So to be clear, you're trying to use the recommendProducts method of MatrixFactorizationModel? I don't see predictAll in 1.3.1
1.4.0 has a more efficient method to recommend products for all users (or vice versa): https://github.com/apache/spark/blob/v1.4.0/mllib/src/main/scala/org/apache/spark/mllib/recommendation/MatrixFactorizationModel.scala#L152 On Tue, Jun 16, 2015 at 4:30 PM, Ayman Farahat <ayman.fara...@yahoo.com> wrote: > This is 1.3.1 > > Ayman Farahat > -------------------------------------------------- > View my research on my SSRN Author page: > http://ssrn.com/author=1594571 > > ------------------------------ > *From:* Nick Pentreath <nick.pentre...@gmail.com> > *To:* "user@spark.apache.org" <user@spark.apache.org> > *Sent:* Tuesday, June 16, 2015 4:23 AM > *Subject:* Re: ALS predictALL not completing > > Which version of Spark are you using? > > On Tue, Jun 16, 2015 at 6:20 AM, afarahat <ayman.fara...@yahoo.com> wrote: > > Hello; > I have a data set of about 80 Million users and 12,000 items (very sparse > ). > I can get the training part working no problem. (model has 20 factors), > However, when i try using Predict all for 80 Million x 10 items , the jib > does not complete. > When i use a smaller data set say 500k or a million it completes. > Any ideas suggestions ? > Thanks > Ayman > > > > -- > View this message in context: > http://apache-spark-user-list.1001560.n3.nabble.com/ALS-predictALL-not-completing-tp23327.html > Sent from the Apache Spark User List mailing list archive at Nabble.com. > > --------------------------------------------------------------------- > To unsubscribe, e-mail: user-unsubscr...@spark.apache.org > For additional commands, e-mail: user-h...@spark.apache.org > > > > >
