HashMap 源码
属性
默认长度
如不传入初始化长度，则默认长度为 16
/**
* The default initial capacity - MUST be a power of two.
*/
static final int DEFAULT_INITIAL_CAPACITY = 1 << 4; // aka 16阈值
所能容纳的 key-value 对的极限，超过此值就需要进行扩容
/**
* The next size value at which to resize (capacity * load factor).
*/
int threshold;底层数组
HashMap 底层存放 Node 节点的数组，在第一次使用的时候进行初始化，长度总为 2 的 N 次幂
HashMap 保证扩容后长度 n 总为 2 次方是因为计算 Node 所在索引时采用了 (n - 1) & hash 运算进行优化（& 比 % 效率更高），等价于对 n 取模，也就是 h % n
/**
* The table, initialized on first use, and resized as
* necessary. When allocated, length is always a power of two.
* (We also tolerate length zero in some operations to allow
* bootstrapping mechanics that are currently not needed.)
*/
transient Node[] table; 负载因子
如不传入负载因子，默认为 0.75
负载因子过大会导致空间利用率较低，过小会导致碰撞概率变大，查询效率变低
/**
* The load factor used when none specified in constructor.
*/
static final float DEFAULT_LOAD_FACTOR = 0.75f;
扩容为树的阈值
当链表长度大于 8 时，会转变为红黑树
/**
* 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.
*/
static final int TREEIFY_THRESHOLD = 8;回退为链表的阈值
当树中节点少于 6 个时，会转变为链表
/**
* 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.
*/
static final int UNTREEIFY_THRESHOLD = 6;可以树化的最小底层数组长度
如果底层数组长度小于 64 时，说明底层元素并不多，只是分配到某个位置的元素较多，先不转变为红黑树，先扩容底层数组分散开
/**
* 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.
*/
static final int MIN_TREEIFY_CAPACITY = 64;在 treeifyBin(Node 方法中，如果当先底层数组长度小于 MIN_TREEIFY_CAPACITY 会进行扩容
if (tab == null || (n = tab.length) < MIN_TREEIFY_CAPACITY)
resize();重要方法
hash 算法
采用 hashCode() 的高 16 位异或低 16 位实现，可以保证高低 16 位都会参与到运算中
static final int hash(Object key) {
int h;
return (key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 16);
}put 流程
final V putVal(int hash, K key, V value, boolean onlyIfAbsent,
boolean evict) {
Node[] tab; Node p; int n, i;
// 第一次使用，底层数组还没有初始化，进行初始化
if ((tab = table) == null || (n = tab.length) == 0)
n = (tab = resize()).length;
// n 为底层数组长度，(n - 1) & hash 结果为[0,n-1]
// 如果为 null 则此处不存在任何 Node，直接新建 Node 放到此处即可
// HashMap 保证扩容后长度 n 总为 2 次方，因为 & 比 % 具有更高的效率
// 所以采用了 (n - 1) & hash 运算进行优化，等价于对 n 取模，也就是 h % n
if ((p = tab[i = (n - 1) & hash]) == null)
tab[i] = newNode(hash, key, value, null);
else {
Node e; K k;
// 判断 Key 是否已经存在，如果 key 存在，直接处理冲突
if (p.hash == hash &&
((k = p.key) == key || (key != null && key.equals(k))))
e = p;
// 已经转化为红黑树了
else if (p instanceof TreeNode)
// 把节点插入到红黑树中
e = ((TreeNode)p).putTreeVal(this, tab, hash, key, value);
else { // 仍是链表，采用拉链法处理冲突
for (int binCount = 0; ; ++binCount) {
// 遍历到了链表尾部，说明链表中 key 不存在冲突
if ((e = p.next) == null) {
// 把新的 Node 插入到链表尾部
p.next = newNode(hash, key, value, null);
// 在链表尾部新插入了一个 Node，此时链表长度为 binCount + 1
// 相当于：链表长度 (binCount + 1) >= TREEIFY_THRESHOLD
if (binCount >= TREEIFY_THRESHOLD - 1) // -1 for 1st
// 转变为红黑树
treeifyBin(tab, hash);
break;
}
// 链表内有存在 Key，跳出循环，处理冲突
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k))))
break;
p = e;
}
}
// 处理 key 冲突的情况
if (e != null) { // existing mapping for key
V oldValue = e.value;
if (!onlyIfAbsent || oldValue == null)
// 把冲突的 Node 的 value 替换掉
e.value = value;
afterNodeAccess(e);
// 返回被替换的 Node 的 value
return oldValue;
}
}
++modCount;
// 超过能容纳 KV对的阈值，进行扩容
if (++size > threshold)
resize();
afterNodeInsertion(evict);
return null;
} 扩容方法
final Node[] resize() {
Node[] oldTab = table;
int oldCap = (oldTab == null) ? 0 : oldTab.length;
int oldThr = threshold;
int newCap, newThr = 0;
if (oldCap > 0) {
// 超过最大值，不再进行扩容，此时会发生大量碰撞
if (oldCap >= MAXIMUM_CAPACITY) {
threshold = Integer.MAX_VALUE;
return oldTab;
}
// 扩容为原来的两倍
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);
}
// 计算新的 KV 对阈值
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;
if (oldTab != null) { // 重新计算索引，放入到新表中
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;
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;
}