1类的定义
代码
public class HashMap<K,V> extends AbstractMap<K,V>
implements Map<K,V>, Cloneable, Serializable
说明
- Cloneable 允许被克隆
- Serializable 允许被序列化
2成员变量
代码
static final int DEFAULT_INITIAL_CAPACITY = 1 << 4; // aka 16
static final int MAXIMUM_CAPACITY = 1 << 30;
static final float DEFAULT_LOAD_FACTOR = 0.75f;
static final int TREEIFY_THRESHOLD = 8;
static final int UNTREEIFY_THRESHOLD = 6;
static final int MIN_TREEIFY_CAPACITY = 64;
- DEFAULT_INITIAL_CAPACITY 初始容量,必须是2的幂
- DEFAULT_LOAD_FACTOR 默认负载因子
3常用内部类
代码
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;
}
}
- 每个节点相当于一个 key-value ,是map存储的基本单位
3静态方法
1 hash
static final int hash(Object key) {
int h;
return (key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 16);
}
通过key生成hash值。
2 comparableClassFor
static Class<?> comparableClassFor(Object x) {
if (x instanceof Comparable) {
Class<?> c; Type[] ts, as; Type t; ParameterizedType p;
if ((c = x.getClass()) == String.class) // bypass checks
return c;
if ((ts = c.getGenericInterfaces()) != null) {
for (int i = 0; i < ts.length; ++i) {
if (((t = ts[i]) 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;
}
释义
通过一个对象来返回他的类
解析
- ts = c.getGenericInterfaces()
获直接实现的接口列表
详细参考链接 链接
3tableSizeFor
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;
}
解析
给一个值x,返回n 其中n的范围为 2^(n-1) <x< 2 ^n
4构造函数
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);
}
public HashMap(int initialCapacity) {
this(initialCapacity, DEFAULT_LOAD_FACTOR);
}
public HashMap() {
this.loadFactor = DEFAULT_LOAD_FACTOR; // all other fields defaulted
}
构造函数就是设置负载因子和初始化map大小。
5常用方法
5.1getNode()
public V get(Object key) {
Node<K,V> e;
return (e = getNode(hash(key), key)) == null ? null : e.value;
}
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;
}
解析
- getNode(int hash, Object key) 是一个final方法不能被成
- 方法解释
- 第一步,通过hash值找到 存储位置,在判断这个节点是否和传入的key相同
- 第二步 如果这个节点和传入的key不同,那么判断是否是红黑树节点,如果是红黑树节点,则调用红黑数据获取值
- d如果不是,一直遍历这个链表
总结
其实就是相当于一个列车,有的车厢存的是链表,有的车厢存的是树,如果是树,就调用树的方法,如果是链表就调用链表的遍历方法。
5.2containsKey()
public boolean containsKey(Object key) {
return getNode(hash(key), key) != null;
}
解析
直接调的get方法,判断是否有这个key
5.3 put
public V put(K key, V value) {
return putVal(hash(key), key, value, false, true);
}
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;
}
/*扩容*/
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;
}
解析:
- 调的是putVal方法,putVal是一个final方法。
- 程序解析
- 1如果map为空,调用resize()对map进行扩容。
- 2根据hash值找见节点,判断这个节点是否为空,如果为空,就把传入的节点值存在这里
- 3如果找到的当前节点的key值相同,则将原来的值替换成传入的节点的值
- 4如果找到的当前节点时树节点,则调用红黑树进行添加值
- 5其他值循环遍历链表添加
注意:resize()扩容
当hashmap中的元素越来越多的时候,碰撞的几率也就越来越高(因为数组的长度是固定的),所以为了提高查询的效率,就要对hashmap的数组进行扩容,数组扩容这个操作也会出现在ArrayList中,所以这是一个通用的操作,很多人对它的性能表示过怀疑,不过想想我们的“均摊”原理,就释然了,而在hashmap数组扩容之后,最消耗性能的点就出现了:原数组中的数据必须重新计算其在新数组中的位置,并放进去,这就是resize。
那么hashmap什么时候进行扩容呢?当hashmap中的元素个数超过数组大小loadFactor时,就会进行数组扩容,loadFactor的默认值为0.75,也就是说,默认情况下,数组大小为16,那么当hashmap中元素个数超过160.75=12的时候,就把数组的大小扩展为216=32,即扩大一倍,然后重新计算每个元素在数组中的位置,而这是一个非常消耗性能的操作,所以如果我们已经预知hashmap中元素的个数,那么预设元素的个数能够有效的提高hashmap的性能。比如说,我们有1000个元素new HashMap(1000), 但是理论上来讲new HashMap(1024)更合适,不过上面annegu已经说过,即使是1000,hashmap也自动会将其设置为1024。 但是new HashMap(1024)还不是更合适的,因为0.751000 < 1000, 也就是说为了让0.75 * size > 1000, 我们必须这样new HashMap(2048)才最合适,既考虑了&的问题,也避免了resize的问题。
5.4 putAll
public void putAll(Map<? extends K, ? extends V> m) {
putMapEntries(m, true);
}
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);
}
}
}
解析
- 其实就是循环 putVal();
5.5 removeNode
public V remove(Object key) {
Node<K,V> e;
return (e = removeNode(hash(key), key, null, false, true)) == null ?
null : e.value;
}
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;
}
解析
- 其实就是先找到那个节点,如果是树节点,按照树的删除算法删除,如果是链,则按照链的方法删除。
5.6 clear
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;
}
}
清除数据
5.7 containsValue
public boolean containsValue(Object value) {
Node<K,V>[] tab; V v;
if ((tab = table) != null && size > 0) {
for (int i = 0; i < tab.length; ++i) {
for (Node<K,V> e = tab[i]; e != null; e = e.next) {
if ((v = e.value) == value ||
(value != null && value.equals(v)))
return true;
}
}
}
return false;
}
- 判断是否有相同的值