Core Insights - The article emphasizes the importance of a high-performance, scalable order system in the B2B e-commerce sector, highlighting the transition from traditional monolithic architectures to distributed microservices as a critical solution for handling millions of orders efficiently [2][7]. Technical Challenges and Architectural Evolution - Traditional monolithic order systems face three main bottlenecks: system crashes during peak periods, high service coupling leading to failures, and limited scalability due to hardware constraints [2]. - A case study of a traditional manufacturing e-commerce platform illustrates the financial impact of system failures, with losses exceeding 20 million yuan during peak sales events [2]. Distributed Microservices Architecture Design - The architecture of the Shushang Cloud Java Mall source code is based on a "distributed + microservices" model, which includes independent services for order management, inventory, payment, and logistics, enhancing scalability and performance [3]. - The implementation of ShardingSphere for database sharding limits individual table sizes to 5 million records, significantly improving query performance, as evidenced by a case where order query transactions per second (TPS) increased from 800 to 3200 after sharding [3]. Core Module Practices - The system employs distributed locks and unique order number generation to prevent duplicate orders, achieving a reduction in duplicate order rates from 0.3% to 0.01% [4]. - The payment process integrates multiple channels and features an intelligent payment routing engine that optimizes transaction costs and processing times [6]. Performance Optimization Practices - The article discusses various optimization strategies, including the use of multi-level caching, read-write separation, and dynamic scaling based on CPU usage and order queue length, which collectively enhance system performance [5][6]. - A specific case shows that a food e-commerce platform reduced CPU load from 85% to 30% through read-write separation [6]. Future Outlook - The article predicts that the evolution of order systems will increasingly incorporate AI and cloud-native technologies, positioning them as central components in driving digital transformation for businesses [7]. - The performance metrics indicate that the system can now handle an average of 500,000 orders per day, with peak TPS reaching 3500, and operational costs reduced by 40% through server optimization [8].