JDK11版HashMap源码全部解析(详细)-一文覆盖各方面
1. 概述
本文很长，详细描述了HashMap源码级别的实现原理，并讨论了包括扩容，hash计算，新建HashMap的开销等问题，同时还提供了一些外部资料。由于内容太多，建议阅读时结合目录快速跳转查看。
Java源码阅读最好采用IDEA，Ctrl + N 输入HashMap即可看到HashMap的源码了，HashMap总共有2444行源码
本文查看的是JDK-11.0.1的源码
文章目录
- 1. 概述
- 1.1 内部类
- 1.2 基本实现
- 1.3 扩容原理
- 1.4 hash计算
- 为什么这样计算hash值
- 1.5 元素实际位置计算
- 1.6 插入null原理
- 1.7 new HashMap()开销
- 2. HashMap的变量
- 2.1 DEFAULT_INITIAL_CAPACITY
- 2.2 MAXIMUM_CAPACITY
- 2.3 DEFAULT_LOAD_FACTOR
- 2.4 TREEIFY_THRESHOLD
- 2.5 UNTREEIFY_THRESHOLD
- 2.6 MIN_TREEIFY_CAPACITY
- 2.7 table
- 2.8 entrySet
- 2.9 size
- 2.10 modCount
- 2.11 threshold
- 2.12 loadFactor
- 2.13 serialVersionUID
- 3. HashMap的方法
- 3.1 构造函数
- 3.2 hash(Object key)
- 3.3 comparableClassFor(Object x)
- 3.4 compareComparables(Class kc, Object k, Object x)
- 3.5 tableSizeFor(int cap)
- 3.6 putMapEntries(Map m, boolean evict)
- 3.7 size()
- 3.8 isEmpty()
- 3.9 get(Object key)
- 3.10 getNode(int hash, Object key)
- 3.11 containsKey(Object key)
- 3.12 put(K key, V value)
- 3.13 putVal(int hash, K key, V value, boolean onlyIfAbsent, boolean evict)
- 3.14 resize() 扩容
- 3.15 treeifyBin(Node < K,V > [] tab, int hash)
- 3.16 putAll(Map m)
- 3.17 remove(Object key)
- 3.18 removeNode(int hash, Object key, Object value, boolean matchValue, boolean movable)
- 3.19 clear()
- 3.20 containsValue(Object value)
- 3.21 keySet()
- 3.22 values()
- 3.23 entrySet()
- 3.24 getOrDefault(Object key, V defaultValue)
- 3.25 putIfAbsent(K key, V value)
- 3.26 remove(Object key, Object value)
- 3.27 replace(K key, V oldValue, V newValue)
- 3.28 replace(K key, V value)
- 3.29 computeIfAbsent(K key, Function mappingFunction)
- 3.30 computeIfPresent(K key, BiFunction remappingFunction)
- 3.31 compute(K key, BiFunction remappingFunction)
- 3.32 merge(K key, V value, BiFunction remappingFunction)
- 3.33 forEach(BiConsumer action)
- 3.34 replaceAll(BiFunction function)
- 3.35 clone()
- 3.36 loadFactor()
- 3.37 capacity()
- 3.38 writeObject(java.io.ObjectOutputStream s)
- 3.39 readObject(java.io.ObjectInputStream s)
- 3.41 replacementNode(Node < K,V > p, Node < K,V > next)
- 3.42 newTreeNode(int hash, K key, V value, Node < K,V > next)
- 3.43 replacementTreeNode(Node < K,V > p, Node < K,V > next)
- 3.44 reinitialize()
- 3.45 afterNodeAccess(Node < K,V > p)
- 3.46 afterNodeInsertion(boolean evict)
- 3.47 afterNodeRemoval(Node < K,V > p)
- 3.48 internalWriteEntries(java.io.ObjectOutputStream s)
- 4. HashMap的内部类
- 4.1 Node
- 4.2 KeySet
- 4.3 EntrySet
- 4.4 TreeNode
- 后记
- 参考资料
咱们按照源码顺序来分析HashMap，除了HashMap本身的变量和方法，HashMap中还定义了定义如下内部类：
1.1 内部类
- Node
- KeySet
- Values
- EntrySet
- HashIterator
- KeyIterator
- ValueIterator
- EntryIterator
- HashMapSpliterator
- KeySpliterator
- ValueSpliterator
- EntrySpliterator
- TreeNode：这个类代表红黑树节点，HashMap中对红黑树的操作的方法都在此类中
1.2 基本实现
HashMap底层使用哈希表（数组 + 单链表），当链表过长会将链表转成 红黑树以实现 O(logn) 时间复杂度内查找。
HashMap的定义为class HashMap。
1.3 扩容原理
HashMap采用的扩容策略是，每次加倍，这样，原来位置的Entry在新扩展的数组中要么依然在原来的位置，要么在<原来位置+原来的容量>的位置。
1.4 hash计算
hash()函数计算hash值方法为(key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 16)，计算出的hash值会被缓存在Node.hash中。
为什么这样计算hash值
hash值计算相当于就是将高16位与低16位进行异或，结果是高16不变，低16位变成其异或的新结果。
为什么让低16位与高16为异或合成一个新的结果呢？是因为HashMap的容量通常比较小，在进行长度取模运算时采用的是只取二进制最右端几位，这样高位的二进制信息就没有用到，所带来的结果就是Hash结果分布不太均匀。而高16位与低16位异或后就可以让低位附带高位的信息，加大低位的随机性。具体请参考JDK 源码中 HashMap 的 hash 方法原理是什么？ - 胖君的回答 - 知乎
不明白异或结果的朋友来看下这段验证代码，复制此代码运行即可明白高16位与低16位的异或的结果：
import java.util.Random;
class Scratch {
public static void main(String[] args) {
generateTestCase(41132564);
Random random = new Random();
for (int j = 0; j < 10; j++) {
generateTestCase(random.nextInt(Integer.MAX_VALUE));
}
}
/**
* 显示根据key的hashCode算出最终元素的hash值
*
* @param hashCode 代表key的hashCode
*/
public static void generateTestCase(int hashCode) {
System.out.println("hashCode = " + hashCode + " 时");
show(hashCode);
int k = hashCode >>> 16;
show(k);
int x = hashCode ^ k;
show(x);
System.out.println();
}
/**
* 显示一个数字的二进制，按照高16位在左，低16位在右的方式显示
*/
public static void show(int n) {
String s = Integer.toBinaryString(n);
s = fillZero(s);
System.out.print(s.substring(0, 16));
System.out.print(" | ");
System.out.println(s.substring(16));
}
/**
* 填充0到字符串前面使得总长32
*/
public static String fillZero(String src) {
StringBuilder sb = new StringBuilder(32);
for (int i = 0; i < 32 - src.length(); i++) {
sb.append('0');
}
return sb.append(src).toString();
}
}
这就是为什么HashMap可以放入键值null，因为计算hash中为null的hash值为0，然后putVal插入
1.5 元素实际位置计算
根据hash()获取元素所在链表的位置的方法为：tab[(n - 1) & hash]，由于n为容量是2的幂，n-1的二进制形式是111111这类二进制左边全1的形式，所以这个方法本质是截取hash二进制相应长度的0和1，如下例。
hash: 10111101
n - 1: 00111111
result: 00111101
// hash的最左端的1没有了，相当于只取二进制最右端几位
1.6 插入null原理
在hash计算中（上文），null的hash值为0，然后按照正常的putVal()插入
1.7 new HashMap()开销
从源码中(下文构造函数)我们可以看到：
new HashMap()开销非常少，仅仅确认装载因子。真正的创建table的操作尽可能的往后延迟，这使得HashMap有不少操作都需要检查table是否初始化。这种设计我猜想应该是为了让人们可以不用担心创建HashMap的开销，大量创建HashMap，比如ArrayList
2. HashMap的变量
2.1 DEFAULT_INITIAL_CAPACITY
HashMap的默认容量是16，被DEFAULT_INITIAL_CAPACITY定义。
static final int DEFAULT_INITIAL_CAPACITY = 1 << 4; // aka 16
2.2 MAXIMUM_CAPACITY
其最大容量为 1073741824（2的30次方）
static final int MAXIMUM_CAPACITY = 1 << 30;
2.3 DEFAULT_LOAD_FACTOR
默认装载因子0.75
static final float DEFAULT_LOAD_FACTOR = 0.75f;
2.4 TREEIFY_THRESHOLD
将链表转换成红黑树的阈值为8，即当链表长度>=8时，链表转换成红黑树
static final int TREEIFY_THRESHOLD = 8;
2.5 UNTREEIFY_THRESHOLD
将红黑树转换成链表的阈值为6（<6时转换），注意，这个是在resize（）的过程中调用TreeNode.split()实现
static final int UNTREEIFY_THRESHOLD = 6;
2.6 MIN_TREEIFY_CAPACITY
要树化并不仅仅是超过TREEIFY_THRESHOLD ，同时容量要超过MIN_TREEIFY_CAPACITY，如果只是超过TREEIFY_THRESHOLD，则会进行扩容（调用resize（），因为扩容可以让链表变短），直到扩容>=MIN_TREEIFY_CAPACITY
static final int MIN_TREEIFY_CAPACITY = 64;
2.7 table
哈希表的数组主体定义，使用时初始化，在构造函数中并不会初始化，所以在各种操作中总是要检查其是否为null
transient Node<K,V>[] table;
2.8 entrySet
作为一个entrySet缓存，使用entrySet方法首先检查其是否为null，不为null则使用这个缓存，否则生成一个并缓存至此。
transient Set<Map.Entry<K,V>> entrySet;
2.9 size
HashMap中Entry的数量
transient int size;
2.10 modCount
记录修改内部结构化修改次数，用于实现fail-fast，ConcurrentModificationException就是通过检测这个抛出
transient int modCount;
2.11 threshold
其值=capacity * load factor，当size超过threshhold便进行一次扩容
int threshold;
2.12 loadFactor
装载因子
final float loadFactor;
2.13 serialVersionUID
用于序列化
private static final long serialVersionUID = 362498820763181265L;
3. HashMap的方法
3.1 构造函数
-
该构造函数并不初始化
transient Node，进行容量和装载因子的（范围）合法性验证，然而并没有对容量进行存储，只是用来确定扩容阈值thresholdpublic 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); } -
显然
public HashMap(int initialCapacity) { this(initialCapacity, DEFAULT_LOAD_FACTOR); } -
无参构造函数仅仅确认装载因子
public HashMap() { this.loadFactor = DEFAULT_LOAD_FACTOR; // all other fields defaulted } -
通过Map构造HashMap时，使用默认装载因子，并调用putMapEntries将Map装入HashMap
public HashMap(Map<? extends K, ? extends V> m) { this.loadFactor = DEFAULT_LOAD_FACTOR; putMapEntries(m, false); }
3.2 hash(Object key)
Hash函数负责产生HashCode，计算法则为若key为null则返回0，否则：对key的hashCode的高16位和低16位进行异或
static final int hash(Object key) {
int h;
return (key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 16);// >>>表示无符号右移
}
3.3 comparableClassFor(Object x)
对于一个Object,若其定义时是class X implement Comparable，则返回X，否则返回null，注意一定Comparable中的X一定得是X不能为其子类或父类，用于红黑树中的比较
- 源码如下
static Class<?> comparableClassFor(Object x) {
if (x instanceof Comparable) {
Class<?> c; Type[] ts, as; ParameterizedType p;
if ((c = x.getClass()) == String.class) // bypass checks
return c;
if ((ts = c.getGenericInterfaces()) != null) {
for (Type t : ts) {
if ((t instanceof ParameterizedType) &&
((p = (ParameterizedType) t).getRawType() ==
Comparable.class) &&
(as = p.getActualTypeArguments()) != null &&
as.length == 1 && as[0] == c) // type arg is c
return c;
}
}
}
return null;
}
- 验证代码如下，将如下代码拷贝即可明白其原理。
import java.lang.reflect.ParameterizedType;
import java.lang.reflect.Type;
class Scratch {
public static void main(String[] args) {
System.out.println(comparableClassFor(new C()));// class Scratch$C
System.out.println(comparableClassFor(new CS()));// null
System.out.println(comparableClassFor(new CSI()));// null
System.out.println(comparableClassFor(new CSIC()));// class Scratch$CSIC
}
static Class<?> comparableClassFor(Object x) {
if (x instanceof Comparable) {
Class<?> c; Type[] ts, as; ParameterizedType p;
if ((c = x.getClass()) == String.class) // bypass checks
return c;
if ((ts = c.getGenericInterfaces()) != null) {
for (Type t : ts) {
if ((t instanceof ParameterizedType) &&
((p = (ParameterizedType) t).getRawType() ==
Comparable.class) &&
(as = p.getActualTypeArguments()) != null &&
as.length == 1 && as[0] == c) // type arg is c
return c;
}
}
}
return null;
}
static class C implements Comparable<C> {
@Override
public int compareTo(C o) {
return 0;
}
}
static class CS extends C {}
static class CSI implements Comparable<C> {
@Override
public int compareTo(C o) {
return 0;
}
}
static class CSIC implements Comparable<CSIC> {
@Override
public int compareTo(CSIC o) {
return 0;
}
}
}
3.4 compareComparables(Class kc, Object k, Object x)
如果x=null，返回0；如果x的类型为kc，则返回k.compare(x)；否则返回0
static int compareComparables(Class<?> kc, Object k, Object x) {
return (x == null || x.getClass() != kc ? 0 :
((Comparable)k).compareTo(x));
}
3.5 tableSizeFor(int cap)
对于给定cap，计算>=cap的2的幂。用于计算table数组大小
static final int tableSizeFor(int cap) {
int n = -1 >>> Integer.numberOfLeadingZeros(cap - 1);
return (n < 0) ? 1 : (n >= MAXIMUM_CAPACITY) ? MAXIMUM_CAPACITY : n + 1;
}
3.6 putMapEntries(Map m, boolean evict)
先确定放入map时容量是否应该调整，调整好后，通过putVal一个个放入
final void putMapEntries(Map<? extends K, ? extends V> m, boolean evict) {
int s = m.size();
if (s > 0) {//放入的map的size要大于0才插入
if (table == null) { // pre-size，如果本map的table未初始化（同时没有任何元素），就根据放入map大小以及loadfactor计算出threshold，依然不初始化table
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)//放入的map超过threshold就扩容
resize();
//到这里容量问题解决了，就一个一个putVal插入
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);
}
}
}
3.7 size()
直接返回size变量的值
public int size() {
return size;
}
3.8 isEmpty()
判断size是否等于0
public boolean isEmpty() {
return size == 0;
}
3.9 get(Object key)
通过计算hash并调用getNode找到节点Node，然后返回Node.value，找不到Node则返回null
public V get(Object key) {
Node<K,V> e;
return (e = getNode(hash(key), key)) == null ? null : e.value;
}
3.10 getNode(int hash, Object key)
如果table未初始化以及长度=0或者根据hash找到链表的第一个元素为nul便返回null，否则判断第一个节点是否为要找的节点，否则以后的节点根据红黑树类型或链表类型采用各自的查找策略
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) {//在table初始化了，且table长度大于0并且根据hash找到链表第一个节点不为null时
if (first.hash == hash && // always check first node，如果链表第一个节点就是要找的便返回
((k = first.key) == key || (key != null && key.equals(k))))
return first;
if ((e = first.next) != null) {
//根据节点是红黑树还是链表类型采用不同的查找策略
if (first instanceof TreeNode)
return ((TreeNode<K,V>)first).getTreeNode(hash, key);
do {//链表类型就是顺序遍历查找
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k))))
return e;
} while ((e = e.next) != null);
}
}
return null;
}
3.11 containsKey(Object key)
根据getNode是否找到节点来判断是否存在
public boolean containsKey(Object key) {
return getNode(hash(key), key) != null;
}
3.12 put(K key, V value)
调用putVal放入节点
public V put(K key, V value) {
return putVal(hash(key), key, value, false, true);
}
3.13 putVal(int hash, K key, V value, boolean onlyIfAbsent, boolean evict)
参数解释：
- onlyIfAbsent:为true则不改变已有的值
- evict：用于LinkedList使用，对于hashmap没用，如果为false，table进入创建模式()
先进行table初始化和0长检查判断是否需要扩容，之后如果key所在链表表头未初始化便初始化并插入，否则根据是否树化根据相应策略查找节点，如果onlyIfAbsent为false则插入。插入后size++并根据threshold判断是否扩容resize()
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)//table未初始化或0长便调用resize()初始化
n = (tab = resize()).length;
if ((p = tab[i = (n - 1) & hash]) == null)//如果相应位置的链表还未创建表头，便创建表头
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 {//在链表中顺序查找节点
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);//添加节点的过程中如果超过树化阈值，便执行树化操作
break;
}
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k))))
break;
p = e;
}
}
if (e != null) { // existing mapping for key，e便是插入的key的位置
V oldValue = e.value;
if (!onlyIfAbsent || oldValue == null)
e.value = value;
afterNodeAccess(e);
return oldValue;
}
}
++modCount;
if (++size > threshold)//如果插入后超过扩容阈值便扩容
resize();
afterNodeInsertion(evict);
return null;
}
3.14 resize() 扩容
阅读这部分源码应注意：
- 所有的 Cap (即newCap，oldCap) 都是2的幂，即二进制为
100000这类形式，Cap-1的二进制都为111111这类形式。
原理：
- 先根据限制条件确定newThr和newCap，然后创建新的table，再把旧table的数据（即链表引用）复制过来。同时复制时根据hash值，在同一个链表中的元素根据
oldCap（二进制是10000的形式）& e.hash（判断相应位为0还是1）来划分成两类，一类放在原位置，一类放在原位置+oldCap位置。
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);
}
//以上代码都是根据限制条件确定newThr和newCap
threshold = newThr;
@SuppressWarnings({"rawtypes","unchecked"})
//创建新table
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;//链表只有一个元素则直接放入新数组
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) {//根据oldCap确定元素hash指定位上是0还是1来划分放在原位置还是原位置+oldCap位置，这里是放在原位置
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;//放在原位置
}
if (hiTail != null) {
hiTail.next = null;
newTab[j + oldCap] = hiHead;//原位置+oldCap
}
}
}
}
}
return newTab;
}
3.15 treeifyBin(Node < K,V > [] tab, int hash)
达到树化阈值还需要超过MIN_TREEIFY_CAPACITY才会树化，否则先进行扩容操作，达到后，先将链表Node逐个替换成TreeNode，在调用TreeNode.treeify建立红黑树
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)//达到树化阈值还需要超过MIN_TREEIFY_CAPACITY才会树化，否则先进行扩容操作
resize();
else if ((e = tab[index = (n - 1) & hash]) != null) {
TreeNode<K,V> hd = null, tl = null;
do {//先将链表Node逐个替换成TreeNode
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);//这里进行树化
}
}
3.16 putAll(Map m)
putAll就是调用putMapEntries
public void putAll(Map<? extends K, ? extends V> m) {
putMapEntries(m, true);
}
3.17 remove(Object key)
remove调用removeNode移除节点后，返回节点value
public V remove(Object key) {
Node<K,V> e;
return (e = removeNode(hash(key), key, null, false, true)) == null ?
null : e.value;
}
3.18 removeNode(int hash, Object key, Object value, boolean matchValue, boolean movable)
根据hash查找key的位置并删除，如果matchValue为true，则只有值也相等时才删除，如果movable为false，红黑树的删除不移动node，然后size减小，如果没找到key，返回null
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;//查找key的位置
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)))) {//matchValue控制值也要相等才删除
if (node instanceof TreeNode) //删除key并减小size
((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;
}
3.19 clear()
size置0，table每个Node都置为null
public void clear() {
Node<K,V>[] tab;
modCount++;
if ((tab = table) != null && size > 0) {
size = 0;
for (int i = 0; i < tab.length; ++i)
tab[i] = null;
}
}
3.20 containsValue(Object value)
双重循环查找数组+链表中的每个value
public boolean containsValue(Object value) {
Node<K,V>[] tab; V v;
if ((tab = table) != null && size > 0) {
for (Node<K,V> e : tab) {
for (; e != null; e = e.next) {
if ((v = e.value) == value ||
(value != null && value.equals(v)))
return true;
}
}
}
return false;
}
3.21 keySet()
查看keySet中是否有已缓存的keySet，没有就创建并加入缓存。值得注意的是由于keySet采用视图技术（没有成员变量），所以创建开销近乎为0。
public Set<K> keySet() {
Set<K> ks = keySet;
if (ks == null) {
ks = new KeySet();
keySet = ks;
}
return ks;
}
3.22 values()
查看是否有已缓存的，没有则创建Value()并缓存，由于没有成员变量，所以创建Values开销近乎为0
public Collection<V> values() {
Collection<V> vs = values;
if (vs == null) {
vs = new Values();
values = vs;
}
return vs;
}
3.23 entrySet()
查看是否有已缓存的，没有则创建EntrySet()并缓存，由于没有成员变量，所以创建开销近乎为0
public Set<Map.Entry<K,V>> entrySet() {
Set<Map.Entry<K,V>> es;
return (es = entrySet) == null ? (entrySet = new EntrySet()) : es;
}
3.24 getOrDefault(Object key, V defaultValue)
用getNode查找，找不到则返回defaultValue
@Override
public V getOrDefault(Object key, V defaultValue) {
Node<K,V> e;
return (e = getNode(hash(key), key)) == null ? defaultValue : e.value;
}
3.25 putIfAbsent(K key, V value)
调用putVal，并设定putVal的参数onlyIfAbsent=true。只有不存在key的时候才插入
@Override
public V putIfAbsent(K key, V value) {
return putVal(hash(key), key, value, true, true);
}
3.26 remove(Object key, Object value)
调用removeNode，返回是否删除成功
@Override
public boolean remove(Object key, Object value) {
return removeNode(hash(key), key, value, true, true) != null;
}
3.27 replace(K key, V oldValue, V newValue)
通过getNode寻找到Node，判断oldValue是否与value相等，然后替换value,并有afterNodeAccess钩子用于LinkedHashMap
@Override
public boolean replace(K key, V oldValue, V newValue) {
Node<K,V> e; V v;
if ((e = getNode(hash(key), key)) != null &&
((v = e.value) == oldValue || (v != null && v.equals(oldValue)))) {
e.value = newValue;
afterNodeAccess(e);
return true;
}
return false;
}
3.28 replace(K key, V value)
通过getNode寻找到Node，然后替换value,并有afterNodeAccess钩子用于LinkedHashMap
@Override
public V replace(K key, V value) {
Node<K,V> e;
if ((e = getNode(hash(key), key)) != null) {
V oldValue = e.value;
e.value = value;
afterNodeAccess(e);
return oldValue;
}
return null;
}
3.29 computeIfAbsent(K key, Function mappingFunction)
如果查找不到key不就运行函数，并将函数返回值插入到key中。function不能更改modCount（不能修改HashMap），否则会ConcurrentModificationException
@Override
public V computeIfAbsent(K key,
Function<? super K, ? extends V> mappingFunction) {
if (mappingFunction == null)
throw new NullPointerException();
int hash = hash(key);
Node<K,V>[] tab; Node<K,V> first; int n, i;
int binCount = 0;
TreeNode<K,V> t = null;
Node<K,V> old = null;
if (size > threshold || (tab = table) == null ||
(n = tab.length) == 0)
n = (tab = resize()).length;
if ((first = tab[i = (n - 1) & hash]) != null) {
if (first instanceof TreeNode)
old = (t = (TreeNode<K,V>)first).getTreeNode(hash, key);
else {
Node<K,V> e = first; K k;
do {
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k)))) {
old = e;
break;
}
++binCount;
} while ((e = e.next) != null);
}
V oldValue;
if (old != null && (oldValue = old.value) != null) {//找到后便返回并处理钩子
afterNodeAccess(old);
return oldValue;
}
}//没找到时
int mc = modCount;
V v = mappingFunction.apply(key);
if (mc != modCount) { throw new ConcurrentModificationException(); }
//将mappingFunction产生的返回值作为value插入到key中，如果超过树化阈值就树化，size++
if (v == null) {
return null;
} else if (old != null) {
old.value = v;
afterNodeAccess(old);
return v;
}
else if (t != null)
t.putTreeVal(this, tab, hash, key, v);
else {
tab[i] = newNode(hash, key, v, first);
if (binCount >= TREEIFY_THRESHOLD - 1)
treeifyBin(tab, hash);
}
modCount = mc + 1;
++size;
afterNodeInsertion(true);
return v;
}
3.30 computeIfPresent(K key, BiFunction remappingFunction)
如果查找到key就运行remappingFunction，并将返回值作为value插入。function不能更改modCount（不能修改HashMap），否则会ConcurrentModificationException。如果返回值为null，就通过removeNode删除key
@Override
public V computeIfPresent(K key,
BiFunction<? super K, ? super V, ? extends V> remappingFunction) {
if (remappingFunction == null)
throw new NullPointerException();
Node<K,V> e; V oldValue;
int hash = hash(key);
if ((e = getNode(hash, key)) != null &&
(oldValue = e.value) != null) {//
int mc = modCount;
V v = remappingFunction.apply(key, oldValue);
if (mc != modCount) { throw new ConcurrentModificationException(); }
if (v != null) {
e.value = v;
afterNodeAccess(e);
return v;
}
else
removeNode(hash, key, null, false, true);
}
return null;
}
3.31 compute(K key, BiFunction remappingFunction)
查找key对应的value，如果key不在map中，则value为null，并以这两个参数调用remappingFunction，函数返回值为v。如果之前key不在map中而v不为null，就插入key和v。如果key在map中：如果v为null，就删除key；如果v不为null，则修改value为v。其间还有并发检查和访问插入钩子函数用于实现LRUCache
@Override
public V compute(K key,
BiFunction<? super K, ? super V, ? extends V> remappingFunction) {
if (remappingFunction == null)
throw new NullPointerException();
int hash = hash(key);
Node<K,V>[] tab; Node<K,V> first; int n, i;
int binCount = 0;
TreeNode<K,V> t = null;
Node<K,V> old = null;
if (size > threshold || (tab = table) == null ||
(n = tab.length) == 0)//常规table检查
n = (tab = resize()).length;
if ((first = tab[i = (n - 1) & hash]) != null) {//判断hash相应链表是否存在，然后寻找节点
if (first instanceof TreeNode)
old = (t = (TreeNode<K,V>)first).getTreeNode(hash, key);
else {
Node<K,V> e = first; K k;
do {
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k)))) {
old = e;
break;
}
++binCount;
} while ((e = e.next) != null);
}
}
V oldValue = (old == null) ? null : old.value;
int mc = modCount;
V v = remappingFunction.apply(key, oldValue);//调用函数
if (mc != modCount) { throw new ConcurrentModificationException(); }
if (old != null) {
if (v != null) {
old.value = v;
afterNodeAccess(old);
}
else
removeNode(hash, key, null, false, true);
}
else if (v != null) {
if (t != null)
t.putTreeVal(this, tab, hash, key, v);
else {
tab[i] = newNode(hash, key, v, first);
if (binCount >= TREEIFY_THRESHOLD - 1)
treeifyBin(tab, hash);
}
modCount = mc + 1;
++size;
afterNodeInsertion(true);
}
return v;
}
3.32 merge(K key, V value, BiFunction remappingFunction)
查找key，如果key存在：map中key对应的value如果不为null，就调用remappingFunction，返回值为v，如果返回值为null且调用merge的value为null，则从map中删除key；否则用remappingFunction的返回值插入value；如果调用merge的value不为null，插入value。
@Override
public V merge(K key, V value,
BiFunction<? super V, ? super V, ? extends V> remappingFunction) {
if (value == null)
throw new NullPointerException();
if (remappingFunction == null)
throw new NullPointerException();
int hash = hash(key);
Node<K,V>[] tab; Node<K,V> first; int n, i;
int binCount = 0;
TreeNode<K,V> t = null;
Node<K,V> old = null;
if (size > threshold || (tab = table) == null ||
(n = tab.length) == 0)//常规table检查
n = (tab = resize()).length;
if ((first = tab[i = (n - 1) & hash]) != null) {//检查hash后table中是否存在相应链表，然后寻找key
if (first instanceof TreeNode)
old = (t = (TreeNode<K,V>)first).getTreeNode(hash, key);
else {
Node<K,V> e = first; K k;
do {
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k)))) {
old = e;
break;
}
++binCount;
} while ((e = e.next) != null);
}
}
if (old != null) {
V v;
if (old.value != null) {
int mc = modCount;
v = remappingFunction.apply(old.value, value);
if (mc != modCount) {
throw new ConcurrentModificationException();
}
} else {
v = value;
}
if (v != null) {
old.value = v;
afterNodeAccess(old);
}
else
removeNode(hash, key, null, false, true);
return v;
}
if (value != null) {
if (t != null)
t.putTreeVal(this, tab, hash, key, value);
else {
tab[i] = newNode(hash, key, value, first);
if (binCount >= TREEIFY_THRESHOLD - 1)
treeifyBin(tab, hash);
}
++modCount;
++size;
afterNodeInsertion(true);
}
return value;
}
3.33 forEach(BiConsumer action)
进行基本合法性检查，然后调用foreach循环调用actioin
@Override
public void forEach(BiConsumer<? super K, ? super V> action) {
Node<K,V>[] tab;
if (action == null)
throw new NullPointerException();
if (size > 0 && (tab = table) != null) {
int mc = modCount;
for (Node<K,V> e : tab) {
for (; e != null; e = e.next)
action.accept(e.key, e.value);
}
if (modCount != mc)
throw new ConcurrentModificationException();
}
}
3.34 replaceAll(BiFunction function)
进行基本合法性检查，然后foreach循环调用action并将返回值赋给value
@Override
public void replaceAll(BiFunction<? super K, ? super V, ? extends V> function) {
Node<K,V>[] tab;
if (function == null)
throw new NullPointerException();
if (size > 0 && (tab = table) != null) {
int mc = modCount;
for (Node<K,V> e : tab) {
for (; e != null; e = e.next) {
e.value = function.apply(e.key, e.value);
}
}
if (modCount != mc)
throw new ConcurrentModificationException();
}
}
3.35 clone()
重新初始化，然后把当前HashMap插入到克隆的HashMap中
@Override
public Object clone() {
HashMap<K,V> result;
try {
result = (HashMap<K,V>)super.clone();
} catch (CloneNotSupportedException e) {
// this shouldn't happen, since we are Cloneable
throw new InternalError(e);
}
result.reinitialize();
result.putMapEntries(this, false);
return result;
}
3.36 loadFactor()
直接返回loadFactor
final float loadFactor() { return loadFactor; }
3.37 capacity()
如果table不为null，返回table的长度，否则如果threshold大于0，返回threshol，否则返回16（即DEFAULT_INITIAL_CAPACITY）
final int capacity() {
return (table != null) ? table.length :
(threshold > 0) ? threshold :
DEFAULT_INITIAL_CAPACITY;
}
3.38 writeObject(java.io.ObjectOutputStream s)
通过ObjectOutputStream先写入非static和非transient的变量（即threshold和loadFactor），然后写入capacity，size，最后调用internalWriteEntries()写入table中的键值对
private void writeObject(java.io.ObjectOutputStream s)
throws IOException {
int buckets = capacity();
// Write out the threshold, loadfactor, and any hidden stuff
s.defaultWriteObject();
s.writeInt(buckets);
s.writeInt(size);
internalWriteEntries(s);
}
3.39 readObject(java.io.ObjectInputStream s)
按照writeObject相反的顺序读出变量，但是capacity会被丢弃重新计算出来。最后键值对读出来再putVal进去
private void readObject(java.io.ObjectInputStream s)
throws IOException, ClassNotFoundException {
// Read in the threshold (ignored), loadfactor, and any hidden stuff
s.defaultReadObject();
reinitialize();
if (loadFactor <= 0 || Float.isNaN(loadFactor))
throw new InvalidObjectException("Illegal load factor: " +
loadFactor);
s.readInt(); // Read and ignore number of buckets
int mappings = s.readInt(); // Read number of mappings (size)
if (mappings < 0)
throw new InvalidObjectException("Illegal mappings count: " +
mappings);
else if (mappings > 0) { // (if zero, use defaults)
// Size the table using given load factor only if within
// range of 0.25...4.0
float lf = Math.min(Math.max(0.25f, loadFactor), 4.0f);
float fc = (float)mappings / lf + 1.0f;
int cap = ((fc < DEFAULT_INITIAL_CAPACITY) ?
DEFAULT_INITIAL_CAPACITY :
(fc >= MAXIMUM_CAPACITY) ?
MAXIMUM_CAPACITY :
tableSizeFor((int)fc));
float ft = (float)cap * lf;
threshold = ((cap < MAXIMUM_CAPACITY && ft < MAXIMUM_CAPACITY) ?
(int)ft : Integer.MAX_VALUE);
// Check Map.Entry[].class since it's the nearest public type to
// what we're actually creating.
SharedSecrets.getJavaObjectInputStreamAccess().checkArray(s, Map.Entry[].class, cap);
@SuppressWarnings({"rawtypes","unchecked"})
Node<K,V>[] tab = (Node<K,V>[])new Node[cap];
table = tab;
// Read the keys and values, and put the mappings in the HashMap
for (int i = 0; i < mappings; i++) {
@SuppressWarnings("unchecked")
K key = (K) s.readObject();
@SuppressWarnings("unchecked")
V value = (V) s.readObject();
putVal(hash(key), key, value, false, false);
}
}
}
3.40 newNode(int hash, K key, V value, Node
显然
Node<K,V> newNode(int hash, K key, V value, Node<K,V> next) {
return new Node<>(hash, key, value, next);
}
3.41 replacementNode(Node < K,V > p, Node < K,V > next)
显然
Node<K,V> replacementNode(Node<K,V> p, Node<K,V> next) {
return new Node<>(p.hash, p.key, p.value, next);
}
3.42 newTreeNode(int hash, K key, V value, Node < K,V > next)
显然
TreeNode<K,V> newTreeNode(int hash, K key, V value, Node<K,V> next) {
return new TreeNode<>(hash, key, value, next);
}
3.43 replacementTreeNode(Node < K,V > p, Node < K,V > next)
显然
TreeNode<K,V> replacementTreeNode(Node<K,V> p, Node<K,V> next) {
return new TreeNode<>(p.hash, p.key, p.value, next);
}
3.44 reinitialize()
将除了threshold和loadFactor之外的变量全部初始化
void reinitialize() {
table = null;
entrySet = null;
keySet = null;
values = null;
modCount = 0;
threshold = 0;
size = 0;
}
3.45 afterNodeAccess(Node < K,V > p)
给子类（LinkedHashMap）的钩子
void afterNodeAccess(Node<K,V> p) { }
3.46 afterNodeInsertion(boolean evict)
给子类（LinkedHashMap）的钩子
void afterNodeInsertion(boolean evict) { }
3.47 afterNodeRemoval(Node < K,V > p)
给子类（LinkedHashMap）的钩子
void afterNodeRemoval(Node<K,V> p) { }
3.48 internalWriteEntries(java.io.ObjectOutputStream s)
双重循环遍历所有key同时写入key value至序列化流中。
void internalWriteEntries(java.io.ObjectOutputStream s) throws IOException {
Node<K,V>[] tab;
if (size > 0 && (tab = table) != null) {
for (Node<K,V> e : tab) {
for (; e != null; e = e.next) {
s.writeObject(e.key);
s.writeObject(e.value);
}
}
}
}
4. HashMap的内部类
这里就介绍下Node，KeySet，ValueSet和TreeNode，其它的暂且略去，也比较易懂
4.1 Node
static class Node<K,V> implements Map.Entry<K,V> {
final int hash;
final K key;
V value;
Node<K,V> next;
Node(int hash, K key, V value, Node<K,V> next) {
this.hash = hash;
this.key = key;
this.value = value;
this.next = next;
}
public final K getKey() { return key; }
public final V getValue() { return value; }
public final String toString() { return key + "=" + value; }
public final int hashCode() {
return Objects.hashCode(key) ^ Objects.hashCode(value);
}
public final V setValue(V newValue) {
V oldValue = value;
value = newValue;
return oldValue;
}
public final boolean equals(Object o) {
if (o == this)
return true;
if (o instanceof Map.Entry) {
Map.Entry<?,?> e = (Map.Entry<?,?>)o;
if (Objects.equals(key, e.getKey()) &&
Objects.equals(value, e.getValue()))
return true;
}
return false;
}
}
Node的成员变量包括:
final int hash;
final K key;
V value;
Node<K,V> next;
成员函数基本很明朗，就不怎么解释了
4.2 KeySet
final class KeySet extends AbstractSet<K> {
public final int size() { return size; }
public final void clear() { HashMap.this.clear(); }
public final Iterator<K> iterator() { return new KeyIterator(); }
public final boolean contains(Object o) { return containsKey(o); }
public final boolean remove(Object key) {
return removeNode(hash(key), key, null, false, true) != null;
}
public final Spliterator<K> spliterator() {
return new KeySpliterator<>(HashMap.this, 0, -1, 0, 0);
}
public final void forEach(Consumer<? super K> action) {
Node<K,V>[] tab;
if (action == null)
throw new NullPointerException();
if (size > 0 && (tab = table) != null) {
int mc = modCount;
for (Node<K,V> e : tab) {
for (; e != null; e = e.next)
action.accept(e.key);
}
if (modCount != mc)
throw new ConcurrentModificationException();
}
}
}
可以看到，KeySet是通过将大部分方法委托给其它类（主要是HashMap）来实现的，foreach例外。创建KeySet没有任何开销（就跟new Object()）一样。
4.3 EntrySet
final class EntrySet extends AbstractSet<Map.Entry<K,V>> {
public final int size() { return size; }
public final void clear() { HashMap.this.clear(); }
public final Iterator<Map.Entry<K,V>> iterator() {
return new EntryIterator();
}
public final boolean contains(Object o) {
if (!(o instanceof Map.Entry))
return false;
Map.Entry<?,?> e = (Map.Entry<?,?>) o;
Object key = e.getKey();
Node<K,V> candidate = getNode(hash(key), key);
return candidate != null && candidate.equals(e);
}
public final boolean remove(Object o) {
if (o instanceof Map.Entry) {
Map.Entry<?,?> e = (Map.Entry<?,?>) o;
Object key = e.getKey();
Object value = e.getValue();
return removeNode(hash(key), key, value, true, true) != null;
}
return false;
}
public final Spliterator<Map.Entry<K,V>> spliterator() {
return new EntrySpliterator<>(HashMap.this, 0, -1, 0, 0);
}
public final void forEach(Consumer<? super Map.Entry<K,V>> action) {
Node<K,V>[] tab;
if (action == null)
throw new NullPointerException();
if (size > 0 && (tab = table) != null) {
int mc = modCount;
for (Node<K,V> e : tab) {
for (; e != null; e = e.next)
action.accept(e);
}
if (modCount != mc)
throw new ConcurrentModificationException();
}
}
}
可以看到，EntrySet是通过将大部分方法委托给其它类（主要是HashMap）来实现的，foreach例外。创建EntrySet没有任何开销（就跟new Object()）一样。
4.4 TreeNode
由于源码太长，就不贴上来了。TreeNode主要实现了红黑树的所有操作，对于红黑树的原理，建议查找相关资料。
我们先看下TreeNode的成员变量有哪些：
//继承自Node
final int hash;
final K key;
V value;
Node<K,V> next;
//继承自LinkedHashMap.Entry
Entry<K,V> before, after;
//自带
TreeNode<K,V> parent; // red-black tree links
TreeNode<K,V> left;
TreeNode<K,V> right;
TreeNode<K,V> prev; // needed to unlink next upon deletion
可见，采用TreeNode在使用一般64位JVM(引用大小为8位)，则TreeNode的大小是Node的2.7倍。不过现在服务器内存越来越大，用内存换时间（从O(n)->O(logN)）还是划得来的。
后记
关于利用HashMap中留下的钩子函数，其实是给LinkedHashMap用于实现LRUCache的，如何实现请看这篇文章：如何设计实现一个LRU Cache？
参考资料
- 阿里二面准备(Java 研发)
- 基础知识(一) HashMap 源码详解
- HashMap的扩容及树化过程
- HashMap.comparableClassFor(Object x)方法解读