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Big Data Analytics with R

You're reading from  Big Data Analytics with R

Product type Book
Published in Jul 2016
Publisher Packt
ISBN-13 9781786466457
Pages 506 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Simon Walkowiak Simon Walkowiak
Profile icon Simon Walkowiak

Table of Contents (16) Chapters

Big Data Analytics with R
Credits
About the Author
Acknowledgement
About the Reviewers
www.PacktPub.com
Preface
1. The Era of Big Data 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

PostgreSQL with R on Amazon RDS


The methods for launching various open-source SQL databases described in the preceding two sections present just one way of connecting R to data stored in these databases. An alternative approach is offered by Amazon RDS - a managed and highly-scalable solution for database management. In fact, Amazon RDS is probably the easiest and fastest method of deploying a fully-operational SQL database, as it requires very minimal input from users. It also allows support for remote connectivity from RStudio, ensuring that users can quickly connect to the database in the cloud from the comfort of their local computer.

Launching an Amazon RDS database instance

Setting up and launching the database instance on Amazon RDS is generally very user friendly. The following instructions will guide you through the process and will let you create a small, Free Usage Tier (as of April 2016) t2.micro RDS instance with a PostgreSQL database ready for use:

  1. Go to https://aws.amazon.com...

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