Ok ... Actually my problem is more multi thread which take long time ... like 3sec when 100 threads/sec. I thought that could have helped me .. but no link actually :s sorry
markrmiller wrote: > > Kick off some indexing more than once - eg, post a folder of docs, and > while thats working, post another. > > I've been thinking about a multi threaded UpdateProcessor as well - that > could be interesting. > > - Mark > > sunnyfr wrote: >> Hi, >> I was reading this post and I wondering how can I parallelize document >> processing??? >> Thanks Erik >> >> >> Erik Hatcher wrote: >> >>> On Feb 21, 2007, at 4:25 PM, Jack L wrote: >>> >>>>> couple of times today at around 158 documents / sec. >>>>> >>>> This is not bad at all. How about search performance? >>>> How many concurrent queries have people been having? >>>> What does the response time look like? >>>> >>> I'm the only user :) What I've done is a proof-of-concept for our >>> library. We have 3.7M records that I've indexed and faceted. Search >>> performance (in my unrealistic single user scenario) is blazing (50ms >>> or so) for purely full-text queries. For queries that return facets, >>> the response times are actually quite good too (~900ms, or less >>> depending on the request) - provided the filter cache is warmed and >>> large enough. This is running on my laptop (MacBook Pro, 2GB RAM, >>> 1.83GHz) - I'm sure on a beefier box it'll only get better. >>> >>> >>>>> Thanks to the others that clarified. I run my indexers in >>>>> parallel... but a single instance of Solr (which in turn handles >>>>> requests in parallel as well). >>>>> >>>> Do you feel if multi-threaded posting is helpful? >>>> >>> It depends. If the data processing can be parallelized and your >>> hardware supports it, it can certainly make a big difference... it >>> did in my case. Both CPUs were cooking during my parallel indexing >>> runs. >>> >>> Erik >>> >>> >>> >>> >>> >>> >> >> > > > -- View this message in context: http://www.nabble.com/solr-performance-tp9055437p20833662.html Sent from the Solr - User mailing list archive at Nabble.com.
