一 什么是映射？
借助关键码直接查找数据元素并对其进行操作的数据结构就是映射，映射中的数据是以(key, value)的形式进行存储的，其中 key 为关键码对象，value 为具体的数据对象。生活中有很多地方都使用这样的数据结构来存储数据，比如：字典 车牌号 身份证等
映射图示
二 基于链表的映射实现
1⃣️ 定义Map接口
package com.mufeng.map;
/**
* Created by wb-yxk397023 on 2018/7/5.
*/
public interface Map {
/**
* 向Map中添加元素
* @param key
* @param value
*/
void add(K key, V value);
/**
* 根据K值找到V，并从Map中删除
* @param key
* @return
*/
V remove(K key);
/**
* 根据K值查看Map中是否包含该元素
* @param key
* @return
*/
boolean contains(K key);
/**
* 根据K值查询V值
* @param key
* @return
*/
V get(K key);
/**
* 根据K值修改Value值
* @param key
* @param newValue
*/
void set(K key, V newValue);
/**
* 查看Map中的元素个数
* @return
*/
int getSize();
/**
* 查看Map是否为空
* @return
*/
boolean isEmpty();
}
2⃣️ 实现具体的Map类
package com.mufeng.map;
/**
* Created by wb-yxk397023 on 2018/7/5.
*/
public class LinkedListMap implements Map {
@Override
public void add(K key, V value) {
Node node = getNode(key);
if (node == null){
dummyHead.next = new Node(key, value, dummyHead.next);
size++;
}else {
node.value = value;
}
}
@Override
public V remove(K key) {
Node prev = dummyHead;
while (prev.next != null){
if (prev.next.key.equals(key)){
break;
}
prev = prev.next;
}
if (prev.next != null){
Node delNode = prev.next;
prev.next = delNode.next;
delNode.next = null;
size--;
return delNode.value;
}
return null;
}
@Override
public boolean contains(K key) {
return getNode(key) != null;
}
@Override
public V get(K key) {
Node node = getNode(key);
return node == null ? null : node.value;
}
@Override
public void set(K key, V newValue) {
Node node = getNode(key);
if (node == null){
throw new IllegalArgumentException(key + " doesn't exist!");
}
node.value = newValue;
}
@Override
public int getSize() {
return size;
}
@Override
public boolean isEmpty() {
return size == 0;
}
private Node dummyHead;
private int size;
public LinkedListMap(){
dummyHead = new Node();
size = 0;
}
/**
* 通用方法封装
* @param key
* @return
*/
private Node getNode(K key){
Node cur = dummyHead.next;
while (cur != null){
if (cur.key.equals(key)){
return cur;
}
cur = cur.next;
}
return null;
}
/**
* 内部类Node
*/
private class Node{
private K key;
private V value;
private Node next;
public Node(K key, V value, Node next){
this.key = key;
this.value = value;
this.next = next;
}
public Node(K key){
this(key,null,null);
}
public Node(){
this(null,null,null);
}
@Override
public String toString(){
return key.toString() + " : " + value.toString();
}
}
}
3⃣️ 测试
public static void main(String[] args){
System.out.println("Pride and Prejudice");
ArrayList words = new ArrayList<>();
if(FileOperation.readFile("pride-and-prejudice.txt", words)) {
System.out.println("Total words: " + words.size());
LinkedListMap map = new LinkedListMap<>();
for (String word : words) {
if (map.contains(word))
map.set(word, map.get(word) + 1);
else
map.add(word, 1);
}
System.out.println("Total different words: " + map.getSize());
System.out.println("Frequency of PRIDE: " + map.get("pride"));
System.out.println("Frequency of PREJUDICE: " + map.get("prejudice"));
}
System.out.println();
}
测试结果
三 基于二分搜索树的映射实现
1⃣️ 实现具体的Map类
package com.mufeng.map;
/**
* Created by wb-yxk397023 on 2018/7/5.
*/
public class BSTMap, V> implements Map{
@Override
public void add(K key, V value) {
root = add(root, key, value);
}
@Override
public V remove(K key) {
Node node = getNode(root, key);
if (node != null){
root = remove(root, key);
return node.value;
}
return null;
}
@Override
public boolean contains(K key) {
return getNode(root, key) != null;
}
@Override
public V get(K key) {
Node node = getNode(root, key);
return node == null ? null : node.value;
}
@Override
public void set(K key, V newValue) {
Node node = getNode(root, key);
if (node == null){
throw new IllegalArgumentException(key + " doesn't exist! ");
}
node.value = newValue;
}
@Override
public int getSize() {
return size;
}
@Override
public boolean isEmpty() {
return size == 0;
}
private Node root;
private int size;
public BSTMap(){
root = null;
size = 0;
}
// 返回以node为根的二分搜索树的最小值所在的节点
private Node minimum(Node node){
if(node.left == null)
return node;
return minimum(node.left);
}
// 删除掉以node为根的二分搜索树中的最小节点
// 返回删除节点后新的二分搜索树的根
private Node removeMin(Node node){
if(node.left == null){
Node rightNode = node.right;
node.right = null;
size --;
return rightNode;
}
node.left = removeMin(node.left);
return node;
}
/**
* 删除掉以node为根的二分搜索树中值为key的节点, 递归算法
* 返回删除节点后新的二分搜索树的根
* @param node
* @param key
* @return
*/
private Node remove(Node node, K key){
if( node == null )
return null;
if( key.compareTo(node.key) < 0 ){
node.left = remove(node.left , key);
return node;
}
else if(key.compareTo(node.key) > 0 ){
node.right = remove(node.right, key);
return node;
}
else{ // key.compareTo(node.key) == 0
// 待删除节点左子树为空的情况
if(node.left == null){
Node rightNode = node.right;
node.right = null;
size --;
return rightNode;
}
// 待删除节点右子树为空的情况
if(node.right == null){
Node leftNode = node.left;
node.left = null;
size --;
return leftNode;
}
// 待删除节点左右子树均不为空的情况
// 找到比待删除节点大的最小节点, 即待删除节点右子树的最小节点
// 用这个节点顶替待删除节点的位置
Node successor = minimum(node.right);
successor.right = removeMin(node.right);
successor.left = node.left;
node.left = node.right = null;
return successor;
}
}
/**
* 返回以node为根节点的二分搜索树中，key所在的节点
* @param node
* @param key
* @return
*/
private Node getNode(Node node, K key){
if (node == null){
return null;
}
if (key.compareTo(node.key) == 0){
return node;
}else if (key.compareTo(node.key) < 0){
return getNode(node.left, key);
}else {
return getNode(node.right, key);
}
}
/**
* 向以node为根的二分搜索树中插入元素，递归算法
* 返回插入新节点后二分搜索树的根
* @param node
* @param key
* @param value
* @return
*/
private Node add(Node node, K key, V value){
// 递归的终止条件
if (node == null){
size++;
return new Node(key, value);
}
// 递归调用
if (key.compareTo(node.key) < 0){
node.left = add(node.left, key, value);
}else if (key.compareTo(node.key) > 0){
node.right = add(node.right, key, value);
}else if (key.compareTo(node.key) == 0){
node.value = value;
}
return node;
}
/**
* 内部类
*/
private class Node{
public K key;
public V value;
public Node left, right;
public Node(K key, V value){
this.key = key;
this.value = value;
left = null;
right = null;
}
}
}
2⃣️ 测试
public static void main(String[] args){
System.out.println("Pride and Prejudice");
ArrayList words = new ArrayList<>();
if(FileOperation.readFile("pride-and-prejudice.txt", words)) {
System.out.println("Total words: " + words.size());
BSTMap map = new BSTMap<>();
for (String word : words) {
if (map.contains(word))
map.set(word, map.get(word) + 1);
else
map.add(word, 1);
}
System.out.println("Total different words: " + map.getSize());
System.out.println("Frequency of PRIDE: " + map.get("pride"));
System.out.println("Frequency of PREJUDICE: " + map.get("prejudice"));
}
System.out.println();
}
测试结果
四 两种实现方式的性能对比
1⃣️ 测试类
import java.util.ArrayList;
public class Main {
private static double testMap(Map map, String filename){
long startTime = System.nanoTime();
System.out.println(filename);
ArrayList words = new ArrayList<>();
if(FileOperation.readFile(filename, words)) {
System.out.println("Total words: " + words.size());
for (String word : words){
if(map.contains(word))
map.set(word, map.get(word) + 1);
else
map.add(word, 1);
}
System.out.println("Total different words: " + map.getSize());
System.out.println("Frequency of PRIDE: " + map.get("pride"));
System.out.println("Frequency of PREJUDICE: " + map.get("prejudice"));
}
long endTime = System.nanoTime();
return (endTime - startTime) / 1000000000.0;
}
public static void main(String[] args) {
String filename = "pride-and-prejudice.txt";
BSTMap bstMap = new BSTMap<>();
double time1 = testMap(bstMap, filename);
System.out.println("BST Map: " + time1 + " s");
System.out.println();
LinkedListMap linkedListMap = new LinkedListMap<>();
double time2 = testMap(linkedListMap, filename);
System.out.println("Linked List Map: " + time2 + " s");
}
}
测试结果