In this chapter we have began our journey through the meanders of Big Data analytics with R. First, we introduced you to the structure, definition, and major limitations of the R programming language hoping that this may clarify why traditionally R was an unlikely choice for a Big Data analyst. But then we showed you how some of these concerns can be quite easily dispelled by using several powerful R packages which facilitate processing and analysis of large datasets.
We have spent a large proportion of this chapter on approaches, that allow out-of-memory data management, first through the ff and ffbase packages, and later by presenting methods contained within the bigmemory package and other libraries that support operations and analytics on big.matrix objects.
In the second part of the chapter we moved on to methods that can potentially boost the performance of your R code. We explored several applications of parallel computing through the parallel and foreach packages and you learnt...