Christopher Phillips & Kevin Schmidt 
Programming Elastic MapReduce 
Using AWS Services to Build an End-to-End Application

Although you dont need a large computing infrastructure to process massive amounts of data with Apache Hadoop, it can still be difficult to get started. This practical guide shows you how to quickly launch data analysis projects in the cloud by using Amazon Elastic Map Reduce (EMR), the hosted Hadoop framework in Amazon Web Services (AWS).Authors Kevin Schmidt and Christopher Phillips demonstrate best practices for using EMR and various AWS and Apache technologies by walking you through the construction of a sample Map Reduce log analysis application. Using code samples and example configurations, youll learn how to assemble the building blocks necessary to solve your biggest data analysis problems.Get an overview of the AWS and Apache software tools used in large-scale data analysis Go through the process of executing a Job Flow with a simple log analyzer Discover useful Map Reduce patterns for filtering and analyzing data sets Use Apache Hive and Pig instead of Java to build a Map Reduce Job Flow Learn the basics for using Amazon EMR to run machine learning algorithms Develop a project cost model for using Amazon EMR and other AWS tools