R: Recipes for Analysis, Visualization and Machine Learning

Manipulating data with plyrmr

While writing a MapReduce program with rmr2 is much easier than writing a native Java version, it is still hard for nondevelopers to write a MapReduce program. Therefore, you can use plyrmr, a high-level abstraction of the MapReduce program, so that you can use plyr-like operations to manipulate big data. In this recipe, we will introduce some operations you can use to manipulate data.

Getting ready

In this recipe, you should have completed the previous recipes by installing plyrmr and rmr2 in R.

How to do it...

Perform the following steps to manipulate data with plyrmr:

1. First, you need to load both plyrmr and rmr2 into R:

   > library(rmr2)
   > library(plyrmr)
   

2. You can then set the execution mode to the local mode:

   > plyrmr.options(backend="local") ...