Thanks for the suggestion, Dennis. I decided to implement this as you
described on my collection of about 400,000 documents, but I did not
receive the results I expected.
Prior to putting the indexes on a tmpfs, I did a bit of benchmarking and
found that it usually takes a little under two seconds for each facet
query. After moving my indexes from disk to a tmpfs file system, I seem
to get about the same result from facet queries: about two seconds.
Does anyone have any insight into this? Doesn't it seem odd that my
response times are about the same? Thanks for the help.
Matt Phillips
Dennis Kubes wrote:
One way to do this if you are running on linux is to create a tempfs
(which is ram) and then mount the filesystem in the ram. Then your
index acts normally to the application but is essentially served from
Ram. This is how we server the Nutch lucene indexes on our web search
engine (www.visvo.com) which is ~100M pages. Below is how you can
achieve this, assuming your indexes are in /path/to/indexes:
mv /path/to/indexes /path/to/indexes.dist
mkdir /path/to/indexes
cd /path/to
mount -t tmpfs -o size=2684354560 none /path/to/indexes
rsync --progress -aptv indexes.dist/* indexes/
chown -R user:group indexes
This would of course be limited by the amount of RAM you have on the
machine. But with this approach most searches are sub-second.
Dennis Kubes
Evgeniy Strokin wrote:
Hello,...
we have 110M records index under Solr. Some queries takes a while, but
we need sub-second results. I guess the only solution is cache
(something else?)...
We use standard LRUCache. In docs it says (as far as I understood)
that it loads view of index in to memory and next time works with
memory instead of hard drive.
So, my question: hypothetically, we can have all index in memory if
we'd have enough memory size, right? In this case the result should
come up very fast. We have very rear updates. So I think this could be
a solution.
How should I configure the cache to achieve such approach?
Thanks for any advise.
Gene
