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

Chapter 6. R with Non-Relational (NoSQL) Databases

In the previous chapter we showed that R connects very well with traditional, relational, SQL databases. They are still used in the majority of business scenarios, especially when dealing with standard, two-dimensional, rectangular data. However, recently a new range of non-relational or NoSQL databases have been rapidly emerged mostly in response to the growing ecosystem of applications that collect and process different types of data with more flexible, or no, schema. In these times of dynamic development of the Internet of Things, such databases are of particular interest. The growth of many NoSQL databases, especially the open source ones, are also passionately supported by extremely vibrant and dynamic communities of developers, many of whom are R users at the same time. In this chapter, we will guide you through a number of tutorials to help you achieve the following objectives:

  • Understanding data models, basic NoSQL commands, and the...