JDK1.8 HashMap源码分析 / 憋错料

一、HashMap概述

在JDK1.8之前，HashMap采用数组+链表实现，即使用链表处理冲突，同一hash值的链表都存储在一个链表里。但是当位于一个桶中的元素较多，即hash值相等的元素较多时，通过key值依次查找的效率较低。而JDK1.8中，HashMap采用数组+链表+红黑树实现，当链表长度超过阈值（8）时，将链表转换为红黑树，这样大大减少了查找时间。

下图中代表jdk1.8之前的hashmap结构，左边部分即代表哈希表，也称为哈希数组，数组的每个元素都是一个单链表的头节点，链表是用来解决冲突的，如果不同的key映射到了数组的同一位置处，就将其放入单链表中。（此图借用网上的图）

图一、jdk1.8之前hashmap结构图

jdk1.8之前的hashmap都采用上图的结构，都是基于一个数组和多个单链表，hash值冲突的时候，就将对应节点以链表的形式存储。如果在一个链表中查找其中一个节点时，将会花费O（n）的查找时间，会有很大的性能损失。到了jdk1.8，当同一个hash值的节点数不小于8时，不再采用单链表形式存储，而是采用红黑树，如下图所示（此图是借用的图）

图二、jdk1.8 hashmap结构图

二、重要的field

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//table就是存储Node类的数组，就是对应上图中左边那一栏，
/**
* 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<K,V>[] table;
/**
* The number of key-value mappings contained in this map.
* 记录hashmap中存储键-值对的数量
*/
transient int size;
/**
* hashmap结构被改变的次数，fail-fast机制
*/
transient int modCount;
/**
* The next size value at which to resize (capacity * load factor).
* 扩容的门限值，当size大于这个值时，table数组进行扩容
*/
int threshold;
/**
* The load factor for the hash table.
*
*/
float loadFactor;
/**
* The default initial capacity - MUST be a power of two.
* 默认初始化数组大小为16
*/
static final int DEFAULT_INITIAL_CAPACITY = 1 << 4; // aka 16
/**
* The maximum capacity, used if a higher value is implicitly specified
* by either of the constructors with arguments.
* MUST be a power of two <= 1<<30.
*/
static final int MAXIMUM_CAPACITY = 1 << 30;
/**
* The load factor used when none specified in constructor.
* 默认装载因子，
*/
static final float DEFAULT_LOAD_FACTOR = 0.75f;
/**
* 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.
* 这是链表的最大长度，当大于这个长度时，链表转化为红黑树
*/
static final int TREEIFY_THRESHOLD = 8;
/**
* 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;
/**
* 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;

三、构造函数

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//可以自己指定初始容量和装载因子
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;
//重新定义了扩容的门限
this.threshold = tableSizeFor(initialCapacity);
}
/**
* Returns a power of two size for the given target capacity.
*/
static final int tableSizeFor(int cap) {
int n = cap - 1;
//先移位再或运算，最终保证返回值是2的整数幂
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;
}
/**
* Constructs an empty <tt>HashMap</tt> with the specified initial
* capacity and the default load factor (0.75).
*
* @param initialCapacity the initial capacity.
* @throws IllegalArgumentException if the initial capacity is negative.
*/
//当知道所要构建的数据容量的大小时，最好直接指定大小，提高效率
public HashMap(int initialCapacity) {
this(initialCapacity, DEFAULT_LOAD_FACTOR);
}
/**
* Constructs an empty <tt>HashMap</tt> with the default initial capacity
* (16) and the default load factor (0.75).
*/
public HashMap() {
this.loadFactor = DEFAULT_LOAD_FACTOR; // all other fields defaulted
}
//将map直接放入hashmap中
public HashMap(Map<? extends K, ? extends V> m) {
this.loadFactor = DEFAULT_LOAD_FACTOR;
putMapEntries(m, false);
}
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);
}
}
}
/**
* Basic hash bin node, used for most entries. (See below for
* TreeNode subclass, and in LinkedMyHashMap for its Entry subclass.)
*/
在hashMap的结构图中，hash数组就是用Node型数组实现的，许多Node类通过next组成链表，key、value实际存储在Node内部类中。
public 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;
}
}

四、重要的方法分析

1.put方法

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/**
* Associates the specified value with the specified key in thismap.
* If the map previously contained a mapping for the key, the old
* value is replaced.
*
*/
public V put(K key, V value) {
return putVal(hash(key), key, value, false, true);
}
static final int hash(Object key) {
int h;
//key的值为null时，hash值返回0，对应的table数组中的位置是0
return (key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 16);
}
/**
* Implements Map.put and related methods
*
* @param hash hash for key
* @param key the key
* @param value the value to put
* @param onlyIfAbsent if true, don‘t change existing value
* @param evict if false, the table is in creation mode.
* @return previous value, or null if none
*/
final V putVal(int hash, K key, V value, boolean onlyIfAbsent,
boolean evict) {
Node<K,V>[] tab; Node<K,V> p; int n, i;
//先将table赋给tab，判断table是否为null或大小为0，若为真，就调用resize（）初始化
if ((tab = table) == null || (n = tab.length) == 0)
n = (tab = resize()).length;
//通过i = (n - 1) & hash得到table中的index值，若为null，则直接添加一个newNode
if ((p = tab[i = (n - 1) & hash]) == null)
tab[i] = newNode(hash, key, value, null);
else {
//执行到这里，说明发生碰撞，即tab[i]不为空，需要组成单链表或红黑树
Node<K,V> e; K k;
if (p.hash == hash &&
((k = p.key) == key || (key != null && key.equals(k))))
//此时p指的是table[i]中存储的那个Node，如果待插入的节点中hash值和key值在p中已经存在，则将p赋给e
e = p;
//如果table数组中node类的hash、key的值与将要插入的Node的hash、key不吻合，就需要在这个node节点链表或者树节点中查找。
else if (p instanceof TreeNode)
//当p属于红黑树结构时，则按照红黑树方式插入
e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value);
else {
//到这里说明碰撞的节点以单链表形式存储，for循环用来使单链表依次向后查找
for (int binCount = 0; ; ++binCount) {
//将p的下一个节点赋给e，如果为null，创建一个新节点赋给p的下一个节点
if ((e = p.next) == null) {
p.next = newNode(hash, key, value, null);
//如果冲突节点达到8个，调用treeifyBin(tab, hash)，这个treeifyBin首先回去判断当前hash表的长度，如果不足64的话，实际上就只进行resize，扩容table，如果已经达到64，那么才会将冲突项存储结构改为红黑树。
if (binCount >= TREEIFY_THRESHOLD - 1) // -1 for 1st
treeifyBin(tab, hash);
break;
}
//如果有相同的hash和key，则退出循环
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k))))
break;
p = e;//将p调整为下一个节点
}
}
//若e不为null，表示已经存在与待插入节点hash、key相同的节点，hashmap后插入的key值对应的value会覆盖以前相同key值对应的value值，就是下面这块代码实现的
if (e != null) { // existing mapping for key
V oldValue = e.value;
//判断是否修改已插入节点的value
if (!onlyIfAbsent || oldValue == null)
e.value = value;
afterNodeAccess(e);
return oldValue;
}
}
++modCount;//插入新节点后，hashmap的结构调整次数+1
if (++size > threshold)
resize();//HashMap中节点数+1，如果大于threshold，那么要进行一次扩容
afterNodeInsertion(evict);
return null;
}

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2.扩容函数resize（）分析

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/**
* Initializes or doubles table size. If null, allocates in
* accord with initial capacity target held in field threshold.
* Otherwise, because we are using power-of-two expansion, the
* elements from each bin must either stay at same index, or move
* with a power of two offset in the new table.
*
* @return the table
*/
final Node<K,V>[] resize() {
Node<K,V>[] oldTab = table;//定义临时Node数组型变量，作为hash table
//读取hash table的长度
int oldCap = (oldTab == null) ? 0 : oldTab.length;
int oldThr = threshold;//读取扩容门限
int newCap, newThr = 0;//初始化新的table长度和门限值
if (oldCap > 0) {
//执行到这里，说明table已经初始化
if (oldCap >= MAXIMUM_CAPACITY) {
threshold = Integer.MAX_VALUE;
return oldTab;
}
//二倍扩容，容量和门限值都加倍
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
//用构造器初始化了门限值，将门限值直接赋给新table容量
newCap = oldThr;
else {
// zero initial threshold signifies using defaults
//老的table容量和门限值都为0，初始化新容量，新门限值，在调用hashmap（）方式构造容器时，就采用这种方式初始化
newCap = DEFAULT_INITIAL_CAPACITY;
newThr = (int)(DEFAULT_LOAD_FACTOR * DEFAULT_INITIAL_CAPACITY);
}
if (newThr == 0) {
//如果门限值为0，重新设置门限
float ft = (float)newCap * loadFactor;
newThr = (newCap < MAXIMUM_CAPACITY && ft < (float)MAXIMUM_CAPACITY ?
(int)ft : Integer.MAX_VALUE);
}
threshold = newThr;//更新新门限值为threshold
@SuppressWarnings({"rawtypes","unchecked"})
//初始化新的table数组
Node<K,V>[] newTab = (Node<K,V>[])new Node[newCap];
table = newTab;
//当原来的table不为null时，需要将table[i]中的节点迁移
if (oldTab != null) {
for (int j = 0; j < oldCap; ++j) {
Node<K,V> e;
//取出链表中第一个节点保存，若不为null，继续下面操作
if ((e = oldTab[j]) != null) {
oldTab[j] = null;//主动释放
if (e.next == null)
//链表中只有一个节点，没有后续节点，则直接重新计算在新table中的index，并将此节点存储到新table对应的index位置处
newTab[e.hash & (newCap - 1)] = e;
else if (e instanceof TreeNode)
//若e是红黑树节点，则按红黑树移动
((TreeNode<K,V>)e).split(this, newTab, j, oldCap);
else { // preserve order
//迁移单链表中的每个节点
Node<K,V> loHead = null, loTail = null;
Node<K,V> hiHead = null, hiTail = null;
Node<K,V> next;
do {
//下面这段暂时没有太明白，通过e.hash & oldCap将链表分为两队，参考知乎上的一段解释
/**
* 把链表上的键值对按hash值分成lo和hi两串，lo串的新索引位置与原先相同[原先位
* j]，hi串的新索引位置为[原先位置j+oldCap]；
* 链表的键值对加入lo还是hi串取决于判断条件if ((e.hash & oldCap) == 0)，因为* capacity是2的幂，所以oldCap为10...0的二进制形式，若判断条件为真，意味着
* oldCap为1的那位对应的hash位为0，对新索引的计算没有影响（新索引
* =hash&(newCap-*1)，newCap=oldCap<<2）；若判断条件为假，则 oldCap为1的那位* 对应的hash位为1，
* 即新索引=hash&( newCap-1 )= hash&( (oldCap<<2) - 1)，相当于多了10...0，
* 即 oldCap
* 例子：
* 旧容量=16，二进制10000；新容量=32，二进制100000
* 旧索引的计算：
* hash = xxxx xxxx xxxy xxxx
* 旧容量-1 1111
* &运算 xxxx
* 新索引的计算：
* hash = xxxx xxxx xxxy xxxx
* 新容量-1 1 1111
* &运算 y xxxx
* 新索引 = 旧索引 + y0000，若判断条件为真，则y=0(lo串索引不变)，否则y=1(hi串
* 索引=旧索引+旧容量10000)
*/
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;
}