A few points to consider: a) SparkR gives the union of R_in_a_single_machine and the distributed_computing_of_Spark: b) It also gives the ability to wrangle with data in R, that is in the Spark eco system c) Coming to MLlib, the question is MLlib and R (not MLlib or R) - depending on the scale, data location et al d) As Ali mentioned, some of the MLlib might not be supported in R (I haven't looked at it that carefully, but can be resolved by the APIs), OTOH, 1.5 is on it's way. e) So it all depends on the algorithms that one wants to use and whether one needs R for pre or post processing HTH. Cheers <k/>
On Wed, Aug 5, 2015 at 11:24 AM, praveen S <mylogi...@gmail.com> wrote: > I was wondering when one should go for MLib or SparkR. What is the > criteria or what should be considered before choosing either of the > solutions for data analysis? > or What is the advantages of Spark MLib over Spark R or advantages of > SparkR over MLib? >
