Machine Learning with R Cookbook - Second Edition

How to do it...

Perform the following steps to compare the performance of a standard R program and an R MapReduce program:

1. First, you can implement a standard R program to have all numbers squared:

        > a.time = proc.time() 
        > small.ints2=1:100000 
        > result.normal = sapply(small.ints2, function(x) x^2) 
        > proc.time() - a.time  

2. To compare the performance, you can implement an R MapReduce program to have all numbers squared:

        > b.time = proc.time() 
        > small.ints= to.dfs(1:100000) 
        > result = mapreduce(input = small.ints, map = function(k,v)        cbind(v,v^2)) 
        > proc.time() - b.time