You can call IndexReader.setTermInfosIndexDivisor(int) to reduce how many index terms are loaded in memory. EG setting it to 10 will load 1/10th what's loaded now, but will slow down searches.

Also, you should understand why your index has so many terms. EG, use Luke to peek at the terms and see if they are "valid". If for example you are accidentally indexing binary content as if it were text that can easily cause a great many, large, unwanted terms.

Mike

<[EMAIL PROTECTED]> wrote:

I'm running Lucene 2.3.1 with Java 1.5.0_14 on 64 bit linux. We have fairly large collections (~1gig collection files, ~1,000,000 documents). When I try to load test our application with 50 users, all doing simple searches via a web interface, we quickly get an OutOfMemory exception. When I do a jmap dump of the heap, this is what I see:

Size    Count   Class description
-------------------------------------------------------
195818576       4263822 char[]
190889608       13259   byte[]
172316640       4307916 java.lang.String
164813120       4120328 org.apache.lucene.index.TermInfo
131823104       4119472 org.apache.lucene.index.Term
37729184        604     org.apache.lucene.index.TermInfo[]
37729184        604     org.apache.lucene.index.Term[]

So 4 of the top 7 memory consumers are Term related. We have 2 gig of RAM available on the system but we get OOM errors no matter the java heap settings. Has anyone seen this issue and know how to solve it?

We do use separate MultiSearcher instances for each search. (We actually have 2 collections that we search via a MultiSearcher.) We tried using a singleton searcher instance but our collections are constantly being updated and the singleton searcher only gives you results since the searcher was opened. Creating new searcher objects at search time gives you up to the minute search results.

I've seen some postings referring to an Index Divisor setting which could reduce the Terms in memory, but I have not seen how to set this value for Lucene.

Any help would be greatly appreciated.

Rich


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