It's an open issue : https://issues.apache.org/jira/browse/SPARK-4587
That's being said, you can workaround the issue by serializing the Model (simple java serialization) and then restoring it before calling the predicition job. Best Regards, On 22/10/2015 14:33, Sebastian Kuepers wrote: > Hey, > > I try to figure out the best practice on saving and loading models > which have bin fitted with the ML package - i.e. with the RandomForest > classifier. > > There is PMML support in the MLib package afaik but not in ML - is > that correct? > > How do you approach this, so that you do not have to fit your model > before every prediction job? > > Thanks, > Sebastian > > > Sebastian Küpers > Account Director > > Publicis Pixelpark > Leibnizstrasse 65, 10629 Berlin > T +49 30 5058 1838 > M +49 172 389 28 52 > sebastian.kuep...@publicispixelpark.de > Web: publicispixelpark.de, Twitter: @pubpxp > Facebook: publicispixelpark.de/facebook > Publicis Pixelpark - eine Marke der Pixelpark AG > Vorstand: Horst Wagner (Vorsitzender), Dirk Kedrowitsch > Aufsichtsratsvorsitzender: Pedro Simko > Amtsgericht Charlottenburg: HRB 72163 > > > > > > ------------------------------------------------------------------------ > Disclaimer The information in this email and any attachments may > contain proprietary and confidential information that is intended for > the addressee(s) only. If you are not the intended recipient, you are > hereby notified that any disclosure, copying, distribution, retention > or use of the contents of this information is prohibited. When > addressed to our clients or vendors, any information contained in this > e-mail or any attachments is subject to the terms and conditions in > any governing contract. If you have received this e-mail in error, > please immediately contact the sender and delete the e-mail.
