Thank you, Adrien. That answers my questions. On Wednesday, July 16, 2014 5:24:36 AM UTC-4, Adrien Grand wrote: > > On Tue, Jul 15, 2014 at 3:25 PM, David Smith <[email protected] > <javascript:>> wrote: > >> Thanks, Adrien. That brings me closer. >> >> So when the documentations say doc values do not support filtering, it's >> talking about fielddata filtering for what's loaded into memory (anod not >> filtering as part of a query... say term filter). >> > > Exactly. > > >> For further clarification - can a field that is not analyzed and only >> kept as doc values be used for querying/filtering (say a term filter on a >> numeric field or match query on a string field)? Or do all >> querying/filtering required the field to be in the uninverted index? >> > > Doc values play no role when filtering (except for some filters that > support a `fielddata` mode, such as the range filter[1]). So if your field > has `index: no` you cannot use it in filters, and if it has `index: > not_analyzed` then you can, no matter whether doc values are enabled or not. > > [1] > http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/query-dsl-range-filter.html#_execution > > >> What I'm trying to understand how we can optimize querying/filtering in a >> large index (5 billion documents / 1 TB)? It's very hard to run a simple >> term filter because a bitset filter will need to be calculated that >> includes every single document. Wouldn't that utilize a lot of memory? Is >> there a way to speed that up? >> > > If your filters are unlikely to be reused, then you should not cache them > by setting _cache to false. Caching filters only make filtering faster when > the likelyhood of reusing filters is high. > > -- > Adrien Grand >
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