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Update 缓存.md

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补充布隆过滤器的原理说明和示意图，以及 LRU 中 HashMap 与双向链表的结构图。
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2026-10-25 19:34:21 +08:00
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notes/pics/bloom-filter.png
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notes/缓存.md
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@@ -97,6 +97,10 @@ CDN 主要有以下优点：
- 对这些不存在的数据缓存一个空数据，并设置较短的过期时间；
- 使用布隆过滤器保存所有存在的 Key，对不存在的 Key 的请求直接拒绝。
布隆过滤器用多个哈希函数把 Key 映射到位数组的多个位置并置为 1。查询时只要有一个位置为 0，Key 就一定不存在；全部为 1 时 Key 可能存在，存在一定的误判率。
<div align="center"> <img src="pics/bloom-filter.png" width="560px"/> </div><br>
### 缓存击穿
指的是某个热点数据的缓存过期时，大量对它的请求同时到达数据库。
@@ -200,6 +204,8 @@ Redis Cluster 使用的不是一致性哈希，而是把 Key 映射到固定的
- 访问某个节点时，将其从原来的位置删除，并重新插入到链表头部。这样就能保证链表尾部存储的就是最近最久未使用的节点，当节点数量大于缓存最大空间时就淘汰链表尾部的节点。
- 为了使删除操作时间复杂度为 O(1)，就不能采用遍历的方式找到某个节点。HashMap 存储着 Key 到节点的映射，通过 Key 就能以 O(1) 的时间得到节点，然后再以 O(1) 的时间将其从双向队列中删除。
<div align="center"> <img src="pics/lru.png" width="560px"/> </div><br>
Java 的 LinkedHashMap 内部就是这种结构，把 accessOrder 设为 true 并重写 removeEldestEntry 方法，就可以直接得到一个 LRU 缓存。
```java
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