- Big Data Analytics with R and Hadoop
- Table of Contents
- Big Data Analytics with R and Hadoop
- Credits
- About the Author
- Acknowledgment
- About the Reviewers
- www.PacktPub.com
- Preface
- Introducing R
- Understanding features of R
- Studying the popularity of R
- Introducing Big Data
- Getting information about popular organizations that hold Big Data
- Introducing Hadoop
- Exploring Hadoop features
- What this book covers
- What you need for this book
- Who this book is for
- Conventions
- Reader feedback
- Customer support
- 1. Getting Ready to Use R and Hadoop
- 2. Writing Hadoop MapReduce Programs
- Understanding the basics of MapReduce
- Introducing Hadoop MapReduce
- Understanding the Hadoop MapReduce fundamentals
- Writing a Hadoop MapReduce example
- Learning the different ways to write Hadoop MapReduce in R
- Summary
- 3. Integrating R and Hadoop
- 4. Using Hadoop Streaming with R
- Understanding the basics of Hadoop streaming
- Understanding how to run Hadoop streaming with R
- Understanding a MapReduce application
- Understanding how to code a MapReduce application
- Understanding how to run a MapReduce application
- Understanding how to explore the output of MapReduce application
- Understanding basic R functions used in Hadoop MapReduce scripts
- Monitoring the Hadoop MapReduce job
- Exploring the HadoopStreaming R package
- Summary
- 5. Learning Data Analytics with R and Hadoop
- 6. Understanding Big Data Analysis with Machine Learning
- 7. Importing and Exporting Data from Various DBs
- A. References
- Index
To install RStudio, perform the following steps:
- Navigate to http://www.rstudio.com/ide/download/desktop.
- Download the latest version of RStudio for your operating system.
- Execute the installer file and install RStudio.
The RStudio organization and user community has developed a lot of R packages for graphics and visualization, such as ggplot2, plyr, Shiny, Rpubs, and devtools.
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