HashMap
特征
线程不安全的, 多线程环境下可以采用concurrent并发包下的concurrentHashMap
数据结构
哈希表
用于存储Node<K-V>键值对
是一个Node数组
Node是数组+链表的复合结构
public class HashMap<K,V> extends AbstractMap<K,V>
implements Map<K,V>, Cloneable, Serializable transient Node<K,V>[] table; //哈希表
static class Node<K,V> implements Map.Entry<K,V> {
final int hash; //hash值
final K key; //key值
V value; //value值
Node<K,V> next; //node指针
}当哈希表的size到达一定值时, 会转换为红黑树
static final class TreeNode<K,V> extends LinkedHashMap.Entry<K,V> {
TreeNode<K,V> parent; // red-black tree links
TreeNode<K,V> left; //左子树
TreeNode<K,V> right; //右子树
TreeNode<K,V> prev; // needed to unlink next upon deletion
boolean red;
}构造方法
//无参构造
//默认负载因子 DEFAULT_LOAD_FACTOR= 0.75F
public HashMap() {
this.loadFactor = DEFAULT_LOAD_FACTOR; // all other fields defaulted
}
//有参构造(初始化容量)
//使用默认负载因子 DEFAULT_LOAD_FACTOR
public HashMap(int initialCapacity) {
this(initialCapacity, DEFAULT_LOAD_FACTOR);
}
//有参构造(初始化容量, 负载因子)
public HashMap(int initialCapacity, float loadFactor) {
if (initialCapacity < 0)
throw new IllegalArgumentException;
if (initialCapacity > MAXIMUM_CAPACITY)
initialCapacity = MAXIMUM_CAPACITY;
if (loadFactor <= 0 || Float.isNaN(loadFactor))
throw new IllegalArgumentException;
this.loadFactor = loadFactor;
this.threshold = tableSizeFor(initialCapacity);
}loadFactor \ capacity \ threshold 配和使用
添加操作
//put(key, value)方法
public V put(K key, V value) {
//hash(key)是计算key的hash值并以此为参传输数据
return putVal(hash(key), key, value, false, true);
}
//putVal方法
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null 或者 table的长度为0. 进行扩容操作resize()方法
if ((tab = table) == null || (n = tab.length) == 0)
n = (tab = resize()).length;
//table为hash的索引是否有元素, 如果无元素, 将K-V放入该空间
if ((p = tab[i = (n - 1) & hash]) == null)
tab[i] = newNode(hash, key, value, null);
//如果有元素进行如下操作
else {
Node<K,V> e; K k;
//如果 添加key和旧key相同 , 替换value的值
if (p.hash == hash &&
((k = p.key) == key || (key != null && key.equals(k))))
e = p;
//如果不相同, p为TreeNode时, 添加到Tree上面
else if (p instanceof TreeNode)
e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value);
//不相同, 并且p不为TreeNode, 即为链表Node, 添加到Node上面
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
//插入后, Node的长度 >8时, 转换成树
treeifyBin(tab, hash);
break;
}
//插入链表时, 依次比较key, 相同的话就替换原value
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k))))
break;
p = e;
}
}
//当key已经存在时, 替换value
if (e != null) { // existing mapping for key
V oldValue = e.value;
if (!onlyIfAbsent || oldValue == null)
e.value = value;
afterNodeAccess(e);
return oldValue;
}
}
++modCount;
//如果添加成功后, table存的Node数量 > 临界值, 将扩容
if (++size > threshold)
resize();
afterNodeInsertion(evict);
return null;
}
threshold = capacity * loadFactor
capacity即为map的容量, threshold为临界长度, loadFactor负载因子(默认0.75)
扩容源码
final Node<K,V>[] resize() {
Node<K,V>[] oldTab = table;
int oldCap = (oldTab == null) ? 0 : oldTab.length;
int oldThr = threshold;
int newCap, newThr = 0;
//oldTable的容量大于0
if (oldCap > 0) {
//table容量的最大值限制
if (oldCap >= MAXIMUM_CAPACITY) {
//容量大于最大容量1<<30, 设置临界值MAX_VALUE
threshold = Integer.MAX_VALUE;
return oldTab;
}
//如果: 默认的容量16 <= 容量*2 < 最大容量
//设置 new容量 = 2 * old容量
else if ((newCap = oldCap << 1) < MAXIMUM_CAPACITY &&
oldCap >= DEFAULT_INITIAL_CAPACITY)
newThr = oldThr << 1; // double threshold
}
//如果threshold > 0(即使用初始容量的有参构造器时)
else if (oldThr > 0) // initial capacity was placed in threshold
newCap = oldThr;
//默认构造器, 默认容量DEFAULT_INITIAL_CAPACITY（16), 临界值为(12)
else { // zero initial threshold signifies using defaults
newCap = DEFAULT_INITIAL_CAPACITY;
newThr = (int)(DEFAULT_LOAD_FACTOR * DEFAULT_INITIAL_CAPACITY);
}
//对临界值做判断，确保其不为0，因为在上面第二种情况(oldThr > 0)，并没有计算newThr
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"})
// 构造新表，初始化表中数据
Node<K,V>[] newTab = (Node<K,V>[])new Node[newCap];
table = newTab;
if (oldTab != null) {
//遍历将原来table中的数据放到扩容后的新表中来
for (int j = 0; j < oldCap; ++j) {
Node<K,V> e;
if ((e = oldTab[j]) != null) {
oldTab[j] = null;
//没有链表Node节点，直接放到新的table中下标为hah中
if (e.next == null)
newTab[e.hash & (newCap - 1)] = e;
//如果是treeNode节点，则树上的节点放到newTab中
else if (e instanceof TreeNode)
((TreeNode<K,V>)e).split(this, newTab, j, oldCap);
//如果e后面还有链表节点，则遍历e所在的链表，
else { // preserve order
Node<K,V> loHead = null, loTail = null;
Node<K,V> hiHead = null, hiTail = null;
Node<K,V> next;
//链表中的节点, 再次hash后, 位置是否改变
do {
next = e.next;
//没改变的在原来的位置
if ((e.hash & oldCap) == 0) {
if (loTail == null)
loHead = e;
else
loTail.next = e;
loTail = e;
}
//改变的需要移动到相应位置
else {
if (hiTail == null)
hiHead = e;
else
hiTail.next = e;
hiTail = e;
}
} while ((e = next) != null);
//下标不变，将原表某个下标的元素放到扩容表同样位置
if (loTail != null) {
loTail.next = null;
newTab[j] = loHead;
}
//下标改变, [下标+增加的扩容量]的位置上
if (hiTail != null) {
hiTail.next = null;
newTab[j + oldCap] = hiHead;
}
}
}
}
}
return newTab;
}
删除操作
public V remove(Object key) {
Node<K,V> e;
return (e = removeNode(hash(key), key, null, false, true)) == null ?
null : e.value;
}
//removeDo()
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;
}查找操作
public V get(Object key) {
Node<K,V> e;
return (e = getNode(hash(key), key)) == null ? null : e.value;
}
//getDo()
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;
}HashMap
基于红黑树实现
static final class Entry<K,V> implements Map.Entry<K,V> {
K key;
V value;
Entry<K,V> left;
Entry<K,V> right;
Entry<K,V> parent;
boolean color = BLACK;
}
private transient Entry<K,V> root;可以指定排序的比较器
树的数据结构不再详细介绍
扫一扫
被折叠的 条评论
为什么被折叠?
到【灌水乐园】发言
