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- 添加 sections 定义文件,包含性能优化各领域分类 - 添加规则模板文件,规范文档结构和标签定义 - 添加异步操作优化规则,包括防止瀑布流、并行化、延迟等待等 - 添加包大小优化规则,包括避免桶式导入、动态导入、预加载等 - 添加服务端性能优化规则,包括 API 路
1.3 KiB
1.3 KiB
title, impact, impactDescription, tags
| title | impact | impactDescription | tags |
|---|---|---|---|
| Cross-Request LRU Caching | HIGH | caches across requests | server, cache, lru, cross-request |
Cross-Request LRU Caching
React.cache() only works within one request. For data shared across sequential requests (user clicks button A then button B), use an LRU cache.
Implementation:
import { LRUCache } from 'lru-cache'
const cache = new LRUCache<string, any>({
max: 1000,
ttl: 5 * 60 * 1000 // 5 minutes
})
export async function getUser(id: string) {
const cached = cache.get(id)
if (cached) return cached
const user = await db.user.findUnique({ where: { id } })
cache.set(id, user)
return user
}
// Request 1: DB query, result cached
// Request 2: cache hit, no DB query
Use when sequential user actions hit multiple endpoints needing the same data within seconds.
With Vercel's Fluid Compute: LRU caching is especially effective because multiple concurrent requests can share the same function instance and cache. This means the cache persists across requests without needing external storage like Redis.
In traditional serverless: Each invocation runs in isolation, so consider Redis for cross-process caching.
Reference: https://github.com/isaacs/node-lru-cache