Reason: The original steps 1 and 3 in the redisRateLimitHandler method were not atomic, leading to poor precision under high concurrent requests. For example, with a rate limit set to 60, sending 200 concurrent requests would result in none being blocked, whereas theoretically around 140 should be intercepted.
Solution: I chose not to merge steps 1 and 3 into a single Lua script because a single atomic operation involving read, write, and delete operations could suffer from performance issues under high concurrency. Instead, I implemented a token bucket algorithm to optimize this, reducing the atomic operation to just read and write steps while significantly decreasing the memory footprint.
- Add new context keys for user-related information
- Modify user cache and authentication middleware to populate context
- Refactor quota and notification services to use context-based user data
- Remove redundant database queries by leveraging context information
- Update various components to use new context-based user retrieval methods
- Replaced references to common.GroupRatio and common.UserUsableGroups with corresponding functions from the new setting package across multiple controllers and services.
- Introduced new setting functions for managing group ratios and user usable groups, enhancing code organization and maintainability.
- Updated related functions to ensure consistent behavior with the new setting package integration.
- Introduced a new constant `ContextKeyRequestStartTime` to store the request start time in the context, enhancing request tracking.
- Updated the `Distribute` middleware to set the request start time in the context using the new constant.
- Modified the `GenRelayInfo` function to retrieve the request start time from the context, ensuring accurate timing information is used in relay operations.
