Enabling Exploratory Analysis of Large Data with Apache Spark and R

R has evolved to become an ideal environment for exploratory data analysis. The language is highly flexible - there is an R package for almost any algorithm and the environment comes with integrated help and visualization. SparkR brings distributed computing and the ability to handle very large data to this list. SparkR is an R package distributed within Apache Spark. It exposes Spark DataFrames, which was inspired by R data.frames, to R. With Spark DataFrames, and Spark’s in-memory computing engine, R users can interactively analyze and explore terabyte size data sets. In this webinar, Hossein will introduce SparkR and how it integrates the two worlds of Spark and R. He will demonstrate one of the most important use cases of SparkR: the exploratory analysis of very large data. Specifically, he will show how Spark’s features and capabilities, such as caching distributed data and integrated SQL execution, complement R’s great tools such as visualization and diverse packages in a real world data analysis project with big data.