Hi Swapna, I can't give you source code for legal reasons but you should be able to setup Hadoop based map reduce jobs that invoke mahout item similarity and clustering algorithms to run in offline mode in a local or dev hadoop cluster. I wrote some scala code to invoke mahout and stream out results to stdout and then store the results inside hdfs. The mahout documentation as well as the unit tests should help you get this configured and started. For the clustering algorithms you will need to have a process to take a csv file and generate a sequence vector that serves as the input.
After the offline process completes you can then have a script or some other process that moves a subset (or maybe all) the offline data computed by mahout to a real time low latency database to render out these results through a webapp. I have most of this infrastructure working at the moment. Also please direct these to the user alias so everyone can benefit from the discussion. Let me know if you have more specific questions. Regards Sent from my iPhone On Jul 16, 2012, at 4:26 PM, Swapna Yeleswarapu <[email protected]> wrote: > Hi Saikat, > > I was reading your questions on > > http://comments.gmane.org/gmane.comp.apache.mahout.user/13362 > > And was wondering if you got a chance to implement what you were trying to > do. I am trying to do something similar for learning stuff. > > Can you tell me example of how you did a hybrid mode(Offline precomputation > and online reco)? > > Could appreciate it if you had any readily available source code which could > help me set things up. > > Thanks > Swapna
