You are previewing Instant MapReduce Patterns – Hadoop Essentials How-to.
O'Reilly logo
Instant MapReduce Patterns – Hadoop Essentials How-to

Book Description

Practical recipes to write your own MapReduce solution patterns for Hadoop programs

  • Learn something new in an Instant! A short, fast, focused guide delivering immediate results.

  • Learn how to install, configure, and run Hadoop jobs

  • Seven recipes, each describing a particular style of the MapReduce program to give you a good understanding of how to program with MapReduce

  • A concise introduction to Hadoop and common MapReduce patterns

In Detail

MapReduce is a technology that enables users to process large datasets and Hadoop is an implementation of MapReduce. We are beginning to see more and more data becoming available, and this hides many insights that might hold key to success or failure. However, MapReduce has the ability to analyze this data and write code to process it.

Instant MapReduce Patterns: Hadoop Essentials How-to is a concise introduction to Hadoop and programming with MapReduce. It is aimed to get you started and give you an overall feel for programming with Hadoop so that you will have a well-grounded foundation to understand and solve all of your MapReduce problems as needed.

Instant MapReduce Patterns: Hadoop Essentials How-to will start with the configuration of Hadoop before moving on to writing simple examples and discussing MapReduce programming patterns.

We will start simply by installing Hadoop and writing a word count program. After which, we will deal with the seven styles of MapReduce programs: analytics, set operations, cross correlation, search, graph, Joins, and clustering. For each case, you will learn the pattern and create a representative example program. The book also provides you with additional pointers to further enhance your Hadoop skills.

Table of Contents

  1. Instant MapReduce Patterns – Hadoop Essentials How-to
    1. Instant MapReduce Patterns – Hadoop Essentials How-to
    2. Credits
    3. About the Author
    4. About the Reviewer
    5. www.PacktPub.com
      1. Support files, eBooks, discount offers and more
        1. Why Subscribe?
        2. Free Access for Packt account holders
    6. Preface
      1. What this book covers
      2. What you need for this book
      3. Who this book is for
      4. Conventions
      5. Reader feedback
      6. Customer support
        1. Downloading the example code
        2. Errata
        3. Piracy
        4. Questions
    7. 1. Instant MapReduce Patterns – Hadoop Essentials How-to
      1. Writing a word count application using Java (Simple)
        1. Getting ready
        2. How to do it...
        3. How it works...
      2. Writing a word count application with MapReduce and running it (Simple)
        1. Getting ready
        2. How to do it...
        3. How it works...
        4. There's more...
      3. Installing Hadoop in a distributed setup and running a word count application (Simple)
        1. Getting ready
        2. How to do it...
        3. How it works...
      4. Writing a formatter (Intermediate)
        1. Getting ready
        2. How to do it...
        3. How it works...
        4. There's more...
      5. Analytics – drawing a frequency distribution with MapReduce (Intermediate)
        1. Getting ready
        2. How to do it...
        3. How it works...
        4. There's more...
      6. Relational operations – join two datasets with MapReduce (Advanced)
        1. Getting ready
        2. How to do it...
        3. How it works...
        4. There's more...
      7. Set operations with MapReduce (Intermediate)
        1. Getting ready
        2. How to do it...
        3. How it works...
        4. There's more...
      8. Cross correlation with MapReduce (Intermediate)
        1. Getting ready
        2. How to do it...
        3. How it works...
        4. There's more...
      9. Simple search with MapReduce (Intermediate)
        1. Getting ready
        2. How to do it...
        3. How it works...
        4. There's more...
      10. Simple graph operations with MapReduce (Advanced)
        1. Getting ready
        2. How to do it...
        3. How it works...
        4. There's more...
      11. Kmeans with MapReduce (Advanced)
        1. Getting ready
        2. How to do it...
        3. How it works...
        4. There's more...