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

MongoDB with R

After the short introduction provided earlier, you should now be able to define the basic characteristics of a variety of NoSQL databases. In this part of the book, we will explore the features and practical applications of MongoDB.

Introduction to MongoDB

MongoDB is one of the examples of non-relational data storage systems, and it also supports a number of data processing and analytics frameworks such as complex aggregations and even MapReduce jobs. All these operations are carried out by the means of MongoDB NoSQL queries - an alternative to the standard SQL language for querying relational databases. As you will soon find out, MongoDB NoSQL commands are very expressive and quite simple to learn. The only problem that most users encounter is the quite convoluted syntax (BSON format) for complex aggregations and queries, but we will explore this issue in the following sections.

MongoDB data models

One of the reasons for this difficulty in writing very complex aggregations using...