Yura Smolsky wrote:
Hello, mark.
mh> 2) My app uses long queries, some of which include
mh> very common terms. Using the "MoreLikeThis" query to
mh> drop common terms drastically improved performance. If
mh> your "killer queries" are long ones you could spot
mh> them and service them with a MoreLik
Hello, mark.
mh> 2) My app uses long queries, some of which include
mh> very common terms. Using the "MoreLikeThis" query to
mh> drop common terms drastically improved performance. If
mh> your "killer queries" are long ones you could spot
mh> them and service them with a MoreLikeThis or simply
mh>
In addition to the comments already made, I recently
recently found these changes to be useful:
1) Swapping out Sun 1.4.2_05 JVM for BEA's JRockit JVM
halved my query times. (In both cases did not tweak
any default JVM settings other than -Xmx to ensure
adequate memory allocation).
2) My app use
Daniel,
On Thursday 07 April 2005 00:54, Chris Hostetter wrote:
>
> : Queries: The query strings are of highly differing complexity, from
> : simple x:y to long queries involving conjunctions, disjunctions and
> : wildecard queries.
> :
> : 90% of the queries run brilliantly. Problem is that 10%
Daniel Herlitz wrote:
Hi everybody,
We have been using Lucene for about one year now with great success.
Recently though the index has growed noticably and so has the number of
searches. I was wondering if anyone would like to comment on these
figures and say if it works for them?
Index size: ~
: Queries: The query strings are of highly differing complexity, from
: simple x:y to long queries involving conjunctions, disjunctions and
: wildecard queries.
:
: 90% of the queries run brilliantly. Problem is that 10% of the queries
: (simple or not) take a long time, on average more that 10 se
Hi everybody,
We have been using Lucene for about one year now with great success.
Recently though the index has growed noticably and so has the number of
searches. I was wondering if anyone would like to comment on these
figures and say if it works for them?
Index size: ~2.5 GB, on disk
Number