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Hadoop 2 Quick-Start Guide: Learn the Essentials of Big Data Computing in the Apache Hadoop 2 Ecosystem

Hadoop 2 Quick-Start Guide: Learn the Essentials of Big Data Computing in the Apache Hadoop 2 Ecosystem

          
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About the Book

Get Started Fast with Apache Hadoop® 2, YARN, and Today’s Hadoop Ecosystem   With Hadoop 2.x and YARN, Hadoop moves beyond MapReduce to become practical for virtually any type of data processing. Hadoop 2.x and the Data Lake concept represent a radical shift away from conventional approaches to data usage and storage. Hadoop 2.x installations offer unmatched scalability and breakthrough extensibility that supports new and existing Big Data analytics processing methods and models.   Hadoop® 2 Quick-Start Guide is the first easy, accessible guide to Apache Hadoop 2.x, YARN, and the modern Hadoop ecosystem. Building on his unsurpassed experience teaching Hadoop and Big Data, author Douglas Eadline covers all the basics you need to know to install and use Hadoop 2 on personal computers or servers, and to navigate the powerful technologies that complement it.   Eadline concisely introduces and explains every key Hadoop 2 concept, tool, and service, illustrating each with a simple “beginning-to-end” example and identifying trustworthy, up-to-date resources for learning more.   This guide is ideal if you want to learn about Hadoop 2 without getting mired in technical details. Douglas Eadline will bring you up to speed quickly, whether you’re a user, admin, devops specialist, programmer, architect, analyst, or data scientist.   Coverage Includes Understanding what Hadoop 2 and YARN do, and how they improve on Hadoop 1 with MapReduce Understanding Hadoop-based Data Lakes versus RDBMS Data Warehouses Installing Hadoop 2 and core services on Linux machines, virtualized sandboxes, or clusters Exploring the Hadoop Distributed File System (HDFS) Understanding the essentials of MapReduce and YARN application programming Simplifying programming and data movement with Apache Pig, Hive, Sqoop, Flume, Oozie, and HBase Observing application progress, controlling jobs, and managing workflows Managing Hadoop efficiently with Apache Ambari–including recipes for HDFS to NFSv3 gateway, HDFS snapshots, and YARN configuration Learning basic Hadoop 2 troubleshooting, and installing Apache Hue and Apache Spark  

Table of Contents:
Foreword         xi Preface          xiii Acknowledgments         xix About the Author          xxi   Chapter 1: Background and Concepts         1 Defining Apache Hadoop  1 A Brief History of Apache Hadoop  3 Defining Big Data  4 Hadoop as a Data Lake  5 Using Hadoop: Administrator, User, or Both  6 First There Was MapReduce  7 Moving Beyond MapReduce with Hadoop V2   13 The Apache Hadoop Project Ecosystem   15 Summary and Additional Resources   18   Chapter 2: Installation Recipes         19 Core Hadoop Services   19 Planning Your Resources   21 Installing on a Desktop or Laptop   23 Installing Hadoop with Ambari   40 Installing Hadoop in the Cloud Using Apache Whirr   56 Summary and Additional Resources   62   Chapter 3: Hadoop Distributed File System Basics          63 Hadoop Distributed File System Design Features   63 HDFS Components   64 HDFS User Commands   72 HDFS Web GUI   77 Using HDFS in Programs   77 Summary and Additional Resources   83   Chapter 4: Running Example Programs and Benchmarks          85 Running MapReduce Examples   85 Running Basic Hadoop Benchmarks   95 Summary and Additional Resources   98   Chapter 5: Hadoop MapReduce Framework         101 The MapReduce Model   101 MapReduce Parallel Data Flow   104 Fault Tolerance and Speculative Execution   107 Summary and Additional Resources   109   Chapter 6: MapReduce Programming          111 Compiling and Running the Hadoop WordCount Example   111 Using the Streaming Interface   116 Using the Pipes Interface   119 Compiling and Running the Hadoop Grep Chaining Example   121 Debugging MapReduce   124 Summary and Additional Resources   128   Chapter 7: Essential Hadoop Tools         131 Using Apache Pig   131 Using Apache Hive   134 Using Apache Sqoop to Acquire Relational Data   139 Using Apache Flume to Acquire Data Streams   148 Manage Hadoop Workflows with Apache Oozie   154 Using Apache HBase   163 Summary and Additional Resources   169   Chapter 8: Hadoop YARN Applications          171 YARN Distributed-Shell   171 Using the YARN Distributed-Shell   172 Structure of YARN Applications   178 YARN Application Frameworks   179 Summary and Additional Resources   184   Chapter 9: Managing Hadoop with Apache Ambari          185 Quick Tour of Apache Ambari   186 Managing Hadoop Services   194 Changing Hadoop Properties   198 Summary and Additional Resources   204   Chapter 10: Basic Hadoop Administration Procedures           205 Basic Hadoop YARN Administration   206 Basic HDFS Administration   208 Capacity Scheduler Background   220 Hadoop Version 2 MapReduce Compatibility   222 Summary and Additional Resources   225   Appendix A: Book Webpage and Code Download          227   Appendix B: Getting Started Flowchart and Troubleshooting Guide         229 Getting Started Flowchart   229 General Hadoop Troubleshooting Guide   229   Appendix C: Summary of Apache Hadoop Resources by Topic          243 General Hadoop Information   243 Hadoop Installation Recipes   243 HDFS   244 Examples   244 MapReduce   245 MapReduce Programming   245 Essential Tools   245 YARN Application Frameworks   246 Ambari Administration   246 Basic Hadoop Administration   247   Appendix D: Installing the Hue Hadoop GUI         249 Hue Installation   249 Starting Hue   253 Hue User Interface   253   Appendix E: Installing Apache Spark         257 Spark Installation on a Cluster   257 Starting Spark across the Cluster   258 Installing and Starting Spark on the Pseudo-distributed Single-Node Installation   260 Run Spark Examples   260   Index         261  


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Product Details
  • ISBN-13: 9780134049984
  • Publisher: Pearson Education (US)
  • Publisher Imprint: Addison Wesley
  • Language: English
  • Sub Title: Learn the Essentials of Big Data Computing in the Apache Hadoop 2 Ecosystem
  • ISBN-10: 0134049985
  • Publisher Date: 14 Oct 2015
  • Binding: Digital download
  • No of Pages: 304
  • Weight: 1 gr


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