Professional Hadoop Solutions

Boris Lublinsky 지음

Wrox 2013년 09월 12일 출간

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The go-to guidebook for deploying Big Data solutions with HadoopToday's enterprise architects need to understand how the Hadoop frameworks and APIs fit together, and how they can be integrated to deliver real-world solutions. This book is a practical, detailed guide to building and implementing those solutions, with code-level instruction in the popular Wrox tradition. It covers storing data with HDFS and Hbase, processing data with MapReduce, and automating data processing with Oozie. Hadoop security, running Hadoop with Amazon Web Services, best practices, and automating Hadoop processes in real time are also covered in depth. With in-depth code examples in Java and XML and the latest on recent additions to the Hadoop ecosystem, this complete resource also covers the use of APIs, exposing their inner workings and allowing architects and developers to better leverage and customize them.The ultimate guide for developers, designers, and architects who need to build and deploy Hadoop applicationsCovers storing and processing data with various technologies, automating data processing, Hadoop security, and delivering real-time solutionsIncludes detailed, real-world examples and code-level guidelinesExplains when, why, and how to use these tools effectivelyWritten by a team of Hadoop experts in the programmer-to-programmer Wrox styleProfessional Hadoop Solutions is the reference enterprise architects and developers need to maximize the power of Hadoop.

목차

Introduction xviiChapter 1: Big Data and the Hadoop Ecosystem 1Big Data Meets Hadoop 2Hadoop: Meeting the Big Data Challenge 3Data Science in the Business World 5The Hadoop Ecosystem 7Hadoop Core Components 7Hadoop Distributions 10Developing Enterprise Applications with Hadoop 12Summary 16Chapter 2: Storing Data in Hadoop 19HDFS 19HDFS Architecture 20Using HDFS Files 24Hadoop-Specific File Types 26HDFS Federation and High Availability 32HBase 34HBase Architecture 34HBase Schema Design 40Programming for HBase 42New HBase Features 50Combining HDFS and HBase for Effective Data Storage 53Using Apache Avro 53Managing Metadata with HCatalog 58Choosing an Appropriate Hadoop Data Organization for Your Applications 60Summary 62Chapter 3: Processing Your Data with MapReduce 63Getting to Know MapReduce 63MapReduce Execution Pipeline 65Runtime Coordination and Task Management in MapReduce 68Your First MapReduce Application 70Building and Executing MapReduce Programs 74Designing MapReduce Implementations 78Using MapReduce as a Framework for Parallel Processing 79Simple Data Processing with MapReduce 81Building Joins with MapReduce 82Building Iterative MapReduce Applications 88To MapReduce or Not to MapReduce? 94Common MapReduce Design Gotchas 95Summary 96Chapter 4: Customizing MapReduce Execution 97Controlling MapReduce Execution with InputFormat 98Implementing InputFormat for Compute-Intensive Applications 100Implementing InputFormat to Control

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저자(글) Boris Lublinsky

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Boris Lublinsky is principal architect at Nokia and an author of more than 70 publications, including Applied SOA: Service#45;Oriented Architecture and Design Strategies.Kevin T. Smith is Director of Technology Solutions for the AMS division of Novetta Solutions, where he builds highly secure, data#45;oriented solutions for customers.Alexey Yakubovich is a system architect at Hortonworks and a member of the Object Management Group SIG on SOA governance and model#45;driven architecture.