transient Node<K,V>[] table;
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;
}
...
}
static final int hash(Object key) {
int h;
return (key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 16);
}
// h >>> 16 是让h无符号右移16
是用key计算hashCode,然后与key做无符号右移16位 , 是为了让高位移动,让hash均匀
^是异或运算符,异或的规则是转换成二进制比较,相同为0,不同为1.
& 是与运算, 11为1
(h = key.hashCode())^(h >>>16); 的原因是n-1的高位是0, 因此(n-1) & hash 会导致部分高位无法使用,造成系统的浪费, 为了能够使用高位来做index, 因此将h>>>16位, 这样的话(n-1)& hash将会变得更加均匀
最早计算index = hash % n
hashMap里hash算法可能使得hashCode(key1)==hashCode(key2)
从而产生hash碰撞.
如果出现hash碰撞, hashMap将相同的hashCode值的元素, 按照链表的形式存储
当hash值相同,按照链表存储, 当链表的长度>8 ,将链表转化为二叉树; 当
static final int DEFAULT_INITIAL_CAPACITY =1<<4; 默认的初始容量16, 容量不同于size, size是map里的实际数量
static final int MAXIMUM_CAPACITY =1<<30; hashMap最大的容量
static final float DEFAULT_LOAD_FACTOR =0.75f; 默认的加载因子, 负载因子=size除以实际容量, 值越大,hash表越满
static final int TREEIFY_THRESHOLD =8; 当链表的长度大于8, 将链表转化为红黑树
static final int UNTREEIFY_THRESHOLD =6; 在进行resize的操作中,如果红黑树的元素小于6, 将红黑树转化为链表。
/**
* The default initial capacity - MUST be a power of two.
*/
static final int DEFAULT_INITIAL_CAPACITY = 1 << 4; // aka 16 默认的初始容量
/**
* The maximum capacity, used if a higher value is implicitly specified
* by either of the constructors with arguments.
* MUST be a power of two <= 1<<30.
*/
static final int MAXIMUM_CAPACITY = 1 << 30;
/**
* The load factor used when none specified in constructor.
*/
static final float DEFAULT_LOAD_FACTOR = 0.75f;
/**
* The bin count threshold for using a tree rather than list for a
* bin. Bins are converted to trees when adding an element to a
* bin with at least this many nodes. The value must be greater
* than 2 and should be at least 8 to mesh with assumptions in
* tree removal about conversion back to plain bins upon
* shrinkage.
*/
static final int TREEIFY_THRESHOLD = 8;
/**
* The bin count threshold for untreeifying a (split) bin during a
* resize operation. Should be less than TREEIFY_THRESHOLD, and at
* most 6 to mesh with shrinkage detection under removal.
*/
static final int UNTREEIFY_THRESHOLD = 6;//在进行resize的操作中,如果红黑树的元素小于6, 将红黑树转化为链表。
/**
* The smallest table capacity for which bins may be treeified.
* (Otherwise the table is resized if too many nodes in a bin.)
* Should be at least 4 * TREEIFY_THRESHOLD to avoid conflicts
* between resizing and treeification thresholds.
*/
static final int MIN_TREEIFY_CAPACITY = 64;
tab[i =(n -1)& hash])可以看出hash的主要作用是帮我们找出key在hashMap中对应的数组下标
1. 计算key的hash值
2. 根据key的hash找出要存储元素的位置
1)tab[i=(n-1)&hash] == null 这个位置没有元素,所以创建新的Node
2) tab[i=(n-1)&hash] != null 这个位置不为空, 产生了hash碰撞, 分为以下两种情况
i) 要插入的元素在Node数组里
ii) 要插入的元素在TreeNode里
iii) 要插入的元素链表里
3) 根据onlyIfAbsent的输入值,来判断是否更新, false更新,true不更新
public V put(K key, V value)
{
return putVal(hash(key), key, value, false, true);
}
/**
* 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;
if ((tab = table) == null || (n = tab.length) == 0)
n = (tab = resize()).length;
if ((p = tab[i = (n - 1) & hash]) == null) //这个位置为null, 所以创建新的数组元素
tab[i] = newNode(hash, key, value, null);
else { // 元素已经存在, 用新的值来替换,要
Node<K,V> e; K k;
//要插入的元素在,在数组里
if (p.hash == hash &&
((k = p.key) == key || (key != null && key.equals(k))))
e = p;
//要插入的元素在TreeNode里
else if (p instanceof TreeNode)
e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value);
//要插入的元素链表里
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, will replace the old value once onlyifAbsent is false
V oldValue = e.value;
if (!onlyIfAbsent || oldValue == null)
e.value = value;
afterNodeAccess(e);
return oldValue;
}
}
++modCount;
if (++size > threshold)
resize();
afterNodeInsertion(evict);
return null;
}
get方法是通过计算key的hash值,并且比较key相等,然后取出key的value
1) 用key所对应的hash找出那个位置上的第一个Node
2) if与 第一个Node的hash相同并且key相同, 直接return 第一个Node
3) if 与第一个node的hash相同, 判断node是在treeNode里还是在链表里
i) if first是TreeNode, 则getTreeNode返回
ii) if first是链表,则用用do while去找first的next的key与输入的key相同的node并返回
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;
}
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原创声明:本文系作者授权腾讯云开发者社区发表,未经许可,不得转载。
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原创声明:本文系作者授权腾讯云开发者社区发表,未经许可,不得转载。
如有侵权,请联系 cloudcommunity@tencent.com 删除。