JDK8 HashMap源码解析

Map的创建：HashMap()

添加键值对：即put(K key, V value)方法

删除对象：即remove(Object key)方法

取单个对象：即get(Object key)方法

判断对象是否存在：containsKey(Object key)

1.构造函数

//默认容量为16
static final int DEFAULT_INITIAL_CAPACITY = 1 << 4;

//最大容量 2的30次方
static final int MAXIMUM_CAPACITY = 1 << 30;

//默认的加载因子
static final float DEFAULT_LOAD_FACTOR = 0.75f;

//哈希桶，存放链表。 长度是2的N次方，或者初始化时为0.
transient Node<K,V>[] table;

//加载因子，用于计算哈希表元素数量的阈值。  threshold = 哈希桶.length * loadFactor;
final float loadFactor;

//哈希表内元素数量的阈值，当哈希表内元素数量超过阈值时，会发生扩容resize()。
int threshold;

//新建一个哈希表，同时将另一个map m 里的所有元素加入表中
public HashMap(Map<? extends K, ? extends V> m) {
this.loadFactor = DEFAULT_LOAD_FACTOR;
putMapEntries(m, false);
}

public HashMap() {
//默认构造函数，赋值加载因子为默认的0.75f
this.loadFactor = DEFAULT_LOAD_FACTOR;
}

public HashMap(int initialCapacity) {
this(initialCapacity, DEFAULT_LOAD_FACTOR);
}

//同时指定初始化容量 以及 加载因子， 用的很少，一般不会修改loadFactor
public HashMap(int initialCapacity, float loadFactor) {
if (initialCapacity < 0)
throw new IllegalArgumentException("Illegal initial capacity: " +
initialCapacity);
if (initialCapacity > MAXIMUM_CAPACITY)
initialCapacity = MAXIMUM_CAPACITY;
if (loadFactor <= 0 || Float.isNaN(loadFactor))
throw new IllegalArgumentException("Illegal load factor: " +
loadFactor);
this.loadFactor = loadFactor;
this.threshold = tableSizeFor(initialCapacity);
}
//返回大于等于cap的最小2次方数
static final int tableSizeFor(int cap) {
//经过下面的 或 和位移 运算， n最终各位都是1。
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;
}

2.扩容函数

final Node<K,V>[] resize() {
Node<K,V>[] oldTab = table;//当前数组
int oldCap = (oldTab == null) ? 0 : oldTab.length;//当前数组容量
int oldThr = threshold;//当前扩容阈值
int newCap, newThr = 0;//初始化容量和阈值为0
if (oldCap > 0) {
if (oldCap >= MAXIMUM_CAPACITY) {//超过最大容量限制，直接返回
threshold = Integer.MAX_VALUE;
return oldTab;
}
//当前数组容量大于等于16切扩容后小于最大容量限制，扩容阈值增加一倍
else if ((newCap = oldCap << 1) < MAXIMUM_CAPACITY &&
oldCap >= DEFAULT_INITIAL_CAPACITY)
newThr = oldThr << 1;
}
//如果当前表是空的，但是有阈值。代表是初始化时指定了容量、阈值的情况HashMap(int，float)、HashMap(int)
else if (oldThr > 0)
newCap = oldThr;//旧阈值成为新容量
else {//未指定容量和阈值HashMap()，默认赋值
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);
}
//更新阈值
threshold = newThr;
//创建新数组，只是创建了一个新的扩容后的容器，无数据
@SuppressWarnings({"rawtypes","unchecked"})
Node<K,V>[] newTab = (Node<K,V>[])new Node[newCap];
//更新数组引用
table = newTab;
//复制链表数据
if (oldTab != null) {
for (int j = 0; j < oldCap; ++j) {
Node<K,V> e;
if ((e = oldTab[j]) != null) {
oldTab[j] = null;//置空以便GC
//如果当前链表中就一个元素，（没有发生哈希碰撞）
if (e.next == null)
//直接将这个元素放置在新的哈希桶里。
newTab[e.hash & (newCap - 1)] = e;
//如果发生过哈希碰撞 ,而且是节点数超过8个，转化成了红黑树
else if (e instanceof TreeNode)
((TreeNode<K,V>)e).split(this, newTab, j, oldCap);
//如果发生过哈希碰撞，节点数小于8个。则要根据链表上每个节点的哈希值，依次放入新哈希桶对应下标位置。
else {
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;
}

3.put(K key, V value)

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);
}

//如果onlyIfAbsent为true则不会覆盖相同key的值，evict为false表示初始化
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)//当前哈希表为空，直接扩容
n = (tab = resize()).length;
//如果当前index的节点是空的，表示没有发生哈希碰撞。直接构建一个新节点Node，挂载在index处即可。
//index是利用哈希值&哈希桶的长度-1，替代模运算
if ((p = tab[i = (n - 1) & hash]) == null)//p获取tab链表节点
tab[i] = newNode(hash, key, value, null);
else {//发生哈希冲突
Node<K,V> e; K k;
if (p.hash == hash &&
((k = p.key) == key || (key != null && key.equals(k))))//哈希值相等，key也相等，覆盖value操作
e = p;
else if (p instanceof TreeNode)
e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value);
else {//不是覆盖操作，则插入一个普通链表节点
//遍历链表
for (int binCount = 0; ; ++binCount) {
if ((e = p.next) == null) {//遍历到尾部则创建新节点
p.next = newNode(hash, key, value, null);
if (binCount >= TREEIFY_THRESHOLD - 1) // -1 for 1st
treeifyBin(tab, hash);
break;
}
//如果找到了要覆盖的节点
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;
}

4.remove(Object key)

public V remove(Object key) {
Node<K,V> e;
return (e = removeNode(hash(key), key, null, false, true)) == null ?
null : e.value;
}

//如果参数matchValue是true，则必须key 、value都相等才删除。
//如果movable参数是false，在删除节点时，不移动其他节点
final Node<K,V> removeNode(int hash, Object key, Object value,
boolean matchValue, boolean movable) {
// p 是待删除节点的前置节点
Node<K,V>[] tab; Node<K,V> p; int n, index;
//如果哈希表不为空，则根据hash值算出的index下 有节点的话。
if ((tab = table) != null && (n = tab.length) > 0 &&
(p = tab[index = (n - 1) & hash]) != null) {
//node是待删除节点
Node<K,V> node = null, e; K k; V v;
//如果链表头的就是需要删除的节点
if (p.hash == hash &&
((k = p.key) == key || (key != null && key.equals(k))))
node = p;//将待删除节点引用赋给node
else if ((e = p.next) != null) {//否则循环遍历 找到待删除节点，赋值给node
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);
}
}
//如果有待删除节点node，  且 matchValue为false，或者值也相等
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)//如果node ==  p，说明是链表头是待删除节点
tab[index] = node.next;
else//否则待删除节点在表中间
p.next = node.next;
++modCount;//修改modCount
--size;//修改size
afterNodeRemoval(node);//LinkedHashMap回调函数
return node;
}
}
return null;
}

void afterNodeRemoval(Node<K,V> p) { }

5.get(Object key)

public V get(Object key) {
Node<K,V> e;
//传入扰动后的哈希值 和 key 找到目标节点Node
return (e = getNode(hash(key), key)) == null ? null : e.value;
}

//传入扰动后的哈希值 和 key 找到目标节点Node
final Node<K,V> getNode(int hash, Object key) {
Node<K,V>[] tab; Node<K,V> first, e; int n; K k;
//查找过程和删除基本差不多， 找到返回节点，否则返回null
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.containsKey(Object key)

public boolean containsKey(Object key) {
return getNode(hash(key), key) != null;
}