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

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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

Description

  • Copyright 2017
  • Dimensions: 7" x 9-1/8"
  • Pages: 848
  • Edition: 1st
  • EPUB (Watermarked)
  • ISBN-10: 0-13-470338-3
  • ISBN-13: 978-0-13-470338-1

This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book.

 

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

Sample Content

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

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