Expert Hadoop Administration: Managing, Tuning, and Securing Spark, YARN, and HDFS

The Comprehensive, Up-to-Date Apache Hadoop Administration Handbook and Reference

“Sam Alapati has worked with production Hadoop clusters for six years. His unique depth of experience has enabled him to write the go-to resource for all administrators looking to spec, size, expand, and secure production Hadoop clusters of any size.”

–Paul Dix, Series Editor

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.

• Understand Hadoop’s architecture from an administrator’s standpoint
• Create simple and fully distributed clusters
• Run MapReduce and Spark applications in a Hadoop cluster
• Manage and protect Hadoop data and high availability
• Work with HDFS commands, file permissions, and storage management
• Move data, and use YARN to allocate resources and schedule jobs
• Manage job workflows with Oozie and Hue
• Secure, monitor, log, and optimize Hadoop
• Benchmark and troubleshoot Hadoop

Table of Contents

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 NameNode and How HDFS Works
Chapter 9 HDFS Commands, HDFS Permissions and HDFS Storage
Chapter 10 Data Protection, File Formats and Accessing HDFS
Chapter 11 NameNode 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 VirtualBox and Linux and Cloning the Virtual Machines