HashMap关键方法
1. 类介绍
官方api地址
该类是基于哈希表对Map接口进行的实现。该实现提供了所有可重写的map操作，并允许null值和null键。（HashMap与Hashtable大致相同，区别是Hashtable是同步的，并且Hashtable的key和value都不允许为null。）这个类不能保证map的顺序;不同时间相同的键值对也可能顺序不一样。
2.成员变量含义
/**
* 空参hashmap，hash表长度
*/
static final int DEFAULT_INITIAL_CAPACITY = 1 << 4; // aka 16
/**
* hash表最大长度
*/
static final int MAXIMUM_CAPACITY = 1 << 30;
/**
* 默认负载因子
*/
static final float DEFAULT_LOAD_FACTOR = 0.75f;
/**
* 当hash值对应链表转换成红黑树阈值之一，链表深度
*/
static final int TREEIFY_THRESHOLD = 8;
/**
* resize()时，相同hash索引下的节点可能会分散到两个索引下，分散后的节点个数小于6将红黑树转为链表
*/
static final int UNTREEIFY_THRESHOLD = 6;
/**
* 当hash值对应链表转换成红黑树阈值之一，hash表长度
*/
static final int MIN_TREEIFY_CAPACITY = 64;
/**
* hash表具体数据结构
*/
transient Node<K,V>[] table;
/**
* 缓存，entrySet
*/
transient Set<Map.Entry<K,V>> entrySet;
/**
* 节点数量
*/
transient int size;
/**
* 修改次数
*/
transient int modCount;
/**
* 当threshold<size时调用resize方法对table扩容
*/
int threshold;
/**
* 负载因子
*/
final float loadFactor;
3.hash算法
计算key的hash
/**
* 计算key的hash
* 1. key为null，hash索引为0
* 2. key的hashCode与hashCode右移16位进行异或的值
*/
static final int hash(Object key) {
int h;
return (key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 16);
}
//hash索引
table.length-1 & (h = hash(key) ^ (h >>> 16))
计算hash表容量
/**
* 计算threshold或table.length的大小，如果是3return4，如果是4return4,最大2的30次幂
* 为什么只能是2的整数次幂？
* hash算法为table.length-1 & (key.hashCode() ^ (key.hashCode() >>> 16))
* 如果table的长度为4，table.length-1的二进制数为00000000000000000000000000000011，任何Ineger与此数按位与都只能得到
* 0，00000000000000000000000000000000
* 1，00000000000000000000000000000001
* 2，00000000000000000000000000000010
* 3，00000000000000000000000000000011
* 这4个值正好对应table的四个索引
*/
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;
}
4.put方法
/**
* 1. 如果table没有初始化，初始化table
* 2. 计算hash索引，如果索引位置为null，new一个Node放到数组中
* 3. 索引位置不为null，与放入hash相等，并且key相同，拿到当前取到的节点
* 4. 如果当前节点是树节点，调用树的putTreeVal
* 5. 使用链表保存这个hash索引的所有键值对，找到链表的最后位置，添加新节点
* 1）如果链表深度>8,hash表长度小于64扩容,大于64转成树
* 2）如果在遍历链表时发现相同的key直接替换掉
*/
final V putVal(int hash, K key, V value, boolean onlyIfAbsent,
boolean evict) {
Node<K,V>[] tab; Node<K,V> p; int n, i;
if ((tab = table) == null || (n = tab.length) == 0)
n = (tab = resize()).length;
if ((p = tab[i = (n - 1) & hash]) == null)
tab[i] = newNode(hash, key, value, null);
else {
Node<K,V> e; K k;
if (p.hash == hash &&
((k = p.key) == key || (key != null && key.equals(k))))
e = p;
else if (p instanceof TreeNode)
e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value);
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;
}
}
if (e != null) {
// existing mapping for key
V oldValue = e.value;
if (!onlyIfAbsent || oldValue == null)
e.value = value;
afterNodeAccess(e);
return oldValue;
}
}
++modCount;
if (++size > threshold)
resize();
afterNodeInsertion(evict);
return null;
}
/**
* 给 Map.putAll 和 Map constructor使用的方法
* 1. table没有初始化，
* 1）如果当前map中没有数据，重新计算threshold
* 2）判断map是否达到增长条件，如果达到扩充一次table
* 2.循环赋值
*/
final void putMapEntries(Map<? extends K, ? extends V> m, boolean evict) {
int s = m.size();
if (s > 0) {
if (table == null) {
// pre-size
float ft = ((float)s / loadFactor) + 1.0F;
int t = ((ft < (float)MAXIMUM_CAPACITY) ?
(int)ft : MAXIMUM_CAPACITY);
if (t > threshold)
threshold = tableSizeFor(t);
}
else if (s > threshold)
resize();
for (Map.Entry<? extends K, ? extends V> e : m.entrySet()) {
K key = e.getKey();
V value = e.getValue();
putVal(hash(key), key, value, false, evict);
}
}
}
5.get方法
/**
* 根据key的hash，key的值拿到
* 1. 计算hash索引拿到首个节点，如果key匹配则返回当前节点
* 2. 判断当前hash索引下是链表还是红黑树
* 1） 链表：从前向后遍历
* 2） 红黑树：找到根节点，树搜索算法
*/
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;
}
6.扩容
/**
* 恒定，如果table.length>=2的30次幂或者threshold>=2的30次幂,threshold=Integer.MAX_VALUE
* 1. 扩容前table初始化过
* 1) 如果table.length>=2的30次幂(到达hash表的最大值)，不对table扩容
* 2）否则table扩容为原来hash表容量的2倍，如果newCap = table.length，2的29次幂>table.length>=16，
* 2. (两个参数的构造方法)扩容前table没有初始化过，table按照threshold初始化
* 3. （空参构造方法）table.length=16,threshold=12
* 4. 创建新的数组，重新计算hash值添加到新table中
*/
final Node<K,V>[] resize() {
Node<K,V>[] oldTab = table;
int oldCap = (oldTab == null) ? 0 : oldTab.length;
int oldThr = threshold;
int newCap, newThr = 0;
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;
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;
}
7.链表何时转为红黑树
/**
* 链表转红黑树
* 条件：链表深度>=8(原本hash索引处有一个节点，next操作7次，也就是8个节点)并且hash表长度>=64
* 1. 不满足条件对hash表扩容
* 2. 满足条件
* 1) 将node节点换成treeNode节点
* 2）将链表转为树
*/
final void treeifyBin(Node<K,V>[] tab, int hash) {
int n, index; Node<K,V> e;
if (tab == null || (n = tab.length) < MIN_TREEIFY_CAPACITY)
resize();
else if ((e = tab[index = (n - 1) & hash]) != null) {
TreeNode<K,V> hd = null, tl = null;
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);
if ((tab[index] = hd) != null)
hd.treeify(tab);
}
}
8.romove方法
/**
* 1. 判断hash表对应位置有值
* 2. 找到当前索引下要删除的key对应的node
* 3. 判断是否等值才删除
*/
final Node<K,V> removeNode(int hash, Object key, Object value,
boolean matchValue, boolean movable) {
Node<K,V>[] tab; Node<K,V> p; int n, index;
if ((tab = table) != null && (n = tab.length) > 0 &&
(p = tab[index = (n - 1) & hash]) != null) {
Node<K,V> node = null, e; K k; V v;
if (p.hash == hash &&
((k = p.key) == key || (key != null && key.equals(k))))
node = p;
else if ((e = p.next) != null) {
if (p instanceof TreeNode)
node = ((TreeNode<K,V>)p).getTreeNode(hash, key);
else {
do {
if (e.hash == hash &&
((k = e.key) == key ||
(key != null && key.equals(k)))) {
node = e;
break;
}
p = e;
} while ((e = e.next) != null);
}
}
if (node != null && (!matchValue || (v = node.value) == value ||
(value != null && value.equals(v)))) {
if (node instanceof TreeNode)
((TreeNode<K,V>)node).removeTreeNode(this, tab, movable);
else if (node == p)
tab[index] = node.next;
else
p.next = node.next;
++modCount;
--size;
afterNodeRemoval(node);
return node;
}
}
return null;
}