Hi, Is there any lower-bound on the size of RDD to optimally utilize the in-memory framework Spark. Say creating RDD for very small data set of some 64 MB is not as efficient as that of some 256 MB, then accordingly the application can be tuned.
So is there a soft-lowerbound related to hadoop-block size or something else ? Thanks in Advance !