Book Image

Big Data Analytics with R

By : Simon Walkowiak
Book Image

Big Data Analytics with R

By: Simon Walkowiak

Overview of this book

Big Data analytics is the process of examining large and complex data sets that often exceed the computational capabilities. R is a leading programming language of data science, consisting of powerful functions to tackle all problems related to Big Data processing. The book will begin with a brief introduction to the Big Data world and its current industry standards. With introduction to the R language and presenting its development, structure, applications in real world, and its shortcomings. Book will progress towards revision of major R functions for data management and transformations. Readers will be introduce to Cloud based Big Data solutions (e.g. Amazon EC2 instances and Amazon RDS, Microsoft Azure and its HDInsight clusters) and also provide guidance on R connectivity with relational and non-relational databases such as MongoDB and HBase etc. It will further expand to include Big Data tools such as Apache Hadoop ecosystem, HDFS and MapReduce frameworks. Also other R compatible tools such as Apache Spark, its machine learning library Spark MLlib, as well as H2O.
Table of Contents (16 chapters)
Big Data Analytics with R
About the Author
About the Reviewers


We began this chapter with a very gentle introduction to Relational Database Management Systems and the basics of Structured Query Language, in order to equip you with the essential skills required to manage RDBMSs on your own.

We then moved on to practical exercises that let you explore a number of techniques of connecting R with relational databases. We first presented how to query and process data locally using a SQLite database, then we thoroughly covered connectivity with MariaDB (and also MySQL, as both are very similar) installed on an Amazon Elastic Cloud Computing instance, and finally we remotely analyzed the data stored and managed in the PostgreSQL database through the Amazon Relational Database Service instance.

Throughout the sections and tutorials of this chapter, you have learned that R can be conveniently used as a tool for the processing and analysis of large, out-of-memory collection of data stored in traditional SQL-operated databases.

In the next chapter, we will...