Carbon copied: *Context*
This is a question mainly about Lucene (or possibly Solr) internals. The main topic is *faceted search*, in which search can happen along multiple independent dimensions (facets) of objects (for example size, speed, price of a car). When implemented with relational database, for a large number of facets multi-field indices are not useful, since facets can be searched in any order, so a specific ordered multi-index is used with low chance, and creating all possible orderings of indices is unbearable. Solr is advertised to cope well with the faceted search task, which if I think correctly has to be connected with Lucene (supposedly) performing well on multi-field queries (where fields of a document relate to facets of an object). *Question* The *inverted index* of Lucene can be stored in a relational database, and naturally taking the intersections of the matching documents can also be trivially achieved with RDBMS using single-field indices. Therefore, Lucene supposedly has some advanced technique for multi-field queries other than just taking the intersection of matching documents based on the inverted index. So the question is, what is this technique/trick? More broadly: Why can Lucene/Solr achieve better faceted search performance theoretically than RDBMS could (if so)? *Note: My first guess would be that Lucene would use some space partitioning method for partitioning a vector space built from the document fields as dimensions, but as I understand Lucene is not purely vector space based.* Thanks, Robin On Wed, Apr 6, 2011 at 3:15 PM, Erick Erickson <erickerick...@gmail.com>wrote: > Please re-post the question here so others can see > the discussion without going to another list. > > Best > Erick > > On Wed, Apr 6, 2011 at 4:09 AM, Robin Palotai <m.palotai.ro...@gmail.com > >wrote: > > > Hello List, > > > > Please see my question at > > > > > http://stackoverflow.com/questions/5552919/how-does-lucene-solr-achieve-high-performance-in-multi-field-faceted-search > > , > > I would be interested to know some details. > > > > Thank you, > > Robin > > >
