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by Kevin O'Dell, Jean-Marc Spaggiari
Architecting HBase Applications
Foreword
Preface
Who Should Read This Book?
How This Book Is Organized
Additional Resources
Conventions Used in This Book
Using Code Examples
SafariĀ® Books Online
How to Contact Us
Acknowledgments
From Kevin
From Jean-Marc
I. Introduction to HBase
1. What Is HBase?
Column-Oriented Versus Row-Oriented
Implementation and Use Cases
2. HBase Principles
Table Format
Table Layout
Table Storage
Internal Table Operations
Compaction
Splits (Auto-Sharding)
Balancing
Dependencies
HBase Roles
Master Server
RegionServer
Thrift Server
REST Server
3. HBase Ecosystem
Monitoring Tools
Cloudera Manager
Apache Ambari
Hannibal
SQL
Apache Phoenix
Apache Trafodion
Splice Machine
Honorable Mentions (Kylin, Themis, Tephra, Hive, and Impala)
Frameworks
OpenTSDB
Kite
HappyBase
AsyncHBase
4. HBase Sizing and Tuning Overview
Hardware
Storage
Networking
OS Tuning
Hadoop Tuning
HBase Tuning
Different Workload Tuning
5. Environment Setup
System Requirements
Operating System
Virtual Machine
Resources
Java
HBase Standalone Installation
HBase in a VM
Local Versus VM
Local Mode
Virtual Linux Environment
QuickStart VM (or Equivalent)
Troubleshooting
IP/Name Configuration
Access to the /tmp Folder
Environment Variables
Available Memory
First Steps
Basic Operations
Import Code Examples
Testing the Examples
Pseudodistributed and Fully Distributed
II. Use Cases
6. Use Case: HBase as a System of Record
Ingest/Pre-Processing
Processing/Serving
User Experience
7. Implementation of an Underlying Storage Engine
Table Design
Table Schema
Table Parameters
Implementation
Data conversion
Generate Test Data
Create Avro Schema
Implement MapReduce Transformation
HFile Validation
Bulk Loading
Data Validation
Table Size
File Content
Data Indexing
Data Retrieval
Going Further
8. Use Case: Near Real-Time Event Processing
Ingest/Pre-Processing
Near Real-Time Event Processing
Processing/Serving
9. Implementation of Near Real-Time Event Processing
Application Flow
Kafka
Flume
HBase
Lily
Solr
Implementation
Data Generation
Kafka
Flume
Serializer
HBase
Lily
Solr
Testing
Going Further
10. Use Case: HBase as a Master Data Management Tool
Ingest
Processing
11. Implementation of HBase as a Master Data Management Tool
MapReduce Versus Spark
Get Spark Interacting with HBase
Run Spark over an HBase Table
Calling HBase from Spark
Implementing Spark with HBase
Spark and HBase: Puts
Spark on HBase: Bulk Load
Spark Over HBase
Going Further
12. Use Case: Document Store
Serving
Ingest
Clean Up
13. Implementation of Document Store
MOBs
Storage
Usage
Too Big
Consistency
Going Further
III. Troubleshooting
14. Too Many Regions
Consequences
Causes
Misconfiguration
Misoperation
Solution
Before 0.98
Starting with 0.98
Prevention
Regions Size
Key and Table Design
15. Too Many Column Families
Consequences
Memory
Compactions
Split
Causes, Solution, and Prevention
Delete a Column Family
Merge a Column Family
Separate a Column Family into a New Table
16. Hotspotting
Consequences
Causes
Monotonically Incrementing Keys
Poorly Distributed Keys
Small Reference Tables
Applications Issues
Meta Region Hotspotting
Prevention and Solution
17. Timeouts and Garbage Collection
Consequences
Causes
Storage Failure
Power-Saving Features
Network Failure
Solutions
Prevention
Reduce Heap Size
Off-Heap BlockCache
Using the G1GC Algorithm
Configure Swappiness to 0 or 1
Disable Environment-Friendly Features
Hardware Duplication
18. HBCK and Inconsistencies
HBase Filesystem Layout
Reading META
Reading HBase on HDFS
General HBCK Overview
Using HBCK
Index
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Architecting HBase Applications
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