HashMap-数组+链表集合

field

常量

    //默认初始化容量，最好为2的幂    static final int DEFAULT_INITIAL_CAPACITY = 1 << 4; // aka 16    //最大容量    static final int MAXIMUM_CAPACITY = 1 << 30;    //默认加载因子    static final float DEFAULT_LOAD_FACTOR = 0.75f;    //由哈希冲突的链表结构转为平衡二叉树结构节点数阈值（桶的数量需要大于MIN_TREEIFY_CAPACITY ）    static final int TREEIFY_THRESHOLD = 8;    //恢复为链表的阈值    static final int UNTREEIFY_THRESHOLD = 6;    //TREEIFY_THRESHOLD  对应需要的桶数量    static final int MIN_TREEIFY_CAPACITY = 64;

变量

    //hash节点数组    transient Node<K,V>[] table;    //元素节点    transient Set<Map.Entry<K,V>> entrySet;    //大小    transient int size;    //操作数    transient int modCount;    //扩容临界值    int threshold;    //加载因子    final float loadFactor;

method

tableSizeFor

//相当机智的算法，用来固定容量为2的倍数 static final int tableSizeFor(int cap) {  //10000        int n = cap - 1;   //可能初始化就为2的倍数，则减去1   1111        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;    }

hash

//高16位于hashcode的低16位 异或取值，保证高16位和低16位的变化同时影响hash值static final int hash(Object key) {        int h;        return (key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 16);    }

resize

//扩容操作，将旧hash表数据移到新的hash表 final Node<K,V>[] resize() {        Node<K,V>[] oldTab = table;        int oldCap = (oldTab == null) ? 0 : oldTab.length;        int oldThr = threshold;        int newCap, newThr = 0;        //如果原来已经初始化过，若原有容量不超过极限值，则扩容两倍        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        }        // 初始化的容量可能被替换（入参）        else if (oldThr > 0) // initial capacity was placed in threshold            newCap = oldThr;            //初始化定义        else {               // zero initial threshold signifies using defaults            newCap = DEFAULT_INITIAL_CAPACITY;            newThr = (int)(DEFAULT_LOAD_FACTOR * DEFAULT_INITIAL_CAPACITY);        }        //计算新的threshold        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;        //将旧hash表移到新的hash表        if (oldTab != null) {            for (int j = 0; j < oldCap; ++j) {                Node<K,V> e;                //如果当前旧节点不为空的情况下                if ((e = oldTab[j]) != null) {                    oldTab[j] = null;                    //如果该节点没有hash冲突，是单节点                    if (e.next == null)                        //直接将hash值与桶的容量与运算求桶的索引位。                        newTab[e.hash & (newCap - 1)] = e;                    else if (e instanceof TreeNode)                        //如果e是平衡树节点，则添加到平衡树中                        ((TreeNode<K,V>)e).split(this, newTab, j, oldCap);                     //该节点下仍有其它元素，需要全部转移                    else { // preserve order                        Node<K,V> loHead = null, loTail = null;                        Node<K,V> hiHead = null, hiTail = null;                        Node<K,V> next;                        //超级超级机智的做法，理解后真是深深敬佩                        do {                            next = e.next;                            //与原来的容量做与运算                                //只有两种结果： 0 或 oldCap（2的幂，这是必然的）                               //这是hash本来就小于oldCap的情况                            if ((e.hash & oldCap) == 0) {                                //将剩下的节点逐个copy                                if (loTail == null)                                    loHead = e;                                else                                    loTail.next = e;                                loTail = e;                            }                            //这是hash本来就大于oldCap的情况                            else {                                //将剩下的节点逐个copy                                if (hiTail == null)                                    hiHead = e;                                else                                    hiTail.next = e;                                hiTail = e;                            }                            //多线程条件下可能反正死循环                            //循环列表                        } while ((e = next) != null);                        //小于oldCap的索引，如果有节点数据，则保持不变                        if (loTail != null) {                            loTail.next = null;                            newTab[j] = loHead;                        }                        //大于oldCap的索引则，如果有节点数据，在原基础上加上oldCap                        if (hiTail != null) {                            hiTail.next = null;                            newTab[j + oldCap] = hiHead;                        }                    }                }            }        }        return newTab;    }

putVal

final V putVal(int hash, K key, V value, boolean onlyIfAbsent,                   boolean evict) {        Node<K,V>[] tab; Node<K,V> p; int n, i;        //如果tab为空或者长度为0，则初始化        if ((tab = table) == null || (n = tab.length) == 0)            n = (tab = resize()).length;         //如果桶中计算出的索引无hash冲突，则直接添加        if ((p = tab[i = (n - 1) & hash]) == null)            tab[i] = newNode(hash, key, value, null);        else {        //具有hash冲突            Node<K,V> e; K k;            //如果hash值，key值都相同，则覆盖            if (p.hash == hash &&                ((k = p.key) == key || (key != null && key.equals(k))))                e = p;                //红黑树的节点            else if (p instanceof TreeNode)                e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value);            else {                for (int binCount = 0; ; ++binCount) {                    //如果p的下一个元素为null，则将元素添加到P后                    if ((e = p.next) == null) {                        p.next = newNode(hash, key, value, null);                        //到达节点数阈值，则转变为红黑树                        if (binCount >= TREEIFY_THRESHOLD - 1) // -1 for 1st                            treeifyBin(tab, hash);                        break;                    }                    //如果有重复key，则覆盖                    if (e.hash == hash &&                        ((k = e.key) == key || (key != null && key.equals(k))))                        break;                    p = e;                }            }            //e 不为null ，则表示已存在相同的key            if (e != null) { // existing mapping for key                V oldValue = e.value;                if (!onlyIfAbsent || oldValue == null)                    e.value = value;                afterNodeAccess(e);                return oldValue;            }        }        ++modCount;        //超过容量就扩容        if (++size > threshold)            resize();        afterNodeInsertion(evict);        return null;    }

getNode

final Node<K,V> getNode(int hash, Object key) {        Node<K,V>[] tab; Node<K,V> first, e; int n; K k;        //check 是否含有该元素        if ((tab = table) != null && (n = tab.length) > 0 &&            (first = tab[(n - 1) & hash]) != null) {            //检查链表或者二叉树第一个元素            if (first.hash == hash && // always check first node                ((k = first.key) == key || (key != null && key.equals(k))))                return first;                //该节点不在第一个，开始循环检查            if ((e = first.next) != null) {                //红黑树的情况                if (first instanceof TreeNode)                    return ((TreeNode<K,V>)first).getTreeNode(hash, key);                    //循环链表                do {                    if (e.hash == hash &&                        ((k = e.key) == key || (key != null && key.equals(k))))                        return e;                } while ((e = e.next) != null);            }        }        return null;    }