算法<初级> - 第八章 Morris遍历/搜索二叉树/跳表等（完结）
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算法<初级> - 第八章 Morris遍历/搜索二叉树/跳表等（完结）
<一> Morris遍历
- Morris遍历实现二叉树的先中后序遍历，时间复杂度O(n)，额外空间复杂度O(1)
-
如果使用递归/非递归版本都是使用栈来完成二叉树遍历，因为只有指向子指针没有指向父指针，有额外的栈空间。
-
Morris遍历实际上就是一个仿真递归的一个遍历过程，一个二叉树递归实际上会经过自己三次，第一次看左第二次看右第三次返回。哪次打印结点，就是属于哪种遍历方式 - 第一次打印就是先序，第二次打印就是中序
-
当前节点Cur，一开始Cur指向根节点
- Cur无左子树，Cur向右移动：
Cur=Cur.right - Cur有左子树，找左子树上最右节点，mostRight；1）mostRight的右孩子为null，则mostRight.right=Cur，Cur向左移动（左子树移动）。（第一次）2）mostRight的右孩子为当前节点，则mostRight.right=null，Cur向右移动（右子树移动）（第二次）
- 这样的操作实际上就完成了一个类似于栈的操作，保存了父结点位置信息（mostRight.right=Cur）。
- Morris遍历就是一个对于任何一个有左子树的结点两次回到自己，对于没有左子树的结点只回到一次，整体符合先中间再左回到中间再右的顺序。
- 因为Morris遍历没有第三次来到当前的结点时候，所以前中序比较好实现，后序实现需要改动下：当第二次回到当前结点的时候逆序（链表逆序打印再转回来）打印左子树的右边界（printEdge）。
- Cur无左子树，Cur向右移动：
-
算法实现（java）
-
public static class Node {
public int value;
Node left;
Node right;
public Node(int data) {
this.value = data;
}
}
public static void morrisIn(Node head) { // 中序遍历
if (head == null) {
return;
}
Node cur1 = head;
Node cur2 = null;
while (cur1 != null) {
cur2 = cur1.left;
if (cur2 != null) { // 有无左子树
while (cur2.right != null && cur2.right != cur1) { // 找到左子树最右结点
cur2 = cur2.right;
}
if (cur2.right == null) { // 第一次找到，向左移动
cur2.right = cur1;
cur1 = cur1.left;
continue;
} else {
cur2.right = null; // 第二次找到，向右移动
}
}
System.out.print(cur1.value + " ");
cur1 = cur1.right; // 向右移动
}
System.out.println();
}
public static void morrisPre(Node head) { // 先序遍历
if (head == null) {
return;
}
Node cur1 = head;
Node cur2 = null;
while (cur1 != null) {
cur2 = cur1.left;
if (cur2 != null) {
while (cur2.right != null && cur2.right != cur1) {
cur2 = cur2.right;
}
if (cur2.right == null) {
cur2.right = cur1;
System.out.print(cur1.value + " ");
cur1 = cur1.left;
continue;
} else {
cur2.right = null;
}
} else {
System.out.print(cur1.value + " ");
}
cur1 = cur1.right;
}
System.out.println();
}
public static void morrisPos(Node head) { // 后序遍历
if (head == null) {
return;
}
Node cur1 = head;
Node cur2 = null;
while (cur1 != null) {
cur2 = cur1.left;
if (cur2 != null) {
while (cur2.right != null && cur2.right != cur1) {
cur2 = cur2.right;
}
if (cur2.right == null) {
cur2.right = cur1;
cur1 = cur1.left;
continue;
} else {
cur2.right = null;
printEdge(cur1.left);
}
}
cur1 = cur1.right;
}
printEdge(head);
System.out.println();
}
public static void printEdge(Node head) {
Node tail = reverseEdge(head);
Node cur = tail;
while (cur != null) {
System.out.print(cur.value + " ");
cur = cur.right;
}
reverseEdge(tail);
}
public static Node reverseEdge(Node from) {
Node pre = null;
Node next = null;
while (from != null) {
next = from.right;
from.right = pre;
pre = from;
from = next;
}
return pre;
}
// for test -- print tree
public static void printTree(Node head) {
System.out.println("Binary Tree:");
printInOrder(head, 0, "H", 17);
System.out.println();
}
public static void printInOrder(Node head, int height, String to, int len) {
if (head == null) {
return;
}
printInOrder(head.right, height + 1, "v", len);
String val = to + head.value + to;
int lenM = val.length();
int lenL = (len - lenM) / 2;
int lenR = len - lenM - lenL;
val = getSpace(lenL) + val + getSpace(lenR);
System.out.println(getSpace(height * len) + val);
printInOrder(head.left, height + 1, "^", len);
}
public static String getSpace(int num) {
String space = " ";
StringBuffer buf = new StringBuffer("");
for (int i = 0; i < num; i++) {
buf.append(space);
}
return buf.toString();
}
public static void main(String[] args) {
Node head = new Node(4);
head.left = new Node(2);
head.right = new Node(6);
head.left.left = new Node(1);
head.left.right = new Node(3);
head.right.left = new Node(5);
head.right.right = new Node(7);
printTree(head);
morrisIn(head);
morrisPre(head);
morrisPos(head);
printTree(head);
}
<二> 搜索二叉树 / AVL / 红黑树 / SB树
-
搜索二叉树：左子树都比该节点小，右节点都比该节点大 - 便于查询，最大代价为树高O(lgn)
- 搜索、插入、删除（非全子树直接替换，全子树找后继节点替换）
- 缺乏平衡性，搜索效率失衡
- 算法实现（java）- 增删查
- 搜索二叉树的平衡性：都是为了让搜索二叉树不退化成棒状，保持h(logn)高度的设定。
- 以下三种树（AVL，红黑，SB）都是对搜索二叉树的改良，使其保持一定的平衡性，但是本质上没有太大差别，实现的功能都是搜索二叉树，区别就是调整算法成本差别，但都是O(logn)的调整，相差在常数。
- 三种树对失衡的调整都是基于两个源动作的组合，只是发生操作的次数和发生操作的节点区别：
- 左/右旋：根节点跑到调整新节点的哪边，就是那种旋法。eg. 右旋，就是三个节点，我（根节点）变成左孩子的右孩子，原来左孩子的右孩子变成我的左孩子，原来的左孩子变成我的父结点。/ 左旋，我（根节点）变成右孩子的左孩子，原来右孩子的左孩子变成我的右孩子，原来的右孩子变成我的父结点。
- 算法实现（java） - 左右旋
- 失衡调整地点：在插入 / 删除节点往上找到的第一个失衡节点时调整他，那么整个树就平衡了。
-
AVL树平衡二叉树：
- 平衡性：左子树与右子树高度相差不超过1。 - 平衡性的严苛导致失衡后的调整比较频繁
- AVL失衡类型：LL型 / LR型 / RL型 / RR型 - LL(左左失衡)/RR型就直接右旋/左旋即可，LR/RL就是把下面先进行一次调整变成LL/RR型（LR对应先进行RR，RL对应先进行LL），再来右旋/左旋
-
红黑树：
- 一个节点要么是红色要么是黑色
- 根节点一定是黑色，叶子节点一定是黑色
- 每个红色的子结点一定是黑色（不同相邻红）
- 任何节点的左右子链包含黑色节点数量一样
- 红黑树的平衡性：任何节点出发的链，长链不能超过短链的两倍
- 调整相比AVL和SB的coding都要复杂，相比而言没有本质区别。
- 红黑树的调整情况太多，删除五种插入八种，不管那种操作基本操作都是一样的，只不过是由于定义/平衡性不一样而区别的。
-
SB树：
- SB树的平衡性：任何一个侄子节点的结点个数都不能比叔叔节点的结点个数大（叔叔节点不小于侄子节点子树节点数）
// 二叉搜索树
public Node root;
/** Tree size. */
protected int size;
/**
* Because this is abstract class and various trees have different
* additional information on different nodes subclasses uses this abstract
* method to create nodes (maybe of class {@link Node} or maybe some
* different node sub class).
*
* @param value
* Value that node will have.
* @param parent
* Node's parent.
* @param left
* Node's left child.
* @param right
* Node's right child.
* @return Created node instance.
*/
protected Node createNode(int value, Node parent, Node left, Node right) {
return new Node(value, parent, left, right);
}
/**
* Finds a node with concrete value. If it is not found then null is
* returned.
*
* @param element
* Element value.
* @return Node with value provided, or null if not found.
*/
public Node search(int element) { // 搜索数，如果没找到就是null空结点
Node node = root;
while (node != null && node.value != null && node.value != element) {
if (element < node.value) {
node = node.left;
} else {
node = node.right;
}
}
return node;
}
/**
* Insert new element to tree.
*
* @param element
* Element to insert.
*/
public Node insert(int element) { // 插入数
if (root == null) { //如果树没有节点则作为根节点
root = createNode(element, null, null, null);
size++;
return root;
}
Node insertParentNode = null; // 插入位置的父结点
Node searchTempNode = root;
while (searchTempNode != null && searchTempNode.value != null) { // 先进行搜索查看范围直至叶子节点
insertParentNode = searchTempNode;
if (element < searchTempNode.value) {
searchTempNode = searchTempNode.left;
} else {
searchTempNode = searchTempNode.right;
}
}
Node newNode = createNode(element, insertParentNode, null, null);
if (insertParentNode.value > newNode.value) { // 查看父结点与插入节点的位置比较
insertParentNode.left = newNode;
} else {
insertParentNode.right = newNode;
}
size++;
return newNode;
}
/**
* Removes element if node with such value exists.
*
* @param element
* Element value to remove.
*
* @return New node that is in place of deleted node. Or null if element for
* delete was not found.
*/
public Node delete(int element) {
Node deleteNode = search(element);
if (deleteNode != null) {
return delete(deleteNode);
} else {
return null;
}
}
/**
* Delete logic when node is already found.
*
* @param deleteNode
* Node that needs to be deleted.
*
* @return New node that is in place of deleted node. Or null if element for
* delete was not found.
*/
protected Node delete(Node deleteNode) { //
if (deleteNode != null) {
Node nodeToReturn = null;
if (deleteNode != null) {
if (deleteNode.left == null) { // 如果没有左子树
nodeToReturn = transplant(deleteNode, deleteNode.right); // 从右子树找个替换该节点
} else if (deleteNode.right == null) { // 如果没有右子树
nodeToReturn = transplant(deleteNode, deleteNode.left); // 从左子树找个替换该节点
} else { // 如果两个子树都有
Node successorNode = getMinimum(deleteNode.right); // 找到右子树最小值（该节点的后继节点）
if (successorNode.parent != deleteNode) {
transplant(successorNode, successorNode.right); // 后继节点是肯定没有左孩子的（否则就不是右子树最小值了）
successorNode.right = deleteNode.right;
successorNode.right.parent = successorNode;
}
transplant(deleteNode, successorNode);
successorNode.left = deleteNode.left;
successorNode.left.parent = successorNode;
nodeToReturn = successorNode;
}
size--;
}
return nodeToReturn;
}
return null;
}
/**
* Put one node from tree (newNode) to the place of another (nodeToReplace).
*
* @param nodeToReplace
* Node which is replaced by newNode and removed from tree.
* @param newNode
* New node.
*
* @return New replaced node.
*/
private Node transplant(Node nodeToReplace, Node newNode) { // 就是两个节点与其他节点连接环境的替换
if (nodeToReplace.parent == null) { //根节点
this.root = newNode;
} else if (nodeToReplace == nodeToReplace.parent.left) {
nodeToReplace.parent.left = newNode;
} else {
nodeToReplace.parent.right = newNode;
}
if (newNode != null) {
newNode.parent = nodeToReplace.parent;
}
return newNode;
}
/**
* @param element
* @return true if tree contains element.
*/
public boolean contains(int element) {
return search(element) != null;
}
/**
* @return Minimum element in tree.
*/
public int getMinimum() {
return getMinimum(root).value;
}
/**
* @return Maximum element in tree.
*/
public int getMaximum() {
return getMaximum(root).value;
}
// 左右旋
/**
* Rotate to the left.
*
* @param node Node on which to rotate.
* @return Node that is in place of provided node after rotation.
*/
protected Node rotateLeft(Node node) {
Node temp = node.right;
temp.parent = node.parent;
node.right = temp.left;
if (node.right != null) {
node.right.parent = node;
}
temp.left = node;
node.parent = temp;
// temp took over node's place so now its parent should point to temp
if (temp.parent != null) {
if (node == temp.parent.left) {
temp.parent.left = temp;
} else {
temp.parent.right = temp;
}
} else {
root = temp;
}
return temp;
}
/**
* Rotate to the right.
*
* @param node Node on which to rotate.
* @return Node that is in place of provided node after rotation.
*/
protected Node rotateRight(Node node) {
Node temp = node.left;
temp.parent = node.parent;
node.left = temp.right;
if (node.left != null) {
node.left.parent = node;
}
temp.right = node;
node.parent = temp;
// temp took over node's place so now its parent should point to temp
if (temp.parent != null) {
if (node == temp.parent.left) {
temp.parent.left = temp;
} else {
temp.parent.right = temp;
}
} else {
root = temp;
}
return temp;
}
// 红黑树
public class RedBlackTree extends AbstractSelfBalancingBinarySearchTree {
protected enum ColorEnum {
RED,
BLACK
};
protected static final RedBlackNode nilNode = new RedBlackNode(null, null, null, null, ColorEnum.BLACK);
/**
* @see trees.AbstractBinarySearchTree#insert(int)
*/
@Override
public Node insert(int element) {
Node newNode = super.insert(element);
newNode.left = nilNode;
newNode.right = nilNode;
root.parent = nilNode;
insertRBFixup((RedBlackNode) newNode);
return newNode;
}
/**
* Slightly modified delete routine for red-black tree.
*
* {@inheritDoc}
*/
@Override
protected Node delete(Node deleteNode) {
Node replaceNode = null; // track node that replaces removedOrMovedNode
if (deleteNode != null && deleteNode != nilNode) {
Node removedOrMovedNode = deleteNode; // same as deleteNode if it has only one child, and otherwise it replaces deleteNode
ColorEnum removedOrMovedNodeColor = ((RedBlackNode)removedOrMovedNode).color;
if (deleteNode.left == nilNode) {
replaceNode = deleteNode.right;
rbTreeTransplant(deleteNode, deleteNode.right);
} else if (deleteNode.right == nilNode) {
replaceNode = deleteNode.left;
rbTreeTransplant(deleteNode, deleteNode.left);
} else {
removedOrMovedNode = getMinimum(deleteNode.right);
removedOrMovedNodeColor = ((RedBlackNode)removedOrMovedNode).color;
replaceNode = removedOrMovedNode.right;
if (removedOrMovedNode.parent == deleteNode) {
replaceNode.parent = removedOrMovedNode;
} else {
rbTreeTransplant(removedOrMovedNode, removedOrMovedNode.right);
removedOrMovedNode.right = deleteNode.right;
removedOrMovedNode.right.parent = removedOrMovedNode;
}
rbTreeTransplant(deleteNode, removedOrMovedNode);
removedOrMovedNode.left = deleteNode.left;
removedOrMovedNode.left.parent = removedOrMovedNode;
((RedBlackNode)removedOrMovedNode).color = ((RedBlackNode)deleteNode).color;
}
size--;
if (removedOrMovedNodeColor == ColorEnum.BLACK) {
deleteRBFixup((RedBlackNode)replaceNode);
}
}
return replaceNode;
}
/**
* @see trees.AbstractBinarySearchTree#createNode(int, trees.AbstractBinarySearchTree.Node, trees.AbstractBinarySearchTree.Node, trees.AbstractBinarySearchTree.Node)
*/
@Override
protected Node createNode(int value, Node parent, Node left, Node right) {
return new RedBlackNode(value, parent, left, right, ColorEnum.RED);
}
/**
* {@inheritDoc}
*/
@Override
protected Node getMinimum(Node node) {
while (node.left != nilNode) {
node = node.left;
}
return node;
}
/**
* {@inheritDoc}
*/
@Override
protected Node getMaximum(Node node) {
while (node.right != nilNode) {
node = node.right;
}
return node;
}
/**
* {@inheritDoc}
*/
@Override
protected Node rotateLeft(Node node) {
Node temp = node.right;
temp.parent = node.parent;
node.right = temp.left;
if (node.right != nilNode) {
node.right.parent = node;
}
temp.left = node;
node.parent = temp;
// temp took over node's place so now its parent should point to temp
if (temp.parent != nilNode) {
if (node == temp.parent.left) {
temp.parent.left = temp;
} else {
temp.parent.right = temp;
}
} else {
root = temp;
}
return temp;
}
/**
* {@inheritDoc}
*/
@Override
protected Node rotateRight(Node node) {
Node temp = node.left;
temp.parent = node.parent;
node.left = temp.right;
if (node.left != nilNode) {
node.left.parent = node;
}
temp.right = node;
node.parent = temp;
// temp took over node's place so now its parent should point to temp
if (temp.parent != nilNode) {
if (node == temp.parent.left) {
temp.parent.left = temp;
} else {
temp.parent.right = temp;
}
} else {
root = temp;
}
return temp;
}
/**
* Similar to original transplant() method in BST but uses nilNode instead of null.
*/
private Node rbTreeTransplant(Node nodeToReplace, Node newNode) {
if (nodeToReplace.parent == nilNode) {
this.root = newNode;
} else if (nodeToReplace == nodeToReplace.parent.left) {
nodeToReplace.parent.left = newNode;
} else {
nodeToReplace.parent.right = newNode;
}
newNode.parent = nodeToReplace.parent;
return newNode;
}
/**
* Restores Red-Black tree properties after delete if needed.
*/
private void deleteRBFixup(RedBlackNode x) {
while (x != root && isBlack(x)) {
if (x == x.parent.left) {
RedBlackNode w = (RedBlackNode)x.parent.right;
if (isRed(w)) { // case 1 - sibling is red
w.color = ColorEnum.BLACK;
((RedBlackNode)x.parent).color = ColorEnum.RED;
rotateLeft(x.parent);
w = (RedBlackNode)x.parent.right; // converted to case 2, 3 or 4
}
// case 2 sibling is black and both of its children are black
if (isBlack(w.left) && isBlack(w.right)) {
w.color = ColorEnum.RED;
x = (RedBlackNode)x.parent;
} else if (w != nilNode) {
if (isBlack(w.right)) { // case 3 sibling is black and its left child is red and right child is black
((RedBlackNode)w.left).color = ColorEnum.BLACK;
w.color = ColorEnum.RED;
rotateRight(w);
w = (RedBlackNode)x.parent.right;
}
w.color = ((RedBlackNode)x.parent).color; // case 4 sibling is black and right child is red
((RedBlackNode)x.parent).color = ColorEnum.BLACK;
((RedBlackNode)w.right).color = ColorEnum.BLACK;
rotateLeft(x.parent);
x = (RedBlackNode)root;
} else {
x.color = ColorEnum.BLACK;
x = (RedBlackNode)x.parent;
}
} else {
RedBlackNode w = (RedBlackNode)x.parent.left;
if (isRed(w)) { // case 1 - sibling is red
w.color = ColorEnum.BLACK;
((RedBlackNode)x.parent).color = ColorEnum.RED;
rotateRight(x.parent);
w = (RedBlackNode)x.parent.left; // converted to case 2, 3 or 4
}
// case 2 sibling is black and both of its children are black
if (isBlack(w.left) && isBlack(w.right)) {
w.color = ColorEnum.RED;
x = (RedBlackNode)x.parent;
} else if (w != nilNode) {
if (isBlack(w.left)) { // case 3 sibling is black and its right child is red and left child is black
((RedBlackNode)w.right).color = ColorEnum.BLACK;
w.color = ColorEnum.RED;
rotateLeft(w);
w = (RedBlackNode)x.parent.left;
}
w.color = ((RedBlackNode)x.parent).color; // case 4 sibling is black and left child is red
((RedBlackNode)x.parent).color = ColorEnum.BLACK;
((RedBlackNode)w.left).color = ColorEnum.BLACK;
rotateRight(x.parent);
x = (RedBlackNode)root;
} else {
x.color = ColorEnum.BLACK;
x = (RedBlackNode)x.parent;
}
}
}
}
private boolean isBlack(Node node) {
return node != null ? ((RedBlackNode)node).color == ColorEnum.BLACK : false;
}
private boolean isRed(Node node) {
return node != null ? ((RedBlackNode)node).color == ColorEnum.RED : false;
}
/**
* Restores Red-Black tree properties after insert if needed. Insert can
* break only 2 properties: root is red or if node is red then children must
* be black.
*/
private void insertRBFixup(RedBlackNode currentNode) {
// current node is always RED, so if its parent is red it breaks
// Red-Black property, otherwise no fixup needed and loop can terminate
while (currentNode.parent != root && ((RedBlackNode) currentNode.parent).color == ColorEnum.RED) {
RedBlackNode parent = (RedBlackNode) currentNode.parent;
RedBlackNode grandParent = (RedBlackNode) parent.parent;
if (parent == grandParent.left) {
RedBlackNode uncle = (RedBlackNode) grandParent.right;
// case1 - uncle and parent are both red
// re color both of them to black
if (((RedBlackNode) uncle).color == ColorEnum.RED) {
parent.color = ColorEnum.BLACK;
uncle.color = ColorEnum.BLACK;
grandParent.color = ColorEnum.RED;
// grandparent was recolored to red, so in next iteration we
// check if it does not break Red-Black property
currentNode = grandParent;
}
// case 2/3 uncle is black - then we perform rotations
else {
if (currentNode == parent.right) { // case 2, first rotate left
currentNode = parent;
rotateLeft(currentNode);
}
// do not use parent
parent.color = ColorEnum.BLACK; // case 3
grandParent.color = ColorEnum.RED;
rotateRight(grandParent);
}
} else if (parent == grandParent.right) {
RedBlackNode uncle = (RedBlackNode) grandParent.left;
// case1 - uncle and parent are both red
// re color both of them to black
if (((RedBlackNode) uncle).color == ColorEnum.RED) {
parent.color = ColorEnum.BLACK;
uncle.color = ColorEnum.BLACK;
grandParent.color = ColorEnum.RED;
// grandparent was recolored to red, so in next iteration we
// check if it does not break Red-Black property
currentNode = grandParent;
}
// case 2/3 uncle is black - then we perform rotations
else {
if (currentNode == parent.left) { // case 2, first rotate right
currentNode = parent;
rotateRight(currentNode);
}
// do not use parent
parent.color = ColorEnum.BLACK; // case 3
grandParent.color = ColorEnum.RED;
rotateLeft(grandParent);
}
}
}
// ensure root is black in case it was colored red in fixup
((RedBlackNode) root).color = ColorEnum.BLACK;
}
protected static class RedBlackNode extends Node {
public ColorEnum color;
public RedBlackNode(Integer value, Node parent, Node left, Node right, ColorEnum color) {
super(value, parent, left, right);
this.color = color;
}
}
}
<三> 跳表 Skip List
- 跳表：能实现搜索二叉树的功能，但不是树结构，使用的是多级索引的链表，查找效率O(logn)，也是Redis中的一个核心组件。
- 每新添加一个节点，用概念（P=0.5）决定节点层数（eg. 正正反-第2层，反-第0层）
- 用一个head列表管理层数，右边就是多个链表指针，按照节点数值大小排序。
- 查询：从head列最高层表开始，往右边对比走，直至比右边的小就开始往下走，直至找到 / 或者到最底层还没查找到。
- 插入：先判断是否有；为其掷层数，再从所掷层开始逐层设置左右邻指针
- 删除：也是同样先判断，然后从所掷层开始逐层断开左右邻指针，并将两边连接。
- 算法实现（java）
public static class SkipListNode { // 跳表headList
public Integer value;
public ArrayList<SkipListNode> nextNodes;
public SkipListNode(Integer value) {
this.value = value;
nextNodes = new ArrayList<SkipListNode>();
}
}
public static class SkipListIterator implements Iterator<Integer> {
SkipList list;
SkipListNode current;
public SkipListIterator(SkipList list) {
this.list = list;
this.current = list.getHead();
}
public boolean hasNext() {
return current.nextNodes.get(0) != null;
}
public Integer next() {
current = current.nextNodes.get(0);
return current.value;
}
}
public static class SkipList {
private SkipListNode head;
private int maxLevel;
private int size;
private static final double PROBABILITY = 0.5; //概率器
public SkipList() {
size = 0;
maxLevel = 0;
head = new SkipListNode(null);
head.nextNodes.add(null);
}
public SkipListNode getHead() {
return head;
}
public void add(Integer newValue) {
if (!contains(newValue)) {
size++;
int level = 0;
while (Math.random() < PROBABILITY) {
level++;
}
while (level > maxLevel) {
head.nextNodes.add(null);
maxLevel++;
}
SkipListNode newNode = new SkipListNode(newValue);
SkipListNode current = head;
do { // 从最上层开始设置左右邻指针
current = findNext(newValue, current, level);
newNode.nextNodes.add(0, current.nextNodes.get(level)); // 先加上层数
current.nextNodes.set(level, newNode); //再设置邻指向
} while (level-- > 0);
}
}
public void delete(Integer deleteValue) {
if (contains(deleteValue)) {
SkipListNode deleteNode = find(deleteValue);
size--;
int level = maxLevel;
SkipListNode current = head;
do {
current = findNext(deleteNode.value, current, level);
if (deleteNode.nextNodes.size() > level) {
current.nextNodes.set(level, deleteNode.nextNodes.get(level));
}
} while (level-- > 0);
}
}
// Returns the skiplist node with greatest value <= e
private SkipListNode find(Integer e) { // 查询数
return find(e, head, maxLevel);
}
// Returns the skiplist node with greatest value <= e
// Starts at node start and level
private SkipListNode find(Integer e, SkipListNode current, int level) {
do {
current = findNext(e, current, level);
} while (level-- > 0);
return current;
}
// Returns the node at a given level with highest value less than e
private SkipListNode findNext(Integer e, SkipListNode current, int level) {
SkipListNode next = current.nextNodes.get(level);
while (next != null) {
Integer value = next.value;
if (lessThan(e, value)) { // e < value
break;
}
current = next;
next = current.nextNodes.get(level);
}
return current;
}
public int size() {
return size;
}
public boolean contains(Integer value) {
SkipListNode node = find(value);
return node != null && node.value != null && equalTo(node.value, value);
}
public Iterator<Integer> iterator() {
return new SkipListIterator(this);
}
/******************************************************************************
* Utility Functions *
******************************************************************************/
private boolean lessThan(Integer a, Integer b) {
return a.compareTo(b) < 0;
}
private boolean equalTo(Integer a, Integer b) {
return a.compareTo(b) == 0;
}
}
public static void main(String[] args) {
}
内容总结
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