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
Christopher Phillips & Kevin Schmidt
Programming Elastic MapReduce [PDF ebook]
Using AWS Services to Build an End-to-End Application
Programming Elastic MapReduce [PDF ebook]
Using AWS Services to Build an End-to-End Application
ซื้อ eBook เล่มนี้และรับฟรีอีก 1 เล่ม!
ภาษา อังกฤษ ● รูป PDF ● หน้า 174 ● ISBN 9781449364052 ● สำนักพิมพ์ O’Reilly Media ● การตีพิมพ์ 2013 ● ที่สามารถดาวน์โหลดได้ 6 ครั้ง ● เงินตรา EUR ● ID 2853490 ● ป้องกันการคัดลอก Adobe DRM
ต้องใช้เครื่องอ่านหนังสืออิเล็กทรอนิกส์ที่มีความสามารถ DRM