Sorry, should have been more clear. I was referring to if one is using a user based recommender (e.g GenericUserBasedRecommender) vs. item based recommender. Our general recommendation is that user based approaches won't scale, I was wondering what the general cutoff is on a single machine, more or less. Is it still 100M data points, roughly speaking?
On Oct 26, 2011, at 8:57 AM, Sean Owen wrote: > Limits in terms of scalability? If you mean, how much can you fit on > one machine without Hadoop, I usually say 100M data points or so. > Beyond that you can go as big as you like, but on Hadoop. > > On Wed, Oct 26, 2011 at 1:56 PM, Grant Ingersoll <[email protected]> wrote: >> I seem to recall past discussions on where one hits the bottleneck w/ user >> based recommendation approaches in Mahout, but I can't seem to locate it >> anymore. Anyone know off hand? Where do user based approaches hit their >> limits, more or less? >> >> Thanks, >> Grant >>
