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A Definitive Guide to Apache ShardingSphere

A Definitive Guide to Apache ShardingSphere

By : Trista Pan , Zhang Liang, Yacine Si Tayeb
4.8 (8)
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A Definitive Guide to Apache ShardingSphere

A Definitive Guide to Apache ShardingSphere

4.8 (8)
By: Trista Pan , Zhang Liang, Yacine Si Tayeb

Overview of this book

Apache ShardingSphere is a new open source ecosystem for distributed data infrastructures based on pluggability and cloud-native principles that helps enhance your database. This book begins with a quick overview of the main challenges faced by database management systems (DBMSs) in production environments, followed by a brief introduction to the software's kernel concept. After that, using real-world examples of distributed database solutions, elastic scaling, DistSQL, synthetic monitoring, database gateways, and SQL authority and user authentication, you’ll fully understand ShardingSphere's architectural components, how they’re configured and can be plugged into your existing infrastructure, and how to manage your data and applications. You’ll also explore ShardingSphere-JDBC and ShardingSphere-Proxy, the ecosystem’s clients, and how they can work either concurrently or independently to address your needs. You’ll then learn how to customize the plugin platform to define personalized user strategies and manage multiple configurations seamlessly. Finally, the book enables you to get up and running with functional and performance tests for all scenarios. By the end of this book, you’ll be able to build and deploy a customized version of ShardingSphere, addressing the key pain points encountered in your data management infrastructure.
Table of Contents (18 chapters)
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1
Section 1: Introducing Apache ShardingSphere
4
Section 2: Apache ShardingSphere Architecture, Installation, and Configuration
10
Section 3: Apache ShardingSphere Real-World Examples, Performance, and Scenario Tests

Configuration – scaling

Elastic scale-out is at the core of ShardingSphere, and its relevant configurations are placed in the sharding rule YAML configuration. Although it requires a long process, it can be easily operated through DistSQL.

Scale-out has two modes, namely an automated process and a manual process. The completionDetector configuration should be active in automated processes, while the other configurations can be turned on according to actual needs. Then, trigger elastic scale-out [job] until it is done. In the manual process, each stage of elastic scale-out can be controlled.

This section will discuss two things:

  • The elastic scale-out job DistSQL syntax and examples
  • The elastic scale-out YAML configuration

DistSQL for job management

Users can control the whole process of scaling data migration through DistSQL, including starting and stopping scaling jobs, viewing progress, disabling reads, checking scaling, switching configurations...

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