HBase The Definitive Guide 1st Edition by Lars George ISBN 978-1449396107 1449396100
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ISBN 10: 1449396100
ISBN 13: 978-1449396107
Author: Lars George
If you’re looking for a scalable storage solution to accommodate a virtually endless amount of data, this book shows you how Apache HBase can fulfill your needs. As the open source implementation of Google’s BigTable architecture, HBase scales to billions of rows and millions of columns, while ensuring that write and read performance remain constant. Many IT executives are asking pointed questions about HBase. This book provides meaningful answers, whether you’re evaluating this non-relational database or planning to put it into practice right away.
- Discover how tight integration with Hadoop makes scalability with HBase easier
- Distribute large datasets across an inexpensive cluster of commodity servers
- Access HBase with native Java clients, or with gateway servers providing REST, Avro, or Thrift APIs
- Get details on HBase’s architecture, including the storage format, write-ahead log, background processes, and more
- Integrate HBase with Hadoop’s MapReduce framework for massively parallelized data processing jobs
- Learn how to tune clusters, design schemas, copy tables, import bulk data, decommission nodes, and many other tasks
Table of contents:
Chapter 1: Introduction
1.1 The Dawn of Big Data
1.2 The Problem with Relational Database Systems
1.3 Nonrelational Database Systems, Not-Only SQL or NoSQL?
1.4 Building Blocks
1.5 HBase: The Hadoop Database
Chapter 2: Installation
2.1 Quick-Start Guide
2.2 Requirements
2.3 Filesystems for HBase
2.4 Installation Choices
2.5 Run Modes
2.6 Configuration
2.7 Deployment
2.8 Operating a Cluster
Chapter 3: Client API: The Basics
3.1 General Notes
3.2 CRUD Operations
3.3 Batch Operations
3.4 Row Locks
3.5 Scans
3.6 Miscellaneous Features
Chapter 4: Client API: Advanced Features
4.1 Filters
4.2 Counters
4.3 Coprocessors
4.4 HTablePool
4.5 Connection Handling
Chapter 5: Client API: Administrative Features
5.1 Schema Definition
5.2 HBaseAdmin
Chapter 6: Available Clients
6.1 Introduction to REST, Thrift, and Avro
6.2 Interactive Clients
6.3 Batch Clients
6.4 Shell
6.5 Web-based UI
Chapter 7: MapReduce Integration
7.1 Framework
7.2 MapReduce over HBase
Chapter 8: Architecture
8.1 Seek Versus Transfer
8.2 Storage
8.3 Write-Ahead Log
8.4 Read Path
8.5 Region Lookups
8.6 The Region Life Cycle
8.7 ZooKeeper
8.8 Replication
Chapter 9: Advanced Usage
9.1 Key Design
9.2 Advanced Schemas
9.3 Secondary Indexes
9.4 Search Integration
9.5 Transactions
9.6 Bloom Filters
9.7 Versioning
Chapter 10: Cluster Monitoring
10.1 Introduction
10.2 The Metrics Framework
10.3 Ganglia
10.4 JMX
10.5 Nagios
Chapter 11: Performance Tuning
11.1 Garbage Collection Tuning
11.2 Memstore-Local Allocation Buffer
11.3 Compression
11.4 Optimizing Splits and Compactions
11.5 Load Balancing
11.6 Merging Regions
11.7 Client API: Best Practices
11.8 Configuration
11.9 Load Tests
Chapter 12: Cluster Administration
12.1 Operational Tasks
12.2 Data Tasks
12.3 Additional Tasks
12.4 Changing Logging Levels
12.5 Troubleshooting
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