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Programming Elastic Mapreduce de Kevin Schmidt

Programming Elastic Mapreduce

Autor Kevin Schmidt, Christopher Phillips
en Limba Engleză Paperback – 28 ian 2014
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).
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Specificații

ISBN-13: 9781449363628
ISBN-10: 1449363628
Pagini: 171
Dimensiuni: 177 x 233 x 12 mm
Greutate: 0.31 kg
Editura: O'Reilly

Cuprins

Preface; What Is AWS?; What's in This Book?; Sign Up for AWS; Code Samples in This Book; Conventions Used in This Book; Using Code Examples; Safari® Books Online; How to Contact Us; Acknowledgments; Chapter 1: Introduction to Amazon Elastic MapReduce; 1.1 Amazon Web Services Used in This Book; 1.2 Amazon Elastic MapReduce; 1.3 Amazon EMR and the Hadoop Ecosystem; 1.4 Amazon Elastic MapReduce Versus Traditional Hadoop Installs; 1.5 Application Building Blocks; Chapter 2: Data Collection and Data Analysis with AWS; 2.1 Log Analysis Application; 2.2 Log Messages as a Data Set for Analytics; 2.3 Understanding MapReduce; 2.4 Collection Stage; 2.5 Simulating Syslog Data; 2.6 Developing a MapReduce Application; 2.7 Custom JAR MapReduce Job; 2.8 Running an Amazon EMR Cluster; 2.9 Viewing Our Results; 2.10 Debugging a Job Flow; 2.11 Our Application and Real-World Uses; Chapter 3: Data Filtering Design Patterns and Scheduling Work; 3.1 Extending the Application Example; 3.2 Understanding Web Server Logs; 3.3 Finding Errors in the Web Logs Using Data Filtering; 3.4 Building Summary Counts in Data Sets; 3.5 Job Flow Scheduling; 3.6 Scheduling with AWS Data Pipeline; 3.7 Real-World Uses; Chapter 4: Data Analysis with Hive and Pig in Amazon EMR; 4.1 Amazon Job Flow Technologies; 4.2 What Is Pig?; 4.3 Utilizing Pig in Amazon EMR; 4.4 What Is Hive?; 4.5 Utilizing Hive in Amazon EMR; 4.6 Our Application with Hive and Pig; Chapter 5: Machine Learning Using EMR; 5.1 A Quick Tour of Machine Learning; 5.2 Python and EMR; 5.3 What's Next?; Chapter 6: Planning AWS Projects and Managing Costs; 6.1 Developing a Project Cost Model; 6.2 Optimizing AWS Resources to Reduce Project Costs; 6.3 Amazon Tools for Estimating Your Project Costs; Amazon Web Services Resources and Tools; Amazon AWS Online Resources; Amazon AWS Cost Estimation Tools; AWS Best Practices and Architecture; Amazon EMR Distributions; Cloud Computing, Amazon Web Services, and Their Impacts; AWS Service Delivery Models; Performance; Elasticity and Growth; Security; Uptime and Availability; Installation and Setup; Prerequisites; Installing Hadoop; Building MapReduce Applications; Running MapReduce Applications Locally; Installing Pig; Installing Hive; Index; Colophon;