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Programming MapReduce with Scalding

You're reading from Programming MapReduce with Scalding A practical guide to designing, testing, and implementing complex MapReduce applications in Scala

Product type Paperback

Published in Jun 2014

Publisher

ISBN-13 9781783287017

Length 148 pages

Edition 1st Edition

Languages

Scala

Tools

Hadoop

Concepts

Front End Web Development

Author (1):

Antonios Chalkiopoulos

View More author details

Table of Contents (11) Chapters

Preface

1. Introduction to MapReduce

2. Get Ready for Scalding FREE CHAPTER

3. Scalding by Example

4. Intermediate Examples

5. Scalding Design Patterns

6. Testing and TDD

7. Running Scalding in Production

8. Using External Data Stores

9. Matrix Calculations and Machine Learning

Index

Chapter 1. Introduction to MapReduce

In this first chapter, we will take a look at the core technologies used in the distributed model of Hadoop; more specifically, we cover the following:

The Hadoop platform and the framework it provides
The MapReduce programming model
Technologies built on top of MapReduce that provide an abstraction layer and an API that is easier to understand and work with

In the following diagram, Hadoop stands at the base, and MapReduce as a design pattern enables the execution of distributed jobs. MapReduce is a low-level programming model. Thus, a number of libraries such as Cascading, Pig, and Hive provide alternative APIs and are compiled into MapReduce. Cascading, which is a Java application framework, has a number of extensions in functional programming languages, with Scalding being the one presented in this book.

Introduction to MapReduce

The rest of the chapter is locked

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Authors (1)

Antonios Chalkiopoulos

Antonios Chalkiopoulos

Antonios Chalkiopoulos is a developer living in London and a professional working with Hadoop and Big Data technologies. He completed a number of complex MapReduce applications in Scalding into 40-plus production nodes HDFS Cluster. He is a contributor to Scalding and other open source projects, and he is interested in cloud technologies, NoSQL databases, distributed real-time computation systems, and machine learning. He was involved in a number of Big Data projects before discovering Scala and Scalding. Most of the content of this book comes from his experience and knowledge accumulated while working with a great team of engineers.

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