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chore: add hash index description #281

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chore: add hash index description #281

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10 changes: 8 additions & 2 deletions mysql/index/index_interview.md
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Expand Up @@ -152,9 +152,15 @@ B+Tree 只在叶子节点存储数据，而 B 树 的非叶子节点也要存储

***3, B+Tree vs Hash***

Hash 在做等值查询的时候效率贼快，搜索复杂度为 O(1)。
Hash 在做等值查询的时候效率贼快，搜索复杂度为 O(1)。但也有其局限性：

但是 Hash 表不适合做范围查询，它更适合做等值的查询，这也是 B+Tree 索引要比 Hash 表索引有着更广泛的适用场景的原因。
- **数据顺序性**：哈希表无法提供数据的顺序访问，更适合做等值的查询。很多查询不仅需要找到特定的键值，还需要根据键值排序来返回结果，或者执行范围查询。B+Tree 可以很好地支持，Hash 表则无法做到。

- **空间效率**：可能导致空间利用效率不高，特别是在处理大量数据时。数据量变大时冲突也会增加。

- **需要重新构建**：哈希索引通常只存储在内存中，当数据库重启或发生崩溃时，需要重新构建。

因此，B+Tree 索引要比 Hash 表索引有着更广泛的适用场景。

### 按物理存储分类

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