二叉查找树,也叫二叉搜索树,优势就在于查找,跟二分查找一样,时间复杂度为 O(logn),如何做到的呢?就在于构造二叉树的时候,有这样一个规定,即左边的节点必须小于根节点,右边的节点必须大于跟节点,下面就来实现将任意无序的节点构造成一个二叉查找树的过程。
定义节点 在二叉树系列的第一篇文章里,其实已经定义了二叉树的节点,包括节点数据,左孩子,右孩子,但是在这里打算多添加一个父节点,让父子节点之间双向引用,使查找更灵活。
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 public class TreeNode <T > { private T data; private TreeNode<T> leftChild; private TreeNode<T> rightChild; private TreeNode<T> parent; TreeNode(T data) { this .data = data; this .parent = null ; this .leftChild = null ; this .rightChild = null ; } public T getData () { return data; } public void setData (T data) { this .data = data; } }
添加节点 添加节点的过程,就是构造查找二叉树的过程,本质上,就是定义一个 put 方法,在方法里面,实现元素的摆放位置。
先整理一下步骤:
创建跟节点
从根节点开始遍历
如果根节点为空,跳出,执行步骤 3
令 P = N 记录跟节点,如果插入的节点 A < 根节点 N,令 N = N.leftChild,重复步骤 2
令 P = N 记录跟节点,如果插入的节点 A > 根节点 N,令 N = N.rightChild,重复步骤 2
如果插入的值 A = 根节点的值 N,return 该节点
判断 P 节点的值与插入的节点 A 的值的大小
如果 P > A,则 P.leftChild = A;
如果 P < A,则 P.rightChild = A;
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 public TreeNode root;public TreeNode put (int data) { TreeNode<Integer> node; TreeNode<Integer> parent = null ; if (root == null ) { root = new TreeNode<>(data); return root; } node = root; while (node != null ) { parent = node; if (node.getData() > data) { node = node.leftChild; } else if (node.getData() < data) { node = node.rightChild; } else { return new TreeNode<>(data); } } node = new TreeNode<>(data); if (parent.getData() > data) { parent.leftChild = node; } else { parent.rightChild = node; } node.parent = parent; return node; }
测试添加方法 因为二叉查找树的特性就是 左孩子 < 根节点 < 右孩子,这与二叉树的中序排序一模一样,所以这里就将无序的值,构造成二叉查找树,然后中序遍历该二叉查找树的值,看是否从小到大排列。
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 public class SearchBinaryTree { public static void main (String[] args) { SearchBinaryTree searchBinaryTree = new SearchBinaryTree(); int [] arr = {43 , 15 , 30 , 45 , 50 , 65 }; for (int a : arr) { searchBinaryTree.put(a); } searchBinaryTree.midOrder(searchBinaryTree.root); } public void midOrder (TreeNode node) { if (node == null ) { return ; } midOrder(node.leftChild); System.out.print(node.getData() + " " ); midOrder(node.rightChild); } }
看下打印结果:
现在,二叉查找树添加元素的的过程就算完成了。
删除节点
查找到要删除的节点 node
取出 node 的父节点与左右孩子节点 (可能没有)
根据要删除节点所处的位置不同情况,重新定义节点间的引用
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 public TreeNode<Integer> searchNode (int data) { if (root == null ) return null ; TreeNode<Integer> node = root; while (node != null ) { if (node.getData() > data) { node = node.leftChild; } else if (node.getData() < data) { node = node.rightChild; } else { return node; } } return null ; }
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 public void remove (int data) { TreeNode<Integer> node = searchNode(data); if (node == null ) { throw new RuntimeException("the data is not the in the binaryTree,remove failed" ); } TreeNode<Integer> leftNode = node.leftChild; TreeNode<Integer> rightNode = node.rightChild; TreeNode<Integer> parentNode = node.parent; if (parentNode != null ) { removeUnRootNode(node, leftNode, rightNode, parentNode); } else { removeRootNode(node, leftNode, rightNode); } }
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 private void removeRootNode (TreeNode<Integer> node, TreeNode<Integer> leftNode, TreeNode<Integer> rightNode) { if (leftNode == null && rightNode == null ) { root = null ; } else if (leftNode == null && rightNode != null ) { rightNode.parent = null ; root = rightNode; } else if (leftNode != null && rightNode == null ) { leftNode.parent = null ; root = leftNode; } else if (leftNode != null && rightNode != null ) { TreeNode<Integer> bottomNode = rightNode; while (bottomNode.leftChild != null ) { bottomNode = bottomNode.leftChild; } leftNode.parent = bottomNode; bottomNode.leftChild = leftNode; root = bottomNode; } node.leftChild = null ; node.rightChild = null ; node = null ; }
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 private void removeUnRootNode (TreeNode<Integer> node, TreeNode<Integer> leftNode, TreeNode<Integer> rightNode, TreeNode<Integer> parentNode) { if (leftNode == null && rightNode == null ) { node.parent = null ; if (parentNode.leftChild == node) { parentNode.leftChild = null ; } else { parentNode.rightChild = null ; } } else if (leftNode != null && rightNode == null ) { leftNode.parent = parentNode; if (parentNode.leftChild == node) { parentNode.leftChild = leftNode; } else { parentNode.rightChild = leftNode; } } else if (leftNode == null && rightNode != null ) { rightNode.parent = parentNode; if (parentNode.leftChild == node) { parentNode.leftChild = rightNode; } else { parentNode.rightChild = rightNode; } } else if (leftNode != null && rightNode != null ) { TreeNode<Integer> bottomNode = rightNode; while (bottomNode.leftChild != null ) { bottomNode = bottomNode.leftChild; } leftNode.parent = bottomNode; bottomNode.leftChild = leftNode; rightNode.parent = parentNode; } node.leftChild = null ; node.rightChild = null ; node.parent = null ; node = null ; }
删除元素的代码情况比较多,感觉这里还有优化的空间。
测试删除 1 2 3 4 5 6 7 8 9 10 11 12 public static void main (String[] args) { SearchBinaryTree searchBinaryTree = new SearchBinaryTree(); int [] arr = {43 , 15 , 30 , 45 , 50 , 65 }; for (int a : arr) { searchBinaryTree.put(a); } searchBinaryTree.midOrder(searchBinaryTree.root); searchBinaryTree.remove(50 ); System.out.println(); searchBinaryTree.midOrder(searchBinaryTree.root); }
看下打印结果:
1 2 15 30 43 45 50 65 15 30 43 45 65
如果移除根节点 43,打印结果:
1 2 15 30 43 45 50 65 15 30 45 50 65
二叉查找树的删除操作就算完成了。
Title: 二叉查找树节添加删除节点的细节
Author: mjd507
Date: 2017-06-03
Last Update: 2024-01-27
Blog Link: https://mjd507.github.io/2017/06/03/Data-Structure-Binary-Tree-3/
Copyright Declaration: This station is mainly used to sort out incomprehensible knowledge. I have not fully mastered most of the content. Please refer carefully.