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Big Data Analytics with R

You're reading from Big Data Analytics with R Leverage R Programming to uncover hidden patterns in your Big Data

Product type Paperback

Published in Jul 2016

Publisher Packt

ISBN-13 9781786466457

Length 506 pages

Edition 1st Edition

Languages

R

Tools

Hadoop

Concepts

Big Data

Author (1):

Simon Walkowiak

View More author details

Table of Contents (10) Chapters

Preface

1. The Era of Big Data FREE CHAPTER

2. Introduction to R Programming Language and Statistical Environment

3. Unleashing the Power of R from Within

4. Hadoop and MapReduce Framework for R

5. R with Relational Database Management Systems (RDBMSs)

6. R with Non-Relational (NoSQL) Databases

7. Faster than Hadoop - Spark with R

8. Machine Learning Methods for Big Data in R

9. The Future of R - Big, Fast, and Smart Data

Chapter 4. Hadoop and MapReduce Framework for R

In this chapter we are entering the diverse world of Big Data tools and applications that can be relatively easily integrated with the R language. In this chapter, we will present you with a set of guidelines and tips on the following topics:

Deploying cloud-based virtual machines with Hadoop, the ready-to-use Hadoop Distributed File System (HDFS), and MapReduce frameworks
Configuring your instance/virtual machine to include essential libraries and useful supplementary tools for data management in HDFS
Managing HDFS using shell/Terminal commands and running a simple MapReduce word count in Java for comparison
Integrating R statistical environment with Hadoop on a single-node cluster
Managing files in HDFS and run simple MapReduce jobs using the rhadoop bundle of R packages
Carrying out more complex MapReduce tasks on large-scale electricity meter readings datasets on a multi-node HDInsight cluster on Microsoft Azure

However...

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Authors (1)

Walkowiak

Walkowiak

Simon Walkowiak is a cognitive neuroscientist and a managing director of Mind Project Ltd a Big Data and Predictive Analytics consultancy based in London, United Kingdom. As a former data curator at the UK Data Service (UKDS, University of Essex) European largest socio-economic data repository, Simon has an extensive experience in processing and managing large-scale datasets such as censuses, sensor and smart meter data, telecommunication data and well-known governmental and social surveys such as the British Social Attitudes survey, Labour Force surveys, Understanding Society, National Travel survey, and many other socio-economic datasets collected and deposited by Eurostat, World Bank, Office for National Statistics, Department of Transport, NatCen and International Energy Agency, to mention just a few. Simon has delivered numerous data science and R training courses at public institutions and international companies. He has also taught a course in Big Data Methods in R at major UK universities and at the prestigious Big Data and Analytics Summer School organized by the Institute of Analytics and Data Science (IADS).

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