Hey Chris, On Mon, Oct 12, 2009 at 10:30 AM, Christoph Boosz < christoph.bo...@googlemail.com> wrote:
> Thanks for your reply. > Yes, it's likely that many terms occur in few documents. > > If I understand you right, I should do the following: > -Write a HitCollector that simply increments a counter > -Get the filter for the user query once: new CachingWrapperFilter(new > QueryWrapperFilter(userQuery)); > -Create a TermQuery for each term > -Perform the search and read the counter of the HitCollector > > I did that, but it didn't get faster. Any ideas why? > This killer is the "TermQuery for each term" part - this is huge. You need to invert this process, and use your query as is, but while walking in the HitCollector, on each doc which matches your query, increment counters for each of the terms in that document (which means you need an in-memory forward lookup for your documents, like a multivalued FieldCache - and if you've got roughly the same number of terms as documents, this cache is likely to be as large as your entire index - a pretty hefty RAM cost). But a good thing to keep in mind is that doing this kind of faceting (massively multivalued on a huge term-set) requires a lot of computation, even if you have all the proper structures living in memory: For each document you look at (which matches your query), you need to look at all of the terms in that document, and increment a counter for that term. So however much time it would normally take for you to do the driving query, it can take as much as that multiplied by the average number of terms in a document in your index. If your documents are big, this could be a pretty huge latency penalty. -jake
