Are you on Solr 1.3 or a recent nightly build? The development version of 1.4 has a number of scalability enhancements.
-Yonik On Fri, Jan 9, 2009 at 12:18 AM, smock <harish.agar...@gmail.com> wrote: > > Hi Yonik, > > In some ways I have a 'small index' (~8 million documents at the moment). > However, I have a lot of attributes (currently about 30, but I'm expecting > that number to keep growing) and am interested in faceting across all of > them for every search (on a completely unrelated note, if you have any idea > if setting facet.fields to 'all' is an option, please let me know how to do > it) - this is where performance started to suffer when I was using sphinx. > Search times increased quite a bit, proportional to the number of hits > returned by a search (because the number of hits is directly related to the > facet computation time). I found with sphinx that distributing my index was > a big win when doing these faceted searches because every node had to deal > with less facets per index. > > In addition, while I'm okay with depending on intermediate caching > (documentCaches, filterCaches, etc.) to help speed up searches - I would > like every first search to be as fast as possible. My index sees a lot of > unique queries and I don't want to depend on a querycache to speed things > up. > > -Harish > > > > yonik wrote: >> >> Maybe we should back up a bit and look at your requirements: both >> query latency and throughput. >> If the index is small enough, distributed search is definitely not the >> first step to take to address performance issues - there are many >> other things to look into first. >> >> Start by looking at what queries are slowest, and we may be able to >> help speed them up through some optimizations. >> >> -Yonik >> >> > > -- > View this message in context: > http://www.nabble.com/Solr-on-a-multiprocessor-machine-tp21360747p21366406.html > Sent from the Solr - User mailing list archive at Nabble.com. > >
