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浅析HashMap

基于数组的ArrayList长于按索引获取对应元素,而在中间位置插入和删除元素,都涉及了对数组整体的移动、复制等操作,相比于链表的插入删除来说代价比较大。基于链表的LinkedList长于随机插入删除,Java的双向链表(LinekdList)只能从头到尾或者从尾到头遍历链表获取元素,相较于ArrayList也是比较慢的。那么有没有一种折中的解决方案,使得插入删除和取元素都比较便捷呢?我认为HashMap可以算是这么一种折中的解决方案。

HashMap概述

HashMap是一个实现了Map接口的哈希表,允许使用null值和null键。除了非同步和允许使用null之外,HashMap类与Hashtable大致相同。HashMap不保证映射的顺序,不保证该顺序恒久不变。

HashMap不是线程安全的,如果想要使用线程安全的HashMap,可以通以下代码来得到:

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Map map = Collections.synchronizedMap(new HashMap());

源码实现

HashMap在实现上采用了类似“链表的数组”这种数据结构,也有将之称为“拉链法”的,实现方式如图。

拉链法

当HashMap根据key计算的hash值一样时,就发生了碰撞,这时就会根据如图所示的结构存储存储对应的对象。而这种碰撞发生非常多的话,那么HashMap读取对象的速度就会变慢。在java 8之后,如果一个“桶”的记录过大(TREEIFY_THRESHOLD = 8),HashMap会动态的使用一个专门的treemap实现来替换它。这样可以降低频繁发生碰撞时读对象的时间复杂度,当然,这需要你插入的key实现了Comparable接口,否则这样的优化是你享受不到的~

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// 单向链表的数据结构
static class Node<K,V> implements Map.Entry<K,V> {
final int hash;
final K key;
V value;
// 下个节点的引用
Node<K,V> next;

// 在构造函数中初始化
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;
}

// 复写equal方法
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;
}
}

重要的属性:

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  /**
* 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.)
*/
// 存储元素的实体数组
transient Node<K,V>[] table;

/**
* The number of key-value mappings contained in this map.
*/
// map的容量
transient int size;

/**
* The next size value at which to resize (capacity * load factor).
*
* @serial
*/
// (The javadoc description is true upon serialization.
// Additionally, if the table array has not been allocated, this
// field holds the initial array capacity, or zero signifying
// DEFAULT_INITIAL_CAPACITY.)
// 当实际大小超过此值时,会进行扩容 threshold = 容量 * 加载因子
int threshold;

/**
* The load factor for the hash table.
*
* @serial
*/
// 哈希表的加载因子,加载因子在这种实现方式中是数组被填充的程度,哈希表
// 填充的越满,发生冲突的机会越大。在Java的实现中默认的加载因子是0.75
final float loadFactor;

接下来看一下HashMap默认的无参构造函数,看一下HashMap是如何初始化的:

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/**
* 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
}

根据注释来看说是用默认的初始化容量(16)和默认的加载因子(0.75)来构造一个空的哈希Map。虽然注释是这么说的,但是并没有看到其他的动作,特别是上面提到的table这个数组,在构造函数中没有初始化的动作,其实他是在插入元素的时候才真正的初始化这个数组。来看一下我们平时调用的map.put(key,value)是如何实现的:

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public V put(K key, V value) {
return putVal(hash(key), key, value, false, true);
}

具体的实现是putVal,那么看下这个方法:

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/**
* 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;
// 如果table为空
if ((tab = table) == null || (n = tab.length) == 0)
// 事实上调用了resize(),初始化的动作就是在resize方法中完成的
n = (tab = resize()).length;
// 这里根据哈希计算数组下标还是有点玄机的,留待之后讨论
// 这里如果数组对应的索引下还没有插入值,将值插入
if ((p = tab[i = (n - 1) & hash]) == null)
tab[i] = newNode(hash, key, value, null);
else {// 如果已经有值了,即发生了冲突
Node<K,V> e; K k;
// 如果键值相同
if (p.hash == hash &&
((k = p.key) == key || (key != null && key.equals(k))))
e = p;
// HashMap如果频繁的发生碰撞,那么速度就会变慢,在java8 之后
// 如果同一个索引频繁的发生碰撞,那么就会将这个索引底下的链表
// 转换为红黑树,提升搜索的速度。很好,很牛逼的改进!
else if (p instanceof TreeNode)
e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value);
else {
// 不想注释了,自己看吧
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;
}

以上简单的看了下HashMap是如何插入一个值的,在计算索引上,HashMap并没有采用我们平时的哈希值对数组长度取余。而是采用了效率比较高的 & 运算,h & (length - 1),在注释中也说了,哈希表的长度必须是2的次幂,这么做的好处是什么呢?首先是h & (length - 1),length是2的次幂,那么length - 1用二进制表示的话必定全是1,而采用&运算的话,无论是0或1和1进行&运算,其结果既可能是0,也可能是1,这样就保证了运算后的均匀性。

在以上的注释中也提到了对table的初始化是在resize方法中完成的,那么看看resize方法:

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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;
int oldCap = (oldTab == null) ? 0 : oldTab.length;
int oldThr = threshold;
int newCap, newThr = 0;
// 原数组不空
if (oldCap > 0) {
// 如果oldCap已经为最大容量
if (oldCap >= MAXIMUM_CAPACITY) {
threshold = Integer.MAX_VALUE;
return oldTab;
}
// 每次扩容是之前的2倍,一直是2的次幂
else if ((newCap = oldCap << 1) < MAXIMUM_CAPACITY &&
oldCap >= DEFAULT_INITIAL_CAPACITY)
newThr = oldThr << 1; // double threshold
}
// 重新创建table数组,原数组为空,oldThr不为空
// 扩展为oldThr大小
else if (oldThr > 0) // initial capacity was placed in threshold
newCap = oldThr;
// 原数组为空,oldThr为空,全部使用默认值
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;
// 桶中只有一个元素
if (e.next == null)
newTab[e.hash & (newCap - 1)] = e;
// 如果第一个节点是TreeNode
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;
}

接下来再看一下get方法是如何获取到值得

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/**
* Returns the value to which the specified key is mapped,
* or {@code null} if this map contains no mapping for the key.
*
* <p>More formally, if this map contains a mapping from a key
* {@code k} to a value {@code v} such that {@code (key==null ? k==null :
* key.equals(k))}, then this method returns {@code v}; otherwise
* it returns {@code null}. (There can be at most one such mapping.)
*
* <p>A return value of {@code null} does not <i>necessarily</i>
* indicate that the map contains no mapping for the key; it's also
* possible that the map explicitly maps the key to {@code null}.
* The {@link #containsKey containsKey} operation may be used to
* distinguish these two cases.
*
* @see #put(Object, Object)
*/
public V get(Object key) {
Node<K,V> e;
return (e = getNode(hash(key), key)) == null ? null : e.value;
}

/**
* Implements Map.get and related methods
*
* @param hash hash for key
* @param key the key
* @return the node, or null if none
*/
final Node<K,V> getNode(int hash, Object key) {
Node<K,V>[] tab; Node<K,V> first, e; int n; K k;
// hash & (length - 1)得到红黑树的树根或者是链表头
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)// 红黑树
return ((TreeNode<K,V>)first).getTreeNode(hash, key);
do { // 链表
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k))))
return e;
} while ((e = e.next) != null);
}
}
return null;
}

浅析暂时就到这了。