That's what a normal query does - Lucene takes all the terms used in the query and sums them up for each document in the response, producing a single number, the score, for each document. That's the way Solr is designed to be used. You still haven't elaborated why you are trying to use Solr in a way other than it was intended.
-- Jack Krupansky On Sat, Oct 24, 2015 at 11:13 AM, Aki Balogh <a...@marketmuse.com> wrote: > Gotcha - that's disheartening. > > One idea: when I run termfreq, I get all of the termfreqs for each document > one-by-one. > > Is there a way to have solr sum it up before creating the request, so I > only receive one number in the response? > > > On Sat, Oct 24, 2015 at 11:05 AM, Upayavira <u...@odoko.co.uk> wrote: > > > If you mean using the term frequency function query, then I'm not sure > > there's a huge amount you can do to improve performance. > > > > The term frequency is a number that is used often, so it is stored in > > the index pre-calculated. Perhaps, if your data is not changing, > > optimising your index would reduce it to one segment, and thus might > > ever so slightly speed the aggregation of term frequencies, but I doubt > > it'd make enough difference to make it worth doing. > > > > Upayavira > > > > On Sat, Oct 24, 2015, at 03:37 PM, Aki Balogh wrote: > > > 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 > > > > > > > > > > > >
