HashMap是平时编码使用频繁的类，也是面试会经常问到的东西，源码有非常多的精妙的设计，通过阅读源码分析HashMap是非常有必要的，由于篇幅所限，在此只分析部分重要方法。
HashMap和HashTable非常的相似，除了它是不同步的（非线程安全）并且可以为空值(key ，value)。不过可以通过Collections.synchronizedMap方法使其同步。
下面先用图（来源）来描绘一下HashMap。
HashMap由数组+链表+红黑树构成。HashMap继承AbstractMap并实现Map,Cloneable,Serializable接口。要注意HashMap的实例有两个影响其性能的参数：初始容量和负载因子。
- 负载因子
static final float DEFAULT_LOAD_FACTOR = 0.75f;
- 初始容量
static final int DEFAULT_INITIAL_CAPACITY=16;
为什么要是2的幂？
：HashMap为提高get put效率，减少碰撞。取模算法hash%length ,hashmap将其优化成位运算hash&(length-1)，但hash%length等于hash&(length-1)的前提是length是2的n次幂。
红黑树与链表转化的关键成员变量
static final int TREEIFY_THRESHOLD = 8;
static final int UNTREEIFY_THRESHOLD = 6;
static final int MIN_TREEIFY_CAPACITY = 64;
当这个链表长度大于阈值8并且数组长度大于64则进行将链表变为红黑树。
将链表转换成红黑树前会判断，如果阈值大于8，但是数组长度小64，此时并不会将链表变为红黑树。而是选择进行数组扩容。
以上都是为了提升性能和效率，红黑树为维持平衡本身有一定开销
数组表：
transient Node[] table;
fail-fast 机制变量
transient int modCount;
其余的成员变量：
static final int MAXIMUM_CAPACITY = 1 << 30;
transient int size;
int threshold;
final float loadFactor;
基本的Node节点
static class Node implements Map.Entry{
final int hash;
final K key;
V value;
Node next;
// ...get set
@Override
public V setValue(V newValue) {
V oldValue = value;
value=newValue;
return oldValue;
}
@Override
public final int hashCode() {
return Objects.hashCode(key) ^ Objects.hashCode(value);
}
@Override
public boolean equals(Object obj) {
//如果是同一个对象
if(obj==this){
return true;
}
//否则先判断类型，再比较键和值
if (obj instanceof Map.Entry) {
Map.Entry e = (Map.Entry)obj;
if (Objects.equals(key, e.getKey()) &&
Objects.equals(value, e.getValue()))
return true;
}
return false;
}
}
初始化
这里可以注意到，初始化时并没有创建数组，而是在第一次写入时创建。
public HashMap(int initialCapacity, float loadFactor) {
if (initialCapacity < 0) {
throw new IllegalArgumentException("Illegal initial capacity: " +
initialCapacity);
}
if (initialCapacity > MAXIMUM_CAPACITY) {
initialCapacity = MAXIMUM_CAPACITY;
}
if (loadFactor <= 0 || Float.isNaN(loadFactor)) {
throw new IllegalArgumentException("Illegal load factor: " +
loadFactor);
}
this.loadFactor = loadFactor;
this.threshold = tableSizeFor(initialCapacity);
}
static final int tableSizeFor(int cap) {
int n = cap - 1;
n |= n >>> 1;
n |= n >>> 2;
n |= n >>> 4;
n |= n >>> 8;
n |= n >>> 16;
return (n < 0) ? 1 : (n >= MAXIMUM_CAPACITY) ? MAXIMUM_CAPACITY : n + 1;
}
put操作
public V put(K key, V value) {
return putVal(hash(key), key, value, false, true);
}
final V putVal(int hash, K key, V value, boolean onlyIfAbsent,
boolean evict) {
Node[] tab; Node p; int n, i;
//如果数组初始为空
if ((tab = table) == null || (n = tab.length) == 0)
n = (tab = resize()).length;
//如果要放的位置为空（即未被占用）
if ((p = tab[i = (n - 1) & hash]) == null)
tab[i] = newNode(hash, key, value, null);
else {
Node e; K k;
//如果要要放的位置有元素了
//如果要放的元素的key等于原有的元素的key
if (p.hash == hash &&
((k = p.key) == key || (key != null && key.equals(k))))
e = p;
//如果是红黑树，按照红黑树的方式放
else if (p instanceof TreeNode)
e = ((TreeNode)p).putTreeval(this, tab, hash, key, value);
else {
//还是list,按照list的方式放,循环查找
for (int binCount = 0; ; ++binCount) {
if ((e = p.next) == null) {
p.next = newNode(hash, key, value, null);
//如果到了临界值，转为红黑树
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;
}
}
// 新key和旧key相同，直接覆盖
if (e != null) { // existing mapping for key
V oldValue = e.value;
if (!onlyIfAbsent || oldValue == null)
e.value = value;
afterNodeAccess(e);
return oldValue;
}
}
//帮助fail-fast的参数
++modCount;
//判断大小，扩容
if (++size > threshold)
resize();
afterNodeInsertion(evict);
return null;
}
读取
public V get(Object key) {
Node e;
return (e = getNode(hash(key), key)) == null ? null : e.value;
}
final Node getNode(int hash, Object key) {
Node[] tab; Node first, e; int n; K k;
//判空
if ((tab = table) != null && (n = tab.length) > 0 &&
(first = tab[(n - 1) & hash]) != null) {
//检查第一个的key
if (first.hash == hash && // always check first node
((k = first.key) == key || (key != null && key.equals(k))))
return first;
if ((e = first.next) != null) {
//如果是树
if (first instanceof TreeNode)
return ((TreeNode)first).getTreeNode(hash, key);
//如果是list
do {
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k))))
return e;
} while ((e = e.next) != null);
}
}
return null;
}
扩容
final Node[] resize() {
Node[] oldTab = table;
//旧的容量
int oldCap = (oldTab == null) ? 0 : oldTab.length;
//旧的阀值
int oldThr = threshold;
int newCap, newThr = 0;
//判断初始
if (oldCap > 0) {
//判断初始大小，如果大于等于最大默认容量则把阀值变为Integer的最大值，暂时不扩容
if (oldCap >= MAXIMUM_CAPACITY) {
threshold = Integer.MAX_VALUE;
return oldTab;
}
//否则，扩容变为原来容量的两倍
else if ((newCap = oldCap << 1) < MAXIMUM_CAPACITY &&
oldCap >= DEFAULT_INITIAL_CAPACITY)
newThr = oldThr << 1; // double threshold
}
//旧容量<=0，阀值大于0
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;
//创建新数组
@SuppressWarnings({"rawtypes","unchecked"})
Node[] newTab = (Node[])new Node[newCap];
table = newTab;
if (oldTab != null) {
//for循环，对所有元素Hash
for (int j = 0; j < oldCap; ++j) {
Node e;
if ((e = oldTab[j]) != null) {
oldTab[j] = null;
if (e.next == null)
newTab[e.hash & (newCap - 1)] = e;
//如果是树
else if (e instanceof TreeNode)
((TreeNode)e).split(this, newTab, j, oldCap);
else { // preserve order
Node loHead = null, loTail = null;
Node hiHead = null, hiTail = null;
Node 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;
}
