java-up-up/damai
🔥 🔥 官方推荐 🔥 🔥 高并发大麦网售票系统，使用 SpringCloud、Kafka、Redis、Sentinel、ElasticSearch、ShardingSphere 等，通过优化锁的策略、多级缓存管理、数据提前预热、精确的定制限流等多种策略，显著的降低下单延迟。此外还解决各种高并发难题的实际落地解决方案。是面试、就业、提高技术的不二选择！ observed · 2026-08-28
Health v2 · maintenance only
67/100
- Activity 97
- Release rhythm 35
- Longevity 56
Flags: no_releases
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 785
- days_rel: n/a
- days_push: 20
- n_releases_24m: 0
Adoption not part of the score
1061 stars · 103 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
A high-concurrency online ticket booking system (modeled after Damai/大麦网) built with SpringCloud, SpringCloud Alibaba, Kafka, Redis, Sentinel, ElasticSearch, and ShardingSphere. It demonstrates production-style solutions to high-traffic problems such as multi-level caching, distributed locks, data pre-warming, rate limiting, and database sharding, and is primarily aimed at Java developers preparing for interviews.
Use cases
- learn how to build a high-concurrency ticket booking system in Java
- study real-world solutions for flash-sale / ticket-grabbing traffic spikes
- practice microservices architecture with SpringCloud Alibaba, Nacos, and Kafka
- learn multi-level caching, cache penetration/breakdown/avalanche handling
- understand distributed lock and local lock optimization strategies
- learn database sharding with ShardingSphere for massive order data
- prepare a resume project with high-concurrency highlights for Java interviews
- study rate limiting and circuit breaking with Sentinel and Hystrix
When to choose
- you are a Java developer preparing for backend interviews and need a project with high-concurrency highlights
- you want a full reference implementation of a SpringCloud microservices ticketing system
- you want to study production-style patterns for caching, locking, rate limiting, and sharding
- you need an end-to-end example combining Redis, Kafka, ElasticSearch, Sentinel, and ShardingSphere
When to avoid
- you need a production-ready ticketing platform to run your business as-is
- you are not working in the Java/Spring ecosystem
- you want a minimal demo rather than a large multi-service system with heavy infrastructure requirements
- you need a fully supported product with commercial guarantees
Facets
application · maturity active
web-framework caching message-queue search-engine rate-limiting database monitoring api-framework web-development backend microservices developer-tools e-commerce education performance jvm self-hosted ticketing high-concurrency spring-cloud spring-cloud-alibaba redis kafka elasticsearch shardingsphere sentinel nacos distributed-lock flash-sale interview-preparation learning-project docker linux web-server
4 sources
- readme: https://github.com/java-up-up/damai · fetched 2026-08-28 · 56e5e37f816c
- homepage: https://javaup.chat · fetched 2026-08-29 · d3a161d83591
- site_page: https://javaup.chat/ai-programming/codex/getting-started · fetched 2026-08-29 · dd995e715d20
- site_page: https://javaup.chat/link-flow/business-intro/getting-started-overview · fetched 2026-08-29 · 15ce5c5d6cd7
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| java-up-up/damai | main | 67 |
For agents
markdown · JSON · MCP: product_card(name="java-up-up/damai")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem