ConcurrentHashMap

zyouke
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1. ConcurrentHashMap

  1. 相关属性
//最大容量 2的30次幂
private static final int MAXIMUM_CAPACITY = 1 << 30;
//默认初始容量
private static final int DEFAULT_CAPACITY = 16;
//数组的最大容量，主要是toArray()方法使用
static final int MAX_ARRAY_SIZE = Integer.MAX_VALUE - 8;
//并发数，jdk1.8不使用
private static final int DEFAULT_CONCURRENCY_LEVEL = 16;
//加载因子
private static final float LOAD_FACTOR = 0.75f;
//当链表中节点数大于8时转红黑树
static final int TREEIFY_THRESHOLD = 8;
//当红黑树节点数小于6时转成链表
static final int UNTREEIFY_THRESHOLD = 6;
//节点的hash属性为MOVED时，表示map正在扩容
static final int MOVED     = -1; 
//为-2, 代表此元素后接红黑树
static final int TREEBIN   = -2; 
static final int RESERVED  = -3; 
//主要用来计算Hash值的
static final int HASH_BITS = 0x7fffffff; 
// 这是扩容时的标记节点，主要在扩容时使用
ForwardingNode
//容器的计数器，没有竞争时可以表示容器中元素长度
private transient volatile long baseCount;
/**
 * -1 时表示正在初始化
 * tab.length*LOAD_FACTOR(因子 0.75) 时表示初始化完成
 **/
private transient volatile int sizeCtl;

  1. put方法，jdk1.8ConcurrentHashMap是基于cas和synchronized实现线程安全

    • putVal(K key, V value, boolean onlyIfAbsent)方法
    final V putVal(K key, V value, boolean onlyIfAbsent) {
	//对key和value做校验
    if (key == null || value == null) throw new NullPointerException();
    int hash = spread(key.hashCode());
    int binCount = 0;
    for (Node<K,V>[] tab = table;;) {//死循环
    	// f是头节点
        Node<K,V> f; int n, i, fh;
        if (tab == null || (n = tab.length) == 0)//如果数组没有初始化，则初始化数组
            tab = initTable();
        else if ((f = tabAt(tab, i = (n - 1) & hash)) == null) {//获取当前tab中i下标的node，其实是链表或红黑树头节点
        	//cas操作，如果当前tab在i下标上的头节点为null，创建新的node添加到i下标处，成功后跳出死循环，不成功继续下一轮循环
            if (casTabAt(tab, i, null,new Node<K,V>(hash, key, value, null)))
                break;                 
        }
        else if ((fh = f.hash) == MOVED)//帮助扩容
            tab = helpTransfer(tab, f);
        else {
        	//链表的处理
            V oldVal = null;
            //为f即头节点上锁
            synchronized (f) {
            	//再次校验最新获取的node是否与f相等，如果不相等再次进入循环，如果相等则进行下步执行
                if (tabAt(tab, i) == f) {
                    if (fh >= 0) {
                        binCount = 1;
                        for (Node<K,V> e = f;; ++binCount) {
                            K ek;
                            if (e.hash == hash &&
                                ((ek = e.key) == key ||
                                 (ek != null && key.equals(ek)))) {
                                oldVal = e.val;
                                if (!onlyIfAbsent)
                                    e.val = value;
                                break;
                            }
                            //先将e赋值给pred，然后e=e.next;一直循环到当前的链表的最后一个节点，然后将新的key value创建新的node，追加到当前链表的最后。
                            Node<K,V> pred = e;
                            if ((e = e.next) == null) {
                                pred.next = new Node<K,V>(hash, key,
                                                          value, null);
                                break;
                            }
                        }
                    }else if (f instanceof TreeBin) {//红黑树操作
                        Node<K,V> p;
                        binCount = 2;
                        if ((p = ((TreeBin<K,V>)f).putTreeVal(hash, key,
                                                       value)) != null) {
                            oldVal = p.val;
                            if (!onlyIfAbsent)
                                p.val = value;
                        }
                    }
                }
            }
            //表示当前key value添加成功了
            if (binCount != 0) {
            	//判断是否需要转红黑树
                if (binCount >= TREEIFY_THRESHOLD)
                    treeifyBin(tab, i);
                if (oldVal != null)
                    return oldVal;
                break;
            }
        }
    }
    //元素添加完成后，统计数量，并且校验是否需要扩容
    addCount(1L, binCount);
    return null;
}
    • initTable() 方法
    private final Node<K,V>[] initTable() {
    Node<K,V>[] tab; int sc;
    while ((tab = table) == null || tab.length == 0) {
    	//表示已经在初始化，让出cpu资源，直到tab初始化完成后跳出循环
        if ((sc = sizeCtl) < 0)
        	//yield() 让出cpu资源后会再次竞争cpu资源
            Thread.yield(); 
        else if (U.compareAndSwapInt(this, SIZECTL, sc, -1)) {//cas操作，将-1赋值给SIZECTL
            try {
                if ((tab = table) == null || tab.length == 0) {
                    int n = (sc > 0) ? sc : DEFAULT_CAPACITY;
                    @SuppressWarnings("unchecked")
                    Node<K,V>[] nt = (Node<K,V>[])new Node<?,?>[n];
                    table = tab = nt;
                    //这种计算方式其实等同于n*0.75(加载因子)
                    sc = n - (n >>> 2);
                }
            } finally {
                sizeCtl = sc;
            }
            break;
        }
    }
    return tab;
}
    • casTabAt(Node<K,V>[] tab, int i,Node<K,V> c, Node<K,V> v)
    //使用cas在tab的下标为i处添加node，即为头节点
static final <K,V> boolean casTabAt(Node<K,V>[] tab, int i, Node<K,V> c, Node<K,V> v) {
    return U.compareAndSwapObject(tab, ((long)i << ASHIFT) + ABASE, c, v);
}
    • final Node<K,V>[] helpTransfer(Node<K,V>[] tab, Node<K,V> f)帮助扩容的方法，主要将多个线程分散在不同的数组下标区间
    final Node<K,V>[] helpTransfer(Node<K,V>[] tab, Node<K,V> f) {
    Node<K,V>[] nextTab; int sc;
    //当满足如下条件才可以进行扩容
    if (tab != null && (f instanceof ForwardingNode) &&
        (nextTab = ((ForwardingNode<K,V>)f).nextTable) != null) {
        int rs = resizeStamp(tab.length);
        //循环，使用cas形成自旋锁
        while (nextTab == nextTable && table == tab &&
               (sc = sizeCtl) < 0) {
            if ((sc >>> RESIZE_STAMP_SHIFT) != rs || sc == rs + 1 ||
                sc == rs + MAX_RESIZERS || transferIndex <= 0)
                break;
            if (U.compareAndSwapInt(this, SIZECTL, sc, sc + 1)) {
            	//扩容
                transfer(tab, nextTab);
                break;
            }
        }
        return nextTab;
    }
    return table;
}
    • private final void transfer(Node<K,V>[] tab, Node<K,V>[] nextTab)扩容方法，主要采用了高低 位算法
    private final void transfer(Node<K,V>[] tab, Node<K,V>[] nextTab) {
    int n = tab.length, stride;
    if ((stride = (NCPU > 1) ? (n >>> 3) / NCPU : n) < MIN_TRANSFER_STRIDE)
        stride = MIN_TRANSFER_STRIDE; // subdivide range
    if (nextTab == null) {// 初始化新数组
        try {
           	//n << 1 新数组的长度为之前的2倍
            Node<K,V>[] nt = (Node<K,V>[])new Node<?,?>[n << 1];
            nextTab = nt;
        } catch (Throwable ex) {      // try to cope with OOME
            sizeCtl = Integer.MAX_VALUE;
            return;
        }
        nextTable = nextTab;
        transferIndex = n;
    }
    int nextn = nextTab.length;
    //创建一个占位node，标记当前map正在扩容
    ForwardingNode<K,V> fwd = new ForwardingNode<K,V>(nextTab);
    boolean advance = true;
    boolean finishing = false; // to ensure sweep before committing nextTab
    for (int i = 0, bound = 0;;) {
        Node<K,V> f; int fh;
        while (advance) {
            int nextIndex, nextBound;
            if (--i >= bound || finishing)
                advance = false;
            else if ((nextIndex = transferIndex) <= 0) {
                i = -1;
                advance = false;
            }
            else if (U.compareAndSwapInt
                     (this, TRANSFERINDEX, nextIndex,
                      nextBound = (nextIndex > stride ?
                                   nextIndex - stride : 0))) {
                bound = nextBound;
                i = nextIndex - 1;
                advance = false;
            }
        }
        if (i < 0 || i >= n || i + n >= nextn) {
            int sc;
            if (finishing) {
                nextTable = null;
                table = nextTab;
                sizeCtl = (n << 1) - (n >>> 1);
                return;
            }
            if (U.compareAndSwapInt(this, SIZECTL, sc = sizeCtl, sc - 1)) {
                if ((sc - 2) != resizeStamp(n) << RESIZE_STAMP_SHIFT)
                    return;
                finishing = advance = true;
                i = n; // recheck before commit
            }
        }
        else if ((f = tabAt(tab, i)) == null)
            advance = casTabAt(tab, i, null, fwd);
        else if ((fh = f.hash) == MOVED)
            advance = true; // already processed
        else {
            synchronized (f) {
                if (tabAt(tab, i) == f) {
                	//ln，低位节点，此节点不会在扩容时变换所在数组下标
                    //hn 高位节点，此节点在扩容时会向后移动，在数组的新下标为当前下标+扩容长度
                    Node<K,V> ln, hn;
                    if (fh >= 0) {
                    	// 这里面之所以这么算，是因为map扩容时采用了高低位算法，后续会讲解高低位算法
                        int runBit = fh & n;
                        Node<K,V> lastRun = f;
                        //lastRun默认是链表头节点，循环链表，是为了判断当前链表是否全部符合ln或hn
                        for (Node<K,V> p = f.next; p != null; p = p.next) {
                            int b = p.hash & n;
                            if (b != runBit) {
                                runBit = b;
                                lastRun = p;
                            }
                        }
                        if (runBit == 0) {
                            ln = lastRun;
                            hn = null;
                        }
                        else {
                            hn = lastRun;
                            ln = null;
                        }
                        //如果当前链表的头节点不等于lastRun，说明此链表中存在需要移动的节点。重新构建节点
                        for (Node<K,V> p = f; p != lastRun; p = p.next) {
                            int ph = p.hash; K pk = p.key; V pv = p.val;
                            if ((ph & n) == 0)
                                ln = new Node<K,V>(ph, pk, pv, ln);
                            else
                                hn = new Node<K,V>(ph, pk, pv, hn);
                        }
                        //将ln和hn放在新数组相应下标处
                        setTabAt(nextTab, i, ln);
                        setTabAt(nextTab, i + n, hn);
                        //将占位节点放到老数组i下标处
                        setTabAt(tab, i, fwd);
                        advance = true;
                    }
                    //红黑树处理
                    else if (f instanceof TreeBin) {
                        TreeBin<K,V> t = (TreeBin<K,V>)f;
                        TreeNode<K,V> lo = null, loTail = null;
                        TreeNode<K,V> hi = null, hiTail = null;
                        int lc = 0, hc = 0;
                        for (Node<K,V> e = t.first; e != null; e = e.next) {
                            int h = e.hash;
                            TreeNode<K,V> p = new TreeNode<K,V>
                                (h, e.key, e.val, null, null);
                            if ((h & n) == 0) {
                                if ((p.prev = loTail) == null)
                                    lo = p;
                                else
                                    loTail.next = p;
                                loTail = p;
                                ++lc;
                            }
                            else {
                                if ((p.prev = hiTail) == null)
                                    hi = p;
                                else
                                    hiTail.next = p;
                                hiTail = p;
                                ++hc;
                            }
                        }
                        ln = (lc <= UNTREEIFY_THRESHOLD) ? untreeify(lo) :
                            (hc != 0) ? new TreeBin<K,V>(lo) : t;
                        hn = (hc <= UNTREEIFY_THRESHOLD) ? untreeify(hi) :
                            (lc != 0) ? new TreeBin<K,V>(hi) : t;
                        setTabAt(nextTab, i, ln);
                        setTabAt(nextTab, i + n, hn);
                        setTabAt(tab, i, fwd);
                        advance = true;
                    }
                }
            }
        }
    }
}
    • 高低位算法

    int runBit = fh & n;头节点的hash值&原数组的长度，如果等于0则节点迁移时保持在数组原下标处否则需要迁移，迁移的新下标为当前下标+扩容长度。主要与获取节点所在数组下标的位置的算法有关即i = (n - 1) & hash 如图：图（a）表示扩容前的key1和key2两种key确定索引位置的示例，图（b）表示扩容后key1和key2两种key确定索引位置的示例，其中hash1是key1对应的哈希与高位运算结果。元素在重新计算hash之后，因为n变为2倍，那么n-1的mask范围在高位多1bit(红色)，因此新的index就会发生这样的变化 那么这句话的意思是什么呢，通过计算可知，任意一个数&2的n次幂要么等于0要么等于2的n次幂。当等于0的数刚好通过 i = (n - 1)& hash计算出的下标刚好是扩容前的下标。不等于0的数再通过计算后得到的下标刚好是扩容前下标+扩容的长度。

    • private final void addCount(long x, int check),添加计数并校验是否需要扩容
    private final void addCount(long x, int check) {
	//CounterCell计数器数组
   CounterCell[] as; long b, s;
   //cas操作，为baseCount赋值
   if ((as = counterCells) != null ||
       !U.compareAndSwapLong(this, BASECOUNT, b = baseCount, s = b + x)) {
       CounterCell a; long v; int m;
       boolean uncontended = true;
       //随机从as数组中获取CounterCell，并为CounterCell中value属性cas赋值
       if (as == null || (m = as.length - 1) < 0 ||
           (a = as[ThreadLocalRandom.getProbe() & m]) == null ||
           !(uncontended =
             U.compareAndSwapLong(a, CELLVALUE, v = a.value, v + x))) {
           //后续再讲吧
           fullAddCount(x, uncontended);
           return;
       }
       if (check <= 1)
           return;
       //统计下数量
       s = sumCount();
   }
   //处理扩容
   if (check >= 0) {
       Node<K,V>[] tab, nt; int n, sc;
       //s >= (long)(sc = sizeCtl)表示需要扩容
       while (s >= (long)(sc = sizeCtl) && (tab = table) != null &&
              (n = tab.length) < MAXIMUM_CAPACITY) {
           int rs = resizeStamp(n);
           if (sc < 0) {
               if ((sc >>> RESIZE_STAMP_SHIFT) != rs || sc == rs + 1 ||
                   sc == rs + MAX_RESIZERS || (nt = nextTable) == null ||
                   transferIndex <= 0)
                   break;
               if (U.compareAndSwapInt(this, SIZECTL, sc, sc + 1))
                   transfer(tab, nt);
           }
           else if (U.compareAndSwapInt(this, SIZECTL, sc,
                                        (rs << RESIZE_STAMP_SHIFT) + 2))
               transfer(tab, null);
           s = sumCount();
       }
   }
}
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