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

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

Kevin J. Schmidt is a senior manager at Dell SecureWorks, Inc., an industry leading MSSP, which is part of Dell. He is responsible for the design and development of a major part of the company’s 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 industry’s 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 Dell’s own vCloud. These components are used to protect customers who use Dell’s 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 (O’Reilly and Associates, ISBN: 978-0-596-00840-6) and also Logging and Log Management: The Authoritative Guide to Understanding the Concepts Surrounding Logging and Log Management (Syngress, ISBN: 978-1-597-49635-3).