Also note that field1:* does not necessarily match all documents. A document without that field will not match. So it really can’t be optimized they way you might expect since, as Yonik says, all the terms have to be enumerated….
Best, Erick > On Apr 13, 2019, at 12:30 PM, Yonik Seeley <ysee...@gmail.com> wrote: > > More constrained but matching the same set of documents just guarantees > that there is more information to evaluate per document matched. > For your specific case, you can optimize fq = 'field1:* AND field2:value' > to &fq=field1:*&fq=field2:value > This will at least cause field1:* to be cached and reused if it's a common > pattern. > field1:* is slow in general for indexed fields because all terms for the > field need to be iterated (e.g. does term1 match doc1, does term2 match > doc1, etc) > One can optimize this by indexing a term in a different field to turn it > into a single term query (i.e. exists:field1) > > -Yonik > > On Sat, Apr 13, 2019 at 2:58 PM John Davis <johndavis925...@gmail.com> > wrote: > >> Hi there, >> >> We noticed a sizable performance degradation when we add certain fq filters >> to the query even though the result set does not change between the two >> queries. I would've expected solr to optimize internally by picking the >> most constrained fq filter first, but maybe my understanding is wrong. >> Here's an example: >> >> query1: fq = 'field1:* AND field2:value' >> query2: fq = 'field2:value' >> >> If we assume that the result set is identical between the two queries and >> field1 is in general more frequent in the index, we noticed query1 takes >> 100x longer than query2. In case it matters field1 is of type tlongs while >> field2 is a string. >> >> Any tips for optimizing this? >> >> John >>
