Thanks, Jack. I did some more research and found similar results. In our application, we are making multiple (think: 50) concurrent requests to calculate term frequency on a set of documents in "real-time". The faster that results return, the better.
Most of these requests are unique, so cache only helps slightly. This analysis is happening on a single solr instance. Other than moving to solr cloud and splitting out the processing onto multiple servers, do you have any suggestions for what might speed up termfreq at query time? Thanks, Aki On Fri, Oct 23, 2015 at 7:21 PM, Jack Krupansky <jack.krupan...@gmail.com> wrote: > Term frequency applies only to the indexed terms of a tokenized field. > DocValues is really just a copy of the original source text and is not > tokenized into terms. > > Maybe you could explain how exactly you are using term frequency in > function queries. More importantly, what is so "heavy" about your usage? > Generally, moderate use of a feature is much more advisable to heavy usage, > unless you don't care about performance. > > -- Jack Krupansky > > On Fri, Oct 23, 2015 at 8:19 AM, Aki Balogh <a...@marketmuse.com> wrote: > > > Hello, > > > > In our solr application, we use a Function Query (termfreq) very heavily. > > > > Index time and disk space are not important, but we're looking to improve > > performance on termfreq at query time. > > I've been reading up on docValues. Would this be a way to improve > > performance? > > > > I had read that Lucene uses Field Cache for Function Queries, so > > performance may not be affected. > > > > > > And, any general suggestions for improving query performance on Function > > Queries? > > > > Thanks, > > Aki > > >
