Book description
Plan and Implement Hadoop Virtualization for Maximum Performance, Scalability, and Business Agility
Enterprises running Hadoop must absorb rapid changes in big data ecosystems, frameworks, products, and workloads. Virtualized approaches can offer important advantages in speed, flexibility, and elasticity. Now, a world-class team of enterprise virtualization and big data experts guide you through the choices, considerations, and tradeoffs surrounding Hadoop virtualization. The authors help you decide whether to virtualize Hadoop, deploy Hadoop in the cloud, or integrate conventional and virtualized approaches in a blended solution.
First, Virtualizing Hadoop reviews big data and Hadoop from the standpoint of the virtualization specialist. The authors demystify MapReduce, YARN, and HDFS and guide you through each stage of Hadoop data management. Next, they turn the tables, introducing big data experts to modern virtualization concepts and best practices.
Finally, they bring Hadoop and virtualization together, guiding you through the decisions you’ll face in planning, deploying, provisioning, and managing virtualized Hadoop. From security to multitenancy to day-to-day management, you’ll find reliable answers for choosing your best Hadoop strategy and executing it.
Coverage includes the following:
• Reviewing the frameworks, products, distributions, use cases, and roles associated with Hadoop
• Understanding YARN resource management, HDFS storage, and I/O
• Designing data ingestion, movement, and organization for modern enterprise data platforms
• Defining SQL engine strategies to meet strict SLAs
• Considering security, data isolation, and scheduling for multitenant environments
• Deploying Hadoop as a service in the cloud
• Reviewing the essential concepts, capabilities, and terminology of virtualization
• Applying current best practices, guidelines, and key metrics for Hadoop virtualization
• Managing multiple Hadoop frameworks and products as one unified system
• Virtualizing master and worker nodes to maximize availability and performance
• Installing and configuring Linux for a Hadoop environment
Table of contents
- About This eBook
- Title Page
- Copyright Page
- We Want to Hear from You!
- Reader Services
- Dedication Page
- About the Authors
- Contributor
- About the Technical Editor
- Acknowledgments
- Contents at a Glance
- Contents
- Foreword
- Preface
-
Part I: Introduction to Hadoop
- Chapter 1. Understanding the Big Data World
- Chapter 2. Hadoop Fundamental Concepts
- Chapter 3. YARN and HDFS
- Chapter 4. The Modern Data Platform
- Chapter 5. Data Ingestion
- Chapter 6. Hadoop SQL Engines
- Chapter 7. Multitenancy in Hadoop
- Part II: Introduction to Virtualization
-
Part III: Virtualizing Hadoop
-
Chapter 10. Virtualizing Hadoop
- How Are Hadoop Ecosystems Going to Be Managed?
-
Why Consider Virtualizing Hadoop?
- Benefits of Virtualizing Hadoop
- Virtualized Hadoop Can Run as Fast or Faster Than Native
- Coordination and Cross-Purpose Specialization Is the Future
- Barriers Can Be Organizational
- Virtualization Is Not an All or Nothing Option
- Rapid Provisioning and Improving Quality of Development and Test Environments
- Improve High Availability with Virtualization
- Use Virtualization to Leverage Hadoop Workloads
- Hadoop in the Cloud
- Big Data Extensions
- The Path to Virtualization
- The Software-Defined Data Center
- Virtualizing the Network
- vRealize Suite
- Summary
- References
- Chapter 11. Virtualizing Hadoop Master Servers
- Chapter 12. Virtualizing the Hadoop Worker Nodes
- Chapter 13. Deploying Hadoop as a Service in the Private Cloud
- Chapter 14. Understanding the Installation of Hadoop
-
Chapter 15. Configuring Linux for Hadoop
- Supported Linux Platforms
- Different Deployment Models
- Linux Golden Templates
-
Optimal Linux Kernel Parameters and System Settings
- epoll
- Disable Swap Space
- Disable Security During Install
- IO Scheduler Tuning
- Check Transparent Huge Pages Configuration
- Limits.conf
- Partition Alignment for RDMs
- File System Considerations
- Lazy Count Parameter for XFS
- Mount Options
- I/O Scheduler
- Disk Read and Write Options
- Storage Benchmarking
- Java Version
- Set Up NTP
- Enable Jumbo Frames
- Additional Network Considerations
- Summary
-
Chapter 10. Virtualizing Hadoop
- Appendix A. Hadoop Cluster Creation: A Prerequisite Checklist
- Appendix B. Big Data/Hadoop on VMware vSphere Reference Materials
- Index
- Code Snippets
Product information
- Title: Virtualizing Hadoop: How to Install, Deploy, and Optimize Hadoop in a Virtualized Architecture
- Author(s):
- Release date: July 2015
- Publisher(s): VMware Press
- ISBN: 9780133812350
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