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The RevoPemaR package provides a framework for creating Parallel External Memory Algorithms in R using R Reference Classes.
| Package details | Description |
|---|---|
| Current version: | 10.0.0 |
| Built on: | R 3.2.2 |
| Package distribution: | Machine Learning Server (Hadoop) |
When used with the RevoScaleR package, analyses can be distributed automatically on Hadoop clusters using Cloudera's CDH or Hortonworks' HDP. For more information, see Get started with PemaR functions in Microsoft R.
In an R session, load RevoPemaR from the command line by typinglibrary(RevoPemaR).
Note
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.
| 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. |
Add R packages to your computer by running setup for R Server or R Client: