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.
