I guess I can but it would be nicer if that is made a configuration, I can create the issue, test and PR if you guys think its appropiate
On Wed, Jan 7, 2015 at 1:41 PM, Sean Owen <so...@cloudera.com> wrote: > Ah, Fernando means the usersOut / productsOut RDDs, not the intermediate > links RDDs. > Can you unpersist() them, and persist() again at the desired level? the > downside is that this might mean recomputing and repersisting the RDDs. > > On Wed, Jan 7, 2015 at 5:11 AM, Xiangrui Meng <men...@gmail.com> wrote: > >> Which Spark version are you using? We made this configurable in 1.1: >> >> >> https://github.com/apache/spark/blob/master/mllib/src/main/scala/org/apache/spark/mllib/recommendation/ALS.scala#L202 >> >> -Xiangrui >> >> On Tue, Jan 6, 2015 at 12:57 PM, Fernando O. <fot...@gmail.com> wrote: >> >>> Hi, >>> I was doing a tests with ALS and I noticed that if I persist the >>> inner RDDs from a MatrixFactorizationModel the RDD is not replicated, it >>> seems like the storagelevel is hardcoded to MEMORY_AND_DISK, do you think >>> it makes sense to make that configurable? >>> [image: Inline image 1] >>> >> >> >
