HashMap简介
HashMap 是一个散列表，它存储的内容是键值对(key-value)映射。
HashMap 继承于AbstractMap，实现了Map、Cloneable、java.io.Serializable接口。
HashMap 的实现不是同步的，这意味着它不是线程安全的。它的key、value都可以为null。此外，HashMap中的映射不是有序的。
HashMap 的实例有两个参数影响其性能：“初始容量” 和 “加载因子”。容量 是哈希表中桶的数量，初始容量 只是哈希表在创建时的容量。加载因子 是哈希表在其容量自动增加之前可以达到多满的一种尺度。当哈希表中的条目数超出了加载因子与当前容量的乘积时，则要对该哈希表进行 rehash 操作（即重建内部数据结构），从而哈希表将具有大约两倍的桶数。
通常，默认加载因子是 0.75, 这是在时间和空间成本上寻求一种折衷。加载因子过高虽然减少了空间开销，但同时也增加了查询成本（在大多数 HashMap 类的操作中，包括 get 和 put 操作，都反映了这一点）。在设置初始容量时应该考虑到映射中所需的条目数及其加载因子，以便最大限度地减少 rehash 操作次数。如果初始容量大于最大条目数除以加载因子，则不会发生 rehash 操作。
简单版，只实现put和get:
public class MyHashMap<K, V> {
private static int default_length = 16;
private MyEntry<K, V>[] entries;
public MyHashMap() {
super();
entries = new MyEntry[default_length];
}
public V put(K key, V value) {
int index = key.hashCode() % default_length;// hascode值除map大小取余
MyEntry<K, V> prevoius = entries[index];
for (MyEntry<K, V> entry = entries[index]; entry != null; entry = entry.next) {
if (entry.getKey().equals(key)) {
V oldValue = (V) entry.getValue();
entry.setValue(value);
return oldValue;
}
}
MyEntry<K, V> entry = new MyEntry<>(key, value);
entry.next = prevoius;
entries[index] = entry;
return null;
}
public K get(K key){
int index= key.hashCode()%default_length;
for (MyEntry<K,V> entry= entries[index];entry!=null;entry=entry.next){
if(entry.getKey().equals(key)){
return (K)entry.getValue();
}
}
return null;
}
private final class MyEntry<K, V> {
private K key;
private V value;
private MyEntry next;
public MyEntry() {
super();
}
public MyEntry(K key, V value) {
super();
this.key = key;
this.value = value;
}
public MyEntry(K key, V value, MyEntry next) {
super();
this.key = key;
this.value = value;
this.next = next;
}
public K getKey() {
return key;
}
public void setKey(K key) {
this.key = key;
}
public V getValue() {
return value;
}
public void setValue(V value) {
this.value = value;
}
public MyEntry getNext() {
return next;
}
public void setNext(MyEntry next) {
this.next = next;
}
}
}
复杂版：
public class MyHashMap {
//默认初始化大小 16
private static final int DEFAULT_INITIAL_CAPACITY = 16;
//默认负载因子 0.75
private static final float DEFAULT_LOAD_FACTOR = 0.75f;
//临界值
private int threshold;
//元素个数
private int size;
//扩容次数
private int resize;
private MyEntry[] table;
public MyHashMap() {
table = new MyEntry[DEFAULT_INITIAL_CAPACITY];
threshold = (int) (DEFAULT_INITIAL_CAPACITY * DEFAULT_LOAD_FACTOR);
size = 0;
}
private int index(Object key) {
//根据key的hashcode和entry长度取模计算key在entry中的位置
return key.hashCode() % table.length;
}
public void put(Object key, Object value) {
//key为null时需要特殊处理，为简化实现忽略null值
if (key == null) return;
int index = index(key);
//遍历index位置的entry，若找到重复key则更新对应entry的值，然后返回
MyEntry entry = table[index];
while (entry != null) {
if (entry.getKey().hashCode() == key.hashCode() && (entry.getKey() == key || entry.getKey().equals(key))) {
entry.setValue(value);
return;
}
entry = entry.getNext();
}
//若index位置没有entry或者未找到重复的key，则将新key添加到table的index位置
add(index, key, value);
}
private void add(int index, Object key, Object value) {
//将新的entry放到table的index位置第一个，若原来有值则以链表形式存放
MyEntry entry = new MyEntry(key, value, table[index]);
table[index] = entry;
//判断size是否达到临界值，若已达到则进行扩容，将table的capacicy翻倍
if (size++ >= threshold) {
resize(table.length * 2);
}
}
private void resize(int capacity) {
if (capacity <= table.length) return;
MyEntry[] newTable = new MyEntry[capacity];
//遍历原table，将每个entry都重新计算hash放入newTable中
for (int i = 0; i < table.length; i++) {
MyEntry old = table[i];
while (old!=null){
MyEntry next = old.getNext();
int index = index(old.getKey());
old.setNext(newTable[index]);
newTable[index] = old;
old=next;
}
}
//用newTable替table
table = newTable;
//修改临界值
threshold = (int) (table.length * DEFAULT_LOAD_FACTOR);
resize++;
}
public Object get(Object key){
//这里简化处理，忽略null值
if (key == null) return null;
MyEntry entry= getEntry(key);
return entry == null ? null : entry.getValue();
}
public MyEntry getEntry(Object key){
MyEntry entry =table[index(key)];
while (entry!=null){
if (entry.getKey().hashCode()==key.hashCode()&&(entry.getKey()==key||entry.getKey().equals(key))){
return entry;
}
entry = entry.getNext();
}
return entry;
}
public void remove(Object key) {
if (key == null) return;
int index = index(key);
MyEntry pre = null;
MyEntry entry = table[index];
while (entry != null) {
if (entry.getKey().hashCode() == key.hashCode() && (entry.getKey() == key || entry.getKey().equals(key))) {
if (pre == null) table[index] = entry.getNext();
else pre.setNext(entry.getNext());
//如果成功找到并删除，修改size
size--;
return;
}
pre = entry;
entry = entry.getNext();
}
}
public boolean containsKey(Object key) {
if (key == null) return false;
return getEntry(key) != null;
}
public int size() {
return this.size;
}
public void clear() {
for (int i = 0; i < table.length; i++) {
table[i] = null;
}
this.size = 0;
}
@Override
public String toString() {
StringBuilder sb = new StringBuilder();
sb.append(String.format("size:%s capacity:%s resize:%s\n\n", size, table.length, resize));
for (MyEntry entry : table) {
while (entry != null) {
sb.append(entry.getKey() + ":" + entry.getValue() + "\n");
entry = entry.getNext();
}
}
return sb.toString();
}
}
final class MyEntry {
private Object key;
private Object value;
private MyEntry next;
public MyEntry(Object key, Object value, MyEntry next) {
this.key = key;
this.value = value;
this.next = next;
}
public Object getKey() {
return key;
}
public void setKey(Object key) {
this.key = key;
}
public Object getValue() {
return value;
}
public void setValue(Object value) {
this.value = value;
}
public MyEntry getNext() {
return next;
}
public void setNext(MyEntry next) {
this.next = next;
}
}
网友评论