Book Cover
Author Schmidt, Kevin J. (Kevin James)

Title Programming Elastic MapReduce / Kevin Schmidt and Christopher Phillips
Published Sebastopol, CA : O'Reilly Media, [2014]
Online access available from:
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Description 1 online resource (1 volume) : illustrations
Summary Although you don't 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 MapReduce (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 MapReduce log analysis application. Using code samples and example configurations, you'll 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 MapReduce patterns for filtering and analyzing data sets Use Apache Hive and Pig instead of Java to build a MapReduce 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
Notes Online resource; title from title page (Safari, viewed Jan. 30, 2014)
Subject Apache Hadoop.
Big data.
Electronic data processing -- Distributed processing.
Internet programming.
Web services.
Form Electronic book
Author Phillips, Chris, 1971-
ISBN 1449363628
Other Titles Subtitle on cover: Using AWS services to build an end-to-end application