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@@ -23,7 +23,7 @@
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* [平衡二叉树](https://github.com/xingshaocheng/architect-awesome/blob/master/README.md#平衡二叉树)
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* [二叉查找树(BST)](https://github.com/xingshaocheng/architect-awesome/blob/master/README.md#二叉查找树bst)
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* [红黑树](https://github.com/xingshaocheng/architect-awesome/blob/master/README.md#红黑树)
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* [B-,B+,B*树](https://github.com/xingshaocheng/architect-awesome/blob/master/README.md#b-bb树)
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* [B,B+,B*树](https://github.com/xingshaocheng/architect-awesome/blob/master/README.md#b-bb树)
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* [LSM 树](https://github.com/xingshaocheng/architect-awesome/blob/master/README.md#lsm-树)
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* [BitSet](https://github.com/xingshaocheng/architect-awesome/blob/master/README.md#bitset)
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* [常用算法](https://github.com/xingshaocheng/architect-awesome/blob/master/README.md#常用算法)
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@@ -406,12 +406,12 @@
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* 添加阶段后,左旋或者右旋从而再次达到平衡。
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* [《浅谈算法和数据结构: 九 平衡查找树之红黑树》](http://www.cnblogs.com/yangecnu/p/Introduce-Red-Black-Tree.html)
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### B-,B+,B*树
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### B,B+,B*树
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MySQL是基于B+树聚集索引组织表
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* [《B-树,B+树,B\*树详解》](https://blog.csdn.net/aqzwss/article/details/53074186)
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* [《B-树,B+树与B\*树的优缺点比较》](https://blog.csdn.net/bigtree_3721/article/details/73632405)
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* B+ 树的叶子节点链表结构相比于 B- 树便于扫库,和范围检索。
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* B+树的叶子节点链表结构相比于 B-树便于扫库,和范围检索。
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### LSM 树
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LSM(Log-Structured Merge-Trees)和 B+ 树相比,是牺牲了部分读的性能来换取写的性能(通过批量写入),实现读写之间的。
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