HashMap<K,V> extends AbstractMap<K,V>
implements Map<K,V>, Cloneable, Serializable

1.重要属性

threshold：是 HashMap 所能容纳的最⼤的键值对的个数，threshold = capacity *loadFactor，也就是说 capacity 数组⼀定的情况下，负载因⼦越⼤，所能容纳的键值对个数越多，超出 threshold 这个数⽬就重新 resize（扩容），扩容后的 HashMap的容量是之前的2倍。size 是 HashMap 中实际存在的键值对的数量，注意和 Node[]table 的长度 capacity 、容纳最⼤键值对数量 threshold 的区别
loadFactor:负载因子

2.构造方法

2.1

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);
    }
 //任何一个int 数字，都能找到离他最近的 2 的幂次方数字（且比他大
 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;
    }

2.2

public HashMap(int initialCapacity) {
        this(initialCapacity, DEFAULT_LOAD_FACTOR);
    }

    /**
     * Constructs an empty <tt>HashMap</tt> with the default initial capacity
     * (16) and the default load factor (0.75).
     */
    public HashMap() {
        this.loadFactor = DEFAULT_LOAD_FACTOR; // all other fields defaulted
    }

2.3

太烦了可以先不用看
 public HashMap(Map<? extends K, ? extends V> m) {
        this.loadFactor = DEFAULT_LOAD_FACTOR;
        putMapEntries(m, false);
    }

3.常用方法

3.1put(K key, V value)

final V putVal(int hash, K key, V value, boolean onlyIfAbsent,
                   boolean evict) {
        Node<K,V>[] tab; Node<K,V> p; int n, I;
     //步骤1初始化进来
        if ((tab = table) == null || (n = tab.length) == 0)
            //初始化
            n = (tab = resize()).length;
        if ((p = tab[i = (n - 1) & hash]) == null)
            tab[i] = newNode(hash, key, value, null)
        else {
            步骤1
            Node<K,V> e; K k;
           当前hash的key值和hash值一摸一样
            if (p.hash == hash &&
                ((k = p.key) == key || (key != null && key.equals(k))))
                e = p;
            else if (p instanceof TreeNode)
           //如果是二叉树
                e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value);
            else {
           //如果是链表
                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;
    }


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;
            }
            //步骤4 newCap==oldCap*2 ，newThr = oldThr*2
            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
            //初始化newCap =16和newThr = 0.75*16
            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;
//步骤3重新分散分布
        if (oldTab != null) {
            for (int j = 0; j < oldCap; ++j) {
                Node<K,V> e;
                if ((e = oldTab[j]) != null) {
                    oldTab[j] = null;
                    //如果node后面没有链表或者数组，直接存在新数组的指定位置
                    if (e.next == null)
                        newTab[e.hash & (newCap - 1)] = e;
                    else if (e instanceof TreeNode)
                        //在新的Node数组中，将该红黑树进行拆分，（如果拆分后的子树过小(子树的节点小于等于6个)，则取消树化，即将其转为链表结构）；
                        ((TreeNode<K,V>)e).split(this, newTab, j, oldCap);
                    else { // preserve order
                       //链表处理
                        Node<K,V> loHead = null, loTail = null;
                        Node<K,V> hiHead = null, hiTail = null;
                        Node<K,V> next;
                        do {
                            next = e.next;
//如果e.hash&oldCap进行与运算，算出的结果是为0，即说明该Node节点所对应的数组下标不需要改变
                            if ((e.hash & oldCap) == 0) {
                                if (loTail == null)
//如果loTail为null，说明该链表没有头节点
                                    loHead = e;
                                else
//尾插
                                    loTail.next = e;
                                loTail = e;
                            }
                            else {
//如果e.hash&oldCap进行与运算，算出的结果不为0，则更新该Node节点所对应的数组下标
                                if (hiTail == null)
                                    hiHead = e;
                                else
                                    hiTail.next = e;
                                hiTail = e;
                            }
                        } while ((e = next) != null);
//该Node节点所对应的数组下标不需要改变，直接把数组下标对应的节点指向新Node数组下标位置链表的头节点
                        if (loTail != null) {
                            loTail.next = null;
                            newTab[j] = loHead;
                        }
                    //该Node节点所对应的数组下标需要改变，重新计算出所对应的数组下标值，然后指向新Node数组下标位置链表的头节点

                        if (hiTail != null) {
                            hiTail.next = null;
                            newTab[j + oldCap] = hiHead;
                        }
                    }
                }
            }
        }
        return newTab;
    }

1.初始化进来tab和p都是空，执行n = (tab = resize()).length，
然后执行 newCap = 16 ，newThr = 16*0.75=12来着，
然后执行Node<K,V>[] newTab = (Node<K,V>[])new Node[newCap];
初始化长度为16的table，然后执行tab[i] = newNode(hash, key, value, null);

image.png

2.当再有数据进来的时候，如果没有位置没有占用走tab[i] = newNode(hash, key, value, null);如果占用走putval下面一个else就是步骤1，如果是首节点走首节点，树走树，链表走链表
如果链表长度>=7走treeifyBin(tab, hash)

final void treeifyBin(Node<K,V>[] tab, int hash) {
        int n, index; Node<K,V> e;
        if (tab == null || (n = tab.length) < MIN_TREEIFY_CAPACITY）
            resize();
        else if ((e = tab[index = (n - 1) & hash]) != null) {
            TreeNode<K,V> hd = null, tl = null;
            do {
                TreeNode<K,V> p = replacementTreeNode(e, null);
                if (tl == null)
                    hd = p;
                else {
                    p.prev = tl;
                    tl.next = p;
                }
                tl = p;
            } while ((e = e.next) != null);
            if ((tab[index] = hd) != null)
                hd.treeify(tab);
        如果tab的长度<64,走resize()走到步骤3重新分散分布,不然就转化成二叉树
最后执行if (++size > threshold) resize();当putval次数大于阀值，走resize()
就会执行resize的()步骤4扩容，然后数据发散分布

3.2get(Object key)

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;
    }
先查询头节点是不是，不是的话再往下查分节点的东西

扰动函数
static final int hash(Object key) {
int h;
return (key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 16);
}
减少hash冲突
最后hash&（n-1）