jdk1.8 HashMap源码解析

HashMap的key值的hash算法

static final int hash(Object key) {
        int h;
        return (key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 16);
}

计算元素放置的位置的hash算法是:

(capacity - 1) & hash

使用该算法原因是因为与运算，位运算等在计算机中运算计较高效，为什么？？查资料作证．

HashMap的put方法调用，put方法实际调用的是putVal这个方法，接下来分析一下putVal方法．

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table没有初始化，则调用resize()初始化table
       if ((tab = table) == null || (n = tab.length) == 0)
           n = (tab = resize()).length;
       //如果key值hash后的index没有节点，则将该节点值放置在index处,index 是利用 哈希值 & 哈希桶的长度-1
       if ((p = tab[i = (n - 1) & hash]) == null)
           tab[i] = newNode(hash, key, value, null);
       else {
           Node<K,V> e; K k;
           if (p.hash == hash &&
               ((k = p.key) == key || (key != null && key.equals(k))))
               e = p;
           else if (p instanceof TreeNode)
               e = ((TreeNode<K,V>)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);
                       //如果链表数量大于8，则将链表转为红黑数
                       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;
               }
           }
           //新值替换旧值(这是在有相同key的情况下)
           if (e != null) { // existing mapping for key
               V oldValue = e.value;
               if (!onlyIfAbsent || oldValue == null)
                   e.value = value;
               afterNodeAccess(e);
               return oldValue;
           }
       }
       ++modCount;
       //如果当前hashmap的size大于阈值，则进行扩容
       if (++size > threshold)
           resize();
       afterNodeInsertion(evict);
       return null;
   }

resize()方法是用来HashMap扩容的方法．

final Node<K,V>[] resize() {
        //未初始化时table为null
        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;
            }
            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
            //未初始化的情况，第一次会进入到else，初始化capacity和threshold，capacity是HashMap的容量，容量是2的指数，
            //threshold是HashMap在capacity容量内承载的数量，为threshold = capacity * loadfactor
            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;
        if (oldTab != null) {
            for (int j = 0; j < oldCap; ++j) {
                Node<K,V> e;
                if ((e = oldTab[j]) != null) {
                    oldTab[j] = null;
                    if (e.next == null)
                        //如果链表后没有元素了，根据扩容后的容量来重新hash获取key的位置
                        newTab[e.hash & (newCap - 1)] = e;
                    else if (e instanceof TreeNode)
                        //如果该元素是树节点，后续分析
                        ((TreeNode<K,V>)e).split(this, newTab, j, oldCap);
                    else { // preserve order
                        //这个方法不太清楚，待后续分析
                        Node<K,V> loHead = null, loTail = null;
                        Node<K,V> hiHead = null, hiTail = null;
                        Node<K,V> 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;
    }

这是由链表转为红黑树的第一步,先将链表转为TreeNode的双向链表

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) {
        //下面这段代码的主要意思，就是将原来的数组挂截的链表转为TreeNode的双向链表
        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);
    }
}

将链表转换为红黑树的数据结构

final void treeify(Node<K,V>[] tab) {
           TreeNode<K,V> root = null;
           for (TreeNode<K,V> x = this, next; x != null; x = next) {
               next = (TreeNode<K,V>)x.next;
               x.left = x.right = null;
               if (root == null) {
                   x.parent = null;
                   x.red = false;
                   root = x;
               }
               else {
                   K k = x.key;
                   int h = x.hash;
                   Class<?> kc = null;
                   for (TreeNode<K,V> p = root;;) {
                       int dir, ph;
                       K pk = p.key;
                       if ((ph = p.hash) > h)
                           dir = -1;
                       else if (ph < h)
                           dir = 1;
                       else if ((kc == null &&
                                 (kc = comparableClassFor(k)) == null) ||
                                (dir = compareComparables(kc, k, pk)) == 0)
                           dir = tieBreakOrder(k, pk);

                       TreeNode<K,V> xp = p;
                       if ((p = (dir <= 0) ? p.left : p.right) == null) {
                           x.parent = xp;
                           if (dir <= 0)
                               xp.left = x;
                           else
                               xp.right = x;
                           //上面的操作是通过比较key的hash值来生成一个二叉搜索树，下面balanceInsertion这个方法主要是按照红黑树的规则来进行插入的一个算法．
                           root = balanceInsertion(root, x);
                           break;
                       }
                   }
               }
           }
           moveRootToFront(tab, root);
       }