If I'm understanding correctly, you want to use MLlib for offline training and then deploy the learned model to Storm? In this case I don't think there is any problem. However if you are looking for online model update/training, this can be complicated and I guess quite a few algorithms in mllib at this time are designed for offline/batch learning.
On Thu, Jun 19, 2014 at 12:26 AM, Eustache DIEMERT <eusta...@diemert.fr> wrote: > Hi Sparkers, > > We have a Storm cluster and looking for a decent execution engine for > machine learned models. What I've seen from MLLib is extremely positive, > but we can't just throw away our Storm based stack. > > So my question is: is it feasible/recommended to train models in > Spark/MLLib and execute them in another Java environment (Storm in this > case) ? > > Thanks for any insights :) > > Eustache >
