Hi All. I am using Lucene as the backbone of a 'Smart Search'.
I have a layer over search that extensively analyzes results at runtime to bucket them. I do trim the resultset, but only after this procesing since their are non document weights that are combined with the result scores, and the hits are then reordered/modified. This needs to essentially get all docs (cause there's some field level analysis), and the score for each upfront, and it seems to be taking forever to do for a large no of hits. The documents themselves are tiny - less than half a k usually. Hit.doc() and .score() seem to be where its taking time - quite as cautioned in the javadocs. Another peculiarity : the query is basically "keywords" which hits all fields, and you can additionally make it more precise by certain fields as field:value. For the latter case, for a similar number of hits, the same iteration above is much quicker than in the case where a similar number of hits is found by the keywords hitting all fields. The query is NOT visibly slower - but the iteration is. Something to do with how spread out across the index the hits are ? Is there a possible workaround for the .doc()/.score() access ? Can RAMDirectory be used only for searches over a "regular" FSDirectory index - and is it usable when the index size is a multiple of available RAM (this is on RH9 or fedora core) ? Thanks in advance, Sameer -- Sameer Shisodia Bangalore [EMAIL PROTECTED]
