HashMap

一、概述

HashMap是基于哈希表的Map接口实现的，它存储的是内容是键值对<key,value>映射，不保证映射的顺序

数据结构为链表散列，jdk1.8以后链表深度大于8会转为红黑树

HashMap的实例有两个参数影响性能，初始化容量initialCapacity（16）和loadFactor加载因子（0.75）

 

二、源码

1、属性

static final int DEFAULT_INITIAL_CAPACITY = 1 << 4;

map初始的容量16，之所以要是2的幂次，为了方便元素插入时使用位运算计算存放的位置（取模效率较低），也为了更方便扩容（避免扩容后重复处理哈希碰撞）

static final int MAXIMUM_CAPACITY = 1 << 30;

上限取了int类型最大的2的幂次

static final float DEFAULT_LOAD_FACTOR = 0.75f;

负载因子太小了浪费空间并且会发生更多次数的resize，太大了哈希冲突增加会导致性能不好，所以0.75只是一个折中的选择

static final int TREEIFY_THRESHOLD = 8;

当链表长度大于等于8时（且数组长度大于等于64），链表转为红黑树结构，之所以是8因为在负载因子为0.75的情况下（长度为length的数组放入0.75*length个元素），链表长度达到8的概率为0.00000006，非常小（一般只有分布非常不均匀的时候才会触发）

static final int UNTREEIFY_THRESHOLD = 6;

当红黑树个数小于等于6时，重新退化为链表，没有用7因为增加一个差值防止链表和红黑树频繁转换

static final int MIN_TREEIFY_CAPACITY = 64;

当哈希表容量大于等于64时才允许链表到红黑树的转换

 

2、构造方法

public HashMap() {
    //设置负载因子
    this.loadFactor = DEFAULT_LOAD_FACTOR; // all other fields defaulted
}
public HashMap(int initialCapacity) {
    //设置初始大小和负载因子
    this(initialCapacity, DEFAULT_LOAD_FACTOR);
}
public HashMap(int initialCapacity, float loadFactor) {
    //校验范围
    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;
    //设置阈值（如果长度入参不是2的幂次，返回最接近的2的幂次）
    this.threshold = tableSizeFor(initialCapacity);
}
public HashMap(Map<? extends K, ? extends V> m) {
    this.loadFactor = DEFAULT_LOAD_FACTOR;
    //填充map
    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)
            //扩容
            resize();
        //将m中的所有元素添加至HashMap中
        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);
        }
    }
}

　　

3、put方法

public V put(K key, V value) {
    return putVal(hash(key), key, value, false, true);
}
final V putVal(int hash, K key, V value, boolean onlyIfAbsent, boolean evict) {
    Node<K,V>[] tab; Node<K,V> p; int n, i;
    //table未初始化或者长度为0，进行扩容
    if ((tab = table) == null || (n = tab.length) == 0)
        n = (tab = resize()).length;
    //通过位运算判断元素放在桶中的位置
    if ((p = tab[i = (n - 1) & hash]) == null)
        tab[i] = newNode(hash, key, value, null);
    //发生碰撞，桶中已有元素
    else {
        Node<K,V> e; K k;
        //比较key和hash相同，将要覆盖value
        if (p.hash == hash && ((k = p.key) == key || (key != null && key.equals(k))))
            e = p;
        //如果是红黑树
        else if (p instanceof TreeNode)
            e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value);
        //如果是链表
        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;
        }
    }
    //告诉迭代器修改过数量了
    ++modCount;
    //如果实际大小大于阈值就扩容
    if (++size > threshold)
        resize();
    //插入后回调
    afterNodeInsertion(evict);
    return null;
}

　　

4、get方法

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;
    //如果table已经初始化，根据哈希寻找元素不为空
    if ((tab = table) != null && (n = tab.length) > 0 &&
        (first = tab[(n - 1) & hash]) != null) {
        //如果第一个元素就像等，数组
        if (first.hash == hash && // always check first node
            ((k = first.key) == key || (key != null && key.equals(k))))
            return first;
        if ((e = first.next) != null) {
            //如果是红黑树
            if (first instanceof TreeNode)
                return ((TreeNode<K,V>)first).getTreeNode(hash, key);
            do {
                //在链表中查找
                if (e.hash == hash &&
                    ((k = e.key) == key || (key != null && key.equals(k))))
                    return e;
            } while ((e = e.next) != null);
        }
    }
    return null;
}

　　

5、resize方法

final Node<K,V>[] resize() {
    // 当前table保存
    Node<K,V>[] oldTab = table;
    // 保存table大小
    int oldCap = (oldTab == null) ? 0 : oldTab.length;
    // 保存当前阈值 
    int oldThr = threshold;
    int newCap, newThr = 0;
    // 之前table大小大于0
    if (oldCap > 0) {
        // 之前table大于最大容量
        if (oldCap >= MAXIMUM_CAPACITY) {
            // 阈值为最大整形
            threshold = Integer.MAX_VALUE;
            return oldTab;
        }
        // 容量翻倍，使用左移，效率更高
        else if ((newCap = oldCap << 1) < MAXIMUM_CAPACITY &&
            oldCap >= DEFAULT_INITIAL_CAPACITY)
            // 阈值翻倍
            newThr = oldThr << 1; // double threshold
    }
    // 之前阈值大于0
    else if (oldThr > 0)
        newCap = oldThr;
    // oldCap = 0并且oldThr = 0，使用缺省值（如使用HashMap()构造函数，之后再插入一个元素会调用resize函数，会进入这一步）
    else {           
        newCap = DEFAULT_INITIAL_CAPACITY;
        newThr = (int)(DEFAULT_LOAD_FACTOR * DEFAULT_INITIAL_CAPACITY);
    }
    // 新阈值为0
    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table
    Node<K,V>[] newTab = (Node<K,V>[])new Node[newCap];
    table = newTab;
    // 之前的table已经初始化过
    if (oldTab != null) {
        // 复制元素，重新进行hash
        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;
                    // 将同一桶中的元素根据(e.hash & oldCap)是否为0进行分割，分成两个不同的链表，完成rehash
                    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;
}