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The Comprehensive, Up-to-Date Apache Hadoop Administration Handbook and Reference
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 you understand exactly what happens behind the scenes when you administer your cluster. You’ll gain unprecedented insight as you walk through building clusters from scratch and configuring high availability, performance, security, encryption, and other key attributes. The high-value administration skills you learn here will be indispensable no matter what Hadoop distribution you use or what Hadoop applications you run.
About the Author
Part I: Introduction to Hadoop 2—Architecture and Hadoop Clusters
Chapter 1: Introduction to Hadoop 2 and Its Environment
Chapter 2: An Introduction to the Architecture of Hadoop 2
Chapter 3: Creating and Configuring a Simple Hadoop 2 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 Pig, Hive)
Chapter 6: Running Applications in a Cluster—The Spark Framework
Chapter 7: Running Applications in a Cluster—The Spark Framework (Second Part)
Part III: Managing and Protecting Hadoop Data and High Availability
Chapter 8: The Role of the NameNode and How HDFS Works
Chapter 9: HDFS Commands, File Permissions, and HDFS Storage Management
Chapter 10: Data Protection, Compression, and Hadoop Data Formats
Chapter 11: NameNode Operations and High Availability
Part IV: Moving Data, Allocating Resources, Scheduling Jobs, and Security
Chapter 12: Moving Data Into and Out of Hadoop
Chapter 13: YARN, and Resource Allocation in a Hadoop Cluster
Chapter 14: Working with Oozie and Hue to Manage 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: Bechmarking, Optimization, and Performance Tuning
Chapter 19: Configuring and Tuning Apache Spark on YARN
Chapter 20: Optimizing Spark Applications
Chapter 21: Troubleshooting Hadoop—A Sampler