Hi Nick,
>From which version does that apply? I'm using 1.5.2
Thank you,
From: Nick Pentreath mailto:nick.pentre...@gmail.com>>
Date: Tuesday, 9 February 2016 07:02
To: "user@spark.apache.org<mailto:user@spark.apache.org>"
mailto:user@spark.apache.org>>
Sub
In the "new" ALS intermediate RDDs (including the ratings input RDD after
transforming to block-partitioned ratings) is cached using
intermediateRDDStorageLevel, and you can select the final RDD storage level
(for user and item factors) using finalRDDStorageLevel.
The old MLLIB API now calls the n
When using ALS from mllib, would it be better/recommended to cache the ratings
RDD?
I'm asking because when predicting products for users (for example) it is
recommended to cache product/user matrices.
Thank you,
