08-映射 Map
学习资源：慕课网liyubobobo老师的《玩儿转数据结构》
1、映射 map简介
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存储(键，值)数据对的数据结构(Key, Value)
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键与值一一对应
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键不能重复
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重复添加同一个key，新的value会覆盖原先的value
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可以根据键(Key) ，寻找值(Value)
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非常容易使用链表或者二分搜索树实现
// 链表的节点 class Node { K key; V value Node next; } // 二分搜索树的节点 class Node { K key; V value Node Left; Node right ; }
2、map的接口
public interface Map<K, V> {
void add(K key, V value);
V remove(K key);
boolean ifContains(K key);
V get(K key);
void set(K key, V newValue);
int getSize();
boolean isEmpty();
}
3、映射的实现
3.1、基于二分搜索树
public class BSTMap<K extends Comparable<K>, V> implements Map<K, V> {
private class Node {
public K key;
public V value;
public Node left;
public Node right ;
public Node(K key, V value) {
this.key = key;
this.value = value;
this.left = null;
this.right = null;
}
}
private Node root;
private int size;
public BSTMap() {
this.root = null;
this.size = 0;
}
@Override
public void add(K key, V value) {
root = add(root, key, value);
}
private Node add(Node node, K key, V value){
if(node == null){
size++;
return new Node(key, value);
}
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 {
node.value = value;
}
return node;
}
//返回以node为根节点的二分搜索树中，key所在的节点
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);
}
}
@Override
public V remove(K key) {
Node node = getNode(root, key);
if(node == null){
return null;
}
root = remove(root, key);
return node.value;
}
//删除掉以node为根的二分搜索树中键为key的节点，递归算法
//返回删除节点后新的二分搜索树的根
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 {
if(node.left == null){
Node rightNode = node.right;
node.right = null;
size--;
return rightNode;
}
if(node.right == null){
Node leftNode = node.left;
node.left = null;
size--;
return leftNode;
}
Node successor = minimum(node.right);
successor.right = removeMin(node.right);
successor.left = node.left;
node.left = node.right = null;
return successor;
}
}
private Node minimum(Node node){
if(node.left == null){
return node;
}
return minimum(node.left);
}
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;
}
@Override
public boolean ifContains(K key) {
return getNode(root, key) != null;
}
@Override
public V get(K key) {
return getNode(root, key).value;
}
@Override
public void set(K key, V newValue) {
Node node = getNode(root, key);
if(node == null){
throw new IllegalArgumentException(key + "不存在");
}
node.value = newValue;
}
@Override
public int getSize() {
return size;
}
@Override
public boolean isEmpty() {
return size == 0;
}
}
3.2、基于链表
package map;
import linkedList.LinkedList;
public class LinkedListMap<K, V> implements Map<K, V> {
private class Node{
public K key;
public V value;
public 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();
}
}
private int size;
private Node dummyHead;
public LinkedListMap() {
dummyHead = new Node();
size = 0;
}
private Node getNode(K key){
Node cur = dummyHead.next;
while(cur != null){
if(cur.key.equals(key)){
return cur;
}
cur = cur.next;
}
return null;
}
@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 ifContains(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("map 中没有这个key");
}
else {
node.value = newValue;
}
}
@Override
public int getSize() {
return size;
}
@Override
public boolean isEmpty() {
return size == 0;
}
}
4、测试
统计文本的词汇量，测试显示BSTMap速度远快于LinkedListMap
public void test_2{
ArrayList<String> words = new ArrayList<>();
if(FileOperation.readFile("pride-and-prejudice.txt", words)){
System.out.println("单词数：" + words.size());
LinkedListMap<String, Integer> linkedListMap = new LinkedListMap<>();
for(String word : words){
if(!linkedListMap.contains(word)){
linkedListMap.add(word, 1);
}else {
linkedListMap.set(word, linkedListMap.get(word)+1);
}
}
System.out.println("词汇量"+linkedListMap.getSize());
}
public void test_2{
ArrayList<String> words = new ArrayList<>();
if(FileOperation.readFile("pride-and-prejudice.txt", words)){
System.out.println("单词数：" + words.size());
BSTMap<String, Integer> bstMap = new BSTMap<>();
for(String word : words){
if(!bstMap.contains(word)){
bstMap.add(word, 1);
}else {
bstMap.set(word, bstMap.get(word)+1);
}
}
System.out.println("词汇量"+bstMap.getSize());
}
}
5、Java中的Map
TreeMap
底层基于二分搜索树
public class TreeMap<K,V>
extends AbstractMap<K,V>
implements NavigableMap<K,V>, Cloneable, java.io.Serializable
{
}
API接口
HashMap
底层基于哈希表
public class HashMap<K,V> extends AbstractMap<K,V>
implements Map<K,V>, Cloneable, Serializable
{
}
API接口
