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Expert Hadoop Administration

Managing, Tuning, and Securing Spark, YARN, and HDFS

Paperback Engels 2016 9780134597195
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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


Aantal pagina's:799
Hoofdrubriek:IT-management / ICT


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About the Author

Part I: Introduction to Hadoop—Architecture and Hadoop Clusters
1. Introduction to Hadoop and Its Environment
2. An Introduction to the Architecture of Hadoop
3. Creating and Configuring a Simple Hadoop Cluster
4. Planning for and Creating a Fully Distributed Cluster

Part II: Hadoop Application Frameworks
5. Running Applications in a Cluster—The MapReduce Framework (and Hive and Pig)
6. Running Applications in a Cluster—The Spark Framework
7. Running Spark Applications

Part III: Managing and Protecting Hadoop Data and High Availability
8. The Role of the NameNode and How HDFS Works
9. HDFS Commands, HDFS Permissions and HDFS Storage
10. Data Protection, File Formats and Accessing HDFS
11. NameNode Operations, High Availability and Federation

Part IV: Moving Data, Allocating Resources, Scheduling Jobs and Security
12. Moving Data Into and Out of Hadoop
13. Resource Allocation in a Hadoop Cluster
14. Working with Oozie to Manage Job Workflows
15. Securing Hadoop

Part V: Monitoring, Optimization and Troubleshooting
16. Managing Jobs, Using Hue and Performing Routine Tasks
17. Monitoring, Metrics and Hadoop Logging
18. Tuning the Cluster Resources, Optimizing MapReduce Jobs and Benchmarking
19. Configuring and Tuning Apache Spark on YARN
20. Optimizing Spark Applications
21. Troubleshooting Hadoop—A Sampler
22. Installing VirtualBox and Linux and Cloning the Virtual Machines


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