottleneck for multi-term queries: the dictionary lookup 
> is being done
> twice for each term. The first time in Similarity.idf(), where 
> searcher.docFreq() is called.
> The second time when the posting list is opened (TermDocs or TermPositions).
> The dictionary lookup is not cheap, that's why a significant performance 
> improvement is
> possible here if we avoid the second lookup. An easy way to do this is to add 
> a small LRU 
> cache to TermInfosReader. 
> I ran some performance experiments with an LRU cache size of 20, and an 
> mid-size index of
> 500,000 documents from wikipedia. Here are some test results:
> 50,000 AND queries with 3 terms each:
> old:                  152 secs
> new (with LRU cache): 112 secs (26% faster)
> 50,000 OR queries with 3 terms each:
> old:                  175 secs
> new (with LRU cache): 133 secs (24% faster)
> For bigger indexes this patch will probably have less impact, for smaller 
> once more.
> I will attach a patch soon.

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