Hi Manuel, I haven't got to the point where CacheItemSimilarity kicks in. That is, I will have to run a lot of recommendations in order to get a real benefit from it. I would first like to optimize the 'cold start' so it's at least serves at reasonable time. Usually cache is used to prevent repeated calculations, but personally I dont think it's a replacement for optimized performance. Don't you agree?
Also, I will try to profile the app now as you suggest and send the results asap. Thanks! On Thu, Dec 1, 2011 at 4:56 PM, Manuel Blechschmidt < [email protected]> wrote: > Hi Daniel, > actually you are running the profile inside tomcat. You should take a > snapshot and then drill down to the functions where the actual > recommendation takes place. The current screenshots also contains some > profiles from Tomcat threads which are sleeping a lot and therefore taking > a lot of time. > > Further the screenshots does not contain the amount how often the > different functions are called. > > You have to profile multiple requests alone. The CacheItemSimilarity gets > filled therefore it should go faster and faster. > > On 01.12.2011, at 15:11, Daniel Zohar wrote: > > > @Manuel thanks for the tips. I have installed VisualVM and followed are > the > > results > > I did two sampling - > > - With the optimized SamplingCandidateItemsStrategy ( > > http://pastebin.com/6n9C8Pw1): http://static.inky.ws/image/934/image.jpg > > - Without the optimized SamplingCandidateItemsStrategy: > > http://static.inky.ws/image/935/image.jpg > > > > The big hot spot is the function FastIDSet.find(): > > Optimized: 13,759 s > Unoptimized: 246,487 s > > So you see that your optimization already got you a performance boost of > 2000%. > > Did you play around with the CacheItemSimilarity cache sizes? > > /Manuel > > -- > Manuel Blechschmidt > Dortustr. 57 > 14467 Potsdam > Mobil: 0173/6322621 > Twitter: http://twitter.com/Manuel_B > >
