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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

MariaDB with R on a Amazon EC2 instance

In Online Chapter, Pushing R Further (https://www.packtpub.com/sites/default/files/downloads/5396_6457OS_PushingRFurther.pdf), apart from creating a Linux Ubuntu virtual machine with RStudio Server on Microsoft Azure, we have also launched an Amazon Linux EC2 instance. In this section we will deploy an Ubuntu instance with RStudio Server, but this time on Amazon EC2.

Preparing the EC2 instance and RStudio Server for use

The good news is that you should already know how to do this. Initially, simply follow steps 1 through 13 of the section on Creating your first Amazon EC2 instance from Online Chapter, Pushing R Further (https://www.packtpub.com/sites/default/files/downloads/5396_6457OS_PushingRFurther.pdf). Choose a Free Usage Tier Linux Ubuntu instance and (in step 6) create your new key pair with a distinct name, for example rstudio_mariadb.pem. Also in the same step (step 6), add another custom TCP rule for port 3306. This will allow connectivity...

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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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