RevoPemaR package

The RevoPemaR package provides a framework for creating Parallel External Memory Algorithms in R using R Reference Classes.

Package details
Current version: 10.0.0
Built on: R 3.2.2
Package distribution: Machine Learning Server (Hadoop)

How to use RevoPemaR

When used with the RevoScaleR package, analyses can be distributed automatically on Hadoop clusters using Cloudera's CDH or Hortonworks' HDP. For additional documentation, see Get started with PemaR functions in Microsoft R.

In an R session, load RevoPemaR from the command line by typinglibrary(RevoPemaR).


You can load this library on computer that does not have Hadoop (for example, on an R Client instance) if you change the compute context to Hadoop MapReduce or Spark and execute the code in that compute context.

Function list

Class Description
PemaBaseClass A base reference class generator for parallel external memory algorithms.
setPemaClass Returns a generator function for creating a parallel external memory algorithm reference class.
pemaCompute Estimates a parallel external memory algorithm as described by a PEMA reference class object.

Next steps

Add R packages to your computer by running setup for R Server or R Client:

See also

Package Reference