<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>缓存 on Jeanphilo Blog</title><link>https://shio-chan-dev.github.io/jeanblog/zh/tags/%E7%BC%93%E5%AD%98/</link><description>Recent content in 缓存 on Jeanphilo Blog</description><generator>Hugo -- 0.159.2</generator><language>zh-cn</language><lastBuildDate>Wed, 11 Feb 2026 08:02:05 +0800</lastBuildDate><atom:link href="https://shio-chan-dev.github.io/jeanblog/zh/tags/%E7%BC%93%E5%AD%98/index.xml" rel="self" type="application/rss+xml"/><item><title>LeetCode 146：LRU 缓存设计（O(1)）哈希表 + 双向链表实战</title><link>https://shio-chan-dev.github.io/jeanblog/zh/alg/leetcode/hot100/linked-list/146-lru-cache/</link><pubDate>Wed, 11 Feb 2026 08:02:05 +0800</pubDate><guid>https://shio-chan-dev.github.io/jeanblog/zh/alg/leetcode/hot100/linked-list/146-lru-cache/</guid><description>LRUCache 的核心是用哈希表做 O(1) 定位、双向链表维护最近使用顺序，实现 get/put 平均 O(1)。本文按 ACERS 模板给出推导、工程应用与多语言代码。</description></item><item><title>缓存什么时候危险：一致性、失效与业务风险</title><link>https://shio-chan-dev.github.io/jeanblog/zh/dev/architecture/caching-when-dangerous/</link><pubDate>Sat, 24 Jan 2026 12:23:30 +0800</pubDate><guid>https://shio-chan-dev.github.io/jeanblog/zh/dev/architecture/caching-when-dangerous/</guid><description>说明缓存何时会带来风险，并给出适用条件与规避策略。</description></item><item><title>缓存大小如何确定：命中率、成本与稳定性</title><link>https://shio-chan-dev.github.io/jeanblog/zh/dev/system/cache-sizing-principles/</link><pubDate>Sat, 24 Jan 2026 11:06:00 +0800</pubDate><guid>https://shio-chan-dev.github.io/jeanblog/zh/dev/system/cache-sizing-principles/</guid><description>从命中率、成本与一致性风险出发，给出缓存大小的工程化确定方法与示例。</description></item></channel></rss>