Expert Hadoop Administration: Managing, Tuning, and Securing Spark, YARN, and HDFS | First Edition | By Pearson Paperback – 16 August 2017 by Alapati Sam R. (Author)

In Expert Hadoop Administration, leading Hadoop administrator Sam R. Alapati brings together authoritative knowledge for creating, configuring, securing, managing and optimizing production Hadoop clusters in any environment. Drawing on his experience with large-scale Hadoop administration, Alapati integrates action-oriented advice with carefully researched explanations of both problems and solutions. He covers an unmatched range of topics and offers an unparalleled collection of realistic examples. Alapati demystifies complex Hadoop environments, helping readers understand exactly what happens behind the scenes when they administer their cluster. Students will gain unprecedented insight as they walk through building clusters from scratch and configuring high availability, performance, security, encryption and other key attributes. Features The comprehensive, up-to-date Apache Hadoop 2 administration handbook and reference The only Hadoop 2 administration book written by a working Hadoop administrator! Practical examples show how to perform key day-to-day administration tasks and rapidly troubleshoot Hadoop clusters Demystifies complex Hadoop environments and management concepts, offering expert advice and best-practice recommendations Table of Contents Foreword xxvii Preface xxix Acknowledgments xxxv About the Author xxxvii Part I: Introduction to Hadoop—Architecture and Hadoop Clusters Chapter 1: Introduction to Hadoop and Its Environment Chapter 2: An Introduction to the Architecture of Hadoop Chapter 3: Creating and Configuring a Simple Hadoop Cluster Chapter 4: Planning for and Creating a Fully Distributed Cluster Part II: Hadoop Application Frameworks Chapter 5: Running Applications in a Cluster—The MapReduce Framework (and Hive and Pig) Chapter 6: Running Applications in a Cluster—The Spark Framework Chapter 7: Running Spark Applications Part III: Managing and Protecting Hadoop Data and High Availability Chapter 8: The Role of the Name Node and How HDFS Works Chapter 9: HDFS Commands, HDFS Permissions and HDFS Storage Chapter 10: Data Protection, File Formats and Accessing HDFS Chapter 11: Name Node Operations, High Availability and Federation Part IV: Moving Data, Allocating Resources, Scheduling Jobs and Security Chapter 12: Moving Data Into and Out of Hadoop Chapter 13: Resource Allocation in a Hadoop Cluster Chapter 14: Working with Oozie to Manage Job Workflows Chapter 15: Securing Hadoop Part V: Monitoring, Optimization and Troubleshooting Chapter 16: Managing Jobs, Using Hue and Performing Routine Tasks Chapter 17: Monitoring, Metrics and Hadoop Logging Chapter 18: Tuning the Cluster Resources, Optimizing MapReduce Jobs and Benchmarking Chapter 19: Configuring and Tuning Apache Spark on YARN Chapter 20: Optimizing Spark Applications Chapter 21: Troubleshooting Hadoop—A Sampler Chapter 22: Installing Virtual Box and Linux and Cloning the Virtual Machines