HashMap-数组+链表集合
field
常量
//默认初始化容量，最好为2的幂
static final int DEFAULT_INITIAL_CAPACITY = 1 << 4; // aka 16
//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;
//由哈希冲突的链表结构转为平衡二叉树结构节点数阈值（桶的数量需要大于MIN_TREEIFY_CAPACITY ）
static final int TREEIFY_THRESHOLD = 8;
//恢复为链表的阈值
static final int UNTREEIFY_THRESHOLD = 6;
//TREEIFY_THRESHOLD 对应需要的桶数量
static final int MIN_TREEIFY_CAPACITY = 64;变量
//hash节点数组
transient Node[] table;
//元素节点
transient Set> entrySet;
//大小
transient int size;
//操作数
transient int modCount;
//扩容临界值
int threshold;
//加载因子
final float loadFactor; method
tableSizeFor
//相当机智的算法，用来固定容量为2的倍数
static final int tableSizeFor(int cap) { //10000
int n = cap - 1; //可能初始化就为2的倍数，则减去1 1111
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;
}hash
//高16位于hashcode的低16位 异或取值，保证高16位和低16位的变化同时影响hash值
static final int hash(Object key) {
int h;
return (key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 16);
}resize
//扩容操作，将旧hash表数据移到新的hash表
final Node[] resize() {
Node[] oldTab = table;
int oldCap = (oldTab == null) ? 0 : oldTab.length;
int oldThr = threshold;
int newCap, newThr = 0;
//如果原来已经初始化过，若原有容量不超过极限值，则扩容两倍
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
}
// 初始化的容量可能被替换（入参）
else if (oldThr > 0) // initial capacity was placed in threshold
newCap = oldThr;
//初始化定义
else { // zero initial threshold signifies using defaults
newCap = DEFAULT_INITIAL_CAPACITY;
newThr = (int)(DEFAULT_LOAD_FACTOR * DEFAULT_INITIAL_CAPACITY);
}
//计算新的threshold
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[] newTab = (Node[])new Node[newCap];
table = newTab;
//将旧hash表移到新的hash表
if (oldTab != null) {
for (int j = 0; j < oldCap; ++j) {
Node e;
//如果当前旧节点不为空的情况下
if ((e = oldTab[j]) != null) {
oldTab[j] = null;
//如果该节点没有hash冲突，是单节点
if (e.next == null)
//直接将hash值与桶的容量与运算求桶的索引位。
newTab[e.hash & (newCap - 1)] = e;
else if (e instanceof TreeNode)
//如果e是平衡树节点，则添加到平衡树中
((TreeNode)e).split(this, newTab, j, oldCap);
//该节点下仍有其它元素，需要全部转移
else { // preserve order
Node loHead = null, loTail = null;
Node hiHead = null, hiTail = null;
Node next;
//超级超级机智的做法，理解后真是深深敬佩
do {
next = e.next;
//与原来的容量做与运算
//只有两种结果： 0 或 oldCap（2的幂，这是必然的）
//这是hash本来就小于oldCap的情况
if ((e.hash & oldCap) == 0) {
//将剩下的节点逐个copy
if (loTail == null)
loHead = e;
else
loTail.next = e;
loTail = e;
}
//这是hash本来就大于oldCap的情况
else {
//将剩下的节点逐个copy
if (hiTail == null)
hiHead = e;
else
hiTail.next = e;
hiTail = e;
}
//多线程条件下可能反正死循环
//循环列表
} while ((e = next) != null);
//小于oldCap的索引，如果有节点数据，则保持不变
if (loTail != null) {
loTail.next = null;
newTab[j] = loHead;
}
//大于oldCap的索引则，如果有节点数据，在原基础上加上oldCap
if (hiTail != null) {
hiTail.next = null;
newTab[j + oldCap] = hiHead;
}
}
}
}
}
return newTab;
} putVal
final V putVal(int hash, K key, V value, boolean onlyIfAbsent,
boolean evict) {
Node[] tab; Node p; int n, i;
//如果tab为空或者长度为0，则初始化
if ((tab = table) == null || (n = tab.length) == 0)
n = (tab = resize()).length;
//如果桶中计算出的索引无hash冲突，则直接添加
if ((p = tab[i = (n - 1) & hash]) == null)
tab[i] = newNode(hash, key, value, null);
else {
//具有hash冲突
Node e; K k;
//如果hash值，key值都相同，则覆盖
if (p.hash == hash &&
((k = p.key) == key || (key != null && key.equals(k))))
e = p;
//红黑树的节点
else if (p instanceof TreeNode)
e = ((TreeNode)p).putTreeVal(this, tab, hash, key, value);
else {
for (int binCount = 0; ; ++binCount) {
//如果p的下一个元素为null，则将元素添加到P后
if ((e = p.next) == null) {
p.next = newNode(hash, key, value, null);
//到达节点数阈值，则转变为红黑树
if (binCount >= TREEIFY_THRESHOLD - 1) // -1 for 1st
treeifyBin(tab, hash);
break;
}
//如果有重复key，则覆盖
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k))))
break;
p = e;
}
}
//e 不为null ，则表示已存在相同的key
if (e != null) { // existing mapping for key
V oldValue = e.value;
if (!onlyIfAbsent || oldValue == null)
e.value = value;
afterNodeAccess(e);
return oldValue;
}
}
++modCount;
//超过容量就扩容
if (++size > threshold)
resize();
afterNodeInsertion(evict);
return null;
} getNode
final Node getNode(int hash, Object key) {
Node[] tab; Node first, e; int n; K k;
//check 是否含有该元素
if ((tab = table) != null && (n = tab.length) > 0 &&
(first = tab[(n - 1) & hash]) != null) {
//检查链表或者二叉树第一个元素
if (first.hash == hash && // always check first node
((k = first.key) == key || (key != null && key.equals(k))))
return first;
//该节点不在第一个，开始循环检查
if ((e = first.next) != null) {
//红黑树的情况
if (first instanceof TreeNode)
return ((TreeNode)first).getTreeNode(hash, key);
//循环链表
do {
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k))))
return e;
} while ((e = e.next) != null);
}
}
return null;
}