一、基本概念
HashMap基于哈希表的 Map 接口的实现。此实现提供所有可选的映射操作，并允许使用 null 值和 null 键。以前JDK中HashMap采用的是位桶+链表的方式，即我们常说的散列链表的方式，而JDK1.8中采用的是位桶+链表/红黑树的方式，也是非线程安全的。当某个位桶的链表的长度达到某个阀值的时候，这个链表就将转换成红黑树。
注意事项：
- 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；
- 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”；
二、源码分析
1：常量
/**
map的最大容量
*/
static final int MAXIMUM_CAPACITY = 1 << 30;
/**
* 默认加载因子
*/
static final float DEFAULT_LOAD_FACTOR = 0.75f;
/**
将list链表转为红黑数阀值，即list的size超过时转化
*/
static final int TREEIFY_THRESHOLD = 8;
/**
resize操作中，决定是否untreeify的阈值
*/
static final int UNTREEIFY_THRESHOLD = 6;
/**
决定是否转换成tree的最小容量
*/
static final int MIN_TREEIFY_CAPACITY = 64;
2：主要字段
/**
存储元素的数组
*/
transient Node<K,V>[] table;
/**
用于map迭代遍历
*/
transient Set<Map.Entry<K,V>> entrySet;
/**
元素个数
*/
transient int size;
/**
修改次数
*/
transient int modCount;
/**
阀值，用于扩容阀值
＊／
int threshold;
/**
加载因子
*/
final float loadFactor;
3：主要方法
get方法：
public V get(Object key) {
Node<K,V> e;
return (e = getNode(hash(key), key)) == null ? null : e.value;
}
/**
* Implements Map.get and related methods
*
* @param hash hash for key
* @param key the key
* @return the node, or null if none
*/
final Node<K,V> getNode(int hash, Object key) {
Node<K,V>[] tab; Node<K,V> first, e; int n; K k;
if ((tab = table) != null && (n = tab.length) > 0 &&
(first = tab[(n - 1) & hash]) != null) {
if (first.hash == hash && // 总是判断第一个元素是否满足条件
((k = first.key) == key || (key != null && key.equals(k))))
return first;
if ((e = first.next) != null) {
//第一个节点为TreeNode,则调用TreeNode.getTreeNode()方法遍历红黑数进行查询
if (first instanceof TreeNode)
return ((TreeNode<K,V>)first).getTreeNode(hash, key);
do {
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k))))
return e;
} while ((e = e.next) != null);
}
}
return null;
}
put方法
public V put(K key, V value) {
return putVal(hash(key), key, value, false, true);
}
/**
* Implements Map.put and related methods
*
* @param hash hash for key
* @param key the key
* @param value the value to put
* @param onlyIfAbsent if true, don't change existing value
* @param evict if false, the table is in creation mode.
* @return previous value, or null if none
*/
final V putVal(int hash, K key, V value, boolean onlyIfAbsent,
boolean evict) {
Node<K,V>[] tab; Node<K,V> p; int n, i;
if ((tab = table) == null || (n = tab.length) == 0)
//table为空，n为table的长度
n = (tab = resize()).length;
//i位置为空，直接存储
if ((p = tab[i = (n - 1) & hash]) == null)
tab[i] = newNode(hash, key, value, null);
else {
// 若i位置上的值不为空，判断当前位置上的Node p 是否与要插入的key的hash和key相同
Node<K,V> e; K k;
if (p.hash == hash &&
((k = p.key) == key || (key != null && key.equals(k))))
//相同key时直接覆盖
e = p;
else if (p instanceof TreeNode)
//不相同时，若当前p已经为TreeNode,则插入该树上
e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value);
else {
//在i位置上的链表中找到p.next为null的位置，binCount计算出当前链表的长度，如果继续将冲突的节点插入到该链表中，会使链表的长度大于tree化的阈值，则将链表转换成tree。
for (int binCount = 0; ; ++binCount) {
if ((e = p.next) == null) {
p.next = newNode(hash, key, value, null);
if (binCount >= TREEIFY_THRESHOLD - 1) // -1 for 1st
treeifyBin(tab, hash);
break;
}
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k))))
break;
p = e;
}
}
if (e != null) { // existing mapping for key
V oldValue = e.value;
if (!onlyIfAbsent || oldValue == null)
e.value = value;
afterNodeAccess(e);
return oldValue;
}
}
++modCount;
if (++size > threshold)
resize();
afterNodeInsertion(evict);
return null;
}
resize(),由于解决冲突的方法可能是list，也可能是红黑数，所以resize()较为复杂点。
/**
* Initializes or doubles table size. If null, allocates in
* accord with initial capacity target held in field threshold.
* Otherwise, because we are using power-of-two expansion, the
* elements from each bin must either stay at same index, or move
* with a power of two offset in the new table.
*
* @return the table
*/
final Node<K,V>[] resize() {
Node<K,V>[] oldTab = table;
int oldCap = (oldTab == null) ? 0 : oldTab.length;
int oldThr = threshold;
int newCap, newThr = 0;
if (oldCap > 0) {
//若超过最大容量，则不能扩容
if (oldCap >= MAXIMUM_CAPACITY) {
threshold = Integer.MAX_VALUE;
return oldTab;
}
else if ((newCap = oldCap << 1) < MAXIMUM_CAPACITY &&
oldCap >= DEFAULT_INITIAL_CAPACITY)
newThr = oldThr << 1; //阀值扩大2倍
}
else if (oldThr > 0) // initial capacity was placed in threshold
newCap = oldThr;
else { // zero initial threshold signifies using defaults
newCap = DEFAULT_INITIAL_CAPACITY;
newThr = (int)(DEFAULT_LOAD_FACTOR * DEFAULT_INITIAL_CAPACITY);
}
if (newThr == 0) {
float ft = (float)newCap * loadFactor;
newThr = (newCap < MAXIMUM_CAPACITY && ft < (float)MAXIMUM_CAPACITY ?
(int)ft : Integer.MAX_VALUE);
}
threshold = newThr;
@SuppressWarnings({"rawtypes","unchecked"})
// 创建容量为newCap的newTab，并将oldTab中的Node迁移过来，这里需要考虑链表和tree两种情况。
Node<K,V>[] newTab = (Node<K,V>[])new Node[newCap];
table = newTab;
if (oldTab != null) {
for (int j = 0; j < oldCap; ++j) {
Node<K,V> e;
if ((e = oldTab[j]) != null) {
oldTab[j] = null;
if (e.next == null)
newTab[e.hash & (newCap - 1)] = e;
else if (e instanceof TreeNode)
// split方法会将树分割为lower 和upper tree两个树，如果子树的节点数小于了UNTREEIFY_THRESHOLD阈值，则将树untreeify，将节点都存放在newTab中。
((TreeNode<K,V>)e).split(this, newTab, j, oldCap);
else { // preserve order
Node<K,V> loHead = null, loTail = null;
Node<K,V> hiHead = null, hiTail = null;
Node<K,V> next;
do {
next = e.next;
if ((e.hash & oldCap) == 0) {
if (loTail == null)
loHead = e;
else
loTail.next = e;
loTail = e;
}
else {
if (hiTail == null)
hiHead = e;
else
hiTail.next = e;
hiTail = e;
}
} while ((e = next) != null);
if (loTail != null) {
loTail.next = null;
newTab[j] = loHead;
}
if (hiTail != null) {
hiTail.next = null;
newTab[j + oldCap] = hiHead;
}
}
}
}
}
return newTab;
}
remove（）方法
public V remove(Object key) {
Node<K,V> e;
return (e = removeNode(hash(key), key, null, false, true)) == null ?
null : e.value;
}
/**
* Implements Map.remove and related methods
*
* @param hash hash for key
* @param key the key
* @param value the value to match if matchValue, else ignored
* @param matchValue if true only remove if value is equal
* @param movable if false do not move other nodes while removing
* @return the node, or null if none
*/
final Node<K,V> removeNode(int hash, Object key, Object value,
boolean matchValue, boolean movable) {
Node<K,V>[] tab; Node<K,V> p; int n, index;
if ((tab = table) != null && (n = tab.length) > 0 &&
(p = tab[index = (n - 1) & hash]) != null) {
Node<K,V> node = null, e; K k; V v;
if (p.hash == hash &&
((k = p.key) == key || (key != null && key.equals(k))))
node = p;
//若是用红黑数解决冲突则getTreeNode方法查找到节点
else if ((e = p.next) != null) {
if (p instanceof TreeNode)
node = ((TreeNode<K,V>)p).getTreeNode(hash, key);
else {
do {
if (e.hash == hash &&
((k = e.key) == key ||
(key != null && key.equals(k)))) {
node = e;
break;
}
p = e;
} while ((e = e.next) != null);
}
}
if (node != null && (!matchValue || (v = node.value) == value ||
(value != null && value.equals(v)))) {
if (node instanceof TreeNode)
((TreeNode<K,V>)node).removeTreeNode(this, tab, movable);
else if (node == p)
tab[index] = node.next;
else
p.next = node.next;
++modCount;
--size;
afterNodeRemoval(node);
return node;
}
}
return null;
}
HashMap实例
1：Hashmap的遍历方法
package com.csu.collection;
import java.util.HashMap;
import java.util.Iterator;
import java.util.Map.Entry;
import java.util.Set;
public class HashMapTest {
public static void main(String[]args)
{
HashMap<Integer, Integer> map=new HashMap<>();
for(int i=0;i<10000000;i++)
{
map.put(i, i);
}
System.out.println("第一种遍历方法：for each map.entrySet()");
long startTime1=System.currentTimeMillis();
for(Entry<Integer, Integer> entry:map.entrySet())
{
entry.getValue();
entry.getKey();
}
long endTime1=System.currentTimeMillis();
System.out.println("第一种遍历方法用时："+(endTime1-startTime1)+"ms");
System.out.println("第2种遍历方法：map.entrySet()的集合迭代器");
long startTime2=System.currentTimeMillis();
Iterator<Entry<Integer, Integer>> iterator=map.entrySet().iterator();
while(iterator.hasNext())
{
HashMap.Entry<Integer, Integer> entry=(Entry<Integer, Integer>) iterator.next();
entry.getValue();
entry.getKey();
}
long endTime2=System.currentTimeMillis();
System.out.println("第2种遍历方法用时："+(endTime2-startTime2)+"ms");
System.out.println("第3种遍历方法： for each map.keySet()，再调用get获取");
long startTime3=System.currentTimeMillis();
for (Integer key : map.keySet()) {
map.get(key);
}
long endTime3=System.currentTimeMillis();
System.out.println("第3种遍历方法用时："+(endTime3-startTime3)+"ms");
System.out.println("第4种遍历方法：for each map.entrySet()，用临时变量保存map.entrySet()");
long startTime4=System.currentTimeMillis();
Set<Entry<Integer, Integer>> entrySet = map.entrySet();
for (Entry<Integer, Integer> entry : entrySet) {
entry.getKey();
entry.getValue();
}
long endTime4=System.currentTimeMillis();
System.out.println("第4种遍历方法用时："+(endTime4-startTime4)+"ms");
}
}
运行结果
第一种遍历方法：for each map.entrySet()
第一种遍历方法用时：71ms
第2种遍历方法：map.entrySet()的集合迭代器
第2种遍历方法用时：83ms
第3种遍历方法： for each map.keySet()，再调用get获取
第3种遍历方法用时：117ms
第4种遍历方法：for each map.entrySet()，用临时变量保存map.entrySet()
第4种遍历方法用时：84ms
总结：
- a. HashMap的循环，如果既需要key也需要value，直接用for each map.entrySet()；
- 如果只是遍历key而无需value的话，可以直接用for each map.keySet()，再调用get获取。
2：使用Hashmap 实现缓存
public class Student {
private String name;
private String address;
public Student(String name,String address)
{
this.address=address;
this.name=name;
}
public String getName() {
return name;
}
public void setName(String name) {
this.name = name;
}
public String getAddress() {
return address;
}
public void setAddress(String address) {
this.address = address;
}
}
import java.io.Serializable;
public class CacheEntity implements Serializable {
/**
*
*/
private static final long serialVersionUID = 1L;
private final int DEFUALT_TIME=200;//秒
private String key;
private Object value;
private int time;//缓存存活时间，不设置则使用默认值
private long timeoutStamp;// 缓存过期时间戳
@SuppressWarnings("unused")
private CacheEntity()
{
this.timeoutStamp=System.currentTimeMillis()+DEFUALT_TIME*1000;
this.time=DEFUALT_TIME;
}
public CacheEntity(String key,Object value)
{
this.key=key;
this.value=value;
}
public CacheEntity(String key,Object value,long timestamp)
{
this(key,value);
this.timeoutStamp=timestamp;
}
public CacheEntity(String key,Object value,int time)
{
this(key,value);
this.time=time;
this.timeoutStamp=System.currentTimeMillis()+DEFUALT_TIME*1000;
}
public String getKey() {
return key;
}
public void setKey(String key) {
this.key = key;
}
public Object getValue() {
return value;
}
public void setValue(Object value) {
this.value = value;
}
public int getTime() {
return time;
}
public void setTime(int time) {
this.time = time;
}
public long getTimeoutStamp() {
return timeoutStamp;
}
public void setTimeoutStamp(long timeoutStamp) {
this.timeoutStamp = timeoutStamp;
}
}
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
/**
*
* 采用队列，定时循环清理过期缓存
*
*/
public class CacheByHashMap {
private static HashMap<String, CacheEntity> map;
private static List<CacheEntity> tempList;
static{
tempList=new ArrayList<CacheEntity>();
map=new HashMap<String,CacheEntity>(1<<10);
new Thread(new RemoveTimeOutCacheThread()).start();
}
/**
* 添加缓存
* @param key
* @param value
* @param time
*/
public static synchronized void addCache(String key,CacheEntity value,int time)
{
value.setTimeoutStamp(System.currentTimeMillis()+time*1000);
map.put(key, value);
tempList.add(value);
}
/**
* 获取缓存对象
* @param key
* @return
*/
public static synchronized CacheEntity getCache(String key)
{
return map.get(key);
}
/**
* 检查是否包含特定的key
* @param key
* @return
*/
public static synchronized boolean isContainsKey(String key)
{
return map.containsKey(key);
}
/**
* 删除缓存
* @param key
*/
public static synchronized void removeCache(String key)
{
map.remove(key);
}
/**
* 获取缓存数量
* @return
*/
public static int getCacheSize()
{
return map.size();
}
/**
* 清除所有缓存
*/
public static synchronized void clearCache()
{
tempList.clear();
map.clear();
System.out.println("所有缓存被清理");
}
static class RemoveTimeOutCacheThread implements Runnable{
@Override
public void run() {
// TODO Auto-generated method stub
while(true)
{
try {
checkTime();
} catch (Exception e) {
// TODO: handle exception
e.printStackTrace();
}
}
}
private void checkTime() throws InterruptedException
{
CacheEntity value=null;
long timeoutTime=1000l;
if(tempList.size()<1)
{
System.out.println("过期队列为空！");
timeoutTime=1000l;
Thread.sleep(timeoutTime);
return ;
}
value=tempList.get(0);
timeoutTime=value.getTimeoutStamp()-System.currentTimeMillis();
if(timeoutTime>0)
{
Thread.sleep(timeoutTime);
return ;
}
System.out.println("清除过期缓存"+value.getKey());
tempList.remove(value);
removeCache(value.getKey());
}
}
}
测试端代码：
public class CacheTest {
public static void main(String[] args) {
// TODO Auto-generated method stub
Student student1=new Student("zhangsan", "shangsha");
Student student2=new Student("wangqiang", "beijing");
Student student3=new Student("zhangsi", "shanghai");
Student student4=new Student("zhangwu", "wuhan");
Student student5=new Student("zhangqi", "zhengzhou");
Student student6=new Student("zhangba", "shangsha");
CacheEntity cacheEntity1=new CacheEntity("1", student1, 30);
CacheEntity cacheEntity2=new CacheEntity("2", student2, 30);
CacheEntity cacheEntity3=new CacheEntity("3", student3, 30);
CacheEntity cacheEntity4=new CacheEntity("4", student4, 30);
CacheEntity cacheEntity5=new CacheEntity("5", student5, 30);
CacheEntity cacheEntity6=new CacheEntity("6", student6, 30);
//添加缓存
CacheByHashMap.addCache(cacheEntity1.getKey(), cacheEntity1, cacheEntity1.getTime());
CacheByHashMap.addCache(cacheEntity2.getKey(), cacheEntity2, cacheEntity2.getTime());
CacheByHashMap.addCache(cacheEntity3.getKey(), cacheEntity3, cacheEntity3.getTime());
CacheByHashMap.addCache(cacheEntity4.getKey(), cacheEntity4, cacheEntity4.getTime());
CacheByHashMap.addCache(cacheEntity5.getKey(), cacheEntity5, cacheEntity5.getTime());
CacheByHashMap.addCache(cacheEntity6.getKey(), cacheEntity6, cacheEntity6.getTime());
if(CacheByHashMap.isContainsKey("2"))
{
System.out.println(" 该对象已有缓存");
//这里就可以获取缓存如get()
}
else {
CacheByHashMap.addCache(cacheEntity2.getKey(), cacheEntity2, cacheEntity2.getTime());
//这里可以模拟从数据库获取数据，添加到缓存
}
｝
}
运行结果：
该对象已有缓存
清除过期缓存1
清除过期缓存2
清除过期缓存3
清除过期缓存4
清除过期缓存5
清除过期缓存6
过期队列为空！
过期队列为空！