构造器
HashMap提供了四个构造器，
- public HashMap(int initialCapacity, float loadFactor)
- initialCapacity：分配的数组大小，默认值为16，最大值为2^30,且必须为2的幂次方
- loadFactor：加载因子，当数组使用率>loadFactor时，对数组进行扩容
- tableSizeFor：构造器中调用了该方法，作用是计算出大于等于给定数值的2的幂次方数
- 该构造器中并没有对各种成员变量进行初始化（比如table）
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)
- public HashMap()
- public HashMap(Map<? extends K, ? extends V> m)
使用了默认的initialCapacity和loadFactor，并调用putMapEntries插入数据
putMapEntries方法中，先判断table是否存在，如果不存在则依据输入的map大小定义存储空间大小，否则的话判断是否需要扩容，m.size大于当前容量的话则扩容（利用resize方法）；然后对map中的数据依次调用putVal方法插入数据public HashMap(Map<? extends K, ? extends V> m) { this.loadFactor = DEFAULT_LOAD_FACTOR; putMapEntries(m, false); }
解析见注释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); } } }/** * Implements Map.put and related methods * @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; if ((tab = table) == null || (n = tab.length) == 0)//初始化table变量，即新建一个Node<K,V>数组 n = (tab = resize()).length; /** * 根据key的hash值计算要存储的位置，如果该位置没有数据，则直接存储 * 若该位置已有数据存在，则判断该位置链表中有没有目标key * 位置i根据(n - 1) & hash，n为数组table的长度.因为n为2的幂次方，所以等同于hash%n */ if ((p = tab[i = (n - 1) & hash]) == null) tab[i] = newNode(hash, key, value, null); else { Node<K,V> e; K k; //先于表头查找判断key是否存在 if (p.hash == hash && ((k = p.key) == key || (key != null && key.equals(k)))) e = p; //在余下的节点中查找key //如果key不存在，将节点(key,value)加到链表的末尾 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; } } //e不为null，说明当前key已存在，需要更新value if (e != null) { // existing mapping for key V oldValue = e.value; if (!onlyIfAbsent || oldValue == null) e.value = value; afterNodeAccess(e); return oldValue; } } ++modCount; //判断是否需要扩容 if (++size > threshold) resize(); afterNodeInsertion(evict); return null; }
常用方法
put
put方法主要调用了putVal，在上面已有分析。onlyIfAbsent为false，默认不更新已存在的值
public V put(K key, V value) {
return putVal(hash(key), key, value, false, true);
}
get
调用了getNode方法，所以重点看下getNode
public V get(Object key) {
Node<K,V> e;
return (e = getNode(hash(key), key)) == null ? null : e.value;
}
getNode的思路很简单，跟putVal基本一致。先判断table是否为空，为空返回null，否则在数组table中查找相同的key。每次总是先检查hash对应位置的头节点，如果头节点key于目标key不一致则遍历该位置的链表，直到找到key或者遍历结束。
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;
}
contains
- containsKey
也是利用getNode实现的，通过判断getNode方法返回值是否为null - containsValue
遍历table数组中的每个元素，判断是否有相同的value存在
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;
}
remove
HashMap增删改差方法的设计思路都非常一致，这一点非常让人舒服
所以依旧是看一下removeNode方法
public V remove(Object key) {
Node<K,V> e;
return (e = removeNode(hash(key), key, null, false, true)) == null ?
null : e.value;
}
基本思路是在数组table中寻找hash对应的位置上的节点，并在该节点及其链表上寻找hash值和key值都一致的节点，若有符合情况的节点就把它删掉
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) {//目标位置不为空
Node<K,V> node = null, e; K k; V v;
//所有节点搜索操作都优先查询头节点
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);
}
}
//根据节点是否是头节点来完成删除操作
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;
}
内部方法
resize
这个方法的作用：
- 若table为null，初始化table，并赋予threshold默认值
- 若table不为null，将table的容量扩大为2倍，
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) {//原来有数据，则复制到扩容后的新数组中
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;
}
