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This article examines common order‑number generation rules and compares four practical solutions—UUID, database auto‑increment, Snowflake algorithm, and Redis INCR—providing code examples and best‑practice recommendations for building globally unique, fast‑producing identifiers in distributed backend systems.
This article presents several approaches for generating unique, scalable order numbers in Spring Boot, including UUIDs, database sequences or auto‑increment IDs, timestamp‑based strings with random components, and distributed Snowflake IDs, each accompanied by Java code examples and discussion of their advantages and drawbacks.
After encountering duplicate order IDs during a system upgrade, the author analyzes the shortcomings of the original timestamp-and-random-based generator, demonstrates concurrency tests revealing collisions, and presents a revised Java implementation using atomic counters, shortened timestamps, and IP suffixes to reliably produce unique order numbers even under high load.
The article analyzes a real‑world incident where duplicate order IDs were generated under high concurrency, demonstrates the shortcomings of the original Java implementation, and presents a thread‑safe redesign using AtomicInteger, Java 8 date‑time API and container IP suffix to guarantee unique identifiers across parallel requests and clustered instances.
The article details how LeTV upgraded its payment platform in 2015 to handle up to 100,000 orders per second by implementing database sharding based on user IDs, a Snowflake‑style globally unique order ID, asynchronous consistency via message queues, multi‑level data caching, and high‑availability architectures for both master‑slave and load‑balanced deployments.