Architecting HBase Applications
A Guidebook for Successful Development and Design
Samenvatting
HBase is a remarkable tool for indexing mass volumes of data, but getting started with this distributed database and its ecosystem can be daunting. With this hands-on guide, you’ll learn how to architect, design, and deploy your own HBase applications by examining real-world solutions. Along with HBase principles and cluster deployment guidelines, this book includes in-depth case studies that demonstrate how large companies solved specific use cases with HBase.
Authors Jean-Marc Spaggiari and Kevin O’Dell also provide draft solutions and code examples to help you implement your own versions of those use cases, from master data management (MDM) and document storage to near real-time event processing. You’ll also learn troubleshooting techniques to help you avoid common deployment mistakes.
- Learn exactly what HBase does, what its ecosystem includes, and how to set up your environment
- Explore how real-world HBase instances were deployed and put into production
- Examine documented use cases for tracking healthcare claims, digital advertising, data management, and product quality
- Understand how HBase works with tools and techniques such as Spark, Kafka, MapReduce, and the Java API
- Learn how to identify the causes and understand the consequences of the most common HBase issues
Specificaties
Inhoudsopgave
Part 1: Introduction to HBase
1. What Is HBase?
-Column-Oriented Versus Row-Oriented
-Implementation and Use Cases
2. HBase Principles
-Table Format
-Internal Table Operations
-Dependencies
-HBase Roles
3. HBase Ecosystem
-Monitoring Tools
-SQL
-Frameworks
4. HBase Sizing and Tuning Overview
-Hardware
-Storage
-Networking
-OS Tuning
-Hadoop Tuning
-HBase Tuning
-Different Workload Tuning
5. Environment Setup
-System Requirements
-HBase Standalone Installation
-HBase in a VM
-Local Versus VM
-Troubleshooting
-First Steps
-Pseudodistributed and Fully Distributed
Part 2: 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
-Data conversion
-HFile Validation
-Bulk Loading
-Data Validation
-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
-Implementation
-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
-Implementing Spark with HBase
-Going Further
12. Use Case: Document Store
-Serving
-Ingest
-Clean Up
13. Implementation of Document Store
-MOBs
-Consistency
-Going Further
Part 3: Troubleshooting
14. Too Many Regions
-Consequences
-Causes
-Solution
-Prevention
15. Too Many Column Families
-Consequences
-Causes, Solution, and Prevention
16. Hotspotting
-Consequences
-Causes
-Prevention and Solution
17. Timeouts and Garbage Collection
-Consequences
-Causes
-Solutions
-Prevention
18. HBCK and Inconsistencies
-HBase Filesystem Layout
-Reading META
-Reading HBase on HDFS
-General HBCK Overview
-Using HBCK
Index
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