1、初始化
HashMap map= new HashMap(16);
初始值
static final int DEFAULT_INITIAL_CAPACITY = 1 << 4; // aka 16
最大值
static final int MAXIMUM_CAPACITY = 1 << 30;
负载因子
static final float DEFAULT_LOAD_FACTOR = 0.75f;
链表转树的阈值
static final int TREEIFY_THRESHOLD = 8;
树回退链表的阈值
static final int UNTREEIFY_THRESHOLD = 6;
树的最小容量
static final int MIN_TREEIFY_CAPACITY = 64;2、put方法
public V put(K key, V value) {
return putVal(hash(key), key, value, false, true);
}
static final int hash(Object key) {
int h;
return (key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 16); //扰动函数
}hashmap实际上就是数组+链表的散列结构，通过传入的key的hashcode通过一次扰动函数与数组容量取余，得到其下标，（为什么要用扰动函数：首先，一般的hashmap的长度是小于16位的，而key的hashcode值是int类型，为32位，若直接用hashcode与容量取余，则在低16位不变，高16位变化的情况下，其数组下边均一致，容易hash冲突，故将其高16位也纳入计算中，有效降低冲突概率）
no talk show code： 插入hashmap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;
//数组为空或容量为空，则扩容，默认扩容为16，阈值为12
if ((tab = table) == null || (n = tab.length) == 0)
n = (tab = resize()).length;
//未出现hash碰撞，直接放入数组其下标对应位置
if ((p = tab[i = (n - 1) & hash]) == null)
tab[i] = newNode(hash, key, value, null);
//hash碰撞，采用链表法就是将相同hash值的对象组织成一个链表放在hash值对应的槽位
else {
Node<K,V> e; K k;
//传入的key与链表的头节点相同，直接覆盖
if (p.hash == hash &&
((k = p.key) == key || (key != null && key.equals(k))))
e = p;
//当前碰撞节点已为红黑树
else if (p instanceof TreeNode)
e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value);
//未生成红黑树
else {
for (int binCount = 0; ; ++binCount) {
//将新节点放入其尾部，若碰撞的节点个数大于等于8，调用树化方法
if ((e = p.next) == null) {
p.next = newNode(hash, key, value, null);
if (binCount >= TREEIFY_THRESHOLD - 1) // -1 for 1st
treeifyBin(tab, hash);
break;
}
//传入的key与链表的某个节点相同，直接覆盖
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k))))
break;
p = e;
}
}
//传入的key已存在，用传入的value覆盖原value，并返回原value
if (e != null) { // existing mapping for key
V oldValue = e.value;
if (!onlyIfAbsent || oldValue == null)
e.value = value;
afterNodeAccess(e);
return oldValue;
}
}
//记录插入次数
++modCount;
//判断数组已存的节点数是否大于阈值，大于则扩容
if (++size > threshold)
resize();
afterNodeInsertion(evict);
return null;
}3、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;
//旧表已有容量
if (oldCap > 0) {
if (oldCap >= MAXIMUM_CAPACITY) {
threshold = Integer.MAX_VALUE;
return oldTab;
}
//扩容，容量与阈值均乘2
else if ((newCap = oldCap << 1) < MAXIMUM_CAPACITY &&
oldCap >= DEFAULT_INITIAL_CAPACITY)
newThr = oldThr << 1; // double threshold
}
//初始化也是为比传入的容量值大的最小的2的整数倍，如传15则初始容量为16
else if (oldThr > 0) // initial capacity was placed in threshold
newCap = oldThr;
//未传入初始值，则取默认值，容量为16，阈值为12
else { // zero initial threshold signifies using defaults
newCap = DEFAULT_INITIAL_CAPACITY;
newThr = (int)(DEFAULT_LOAD_FACTOR * DEFAULT_INITIAL_CAPACITY);
}
//若新表容量大于int最大值或者新表容量*负载因子大于int最大值，容量取int最大值
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<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) {
//将原节点引用置为空
oldTab[j] = null;
//当前节点非链表节点，直接与新表容量取余得到新表下标，将原节点放入新表此下标即可
if (e.next == null)
newTab[e.hash & (newCap - 1)] = e;
//若是红黑树（待完善））
else if (e instanceof TreeNode)
((TreeNode<K,V>)e).split(this, newTab, j, oldCap);
//链表结构
else { // preserve order
Node<K,V> loHead = null, loTail = null;
Node<K,V> hiHead = null, hiTail = null;
Node<K,V> next;
//用碰撞节点的hash值同旧表容量做与（&）操作，可将原一个链表分成2个链表插入新数组中
//例如3,11,19,27,35,43与旧表容量为8取余均为3，但同8做与（&）操作，结果为0，8,0,8，0,8
//即可将3,19,35放入新表newTab[3]的位置，将11,27,43，放入新表newTab[11]的位置
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;
}4、treeifyBin方法
final void treeifyBin(Node<K,V>[] tab, int hash) {
int n, index; Node<K,V> e;
//虽然链表节点大于8，但是tab的长度小于64，先扩容
if (tab == null || (n = tab.length) < MIN_TREEIFY_CAPACITY)
resize();
//树化
else if ((e = tab[index = (n - 1) & hash]) != null) {
TreeNode<K,V> hd = null, tl = null;
//将所有链表节点转为树节点，并确定其上下关系prev、next
do {
TreeNode<K,V> p = replacementTreeNode(e, null);
if (tl == null)
hd = p;
else {
p.prev = tl;
tl.next = p;
}
tl = p;
} while ((e = e.next) != null);
//真正转红黑树的方法（待完善））
if ((tab[index] = hd) != null)
hd.treeify(tab);
}
}5、treeify方法
final void treeify(Node<K,V>[] tab) {
TreeNode<K,V> root = null;
for (TreeNode<K,V> x = this, next; x != null; x = next) {
next = (TreeNode<K,V>)x.next;
x.left = x.right = null;
//上一个方法确定了上下游的树节点关系，这里将第一个节点置为根节点
if (root == null) {
x.parent = null;
x.red = false;
root = x;
}
else {
K k = x.key;
int h = x.hash;
Class<?> kc = null;
//根据每个节点的hash值依次放到当前叶子节点为空的节点的左或右节点上
//hash大的放入右节点，小的放入左节点，生成一个简单的树
for (TreeNode<K,V> p = root;;) {
int dir, ph;
K pk = p.key;
if ((ph = p.hash) > h)
dir = -1;
else if (ph < h)
dir = 1;
else if ((kc == null &&
(kc = comparableClassFor(k)) == null) ||
(dir = compareComparables(kc, k, pk)) == 0)
dir = tieBreakOrder(k, pk);
TreeNode<K,V> xp = p;
if ((p = (dir <= 0) ? p.left : p.right) == null) {
x.parent = xp;
if (dir <= 0)
xp.left = x;
else
xp.right = x;
//将树转为红黑树（待完善）
root = balanceInsertion(root, x);
break;
}
}
}
}
//保证数组的第一个节点为根节点
moveRootToFront(tab, root);
}