Book Image

Learning Big Data with Amazon Elastic MapReduce

By : Amarkant Singh, Vijay Rayapati
Book Image

Learning Big Data with Amazon Elastic MapReduce

By: Amarkant Singh, Vijay Rayapati

Overview of this book

<p>Amazon Elastic MapReduce is a web service used to process and store vast amount of data, and it is one of the largest Hadoop operators in the world. With the increase in the amount of data generated and collected by many businesses and the arrival of cost-effective cloud-based solutions for distributed computing, the feasibility to crunch large amounts of data to get deep insights within a short span of time has increased greatly.</p> <p>This book will get you started with AWS so that you can quickly create your own account and explore the services provided, many of which you might be delighted to use. This book covers the architectural details of the MapReduce framework, Apache Hadoop, various job models on EMR, how to manage clusters on EMR, and the command-line tools available with EMR. Each chapter builds on the knowledge of the previous one, leading to the final chapter where you will learn about solving a real-world use case using Apache Hadoop and EMR. This book will, therefore, get you up and running with major Big Data technologies quickly and efficiently.</p>
Table of Contents (18 chapters)
Learning Big Data with Amazon Elastic MapReduce
Credits
About the Authors
Acknowledgments
About the Reviewers
www.PacktPub.com
Preface
Index

What is MapReduce?


MapReduce is a style of programming model getting popular with the emergence of easily accessible distributed cloud computing. It is a programming paradigm that allows massively parallel execution and brings in the scalability required for processing huge amounts of data within desired time frames.

As for the definition, here is a quote from an abstract of the initial paper on MapReduce from Google; it says:

"MapReduce is a programming model and an associated implementation for processing and generating large data sets. Users specify a map function that processes a key/value pair to generate a set of intermediate key/value pairs, and a reduce function that merges all intermediate values associated with the same intermediate key.

Programs written in this functional style are automatically parallelized and executed on a large cluster of commodity machines."

The abstract also states that the runtime system, which will be a part of the MapReduce framework, will take care of the...