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

By: Douglas Eadline (author)Paperback

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Get Started Fast with Apache Hadoop (R) 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 (R) 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

About Author

Douglas Eadline began his career as a practitioner and a chronicler of the Linux cluster HPC revolution and now documents Big Data analytics. Starting with the first Beowulf Cluster how-to document, Doug has written hundreds of articles, white papers, and instructional documents covering virtually all aspects of High Performance Computing (HPC). Prior to starting and editing the popular ClusterMonkey.net website in 2005, he served as editor-in-chief for ClusterWorld Magazine, and was senior HPC editor for Linux Magazine. Currently, he is a writer and consultant to the HPC/Data Analytics industry and leader of the Limulus Personal Cluster Project (limulus.basement-supercomputing.com). He authored Hadoop Fundamentals LiveLessons, Second Edition (2015), and Apache Hadoop YARN LiveLessons (2014), and is coauthor of Apache Hadoop (TM) YARN (2014), all from Addison-Wesley.


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

Product Details

  • ISBN13: 9780134049946
  • Format: Paperback
  • Number Of Pages: 304
  • ID: 9780134049946
  • weight: 310
  • ISBN10: 0134049942

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