HashMap是以key-value键值对的形式进行存储数据的,数据结构是以数组+链表或红黑树实现。
数据结构图如下:
一、关键属性
HashMap初始化和方法使用的属性。
/**
* 默认初始容量16(2的4次方)
*/
static final int DEFAULT_INITIAL_CAPACITY = 1 << 4; // aka 16 /**
* 最大容量(2的30次方)
*/
static final int MAXIMUM_CAPACITY = 1 << 30; /**
* 默认加载因子
*/
static final float DEFAULT_LOAD_FACTOR = 0.75f; /**
* 链表节点数大于8变成红黑树
*/
static final int TREEIFY_THRESHOLD = 8; /**
* 红黑树节点数小于6变成链表
*/
static final int UNTREEIFY_THRESHOLD = 6; /**
* 在变成红黑树前判断键值对的数量是否小于64
*/
static final int MIN_TREEIFY_CAPACITY = 64;
二、构造方法
1、HashMap(int initialCapacity, float loadFactor),对参数进行校验并初始化容量和加载因子。
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;
this.threshold = tableSizeFor(initialCapacity);
} 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;
}
2、HashMap(int initialCapacity)调用第一个构造方法。
public HashMap(int initialCapacity) {
this(initialCapacity, DEFAULT_LOAD_FACTOR);
}
3、HashMap(Map<? extends K, ? extends V> m),把参数map集合初始化到新集合中。
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);
}
}
}
4、HashMap()方法只初始化加载因子。
public HashMap() {
this.loadFactor = DEFAULT_LOAD_FACTOR; // all other fields defaulted
}
三、主要方法
1、put(K key, V value)方法,先通过计算hash来判断新元素所在节点数组的位置,
如果位置为空则直接添加新元素放在数组节点上,如果不为空则在通过hash和key来判断新添加的元素是否
和在此数组节点上的元素有相同的key,相同则覆盖,否则在判断此节点是树节点还是普通节点,
树节点则进入红黑树的添加,普通节点进入链表的添加,链表通过循环来判断新节点是覆盖还是在尾部添加,
还是超出8个节点变成红黑树添加。
// 添加元素或覆盖元素
public V put(K key, V value) {
return putVal(hash(key), key, value, false, true);
}
// 计算hash值,即元素所属的数组位置
static final int hash(Object key) {
int h;
return (key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 16);
} 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为初始化或长度为0,则扩容
if ((tab = table) == null || (n = tab.length) == 0)
n = (tab = resize()).length;
// 链表第一个元素直接创建新节点并赋值
if ((p = tab[i = (n - 1) & hash]) == null)
tab[i] = newNode(hash, key, value, null); // 在已有链表或红黑树上添加新节点
else {
Node<K,V> e; K k;
// 如果添加的节点和原有的key相同则覆盖
if (p.hash == hash &&
((k = p.key) == key || (key != null && key.equals(k))))
e = p;
// 如果p为红黑树则在这添加
else if (p instanceof TreeNode)
e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value);
// 链表这边添加
else {
// 循环链表
for (int binCount = 0; ; ++binCount) {
// 下一个为空直接赋值
if ((e = p.next) == null) {
p.next = newNode(hash, key, value, null);
if (binCount >= TREEIFY_THRESHOLD - 1) // -1 for 1st
treeifyBin(tab, hash);
break;
}
// hash和key相同退出循环
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;
}
2、resize()方法,对原map集合进行扩容,容量变为原来2倍。
final Node<K,V>[] resize() {
// 保存当前数组节点
Node<K,V>[] oldTab = table;
// 保存原数组节点大小
int oldCap = (oldTab == null) ? 0 : oldTab.length;
// 保存当前阀值
int oldThr = threshold;
// 声明新数组节点大小和阀值
int newCap, newThr = 0;
// 原map有值
if (oldCap > 0) {
// 原map元素个数已达到最大值
if (oldCap >= MAXIMUM_CAPACITY) {
threshold = Integer.MAX_VALUE;
return oldTab;
}
// 原map容量2倍小于最大值且原map容量大于等于16则扩容
else if ((newCap = oldCap << 1) < MAXIMUM_CAPACITY &&
oldCap >= DEFAULT_INITIAL_CAPACITY)
newThr = oldThr << 1; // double threshold
}
// 只进行初始化没有添加元素的进这个
else if (oldThr > 0) // initial capacity was placed in threshold
newCap = oldThr;
// 只调用HashMap()进这个
else { // zero initial threshold signifies using defaults
newCap = DEFAULT_INITIAL_CAPACITY;
newThr = (int)(DEFAULT_LOAD_FACTOR * DEFAULT_INITIAL_CAPACITY);
}
// 新阀值为0(只进行初始化)
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"})
// 初始化新节点数组
Node<K,V>[] newTab = (Node<K,V>[])new Node[newCap];
table = newTab;
// 原节点数组不为空
if (oldTab != null) {
for (int j = 0; j < oldCap; ++j) {
Node<K,V> e;
// 原数组第一个节点不为空
if ((e = oldTab[j]) != null) {
// 主动释放
oldTab[j] = null;
// 只有数组节点(此索引处只有一个节点)
if (e.next == null)
newTab[e.hash & (newCap - 1)] = e;
// e为红黑树节点
else if (e instanceof TreeNode)
((TreeNode<K,V>)e).split(this, newTab, j, oldCap);
// e为普通节点
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;
}
3、remove(Object key)方法,根据key删除元素。
// 根据key删除元素
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;
// map集合不为空
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;
// 所删节点就在数组节点上
if (p.hash == hash &&
((k = p.key) == key || (key != null && key.equals(k))))
node = p;
else if ((e = p.next) != null) {
// 循环红黑树
if (p instanceof TreeNode)
node = ((TreeNode<K,V>)p).getTreeNode(hash, key);
// 普通节点
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);
}
}
// 找到要删除的节点进行删除
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;
}
4、get(Object key)方法,根据key查找元素。
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;
// map集合不为空
if ((tab = table) != null && (n = tab.length) > 0 &&
(first = tab[(n - 1) & hash]) != null) {
// 所找节点正式在数组节点上
if (first.hash == hash && // always check first node
((k = first.key) == key || (key != null && key.equals(k))))
return first;
// 在链表或红黑树上找节点
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;
}