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.

Related Content you might be interested in

Current Title:

Small book image
Big Data Analytics with R
Simon Walkowiak
Jul, 2016 | 506 pages
No titles found
Table of Contents (16 chapters)
Big Data Analytics with R
Big Data Analytics with R
Credits
Credits
About the Author
About the Author
Acknowledgement
Acknowledgement
About the Reviewers
About the Reviewers
www.PacktPub.com
www.PacktPub.com
Preface
Preface
Free Chapter
1
The Era of Big Data
The Era of Big Data
Big Data – The monster re-defined
Big Data toolbox - dealing with the giant
R – The unsung Big Data hero
Summary
2
Introduction to R Programming Language and Statistical Environment
Introduction to R Programming Language and Statistical Environment
Learning R
Revisiting R basics
Applied data science with R
Summary
3
Unleashing the Power of R from Within
Unleashing the Power of R from Within
Traditional limitations of R
To the memory limits and beyond
Parallel R
Boosting R performance with the data.table package and other tools
Summary
4
Hadoop and MapReduce Framework for R
Hadoop and MapReduce Framework for R
Hadoop architecture
A single-node Hadoop in Cloud
HDInsight - a multi-node Hadoop cluster on Azure
Summary
5
R with Relational Database Management Systems (RDBMSs)
R with Relational Database Management Systems (RDBMSs)
Relational Database Management Systems (RDBMSs)
SQLite with R
MariaDB with R on a Amazon EC2 instance
PostgreSQL with R on Amazon RDS
Summary
6
R with Non-Relational (NoSQL) Databases
R with Non-Relational (NoSQL) Databases
Introduction to NoSQL databases
MongoDB with R
HBase with R
Summary
7
Faster than Hadoop - Spark with R
Faster than Hadoop - Spark with R
Spark for Big Data analytics
Spark with R on a multi-node HDInsight cluster
Summary
8
Machine Learning Methods for Big Data in R
Machine Learning Methods for Big Data in R
What is machine learning?
GLM example with Spark and R on the HDInsight cluster
Naive Bayes with H2O on Hadoop with R
Neural Networks with H2O on Hadoop with R
Summary
9
The Future of R - Big, Fast, and Smart Data
The Future of R - Big, Fast, and Smart Data
The current state of Big Data analytics with R
The future of R
Where to go next
Summary

SQLite with R

In this part of the chapter, we will query a SQLite database installed on a local, personal computer directly from RStudio. But before we can do it, follow the next section to prepare a SQLite database and read the data in.

Preparing and importing data into a local SQLite database

We mentioned earlier that SQLite is, by default, included in some distributions of popular operating systems, for example Mac OS X (since version 10.4) and in Windows 10. You can easily check whether your machine has SQLite installed by starting it through a Terminal/shell window:

$ sqlite3
SQLite version 3.12.1 2016-04-08 15:09:49
Enter ".help" for usage hints.
Connected to a transient in-memory database.
Use ".open FILENAME" to reopen on a persistent database.
sqlite>

If the command produces the preceding output (or similar) your machine is already equipped with SQLite database. If for some reason your operating system does not contain SQLite, visit http://www.sqlite.org/download.html to download...

Previous Section
End of Section 3
Next Section