Hi, I'm wondering how to achieve, say, a Monte Carlo simulation in SparkR without use of low level RDD functions that were made private in 1.4, such as parallelize and map. Something like
parallelize(sc, 1:1000).map ( ### R code that does my computation ) where the code is the same on every node, only with different seeds. (I'm going to use this code with SparkR:::parallelize, but I'm wondering if there is a better way, or whether this might be a use case that would justify not making those functions private?) Many thanks! kristina
