映射
映射
存储(键，值)数据对的数据结构（key，value）
根据键（key），寻找值（value）
可以使用链表或者二分搜索树实现
使用链表实现映射
定义Map的接口：
void add(K key, V value);
V remove(K key);
boolean contains(K key);
V get(K key);
void set(K key, V newValue);
int getSize();
boolean isEmpty();
LinkedListMap.java
public class LinkedListMap implements Map {
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, V value){
this(key, value, null);
}
public Node(){
this(null, null, null);
}
@Override
public String toString(){
return key.toString() + " : " + value.toString();
}
}
private Node dummyHead;
private int size;
public LinkedListMap(){
dummyHead = new Node();
size = 0;
}
@Override
public int getSize(){
return size;
}
@Override
public boolean isEmpty(){
return 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 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 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 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 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;
}
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();
}
} fileOperation.java
public class FileOperation {
// 读取文件名称为filename中的内容，并将其中包含的所有词语放进words中
public static boolean readFile(String filename, ArrayList words){
if (filename == null || words == null){
System.out.println("filename is null or words is null");
return false;
}
// 文件读取
Scanner scanner;
try {
File file = new File(filename);
if(file.exists()){
FileInputStream fis = new FileInputStream(file);
scanner = new Scanner(new BufferedInputStream(fis), "UTF-8");
scanner.useLocale(Locale.ENGLISH);
}
else
return false;
}
catch(IOException ioe){
System.out.println("Cannot open " + filename);
return false;
}
// 简单分词
// 这个分词方式相对简陋, 没有考虑很多文本处理中的特殊问题
// 在这里只做demo展示用
if (scanner.hasNextLine()) {
String contents = scanner.useDelimiter("\\A").next();
int start = firstCharacterIndex(contents, 0);
for (int i = start + 1; i <= contents.length(); )
if (i == contents.length() || !Character.isLetter(contents.charAt(i))) {
String word = contents.substring(start, i).toLowerCase();
words.add(word);
start = firstCharacterIndex(contents, i);
i = start + 1;
} else
i++;
}
return true;
}
// 寻找字符串s中，从start的位置开始的第一个字母字符的位置
private static int firstCharacterIndex(String s, int start){
for( int i = start ; i < s.length() ; i ++ )
if( Character.isLetter(s.charAt(i)) )
return i;
return s.length();
}
} 使用二分搜索树实现Map
BSTMap.java
public class BSTMap, V> implements Map {
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;
}
}
private Node root;
private int size;
public BSTMap(){
root = null;
size = 0;
}
@Override
public int getSize(){
return size;
}
@Override
public boolean isEmpty(){
return size == 0;
}
// 向二分搜索树中添加新的元素(key, value)
@Override
public void add(K key, V value){
root = add(root, key, value);
}
// 向以node为根的二分搜索树中插入元素(key, value)，递归算法
// 返回插入新节点后二分搜索树的根
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 // key.compareTo(node.key) == 0
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.equals(node.key))
return node;
else if(key.compareTo(node.key) < 0)
return getNode(node.left, key);
else // if(key.compareTo(node.key) > 0)
return getNode(node.right, key);
}
@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;
}
// 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;
}
// 从二分搜索树中删除键为key的节点
@Override
public V remove(K key){
Node node = getNode(root, key);
if(node != null){
root = remove(root, key);
return node.value;
}
return null;
}
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;
}
}
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();
}
} 使用链表和二分搜索树实现map性能分析
测试代码：
Main.java
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");
}
} 使用LinkedListMap
增 add O(n)
删 remove O(n)
改 set O(n)
查 get O(n)
查 contains O(n)
BSTMap
增 add O(h)
删 remove O(h)
改 set O(h)
查 get O(h)
查 contains O(h)