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Programming Elastic MapReduce

Christopher Phillips - Kevin Schmidt
pubblicato da O'Reilly Media

Prezzo online:
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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

Dettagli

Generi Informatica e Web » Linguaggi e Applicazioni » Comunicazione e reti informatiche » Database » Scienza dei calcolatori

Editore O'reilly Media

Formato Ebook con Adobe DRM

Pubblicato 10/12/2013

Lingua Inglese

EAN-13 9781449364045

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