HashMap

1.构造函数

//默认size=16,默认负载因子0.75

1.1 

public HashMap() {

this.loadFactor = DEFAULT_LOAD_FACTOR;// all other fields defaulted

}

1.2

//map容量,负载因子

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);

}

/**

* Returns a power of two size for the given target capacity.

* 为了控制hashmap的容量一定是2的n次方

* 通过位移运算,找到大于或等于 cap 的 最小2的n次幂。位运算的速度要优于乘除加减

*/

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.put数据

2.1 

public V put(K key, V value) {

return putVal(hash(key), key, value,false,true);

}

2.2

static final int hash(Object key) {

int h;

// h >>> 16 为了让高位参与运算,使得更均匀

// (h = key.hashCode()) ^ (h >>> 16)

// 先计算key的hash值,然后再用哈希值与自己右移16位做异或运算

// 使用异或 ^运算符 使得运算结果更有随机性,异或运算只有不同才是1

// PS:因为或运算,值会更偏向于1,与运算,值会更偏向于0

    return (key ==null) ?0 : (h = key.hashCode()) ^ (h >>>16);

}

2.3

final V putVal(int hash, K key, V value,boolean onlyIfAbsent,

boolean evict) {

Node[] tab; Node p;int n, i;

//第一次put数据的时候,hashmap才会初始化,并不是在构造函数中

    if ((tab = table) ==null || (n = tab.length) ==0)

n = (tab = resize()).length;

//由于容量是2的n次方,所以 (n - 1) & hash 其实等同于 n % hash

//而且这样运算的效率会更高

    if ((p = tab[i = (n -1) & hash]) ==null)

tab[i] = newNode(hash, key, value,null);

else {

Node e; K k;

if (p.hash == hash &&

((k = p.key) == key || (key !=null && key.equals(k))))

e = p;

else if (pinstanceof TreeNode)

e = ((TreeNode)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;

}

2.4

final Node[] resize() {

Node[] oldTab = table;

int oldCap = (oldTab ==null) ?0 : oldTab.length;

//旧的扩容阈值

    int oldThr = threshold;

//新的容量和扩容阈值

    int newCap, newThr =0;

//说明已经是旧的hashmap可进行resize

    if (oldCap >0) {

//hashmap >=最大容量

        if (oldCap >= MAXIMUM_CAPACITY) {

//扩容阈值=Integer.max

            threshold = Integer.MAX_VALUE;

return oldTab;

}

//容量扩容1倍 后小于最大容量 且  老容量 >= 初始容量

//为什么扩容一倍大小呢?

//扩容一倍大小的原因是

// (1)为了保证hash 到数组位置的效率

// (2)关系到扩容后元素在newCap中的放置问题:

        else if ((newCap = oldCap <<1) < MAXIMUM_CAPACITY &&

oldCap >= DEFAULT_INITIAL_CAPACITY)

//扩容阈值也扩大1倍

            newThr = oldThr <<1;// double threshold

    }

else if (oldThr >0)// initial capacity was placed in threshold

        newCap = oldThr;

else {

// zero initial threshold signifies using defaults

// 如果是new 了一个新的hashmap的时候,会走这一行,初始化容量和扩容阈值

        newCap = DEFAULT_INITIAL_CAPACITY;

newThr = (int)(DEFAULT_LOAD_FACTOR * DEFAULT_INITIAL_CAPACITY);

}

//1.第一次初始化的时候不是0了已经

    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[] newTab = (Node[])new Node[newCap];

table = newTab;

//如果不是初始化进来的

    if (oldTab !=null) {

//要遍历所有的节点

        for (int j =0; j < oldCap; ++j) {

Node e;

//节点为null就continue 不为空的时候,把节点给临时节点e

            if ((e = oldTab[j]) !=null) {

//把老结点 置为null

                oldTab[j] =null;

//如果该结点没有next,也就是没有发生过冲突,桶的位置只有一个元素,把节点放入新的table中

                if (e.next ==null)

//就把值直接扔到对应的位置。这里有个问题,没有发生过冲突的,就直接放进去了,扩容后也不会发生冲突吗

// ,感觉这个很nb啊

                    newTab[e.hash & (newCap -1)] = e;

//如果节点发生过冲突,并且是红黑树的数据结构

                else if (einstanceof TreeNode)

//说明冲突的个数大于8个,那么就把树切割开

                    ((TreeNode)e).split(this, newTab, j, oldCap);

else {// preserve order

                    Node loHead =null, loTail =null;

Node hiHead =null, hiTail =null;

Node 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;

}

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