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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

HDInsight - a multi-node Hadoop cluster on Azure

In Online Chapter , Pushing R Further (https://www.packtpub.com/sites/default/files/downloads/5396_6457OS_PushingRFurther.pdf), we briefly introduced you to HDInsight-a fully-managed Apache Hadoop service that comes as part of the Microsoft Azure platform and is specifically designed for heavy data crunching. In this section, we will deploy a multi-node HDInsight cluster with R and RStudio Server installed and will perform a number of MapReduce jobs on smart electricity meter readings (~414,000,000 cases, four variables, ~12 GB in size) of the Energy Demand Research Project available to download from UK Data Service's online Discover catalog at https://discover.ukdataservice.ac.uk/catalogue/?sn=7591 . But before we can tap into the actual data crunching, we need to set up and prepare an HDInsight cluster to process our data. The configuration of HDInsight is not the simplest task to accomplish, especially if we need...

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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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