本源码为JDK8版本
HashMap的源码较简单，这里主要从源码解析下一些基本操作的原理。
静态常量
首先给出几个基本常量的值
/**
* The default initial capacity - MUST be a power of two
* 默认初始化容量为16（注意容量必须是2的次方）
*/
static final int DEFAULT_INITIAL_CAPACITY = 1 << 4; // aka 16
/**
* The maximum capacity, used if a higher value is implicitly specified
* by either of the constructors with arguments.
* MUST be a power of two <= 1<<30.
* 最大容量为2的30次方，指定容量大于此容量时，会等效于最大容量。
*/
static final int MAXIMUM_CAPACITY = 1 << 30;
/**
* The load factor used when none specified in constructor.
* 默认的装载因子，当size > loadFactor * capacity时会进行扩容
*/
static final float DEFAULT_LOAD_FACTOR = 0.75f;
/**
* The bin count threshold for using a tree rather than list for a
* bin. Bins are converted to trees when adding an element to a
* bin with at least this many nodes. The value must be greater
* than 2 and should be at least 8 to mesh with assumptions in
* tree removal about conversion back to plain bins upon
* shrinkage.
* 当链表的长度>=8，即转为红黑树
*/
static final int TREEIFY_THRESHOLD = 8;
/**
* The bin count threshold for untreeifying a (split) bin during a
* resize operation. Should be less than TREEIFY_THRESHOLD, and at
* most 6 to mesh with shrinkage detection under removal.
* resize时将红黑树转为链表的threshold
*/
static final int UNTREEIFY_THRESHOLD = 6;
/**
* The smallest table capacity for which bins may be treeified.
* (Otherwise the table is resized if too many nodes in a bin.)
* Should be at least 4 * TREEIFY_THRESHOLD to avoid conflicts
* between resizing and treeification thresholds.
* 链表转换为红黑树的最小容量（否则链表长度>=threshold时会直接resize）
*/
static final int MIN_TREEIFY_CAPACITY = 64;
基本节点类型
static class Node<K,V> implements Map.Entry<K,V> {
final int hash;//节点hash值
final K key;
V value;
Node<K,V> next;//next指针
Node(int hash, K key, V value, Node<K,V> next) {
this.hash = hash;
this.key = key;
this.value = value;
this.next = next;
}
//省略
}
计算hash值
static final int hash(Object key) {
int h;
return (key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 16);
}
key.hashCode()即为key值原本的hash值，HashMap的hash方法是保持hash code的高16位不变，高16位与低16位做异或操作。注释解释是，因为已经使用红黑树来处理链表大量的碰撞，因此选择这种最cheap的方法来降低系统消耗，同时也对高位进行了操作（否则由于table的限制高位基本不会使用）。
基本变量
//transient在序列化对象时，变量不会序列化
//table数组
transient Node<K,V>[] table;
//缓存的entrySet()
transient Set<Map.Entry<K,V>> entrySet;
//HashMap的size大小
transient int size;
//对HashMap进行结构修改的次数
transient int modCount;
//当前table的最大容量（默认16）
int threshold;
//装载因子（默认0.75）
final float loadFactor;
HashMap初始化时，若未指定initialCapacity, loadFactor，会指定为默认值。
put操作
public V put(K key, V value) {
return putVal(hash(key), key, value, false, true);
}
这里传入了key的Hash值，hash方法如上。直接看putVal()方法。
final V putVal(int hash, K key, V value, boolean onlyIfAbsent,
boolean evict) {
Node<K,V>[] tab; Node<K,V> p; int n, i;
//若table为空，则先初始化table
if ((tab = table) == null || (n = tab.length) == 0)
n = (tab = resize()).length;
//(n - 1) & hash 确定下标，若该下标不存在，则指定newNode
if ((p = tab[i = (n - 1) & hash]) == null)
tab[i] = newNode(hash, key, value, null);
else {
Node<K,V> e; K k;
//判断p与传入的键值对的key、hash是否相同
if (p.hash == hash &&
((k = p.key) == key || (key != null && key.equals(k))))
e = p;
//若不同，且为红黑树节点，则在红黑树中插入节点
else if (p instanceof TreeNode)
e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value);
//否则，在链表中进行插入操作（插入后若长度>=8，会转为红黑树）
else {
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;
}
}
//定位到e即已存在的节点，替换value值
if (e != null) { // existing mapping for key
V oldValue = e.value;
if (!onlyIfAbsent || oldValue == null)
e.value = value;
afterNodeAccess(e);
return oldValue;
}
}
++modCount;
//插入后会判断size，决定是否扩容
if (++size > threshold)
resize();
afterNodeInsertion(evict);
return null;
}
put操作可总结如下：
首先判断table是否为null，为null会调用resize()方法进行第一次初始化。
(n - 1) & hash 定位下标，若不存在值，则直接插入。
若下标处已有值，则在链表或红黑树上查找做插入操作，这里链表是尾插法。
插入后modCount、size自增，如果size > threshold，会调用resize()方法进行扩容操作。
注意：
链表插入时，若长度>=8，会将链表转换为红黑树。
get操作
public V get(Object key) {
Node<K,V> e;
return (e = getNode(hash(key), key)) == null ? null : e.value;
}
通过getNode(int hash, Object key)方法来获得节点
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 && // always check first node
((k = first.key) == key || (key != null && key.equals(k))))
return first;
if ((e = first.next) != null) {
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;
}
通过源码可以看到，就是非常常规的查找操作，不再赘述。
注意：
红黑树查找时间复杂度：O(logn)
链表查找时间复杂度：O(n)
扩容操作
对HashMap进行扩容时，实际上调用的是resize()方法
final Node<K,V>[] resize() {
Node<K,V>[] oldTab = table;
int oldCap = (oldTab == null) ? 0 : oldTab.length;
int oldThr = threshold;
int newCap, newThr = 0;
//首先要确定新的threshold
if (oldCap > 0) {
if (oldCap >= MAXIMUM_CAPACITY) {
threshold = Integer.MAX_VALUE;
return oldTab;
}
else if ((newCap = oldCap << 1) < MAXIMUM_CAPACITY &&
oldCap >= DEFAULT_INITIAL_CAPACITY)
newThr = oldThr << 1; // double threshold
}
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"})
Node<K,V>[] newTab = (Node<K,V>[])new Node[newCap];
table = newTab;
//复制操作
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)
((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;
}
扩容时，先增大threshold，然后创建newTab，复制原table。
这里注意：
根据(e.hash & oldCap)的结果，
若为0，则下标保持不变，若不为0，则下标+oldCap；（保持相对顺序不变）
