Facet searches cache a filter per unique term for multivalued fields.
There are many ways to reduce memory consumption in these scenarios,
but it usually requires a case-by-case solution.
-Mike
On 21-May-08, at 12:08 PM, Lance Norskog wrote:
We have had major OOM problems doing facet searches. Having 20
searches at
once used up maybe 5G and one faceting request would blow up at 12.
More
important, when a facet request throws an OOM it seems like the
memory is
not released. When a normal search throws an OOM, the memory is
released and
Solr continues to run. We had to get more ram in order to do facet
queries.
This is with Solr 1.3.
-----Original Message-----
From: Mike Klaas [mailto:[EMAIL PROTECTED]
Sent: Wednesday, May 21, 2008 11:23 AM
To: solr-user@lucene.apache.org
Subject: Re: SOLR OOM (out of memory) problem
On 21-May-08, at 4:46 AM, gurudev wrote:
Just to add more:
The JVM heap allocated is 6GB with initial heap size as 2GB. We use
quadro(which is 8 cpus) on linux servers for SOLR slaves.
We use facet searches, sorting.
document cache is set to 7 million (which is total documents in
index)
filtercache 10000
You definitely don't have enough memory to keep 7 million document,
fully
realized in java-object form, in memory.
Nor would you want to. The document cache should aim to keep the most
frequently-occuring documents in memory (in the thousands, perhaps
10's of
thousands). By devoting more memory to the OS disk cache, more of
the 12GB
index can be cached by the OS and thus speed up all document
retreival.
-Mike
