On Tuesday 19 February 2008 21:08:59 [EMAIL PROTECTED] wrote:
1. IndexSearcher with a MultiReader will search the indexes
sequentially?
Not exactly. It will fuse the indexes together such that things like TermEnum
will merge the ones from the real indexes, and will search using those
I have some questions about searching multiple indexes.
1. IndexSearcher with a MultiReader will search the indexes
sequentially?
I think need to use either MultiSearcher or ParallelMultiSearcher
2. ParallelMultiSearcher searches in parallel. How is this
done? One thread
per
No ideas? :(
-Original Message-
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED]
Sent: Samstag, 16. Februar 2008 15:42
To: java-user@lucene.apache.org
Subject: Searching multiple indexes
Hi,
I have some questions about searching multiple indexes.
1. IndexSearcher
Hi,
I have some questions about searching multiple indexes.
1. IndexSearcher with a MultiReader will search the indexes sequentially?
2. ParallelMultiSearcher searches in parallel. How is this done? One thread
per index? When will it return? When the slowest search is fineshed?
3. When I have
Hi,
use MultiFieldQueryParser instead of the Queryparser that you are using.
Like this,
String fields[]={field1,
field2,}
MultiFieldQueryParser parser = new
MultiFieldQueryParser(fields,
new
I have Tokenized multiple items into one index directory as
illustrated below.
I can successfully search on any one indexed field ( as illustrated
below )
...the question is how would I search on all my indexed fields at one
...any ideas ? I have heard of MultiSearch but I am not sure if that
Hi,
there are two ways. The first is to use MultiFieldQueryParser
http://lucene.apache.org/java/docs/api/org/apache/lucene/queryParser/MultiFieldQueryParser.html
or do an extra step in indexing to build a new field as join of those
(e.g. StringBuffer append f1 append f2 ...)
Benefits of
Hi all,
my index size has grown too much and I keep getting outOfMemoryError after
running few searches. I am using all the RAM that the JVM is allowing me 2.6GB.
I am left with two solutions now, the easy and expensive solution is to upgrade
the hardware to a 64-bit System and use more RAM.
