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Programming Elastic Mapreduce: Using Aws Services to Build an End-To-End Application

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Synopses & Reviews

Publisher Comments:

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 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, 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 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

Synopsis:

Amazon now brings the power of Hadoop to the cloud and this book helps you take advantage of it. Youll learn how to move your data to the cloud and analyze datasets utilizing a combination of Amazon EC2, S3, and JobFlows in Amazon EMR. Unlock the power of processing large volumes of data and only pay for what you use with Amazon MapReduce services. Programming Elastic MapReduce gets you started.

  • Store large datasets into Amazon Simple Storage Services (S3)
  • Run Amazon Elastic Compute Cloud (EC2) and Elastic MapReduce (EMR) Jobs to analyze large data sets
  • Discover common pitfalls and advanced features for writing real-world MapReduce programs using Pig
  • Examine case studies and common uses
  • Learn to analyze the cost and plan your projects

About the Author

Kevin J. Schmidt is a senior manager at Dell SecureWorks, Inc., anindustry leading MSSP, which is part of Dell. He is responsible for the design and development of a major part of the companys SIEM platform. This includes data acquisition, correlation, and analysis of log data. Prior to SecureWorks, Kevin worked for Reflex Security, where he worked on an IPS engine and anti-virus software. And prior to this, he was a lead developer and architect at GuardedNet, Inc., which built one of the industrys first SIEM platforms.

He is also a commissioned officer in the United States Navy Reserve (USNR). He has over 19 years of experience in software development and design, 11 of which have been in the network security space. He holds a Bachelor of Science in Computer Science.

Kevin has spent time designing cloud services components at Dell, including virtualized components to run in Dells own vCloud. These components are used to protect customers who use Dells cloud infrastructure. Additionally, he has been working with Hadoop, machine learning, and other technology in the cloud.

Kevin is co-author of Essential SNMP, second edition (OReilly and Associates,

Table of Contents

PrefaceChapter 1: Introduction to Amazon Elastic MapReduceChapter 2: Data Collection and Data Analysis with AWSChapter 3: Data Filtering Design Patterns and Scheduling WorkChapter 4: Data Analysis with Hive and Pig in Amazon EMRChapter 5: Machine Learning Using EMRChapter 6: Planning AWS Projects and Managing CostsAmazon Web Services Resources and ToolsCloud Computing, Amazon Web Services, and Their ImpactsInstallation and SetupIndexColophon

Product Details

ISBN:
9781449363628
Subtitle:
Using AWS Services to Build an End-to-End Application
Author:
Schmidt, Kevin
Author:
Phillips, Christopher
Publisher:
O'Reilly Media
Subject:
Data processing
Subject:
Operating Systems - General
Subject:
AWS;Amazon;EC2;Hadoop;S3;big data;cloud computing;data;data analysis;elastic cloud compute;elastic mapreduce
Edition Description:
Print PDF
Publication Date:
20131229
Binding:
Paperback
Language:
English
Pages:
174
Dimensions:
9.19 x 7 in

Related Subjects

Computers and Internet » Computer Architecture » Parallel
Computers and Internet » Computers Reference » General
Computers and Internet » Internet » Web Publishing
Computers and Internet » Internet » Web Services
Computers and Internet » Operating Systems » General

Programming Elastic Mapreduce: Using Aws Services to Build an End-To-End Application New Trade Paper
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Product details 174 pages O'Reilly Media - English 9781449363628 Reviews:
"Synopsis" by ,

Amazon now brings the power of Hadoop to the cloud and this book helps you take advantage of it. Youll learn how to move your data to the cloud and analyze datasets utilizing a combination of Amazon EC2, S3, and JobFlows in Amazon EMR. Unlock the power of processing large volumes of data and only pay for what you use with Amazon MapReduce services. Programming Elastic MapReduce gets you started.

  • Store large datasets into Amazon Simple Storage Services (S3)
  • Run Amazon Elastic Compute Cloud (EC2) and Elastic MapReduce (EMR) Jobs to analyze large data sets
  • Discover common pitfalls and advanced features for writing real-world MapReduce programs using Pig
  • Examine case studies and common uses
  • Learn to analyze the cost and plan your projects

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