Apache Seata is a distributed transaction solution for microservices, implementing AT (Automatic), TCC, Saga, and XA transaction modes. It provides a Transaction Coordinator (TC) server, client libraries for Resource Managers (RM) and Transaction Managers (TM), and supports multiple databases, serialization formats, and service discovery backends. The architecture is plugin-driven via Java SPI, with a custom EnhancedServiceLoader for loading compressors, serializers, registries, and configuration providers. The codebase includes a Netty-based RPC layer with protocol versioning (v0, v1, v2), a robust Saga state machine engine with a visual designer, and a Spring Boot-based console for cluster management and global transaction monitoring. It integrates deeply with Spring, Dubbo, gRPC, and other RPC frameworks, and offers GraalVM native-image support for server deployments. The repository is extensive with over 30 Maven modules, reflecting both its production maturity and the complexity of maintaining backward compatibility through a deprecated io.seata package layer.
This repository contains a technical book titled 'The Art of Problem-Solving in Software Engineering: How to Make MySQL Better'. It is structured as a collection of Markdown files covering MySQL internals, performance optimization, and problem-solving methodologies. The book does not contain executable code or data processing scripts; instead, it provides theoretical explanations, case studies, and references to MySQL versions 8.0.x and 5.7. Topics include transaction throttling, latch sharding, hybrid data structures, Group Replication enhancements, and performance testing techniques using tools like BenchmarkSQL and SysBench. The repository serves as an educational resource for database administrators, performance engineers, and MySQL contributors seeking to understand and resolve MySQL scalability and performance issues. It emphasizes analytical approaches over trial-and-error, drawing from computer science fundamentals such as queueing theory, distributed systems, and algorithmic optimization. While the book references benchmark results and visualizations (stored as images in the media/ directory), it does not include the raw data, scripts, or tools needed to reproduce those results. As a documentation-focused repository, it lacks traditional software engineering components like APIs, CLI tools, or reusable libraries. Its value lies in the consolidated knowledge presented across chapters, which readers can apply to MySQL tuning and troubleshooting scenarios. The content appears well-organized and researched, but the absence of runnable code or data assets limits its direct utility as a software artifact.