Are you using the "pseudo-distributed" RecommenderJob? There are a few RecommenderJobs!
Can you cache a DataModel in memory across workers in a cluster? No -- the workers are perhaps not on the same machine, or even in the same datacenter. Each worker would have to load its own. But it sounds a bit like you are trying to have a servlet make recommendations in real-time by calling out to Hadoop. This will never work. Hadoop is a big batch-oriented framework. What you can do is pre-compute recommendations with Hadoop, as you are doing, and write to HDFS. Then the servlet can load recs from HDFS, yes. No problem there. On Thu, Dec 30, 2010 at 7:45 AM, Alessandro Binhara <[email protected]> wrote: > Hello everyone > > I am studying the RecommenderJob to run a recommendation system in hadoop. > I have currently DataModule are loaded as a singleton, and it are cached in > memory. I have a servlet responds to requests sent to the mahout. > > Using this RecommenderJob on hadoop. The RecommenderJob will every time > load a datamodel from HDFS files and then processing the recommendation? > > It is possible to use some strategy to get this cache in the cluster? > > The response of the recommendation will be written in HDFS, how do I > identify the answer? Is there any job ID in hadoop? > > thank´s >
