Big Data Analytics with R and Hadoop
By Vignesh Prajapati
Publisher: Packt Publishing
Released: November 2013
Pages: 238

In Detail

Big data analytics is the process of examining large amounts of data of a variety of types to uncover hidden patterns, unknown correlations, and other useful information. Such information can provide competitive advantages over rival organizations and result in business benefits, such as more effective marketing and increased revenue. New methods of working with big data, such as Hadoop and MapReduce, offer alternatives to traditional data warehousing.

Big Data Analytics with R and Hadoop is focused on the techniques of integrating R and Hadoop by various tools such as RHIPE and RHadoop. A powerful data analytics engine can be built, which can process analytics algorithms over a large scale dataset in a scalable manner. This can be implemented through data analytics operations of R, MapReduce, and HDFS of Hadoop.

You will start with the installation and configuration of R and Hadoop. Next, you will discover information on various practical data analytics examples with R and Hadoop. Finally, you will learn how to import/export from various data sources to R. Big Data Analytics with R and Hadoop will also give you an easy understanding of the R and Hadoop connectors RHIPE, RHadoop, and Hadoop streaming.

Approach

Big Data Analytics with R and Hadoop is a tutorial style book that focuses on all the powerful big data tasks that can be achieved by integrating R and Hadoop.

Who this book is for

This book is ideal for R developers who are looking for a way to perform big data analytics with Hadoop. This book is also aimed at those who know Hadoop and want to build some intelligent applications over Big data with R packages. It would be helpful if readers have basic knowledge of R.

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oreillyBig Data Analytics with R and Hadoop
 
3.8

(based on 4 reviews)

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4.0

Good starting point for RHadoop!!

By Sanjay Roy

from Delhi, India

About Me Data Analysis Enthusiast

Verified Reviewer

Pros

  • Example Oriented
  • Nice Hadoop Intro
  • Practical
  • Simple To Grab

Cons

  • Font Should Be Better
  • Lack Conversation
  • Lack Professional Writing

Best Uses

  • Hadoop Accessib To R Apps
  • Poc Implementation
  • R Based Analytics Toolkit

Comments about oreilly Big Data Analytics with R and Hadoop:

The book "Big Data Analytics with R and Hadoop" is a good starting point for folks who have good knowledge on R and a basic fundamental knowledge of Hadoop and Map Reduce paradigm. Though the book is more practical oriented, which is again, a good aspect, i would have liked more real life example of implementing business use-cases for adoption.

 
4.0

practical book

By Kirill K

from London, UK

About Me Developer

Pros

  • Easy to understand

Cons

  • Too basic

Best Uses

  • Novice

Comments about oreilly Big Data Analytics with R and Hadoop:

This is a really interesting and well-written book. The author makes the subject accessible. Definitely worth reading if you are interested in big data analytics with R and Hadoop. The book gives a nice introduction to Hadoop and R programming language and how to integrate them together. It gives a brief overview of a data analysis process and tools which you can use to do that.

 
2.0

1 time read to understand RHadoop workin

By deepakmca05

from Bangalore

Verified Reviewer

Comments about oreilly Big Data Analytics with R and Hadoop:

The book title says "Big Data Analytics with R and Hadoop" but when i read it it looked as if this is hands on book in RHadoop like how to install and go for it.
It missed some good real time examples around data analytics

 
5.0

Big data for all!

By Ndjido

from Paris

Verified Reviewer

Pros

  • Easy to understand

Cons

  • No Reference Numbers

Best Uses

  • Expert
  • Intermediate
  • Novice
  • Student

Comments about oreilly Big Data Analytics with R and Hadoop:

"Big data analitics with R and Hadoop" is a book that guides you througth the integration
Of R into a Hadoop ecosystem. R is a very popular open source statistical software analysis
that provides an object oriented c-like programming languge. R comes with tremendous number of
packages to help one perform very sofisticated data analysis and visualisation. When it comes
to scalabilty, R has limitations and fails to let you analyse big datasets as it runs in an
in-memory mode.
Vigneshe Prajapati shows how to make Hadoop work with R and conduct very sofisticated data
analyses ( clustering, classification, recommendation, ...). I do find the step-by-step process very clear and usefull for those who are new to Hadoop and/or R. Any data analyst can pick up
a few tricks of the trade from this book. One of the many other things i love about this book
is the numerous examples of mapReduce processes. Writting mapReduce programms is much more easy
with R than using java. Not only this guides througth the process of setting up an Hadoop cluster, but it also shows how to get valuable information out of overwhelming amount of data using tools like Rhadoop and Rhipe which have the added advantage of making mapReduce programming more tractable.
With the book Vigneshe Prajapati has really democratize big data!

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