• 【面试专栏】第五篇:Java基础:集合篇-LinkedHashMap、ConcurrentHashMap、TreeMap


    🚩LinkedHashMap(底层是(数组+链表/红黑树)+环形双向链表,继承自HashMap)

    • LinkedHashMap是key键有序的HashMap的一种实现。它除了使用哈希表这个数据结构,使用环形双向链表来保证key的顺序。

    • HashMap是无序的,也就是说,迭代HashMap所得到的元素顺序并不是它们最初放置到HashMap的顺序。HashMap的这一缺点往往会造成诸多不便,因为在有些场景中,我们确需要用到一个可以保持插入顺序的Map。庆幸的是,JDK为我们解决了这个问题,它为HashMap提供了一个子类 —— LinkedHashMap。虽然LinkedHashMap增加了时间和空间上的开销,但是它通过维护一个额外的双向链表保证了迭代顺序。特别地,该迭代顺序可以是插入顺序,也可以是访问顺序。因此,根据链表中元素的顺序可以将LinkedHashMap分为:保持插入顺序的LinkedHashMap 和 保持访问顺序(LRU,get后调整链表序,最新获取的放在最后)的LinkedHashMap,其中LinkedHashMap的默认实现是按插入顺序排序的。

    • 特点:

    • 一般来说,如果需要使用的Map中的key无序,选择HashMap;如果要求key有序,则选择TreeMap。

    • 但是选择TreeMap就会有性能问题,因为TreeMap的get操作的时间复杂度是O(log(n))的,相比于HashMap的O(1)还是差不少的,LinkedHashMap的出现就是为了平衡这些因素,使得能够以O(1)时间复杂度增加查找元素,又能够保证key的有序性

    • 实现原理:

    • 将所有Entry节点链入一个双向链表的HashMap。在LinkedHashMap中,所有put进来的Entry都保存在哈希表中,但由于它又额外定义了一个以head为头结点的双向链表,因此对于每次put进来Entry,除了将其保存到哈希表上外,还会将其插入到双向链表的尾部。

    LinkedHashMap#Entry

    static class Entry extends HashMap.Node {
        Entry before, after;
        Entry(int hash, K key, V value, Node next) {
            super(hash, key, value, next);
        }
    }
    
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    成员变量

    /**
     * The head (eldest) of the doubly linked list.
     */
    transient LinkedHashMap.Entry head;
    
    /**
     * The tail (youngest) of the doubly linked list.
     */
    transient LinkedHashMap.Entry tail;
    
    /**
     * The iteration ordering method for this linked hash map: true
     * for access-order, false for insertion-order.
     *
     * @serial
     */
    final boolean accessOrder;
    
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    构造方法

    public LinkedHashMap(int initialCapacity, float loadFactor) {
        super(initialCapacity, loadFactor);
        accessOrder = false;
    }
    
    /**
     * Constructs an empty insertion-ordered LinkedHashMap instance
     * with the specified initial capacity and a default load factor (0.75).
     *
     * @param  initialCapacity the initial capacity
     * @throws IllegalArgumentException if the initial capacity is negative
     */
    public LinkedHashMap(int initialCapacity) {
        super(initialCapacity);
        accessOrder = false;
    }
    
    /**
     * Constructs an empty insertion-ordered LinkedHashMap instance
     * with the default initial capacity (16) and load factor (0.75).
     */
    public LinkedHashMap() {
        super();
        accessOrder = false;
    }
    
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    /**
     * Constructs an empty LinkedHashMap instance with the
     * specified initial capacity, load factor and ordering mode.
     *
     * @param  initialCapacity the initial capacity
     * @param  loadFactor      the load factor
     * @param  accessOrder     the ordering mode - true for
     *         access-order, false for insertion-order
     * @throws IllegalArgumentException if the initial capacity is negative
     *         or the load factor is nonpositive
     */
    public LinkedHashMap(int initialCapacity,
                         float loadFactor,
                         boolean accessOrder) {
        super(initialCapacity, loadFactor);
        this.accessOrder = accessOrder;
    }
    
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    put

    • 同HashMap,但重写了afterNodeInsertion。
    - void afterNodeInsertion(boolean evict) { // possibly remove eldest
        LinkedHashMap.Entry first;
        if (evict && (first = head) != null && removeEldestEntry(first)) {
            K key = first.key;
            removeNode(hash(key), key, null, false, true);
        }
    }
    //可以自行重写该方法
     protected boolean removeEldestEntry(Map.Entry eldest) {
        return false;
    }
     
    public class LRUHashMap extends LinkedHashMap{
    
            private final int MAX_CACHE_SIZE;
            public BaseLRUCache(int cacheSize) {
    
                  super(cacheSize, 0.75f, true);
                  MAX_CACHE_SIZE = cacheSize;
              }
    
              @Override
              protected boolean removeEldestEntry(Map.Entry eldest) {
                  return size() > MAX_CACHE_SIZE;
              }
    
    
     }
    
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    get

    public V get(Object key) {
        Node e;
        if ((e = getNode(hash(key), key)) == null)
            return null;
        if (accessOrder)
            afterNodeAccess(e);
        return e.value;
    }
    
    
     void afterNodeAccess(Node e) { // move node to last
        LinkedHashMap.Entry last;
        if (accessOrder && (last = tail) != e) {
            LinkedHashMap.Entry p =
                (LinkedHashMap.Entry)e, b = p.before, a = p.after;
            p.after = null;
            if (b == null)
                head = a;
            else
                b.after = a;
            if (a != null)
                a.before = b;
            else
                last = b;
            if (last == null)
                head = p;
            else {
                p.before = last;
                last.after = p;
            }
            tail = p;
            ++modCount;
        }
    }
    
    
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    remove

    • 同HashMap,但重写了afterNodeRemoval。
      void afterNodeRemoval(Node e) { // unlink
        LinkedHashMap.Entry p =
            (LinkedHashMap.Entry)e, b = p.before, a = p.after;
        p.before = p.after = null;
        if (b == null)
            head = a;
        else
            b.after = a;
        if (a == null)
            tail = b;
        else
            a.before = b;
    }
    
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    遍历(迭代环形双向链表)

    entrySet

    public Set> entrySet() {
        Set> es;
        return (es = entrySet) == null ? (entrySet = new LinkedEntrySet()) : es;
    }
    
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    • 它使用的是该迭代器:
    abstract class LinkedHashIterator {
        LinkedHashMap.Entry next;
        LinkedHashMap.Entry current;
        int expectedModCount;
    
        LinkedHashIterator() {
            next = head;
            expectedModCount = modCount;
            current = null;
        }
    
        public final boolean hasNext() {
            return next != null;
        }
    
        final LinkedHashMap.Entry nextNode() {
            LinkedHashMap.Entry e = next;
            if (modCount != expectedModCount)
                throw new ConcurrentModificationException();
            if (e == null)
                throw new NoSuchElementException();
            current = e;
            next = e.after;
            return e;
        }
    
        public final void remove() {
            Node p = current;
            if (p == null)
                throw new IllegalStateException();
            if (modCount != expectedModCount)
                throw new ConcurrentModificationException();
            current = null;
            K key = p.key;
            removeNode(hash(key), key, null, false, false);
            expectedModCount = modCount;
        }
    } 
    final class LinkedEntryIterator extends LinkedHashIterator
        implements Iterator> {
        public final Map.Entry next() { return nextNode(); }
    }
    
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    🚩TreeMap(底层是红黑树)

    • 支持排序的Map实现。

    • 基于红黑树实现,无容量限制。

    • 是非线程安全的。

    • TreeMap是根据key进行排序的,它的排序和定位需要依赖比较器或覆写Comparable接口,也因此不需要key覆写hashCode方法和equals方法,就可以排除掉重复的key,而HashMap的key则需要通过覆写hashCode方法和equals方法来确保没有重复的key

    • TreeMap的查询、插入、删除效率均没有HashMap高,一般只有要对key排序时才使用TreeMap。

    • TreeMap的key不能为null,而HashMap的key可以为null。

    • TreeMap#Entry

    static final class Entry implements Map.Entry {
        K key;
        V value;
        Entry left;
        Entry right;
        Entry parent;
        boolean color = BLACK;
    
        /**
         * Make a new cell with given key, value, and parent, and with
         * {@code null} child links, and BLACK color.
         */
        Entry(K key, V value, Entry parent) {
            this.key = key;
            this.value = value;
            this.parent = parent;
        }
    
        /**
         * Returns the key.
         *
         * @return the key
         */
        public K getKey() {
            return key;
        }
    
        /**
         * Returns the value associated with the key.
         *
         * @return the value associated with the key
         */
        public V getValue() {
            return value;
        }
    
        /**
         * Replaces the value currently associated with the key with the given
         * value.
         *
         * @return the value associated with the key before this method was
         *         called
         */
        public V setValue(V value) {
            V oldValue = this.value;
            this.value = value;
            return oldValue;
        }
    
        public boolean equals(Object o) {
            if (!(o instanceof Map.Entry))
                return false;
            Map.Entry e = (Map.Entry)o;
    
            return valEquals(key,e.getKey()) && valEquals(value,e.getValue());
        }
    
        public int hashCode() {
            int keyHash = (key==null ? 0 : key.hashCode());
            int valueHash = (value==null ? 0 : value.hashCode());
            return keyHash ^ valueHash;
        }
    
        public String toString() {
            return key + "=" + value;
        }
    }
    
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    成员变量

    private final Comparator comparator;
    
    private transient Entry root;
    
    /**
     * The number of entries in the tree
     */
    private transient int size = 0;
    
    /**
     * The number of structural modifications to the tree.
     */
    private transient int modCount = 0;
    
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    构造方法

    public TreeMap() {
        comparator = null;
    }
    
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    public TreeMap(Comparator comparator) {
        this.comparator = comparator;
    }
    
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    put

    public V put(K key, V value) {
        Entry t = root;
        if (t == null) {
            compare(key, key); // type (and possibly null) check
    
            root = new Entry<>(key, value, null);
            size = 1;
            modCount++;
            return null;
        }
        int cmp;
        Entry parent;
        // split comparator and comparable paths
        Comparator cpr = comparator;
        if (cpr != null) {
            do {
                parent = t;
                cmp = cpr.compare(key, t.key);
                if (cmp < 0)
                    t = t.left;
                else if (cmp > 0)
                    t = t.right;
                else
                    return t.setValue(value);
            } while (t != null);
        }
        else {
            if (key == null)
                throw new NullPointerException();
            @SuppressWarnings("unchecked")
                Comparable k = (Comparable) key;
            do {
                parent = t;
                cmp = k.compareTo(t.key);
                if (cmp < 0)
                    t = t.left;
                else if (cmp > 0)
                    t = t.right;
                else
                    return t.setValue(value);
            } while (t != null);
        }
        Entry e = new Entry<>(key, value, parent);
        if (cmp < 0)
            parent.left = e;
        else
            parent.right = e;
        fixAfterInsertion(e);
        size++;
        modCount++;
        return null;
    }
    
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    get

    public V get(Object key) {
        Entry p = getEntry(key);
        return (p==null ? null : p.value);
    }
    
     final Entry getEntry(Object key) {
        // Offload comparator-based version for sake of performance
        if (comparator != null)
            return getEntryUsingComparator(key);
        if (key == null)
            throw new NullPointerException();
        @SuppressWarnings("unchecked")
            Comparable k = (Comparable) key;
        Entry p = root;
        while (p != null) {
            int cmp = k.compareTo(p.key);
            if (cmp < 0)
                p = p.left;
            else if (cmp > 0)
                p = p.right;
            else
                return p;
        }
        return null;
    }
    
     final Entry getEntryUsingComparator(Object key) {
        @SuppressWarnings("unchecked")
            K k = (K) key;
        Comparator cpr = comparator;
        if (cpr != null) {
            Entry p = root;
            while (p != null) {
                int cmp = cpr.compare(k, p.key);
                if (cmp < 0)
                    p = p.left;
                else if (cmp > 0)
                    p = p.right;
                else
                    return p;
            }
        }
        return null;
    }
    
    
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    remove

    public V remove(Object key) {
        Entry p = getEntry(key);
        if (p == null)
            return null;
    
        V oldValue = p.value;
        deleteEntry(p);
        return oldValue;
    } 
    private void deleteEntry(Entry p) {
        modCount++;
        size--;
    
        // If strictly internal, copy successor's element to p and then make p
        // point to successor.
        if (p.left != null && p.right != null) {
            Entry s = successor(p);
            p.key = s.key;
            p.value = s.value;
            p = s;
        } // p has 2 children
    
        // Start fixup at replacement node, if it exists.
        Entry replacement = (p.left != null ? p.left : p.right);
    
        if (replacement != null) {
            // Link replacement to parent
            replacement.parent = p.parent;
            if (p.parent == null)
                root = replacement;
            else if (p == p.parent.left)
                p.parent.left  = replacement;
            else
                p.parent.right = replacement;
    
            // Null out links so they are OK to use by fixAfterDeletion.
            p.left = p.right = p.parent = null;
    
            // Fix replacement
            if (p.color == BLACK)
                fixAfterDeletion(replacement);
        } else if (p.parent == null) { // return if we are the only node.
            root = null;
        } else { //  No children. Use self as phantom replacement and unlink.
            if (p.color == BLACK)
                fixAfterDeletion(p);
    
            if (p.parent != null) {
                if (p == p.parent.left)
                    p.parent.left = null;
                else if (p == p.parent.right)
                    p.parent.right = null;
                p.parent = null;
            }
        }
    }
    
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    containsKey

    public boolean containsKey(Object key) {
        return getEntry(key) != null;
    }
    
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    containsValue

    public boolean containsValue(Object value) {
        for (Entry e = getFirstEntry(); e != null; e = successor(e))
            if (valEquals(value, e.value))
                return true;
        return false;
    }
    final Entry getFirstEntry() {
        Entry p = root;
        if (p != null)
            while (p.left != null)
                p = p.left;
        return p;
    }
    
     static  TreeMap.Entry successor(Entry t) {
        if (t == null)
            return null;
        else if (t.right != null) {
            Entry p = t.right;
            while (p.left != null)
                p = p.left;
            return p;
        } else {
            Entry p = t.parent;
            Entry ch = t;
            while (p != null && ch == p.right) {
                ch = p;
                p = p.parent;
            }
            return p;
        }
    }
    
        static final boolean valEquals(Object o1, Object o2) {
        return (o1==null ? o2==null : o1.equals(o2));
    }
    
    
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    遍历

    public Set> entrySet() {
        EntrySet es = entrySet;
        return (es != null) ? es : (entrySet = new EntrySet());
    } 
    class EntrySet extends AbstractSet> {
        public Iterator> iterator() {
            return new EntryIterator(getFirstEntry());
        } 
        }
    
     
    abstract class PrivateEntryIterator implements Iterator {
        Entry next;
        Entry lastReturned;
        int expectedModCount;
    
        PrivateEntryIterator(Entry first) {
            expectedModCount = modCount;
            lastReturned = null;
            next = first;
        }
    
        public final boolean hasNext() {
            return next != null;
        }
    
        final Entry nextEntry() {
            Entry e = next;
            if (e == null)
                throw new NoSuchElementException();
            if (modCount != expectedModCount)
                throw new ConcurrentModificationException();
            next = successor(e);
            lastReturned = e;
            return e;
        }
    
        final Entry prevEntry() {
            Entry e = next;
            if (e == null)
                throw new NoSuchElementException();
            if (modCount != expectedModCount)
                throw new ConcurrentModificationException();
            next = predecessor(e);
            lastReturned = e;
            return e;
        }
    
        public void remove() {
            if (lastReturned == null)
                throw new IllegalStateException();
            if (modCount != expectedModCount)
                throw new ConcurrentModificationException();
            // deleted entries are replaced by their successors
            if (lastReturned.left != null && lastReturned.right != null)
                next = lastReturned;
            deleteEntry(lastReturned);
            expectedModCount = modCount;
            lastReturned = null;
        }
    } 
    final class EntryIterator extends PrivateEntryIterator> {
        EntryIterator(Entry first) {
            super(first);
        }
        public Map.Entry next() {
            return nextEntry();
        }
    }
    
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    🚩ConcurrentHashMap(底层是数组+链表/红黑树,基于CAS+synchronized)

    • JDK1.7前:分段锁

    • 基于currentLevel划分出了多个Segment来对key-value进行存储,从而避免每次put操作都得锁住整个数组。在默认的情况下,最佳情况下可以允许16个线程并发无阻塞地操作集合对象,尽可能地减少并发时的阻塞现象。

    • put、remove会加锁。get和containsKey不会加锁。

    • 计算size:在不加锁的情况下遍历所有的段,读取其count以及modCount,这两个属性都是volatile类型的,并进行统计,再遍历一次所有的段,比较modCount是否有改变。如有改变,则再尝试两次机上动作。

    • 如执行了三次上述动作,仍然有问题,则遍历所有段,分别进行加锁,然后进行计算,计算完毕后释放所有锁,从而完成计算动作。

    • JDK1.8后:CAS+synchronized

    • bin是桶 bucket的意思

    • ConcurrentHashMap是延迟初始化的,只有在插入数据时,整个HashMap才被初始化为2的次方大小个桶(bin),每个bin包含哈希值相同的一系列Node(一般含有0或1个Node)。每个bin的第一个Node作为这个bin的锁,Hash值为零或者负的将被忽略;

    • 每个bin的第一个Node插入用到CAS原理,这是在ConcurrentHashMap中最常发生的操作,其余的插入、删除、替换操作对bin中的第一个Node加锁,进行操作

    • ConcurrentHashMap的size()函数一般比较少用,同时为了提高增删查改的效率,容器并未在内部保存一个size值,而且采用每次调用size()函数时累加各个bin中Node的个数计算得到,而且这一过程不加锁,即得到的size值不一定是最新的。

    • ConcurrentHashMap#Node

    • Node是最核心的内部类,它包装了key-value键值对,所有插入ConcurrentHashMap的数据都包装在这里面。它与HashMap中的定义很相似,但是但是有一些差别:它对value和next属性设置了volatile属性;’它不允许调用setValue方法直接改变Node的value域;它增加了find方法辅助map.get()方法。

    static class Node implements Map.Entry {
        final int hash;
        final K key;
        volatile V val; // value和next是volatile的
        volatile Node next;
    
        Node(int hash, K key, V val, Node next) {
            this.hash = hash;
            this.key = key;
            this.val = val;
            this.next = next;
        }
    
        public final K getKey()       { return key; }
        public final V getValue()     { return val; }
        public final int hashCode()   { return key.hashCode() ^ val.hashCode(); }
        public final String toString(){ return key + "=" + val; }
        public final V setValue(V value) {
            throw new UnsupportedOperationException();
        }
    
        public final boolean equals(Object o) {
            Object k, v, u; Map.Entry e;
            return ((o instanceof Map.Entry) &&
                    (k = (e = (Map.Entry)o).getKey()) != null &&
                    (v = e.getValue()) != null &&
                    (k == key || k.equals(key)) &&
                    (v == (u = val) || v.equals(u)));
        }
    
        /**
         * Virtualized support for map.get(); overridden in subclasses.
         */
        Node find(int h, Object k) {
            Node e = this;
            if (k != null) {
                do {
                    K ek;
                    if (e.hash == h &&
                        ((ek = e.key) == k || (ek != null && k.equals(ek))))
                        return e;
                } while ((e = e.next) != null);
            }
            return null;
        }
    }
    
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    ConcurrentHashMap#TreeNode

    • 当链表长度过长的时候,会转换为TreeNode。但是与HashMap不相同的是,它并不是直接转换为红黑树,而是把这些结点包装成TreeNode放在TreeBin对象中,由TreeBin完成对红黑树的包装。而且TreeNode在ConcurrentHashMap继承自Node类,而并非HashMap中的继承自LinkedHashMap.Entry类,也就是说TreeNode带有next指针,这样做的目的是方便基于TreeBin的访问。
    static final class TreeNode extends Node {
        TreeNode parent;  // red-black tree links
        TreeNode left;
        TreeNode right;
        TreeNode prev;    // needed to unlink next upon deletion
        boolean red;
    
        TreeNode(int hash, K key, V val, Node next,
                 TreeNode parent) {
            super(hash, key, val, next);
            this.parent = parent;
        }
    
        Node find(int h, Object k) {
            return findTreeNode(h, k, null);
        }
    
        /**
         * Returns the TreeNode (or null if not found) for the given key
         * starting at given root.
         */
        final TreeNode findTreeNode(int h, Object k, Class kc) {
            if (k != null) {
                TreeNode p = this;
                do  {
                    int ph, dir; K pk; TreeNode q;
                    TreeNode pl = p.left, pr = p.right;
                    if ((ph = p.hash) > h)
                        p = pl;
                    else if (ph < h)
                        p = pr;
                    else if ((pk = p.key) == k || (pk != null && k.equals(pk)))
                        return p;
                    else if (pl == null)
                        p = pr;
                    else if (pr == null)
                        p = pl;
                    else if ((kc != null ||
                              (kc = comparableClassFor(k)) != null) &&
                             (dir = compareComparables(kc, k, pk)) != 0)
                        p = (dir < 0) ? pl : pr;
                    else if ((q = pr.findTreeNode(h, k, kc)) != null)
                        return q;
                    else
                        p = pl;
                } while (p != null);
            }
            return null;
        }
    }
    
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    ConcurrentHashMap#TreeBin

    • 这个类并不负责包装用户的key、value信息,而是包装的很多TreeNode节点。它代替了TreeNode的根节点,也就是说在实际的ConcurrentHashMap“数组”中,存放的是TreeBin对象,而不是TreeNode对象,这是与HashMap的区别。另外这个类还带有了读写锁。
    • 可以看到在构造TreeBin节点时,仅仅指定了它的hash值为TREEBIN常量,这也就是个标识位;同时也看到我们熟悉的红黑树构造方法。
    /**
     * TreeNodes used at the heads of bins. TreeBins do not hold user
     * keys or values, but instead point to list of TreeNodes and
     * their root. They also maintain a parasitic read-write lock
     * forcing writers (who hold bin lock) to wait for readers (who do
     * not) to complete before tree restructuring operations.
     */
    static final class TreeBin extends Node {
        TreeNode root;
        volatile TreeNode first;
        volatile Thread waiter;
        volatile int lockState;
        // values for lockState
        static final int WRITER = 1; // set while holding write lock
        static final int WAITER = 2; // set when waiting for write lock
        static final int READER = 4; // increment value for setting read lock
    
        /**
         * Tie-breaking utility for ordering insertions when equal
         * hashCodes and non-comparable. We don't require a total
         * order, just a consistent insertion rule to maintain
         * equivalence across rebalancings. Tie-breaking further than
         * necessary simplifies testing a bit.
         */
        static int tieBreakOrder(Object a, Object b) {
            int d;
            if (a == null || b == null ||
                (d = a.getClass().getName().
                 compareTo(b.getClass().getName())) == 0)
                d = (System.identityHashCode(a) <= System.identityHashCode(b) ?
                     -1 : 1);
            return d;
        }
    
        /**
         * Creates bin with initial set of nodes headed by b.
         */
        TreeBin(TreeNode b) {
            super(TREEBIN, null, null, null);
            this.first = b;
            TreeNode r = null;
            for (TreeNode x = b, next; x != null; x = next) {
                next = (TreeNode)x.next;
                x.left = x.right = null;
                if (r == null) {
                    x.parent = null;
                    x.red = false;
                    r = x;
                }
                else {
                    K k = x.key;
                    int h = x.hash;
                    Class kc = null;
                    for (TreeNode p = r;;) {
                        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 xp = p;
                        if ((p = (dir <= 0) ? p.left : p.right) == null) {
                            x.parent = xp;
                            if (dir <= 0)
                                xp.left = x;
                            else
                                xp.right = x;
                            r = balanceInsertion(r, x);
                            break;
                        }
                    }
                }
            }
            this.root = r;
            assert checkInvariants(root);
        }
     }
    
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    ConcurrentHashMap#ForwardingNode

    /**
     * A node inserted at head of bins during transfer operations.
     */
    static final class ForwardingNode extends Node {
        final Node[] nextTable;
        ForwardingNode(Node[] tab) {
            super(MOVED, null, null, null);
            this.nextTable = tab;
        }
    
        Node find(int h, Object k) {
            // loop to avoid arbitrarily deep recursion on forwarding nodes
            outer: for (Node[] tab = nextTable;;) {
                Node e; int n;
                if (k == null || tab == null || (n = tab.length) == 0 ||
                    (e = tabAt(tab, (n - 1) & h)) == null)
                    return null;
                for (;;) {
                    int eh; K ek;
                    if ((eh = e.hash) == h &&
                        ((ek = e.key) == k || (ek != null && k.equals(ek))))
                        return e;
                    if (eh < 0) {
                        if (e instanceof ForwardingNode) {
                            tab = ((ForwardingNode)e).nextTable;
                            continue outer;
                        }
                        else
                            return e.find(h, k);
                    }
                    if ((e = e.next) == null)
                        return null;
                }
            }
        }
    }
    
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    ConcurrentHashMap#ReservationNode

    /**
     * A place-holder node used in computeIfAbsent and compute
     */
    static final class ReservationNode extends Node {
        ReservationNode() {
            super(RESERVED, null, null, null);
        }
    
        Node find(int h, Object k) {
            return null;
        }
    }
    
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    节点类型

    • hash值大于等于0,则是链表节点,Node

    • hash值为-1 MOVED,则是forwarding nodes,存储nextTable的引用。只有table发生扩容的时候,ForwardingNode才会发挥作用,作为一个占位符放在table中表示当前节点为null或则已经被移动。

    • hash值为-2 TREEBIN,则是红黑树根,TreeBin类型

    • hash值为-3 RESERVED,则是reservation nodes,

    • static final int MOVED = -1; // hash for forwarding nodes
      static final int TREEBIN = -2; // hash for roots of trees
      static final int RESERVED = -3; // hash for transient reservations

    成员变量

    /**
     * The largest possible table capacity.  This value must be
     * exactly 1<<30 to stay within Java array allocation and indexing
     * bounds for power of two table sizes, and is further required
     * because the top two bits of 32bit hash fields are used for
     * control purposes.
     */
    private static final int MAXIMUM_CAPACITY = 1 << 30;
    
    /**
     * The default initial table capacity.  Must be a power of 2
     * (i.e., at least 1) and at most MAXIMUM_CAPACITY.
     */
    private static final int DEFAULT_CAPACITY = 16;
    
    /**
     * The largest possible (non-power of two) array size.
     * Needed by toArray and related methods.
     */
    static final int MAX_ARRAY_SIZE = Integer.MAX_VALUE - 8;
    
    /**
     * The default concurrency level for this table. Unused but
     * defined for compatibility with previous versions of this class.
     */
    private static final int DEFAULT_CONCURRENCY_LEVEL = 16;
    
    /**
     * The load factor for this table. Overrides of this value in
     * constructors affect only the initial table capacity.  The
     * actual floating point value isn't normally used -- it is
     * simpler to use expressions such as {@code n - (n >>> 2)} for
     * the associated resizing threshold.
     */
    private static final float LOAD_FACTOR = 0.75f;
    
    /**
     * The bin count threshold for using a tree rather than list for a
     * bin.  Bins are converted to trees when adding an element to a
     * bin with at least this many nodes. The value must be greater
     * than 2, and should be at least 8 to mesh with assumptions in
     * tree removal about conversion back to plain bins upon
     * shrinkage.
     */
    static final int TREEIFY_THRESHOLD = 8;
    
    /**
     * The bin count threshold for untreeifying a (split) bin during a
     * resize operation. Should be less than TREEIFY_THRESHOLD, and at
     * most 6 to mesh with shrinkage detection under removal.
     */
    static final int UNTREEIFY_THRESHOLD = 6;
    
    /**
     * The smallest table capacity for which bins may be treeified.
     * (Otherwise the table is resized if too many nodes in a bin.)
     * The value should be at least 4 * TREEIFY_THRESHOLD to avoid
     * conflicts between resizing and treeification thresholds.
     */
    static final int MIN_TREEIFY_CAPACITY = 64;
    
    /**
     * Minimum number of rebinnings per transfer step. Ranges are
     * subdivided to allow multiple resizer threads.  This value
     * serves as a lower bound to avoid resizers encountering
     * excessive memory contention.  The value should be at least
     * DEFAULT_CAPACITY.
     */
    private static final int MIN_TRANSFER_STRIDE = 16;
    
    /**
     * The number of bits used for generation stamp in sizeCtl.
     * Must be at least 6 for 32bit arrays.
     */
    private static int RESIZE_STAMP_BITS = 16;
    
    /**
     * The maximum number of threads that can help resize.
     * Must fit in 32 - RESIZE_STAMP_BITS bits.
     */
    private static final int MAX_RESIZERS = (1 << (32 - RESIZE_STAMP_BITS)) - 1;
    
    /**
     * The bit shift for recording size stamp in sizeCtl.
     */
    private static final int RESIZE_STAMP_SHIFT = 32 - RESIZE_STAMP_BITS;
    /*
     * Encodings for Node hash fields. See above for explanation.
     */
    static final int MOVED     = -1; // hash for forwarding nodes
    static final int TREEBIN   = -2; // hash for roots of trees
    static final int RESERVED  = -3; // hash for transient reservations
    static final int HASH_BITS = 0x7fffffff; // usable bits of normal node hash
    
    /** Number of CPUS, to place bounds on some sizings */
    static final int NCPU = Runtime.getRuntime().availableProcessors();
    
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    /**
     * The array of bins. Lazily initialized upon first insertion.
     * Size is always a power of two. Accessed directly by iterators.
     */
    transient volatile Node[] table;
    
    /**
     * The next table to use; non-null only while resizing.
     */
    private transient volatile Node[] nextTable;
    
    /**
     * Base counter value, used mainly when there is no contention,
     * but also as a fallback during table initialization
     * races. Updated via CAS.
     */
    private transient volatile long baseCount;
    
    /**
     * Table initialization and resizing control.  When negative, the
     * table is being initialized or resized: -1 for initialization,
     * else -(1 + the number of active resizing threads).  Otherwise,
     * when table is null, holds the initial table size to use upon
     * creation, or 0 for default. After initialization, holds the
     * next element count value upon which to resize the table.
    
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    • 负数代表正在进行初始化或扩容操作
    • -1代表正在初始化
    • -N 表示有N-1个线程正在进行扩容操作
    正数或0代表hash表还没有被初始化,这个数值表示初始化或下一次进行扩容的大小,这一点类似于扩容阈值的概念。还后面可以看到,它的值始终是当前ConcurrentHashMap容量的0.75倍,这与loadfactor是对应的。
     */
    private transient volatile int sizeCtl;
    
    /**
     * The next table index (plus one) to split while resizing.
     */
    private transient volatile int transferIndex;
    
    /**
     * Spinlock (locked via CAS) used when resizing and/or creating CounterCells.
     */
    private transient volatile int cellsBusy;
    
    /**
     * Table of counter cells. When non-null, size is a power of 2.
     */
    private transient volatile CounterCell[] counterCells;
    
    // views
    private transient KeySetView keySet;
    private transient ValuesView values;
    private transient EntrySetView entrySet;
    
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    构造方法

    public ConcurrentHashMap() {
    }
    
    /**
     * Creates a new, empty map with an initial table size
     * accommodating the specified number of elements without the need
     * to dynamically resize.
     *
     * @param initialCapacity The implementation performs internal
     * sizing to accommodate this many elements.
     * @throws IllegalArgumentException if the initial capacity of
     * elements is negative
     */
    public ConcurrentHashMap(int initialCapacity) {
        if (initialCapacity < 0)
            throw new IllegalArgumentException();
        int cap = ((initialCapacity >= (MAXIMUM_CAPACITY >>> 1)) ?
                   MAXIMUM_CAPACITY :
                   tableSizeFor(initialCapacity + (initialCapacity >>> 1) + 1));
        this.sizeCtl = cap;
    }
    
    /**
     * Creates a new map with the same mappings as the given map.
     *
     * @param m the map
     */
    public ConcurrentHashMap(Map m) {
        this.sizeCtl = DEFAULT_CAPACITY;
        putAll(m);
    }
    
    /**
     * Creates a new, empty map with an initial table size based on
     * the given number of elements ({@code initialCapacity}) and
     * initial table density ({@code loadFactor}).
     *
     * @param initialCapacity the initial capacity. The implementation
     * performs internal sizing to accommodate this many elements,
     * given the specified load factor.
     * @param loadFactor the load factor (table density) for
     * establishing the initial table size
     * @throws IllegalArgumentException if the initial capacity of
     * elements is negative or the load factor is nonpositive
     *
     * @since 1.6
     */
    public ConcurrentHashMap(int initialCapacity, float loadFactor) {
        this(initialCapacity, loadFactor, 1);
    }
    
    /**
     * Creates a new, empty map with an initial table size based on
     * the given number of elements ({@code initialCapacity}), table
     * density ({@code loadFactor}), and number of concurrently
     * updating threads ({@code concurrencyLevel}).
     *
     * @param initialCapacity the initial capacity. The implementation
     * performs internal sizing to accommodate this many elements,
     * given the specified load factor.
     * @param loadFactor the load factor (table density) for
     * establishing the initial table size
     * @param concurrencyLevel the estimated number of concurrently
     * updating threads. The implementation may use this value as
     * a sizing hint.
     * @throws IllegalArgumentException if the initial capacity is
     * negative or the load factor or concurrencyLevel are
     * nonpositive
     */
    public ConcurrentHashMap(int initialCapacity,
                             float loadFactor, int concurrencyLevel) {
        if (!(loadFactor > 0.0f) || initialCapacity < 0 || concurrencyLevel <= 0)
            throw new IllegalArgumentException();
        if (initialCapacity < concurrencyLevel)   // Use at least as many bins
            initialCapacity = concurrencyLevel;   // as estimated threads
        long size = (long)(1.0 + (long)initialCapacity / loadFactor);
        int cap = (size >= (long)MAXIMUM_CAPACITY) ?
            MAXIMUM_CAPACITY : tableSizeFor((int)size);
        this.sizeCtl = cap;
    }
    
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    CAS

    private static final sun.misc.Unsafe U;
    
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    • Unsafe类的几个CAS方法,可以原子性地修改对象的某个属性值
    /**
     * Atomically update Java variable to x if it is currently
     * holding expected.
     * @return true if successful
     */
    public final native boolean compareAndSwapObject(Object o, long offset,
                                                     Object expected,
                                                     Object x);
    
    /**
     * Atomically update Java variable to x if it is currently
     * holding expected.
     * @return true if successful
     */
    public final native boolean compareAndSwapInt(Object o, long offset,
                                                  int expected,
                                                  int x);
    
    /**
     * Atomically update Java variable to x if it is currently
     * holding expected.
     * @return true if successful
     */
    public final native boolean compareAndSwapLong(Object o, long offset,
                                                   long expected,
                                                   long x);
    
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    /**
     * Fetches a reference value from a given Java variable, with volatile
     * load semantics. Otherwise identical to {@link #getObject(Object, long)}
     */
    public native Object getObjectVolatile(Object o, long offset);
    
    /**
     * Stores a reference value into a given Java variable, with
     * volatile store semantics. Otherwise identical to {@link #putObject(Object, long, Object)}
     */
    public native void    putObjectVolatile(Object o, long offset, Object x);
    
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    • Unsafe.getObjectVolatile可以直接获取指定内存的数据,保证了每次拿到数据都是最新的。

    三个核心方法

    • ConcurrentHashMap定义了三个原子操作,用于对指定位置的节点进行操作。正是这些原子操作保证了ConcurrentHashMap的线程安全。
    static final  Node tabAt(Node[] tab, int i) {
        return (Node)U.getObjectVolatile(tab, ((long)i << ASHIFT) + ABASE);
    }
    
    static final  boolean casTabAt(Node[] tab, int i,
                                        Node c, Node v) {
        return U.compareAndSwapObject(tab, ((long)i << ASHIFT) + ABASE, c, v);
    }
    
    static final  void setTabAt(Node[] tab, int i, Node v) {
        U.putObjectVolatile(tab, ((long)i << ASHIFT) + ABASE, v);
    }
    
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    初始化

    • 对于ConcurrentHashMap来说,调用它的构造方法仅仅是设置了一些参数而已。而整个table的初始化是在向ConcurrentHashMap中插入元素的时候发生的。如调用put、computeIfAbsent、compute、merge等方法的时候,调用时机是检查table==null。
    • 初始化方法主要应用了关键属性sizeCtl 如果这个值<0,表示其他线程正在进行初始化,就放弃这个操作。在这也可以看出ConcurrentHashMap的初始化只能由一个线程完成。如果获得了初始化权限,就用CAS方法将sizeCtl置为-1,防止其他线程进入。初始化数组后,将sizeCtl的值改为0.75*n。
    private final Node[] initTable() {
        Node[] tab; int sc;
        while ((tab = table) == null || tab.length == 0) {
            if ((sc = sizeCtl) < 0)
                Thread.yield(); // lost initialization race; just spin
        // 利用CAS方法把sizectl的值置为-1 表示本线程正在进行初始化  
            else if (U.compareAndSwapInt(this, SIZECTL, sc, -1)) {
                try {
                    if ((tab = table) == null || tab.length == 0) {
                        int n = (sc > 0) ? sc : DEFAULT_CAPACITY;
                        @SuppressWarnings("unchecked")
                        Node[] nt = (Node[])new Node[n];
                        table = tab = nt;
        // 相当于0.75*n 设置一个扩容的阈值  
                        sc = n - (n >>> 2);
                    }
                } finally {
                    sizeCtl = sc;
                }
                break;
            }
        }
        return tab;
    }
    
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    spread(hash)

    • h是某个对象的hashCode返回值
    static final int spread(int h) {
        return (h ^ (h >>> 16)) & HASH_BITS;
    }
    
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    • static final int HASH_BITS = 0x7fffffff; // usable bits of normal node hash

    • 类似于Hashtable+HashMap的hash实现,Hashtable中也是和一个魔法值取与,保证结果一定为正数;HashMap中也是将hashCode与其移动低n位的结果再取异或,保证了对象的hashCode的高16位的变化能反应到低16位中,

    size相关

    成员变量

    @sun.misc.Contended static final class CounterCell {
        volatile long value;
        CounterCell(long x) { value = x; }
    }
    
    /**
     * Base counter value, used mainly when there is no contention,
     * but also as a fallback during table initialization
     * races. Updated via CAS.
     */
    private transient volatile long baseCount;
    
    /**
     * Spinlock (locked via CAS) used when resizing and/or creating CounterCells.
     */
    private transient volatile int cellsBusy;
    
    /**
     * Table of counter cells. When non-null, size is a power of 2.
     */
    private transient volatile CounterCell[] counterCells;
    
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    • 每个CounterCell都对应一个bucket,CounterCell中的long值就是对应bucket的binCount。
    • 计算总大小就是将所有bucket的binCount求和,而每个binCount都存储在CounterCell#value中,每当put或者remove时都会更新节点所在bucket对应的CounterCell#value。

    size()

    • 没有直接返回baseCount 而是统计一次这个值,而这个值其实也是一个大概的数值,因此可能在统计的时候有其他线程正在执行插入或删除操作。
    public int size() {
        long n = sumCount();
        return ((n < 0L) ? 0 :
                (n > (long)Integer.MAX_VALUE) ? Integer.MAX_VALUE :
                (int)n);
    }
    
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    • 在baseCount基础上再加上所有counterCell的值求和。
    • 而在addCount时,会先尝试CAS更新baseCount,如果有冲突,则再尝试CAS更新随机的一个counterCell中的value,这样求和就是正确的size了。
    final long sumCount() {
        CounterCell[] as = counterCells; 
        CounterCell a;
        long sum = baseCount;
        if (as != null) {
            for (int i = 0; i < as.length; ++i) {
                if ((a = as[i]) != null)
                    // 所有counter的值求和  
                    sum += a.value;
            }
        }
        return sum;
    }
    
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    put(若bucket第一个结点插入则使用CAS,否则加锁)

    public V put(K key, V value) {
        return putVal(key, value, false);
    }
    
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    整体流程就是首先定义不允许key或value为null的情况放入 。对于每一个放入的值,首先利用spread方法对key的hashcode进行一次hash计算,由此来确定这个值在table中的位置。
    - 如果这个位置是空的,那么直接放入,而且不需要加锁操作。
    - 如果这个位置存在结点,说明发生了hash碰撞,首先判断这个节点的类型。
    - 如果是MOVED节点,则表示正在扩容,帮助进行扩容
    - 如果是链表节点(hash >=0),则得到的结点就是hash值相同的节点组成的链表的头节点。需要依次向后遍历确定这个新加入的值所在位置。如果遇到hash值与key值都与新加入节点是一致的情况,则只需要更新value值即可。否则依次向后遍历,直到链表尾插入这个结点。 如果加入这个节点以后链表长度大于8,就把这个链表转换成红黑树。
    - 如果这个节点的类型已经是树节点的话,直接调用树节点的插入方法进行插入新的值。
    - addCount 增加计数值

    /** Implementation for put and putIfAbsent */
    final V putVal(K key, V value, boolean onlyIfAbsent) {
        if (key == null || value == null) throw new NullPointerException();
        int hash = spread(key.hashCode());
        int binCount = 0;
    // 死循环,只有插入成功时才会跳出
        for (Node[] tab = table;;) {
            Node f; int n, i, fh;
            if (tab == null || (n = tab.length) == 0)
        // table为空则初始化(延迟初始化)
                tab = initTable();
            else if ((f = tabAt(tab, i = (n - 1) & hash)) == null) {
    // hash to index后正好为空,则CAS放入;如果失败那么进入下次循环继续尝试
                if (casTabAt(tab, i, null,
                             new Node(hash, key, value, null)))
                    break;                   // no lock when adding to empty bin
            }
    // 如果index处非空,且hash为MOVED(表示该节点是ForwardingNode),则表示有其它线程正在扩容,则一起进行扩容操作。        
     else if ((fh = f.hash) == MOVED)
                tab = helpTransfer(tab, f);
    // 如果index处非空,且为链表节点或树节点
            else {
                V oldVal = null;
    // 对某个bucket上执行添加操作仅需要锁住第一个Node即可(可以保证不会多线程同时对某个bucket进行写入)
                synchronized (f) {
                    if (tabAt(tab, i) == f) {
        // 1) 如果是链表节点,那么插入到链表中
                        if (fh >= 0) {
    // binCount是该bucket中元素个数
                            binCount = 1;
                            for (Node 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;
                                }
                                Node pred = e;
                                if ((e = e.next) == null) {
                                    pred.next = new Node(hash, key,
                                                              value, null);
                                    break;
                                }
                            }
                        }
        // 2)如果是红黑树树根,那么插入到红黑树中
                        else if (f instanceof TreeBin) {
                            Node p;
                            binCount = 2;
                            if ((p = ((TreeBin)f).putTreeVal(hash, key,
                                                           value)) != null) {
                                oldVal = p.val;
                                if (!onlyIfAbsent)
                                    p.val = value;
                            }
                        }
                    }
                }
    // 插入节点/释放锁之后,如果大小合适调整为红黑树,那么将链表转为红黑树
                if (binCount != 0) {
                    if (binCount >= TREEIFY_THRESHOLD)
                        treeifyBin(tab, i);
                    if (oldVal != null)
                        return oldVal;
                    break;
                }
            }
        }
    // 将当前ConcurrentHashMap的元素数量+1 ,如果超过阈值,那么进行扩容 
        addCount(1L, binCount);
        return null;
    }
    
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    treeifyBin(有锁,数组较小则扩容,较大则转为红黑树)

    private final void treeifyBin(Node[] tab, int index) {
        Node b; int n, sc;
        if (tab != null) {
        // 如果数组长度n小于阈值MIN_TREEIFY_CAPACITY,默认是64,则会调用tryPresize方法把数组长度扩大到原来的两倍,并触发transfer方法,重新调整节点的位置
            if ((n = tab.length) < MIN_TREEIFY_CAPACITY)
                tryPresize(n << 1);
            else if ((b = tabAt(tab, index)) != null && b.hash >= 0) {
                synchronized (b) {
                    if (tabAt(tab, index) == b) {
                        TreeNode hd = null, tl = null;
                        for (Node e = b; e != null; e = e.next) {
                            TreeNode p =
                                new TreeNode(e.hash, e.key, e.val,
                                                  null, null);
                            if ((p.prev = tl) == null)
                                hd = p;
                            else
                                tl.next = p;
                            tl = p;
                        }
                        setTabAt(tab, index, new TreeBin(hd));
                    }
                }
            }
        }
    }
    
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    tryPreSize

    /**
     * Tries to presize table to accommodate the given number of elements.
     *
     * @param size number of elements (doesn't need to be perfectly accurate)
     */
    private final void tryPresize(int size) {
        int c = (size >= (MAXIMUM_CAPACITY >>> 1)) ? MAXIMUM_CAPACITY :
            tableSizeFor(size + (size >>> 1) + 1);
        int sc;
        while ((sc = sizeCtl) >= 0) {
            Node[] tab = table; int n;
            if (tab == null || (n = tab.length) == 0) {
                n = (sc > c) ? sc : c;
                if (U.compareAndSwapInt(this, SIZECTL, sc, -1)) {
                    try {
                        if (table == tab) {
                            @SuppressWarnings("unchecked")
                            Node[] nt = (Node[])new Node[n];
                            table = nt;
                            sc = n - (n >>> 2);
                        }
                    } finally {
                        sizeCtl = sc;
                    }
                }
            }
            else if (c <= sc || n >= MAXIMUM_CAPACITY)
                break;
            else if (tab == table) {
                int rs = resizeStamp(n);
                if (sc < 0) {
                    Node[] nt;
                    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);
            }
        }
    }
    
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    扩容

    tryPresize

    tryPresize在putAll以及treeifyBin中调用

    private final void tryPresize(int size) {
    
    
        // c是扩容之后预计表的大小
        int c = (size >= (MAXIMUM_CAPACITY >>> 1)) ? MAXIMUM_CAPACITY :
            tableSizeFor(size + (size >>> 1) + 1);
        int sc;
    // 没有正在初始化或扩容
        while ((sc = sizeCtl) >= 0) {
            Node[] tab = table; int n;
            if (tab == null || (n = tab.length) == 0) {
                n = (sc > c) ? sc : c;
        // 期间没有其他线程对表操作,则CAS将SIZECTL状态置为-1,表示正在进行初始化
                if (U.compareAndSwapInt(this, SIZECTL, sc, -1)) {
                    try {
                        if (table == tab) {
                            @SuppressWarnings("unchecked")
                            Node[] nt = (Node[])new Node[n];
                            table = nt;
        // 即0.75*n
                            sc = n - (n >>> 2);
                        }
                    } finally {
                        sizeCtl = sc;
                    }
                }
            }
    // 若欲扩容值不大于原阈值,或现有容量>=最值,则do nothing
            else if (c <= sc || n >= MAXIMUM_CAPACITY)
                break;
        // table不为空,且在此期间其他线程未修改table
            else if (tab == table) {
                int rs = resizeStamp(n);
                if (sc < 0) {
                    Node[] nt;
                    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))
        // 协助扩容
                        transfer(tab, nt);
                }
                else if (U.compareAndSwapInt(this, SIZECTL, sc,
                                             (rs << RESIZE_STAMP_SHIFT) + 2))
    // 发起扩容
                    transfer(tab, null);
            }
        }
    }
    
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    addCount

    x=1,check=bucketCount

    private final void addCount(long x, int check) {
    
    
    // 计数值加x
    // 利用CAS方法更新baseCount的值   
        CounterCell[] as; long b, s;
        if ((as = counterCells) != null ||
            !U.compareAndSwapLong(this, BASECOUNT, b = baseCount, s = b + x)) {
    // 如果CAS更新baseCount失败或者counterCells不为空,那么尝试CAS更新当前线程的hashCode对应的bucket的value
            CounterCell a; long v; int m;
            boolean uncontended = true;
        -  if (as == null || (m = as.length - 1) < 0 ||
                (a = as[ThreadLocalRandom.getProbe() & m]) == null ||
                !(uncontended =
                  U.compareAndSwapLong(a, CELLVALUE, v = a.value, v + x))) {
        // 如果两次CAS都失败了,那么调用fullAddCount方法
                fullAddCount(x, uncontended);
                return;
            }
            if (check <= 1)
                return;
            s = sumCount();
        }
    // 以上与扩容无关,如果check值大于等于0 则需要检查是否需要进行扩容操作  
        if (check >= 0) {
            Node[] tab, nt; int n, sc;
     while (s >= (long)(sc = sizeCtl) && (tab = table) != null &&
                   (n = tab.length) < MAXIMUM_CAPACITY) {
                int rs = resizeStamp(n);
    // 如果sizeCtl是小于0的,说明有其他线程正在执行扩容操作,nextTable一定不为空
                if (sc < 0) {
                    if ((sc >>> RESIZE_STAMP_SHIFT) != rs || sc == rs + 1 ||
                        sc == rs + MAX_RESIZERS || (nt = nextTable) == null ||
                        transferIndex <= 0)
                        break;
        // 协助扩容
        if (U.compareAndSwapInt(this, SIZECTL, sc, sc + 1))
                        transfer(tab, nt);
                }
        // 当前线程是唯一的或是第一个发起扩容的线程  此时nextTable=null 
                else if (U.compareAndSwapInt(this, SIZECTL, sc,
                                             (rs << RESIZE_STAMP_SHIFT) + 2))
    // 发起扩容
                    transfer(tab, null);
                s = sumCount();
            }
        }
    }
    
    
    private final void fullAddCount(long x, boolean wasUncontended) {
        int h;
        if ((h = ThreadLocalRandom.getProbe()) == 0) {
            ThreadLocalRandom.localInit();      // force initialization
            h = ThreadLocalRandom.getProbe();
            wasUncontended = true;
        }
        boolean collide = false;                // True if last slot nonempty
        for (;;) {
            CounterCell[] as; CounterCell a; int n; long v;
            if ((as = counterCells) != null && (n = as.length) > 0) {
                if ((a = as[(n - 1) & h]) == null) {
                    if (cellsBusy == 0) {            // Try to attach new Cell
                        CounterCell r = new CounterCell(x); // Optimistic create
                        if (cellsBusy == 0 &&
                            U.compareAndSwapInt(this, CELLSBUSY, 0, 1)) {
                            boolean created = false;
                            try {               // Recheck under lock
                                CounterCell[] rs; int m, j;
                                if ((rs = counterCells) != null &&
                                    (m = rs.length) > 0 &&
                                    rs[j = (m - 1) & h] == null) {
                                    rs[j] = r;
                                    created = true;
                                }
                            } finally {
                                cellsBusy = 0;
                            }
                            if (created)
                                break;
                            continue;           // Slot is now non-empty
                        }
                    }
                    collide = false;
                }
                else if (!wasUncontended)       // CAS already known to fail
                    wasUncontended = true;      // Continue after rehash
                else if (U.compareAndSwapLong(a, CELLVALUE, v = a.value, v + x))
                    break;
                else if (counterCells != as || n >= NCPU)
                    collide = false;            // At max size or stale
                else if (!collide)
                    collide = true;
                else if (cellsBusy == 0 &&
                         U.compareAndSwapInt(this, CELLSBUSY, 0, 1)) {
                    try {
                        if (counterCells == as) {// Expand table unless stale
                            CounterCell[] rs = new CounterCell[n << 1];
                            for (int i = 0; i < n; ++i)
                                rs[i] = as[i];
                            counterCells = rs;
                        }
                    } finally {
                        cellsBusy = 0;
                    }
                    collide = false;
                    continue;                   // Retry with expanded table
                }
                h = ThreadLocalRandom.advanceProbe(h);
            }
            else if (cellsBusy == 0 && counterCells == as &&
                     U.compareAndSwapInt(this, CELLSBUSY, 0, 1)) {
                boolean init = false;
                try {                           // Initialize table
                    if (counterCells == as) {
                        CounterCell[] rs = new CounterCell[2];
                        rs[h & 1] = new CounterCell(x);
                        counterCells = rs;
                        init = true;
                    }
                } finally {
                    cellsBusy = 0;
                }
                if (init)
                    break;
            }
            else if (U.compareAndSwapLong(this, BASECOUNT, v = baseCount, v + x))
                break;                          // Fall back on using base
        }
    }
    
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    transfer

    • 当table容量不足的时候,即table的元素数量达到容量阈值sizeCtl,需要对table进行扩容。 整个扩容分为两部分:

      • 1)构建一个nextTable,大小为table的两倍。
      • 2)把table的数据复制到nextTable中。
    • 这两个过程在单线程下实现很简单,但是ConcurrentHashMap是支持并发插入的,扩容操作自然也会有并发的出现,这种情况下,第二步可以支持节点的并发复制,这样性能自然提升不少,但实现的复杂度也上升了一个台阶。

    • 先看第一步,构建nextTable,毫无疑问,这个过程只能有单个线程进行nextTable的初始化。

    • 通过Unsafe.compareAndSwapInt修改sizeCtl值,保证只有一个线程能够初始化nextTable,扩容后的数组长度为原来的两倍。

    • 节点从table移动到nextTable,大体思想是遍历、复制的过程。

      • 1)首先根据运算得到需要遍历的次数i,然后利用tabAt方法获得i位置的元素f,初始化一个ForwardingNode实例fwd。
      • 2)如果f==null,则在table中的i位置放入fwd,这个过程是采用
    • Unsafe.compareAndSwapObjectf方法实现的,很巧妙的实现了节点的并发移动。

      • 3)如果f是链表的头节点,就构造一个反序链表,把他们分别放在nextTable的i和i+n的位置上,移动完成,采用Unsafe.putObjectVolatile方法给table原位置赋值fwd。
      • 4)如果f是TreeBin节点,也做一个反序处理,并判断是否需要untreeify,把处理的结果分别放在nextTable的i和i+n的位置上,移动完成,同样采用Unsafe.putObjectVolatile方法给table原位置赋值fwd。
      • 5)遍历过所有的节点以后就完成了复制工作,把table指向nextTable,并更新sizeCtl为新数组大小的0.75倍 ,扩容完成。
    • 在多线程环境下,ConcurrentHashMap用两点来保证正确性:ForwardingNode和synchronized。当一个线程遍历到的节点如果是ForwardingNode,则继续往后遍历,如果不是,则将该节点加锁,防止其他线程进入,完成后设置ForwardingNode节点,以便要其他线程可以看到该节点已经处理过了,如此交叉进行,高效而又安全。

    /**
     * Moves and/or copies the nodes in each bin to new table. See
     * above for explanation.
     */
    private final void transfer(Node[] tab, Node[] nextTab) {
        int n = tab.length, stride;
        if ((stride = (NCPU > 1) ? (n >>> 3) / NCPU : n) < MIN_TRANSFER_STRIDE)
            stride = MIN_TRANSFER_STRIDE; // subdivide range
    // 扩容第一步,创建两倍长的数组nextTable,单线程执行
    // initiating只能有一个线程进行构造nextTable,如果别的线程进入发现不为空就不用构造nextTable了
        if (nextTab == null) {            // initiating
            try {
                @SuppressWarnings("unchecked")
                Node[] nt = (Node[])new Node[n << 1];
                nextTab = nt;
            } catch (Throwable ex) {      // try to cope with OOME
                sizeCtl = Integer.MAX_VALUE;
                return;
            }
            nextTable = nextTab;
            // 原先扩容大小
            transferIndex = n;
        }
    // 扩容第二步,把table的数据复制到nextTable中,多线程可以同时进行
        int nextn = nextTab.length;
    // 构造一个ForwardingNode用于多线程之间的共同扩容情况
        ForwardingNode fwd = new ForwardingNode(nextTab);
        boolean advance = true;
        boolean finishing = false; // to ensure sweep before committing nextTab
        // 遍历每个节点
     for (int i = 0, bound = 0;;) {
            Node 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;
                }
            }
    // 得到一个i,i指向table中某一个尚未拷贝的bucket,下面的代码是对i对应的bucket进行拷贝,拷贝完后将bucket赋值为fwd(ForwadingNode)
            //**************************************************************//
     if (i < 0 || i >= n || i + n >= nextn) {
                int sc;
    // 如果原table已经复制结束
                if (finishing) {
                    nextTable = null;
                    table = nextTab;
        // 修改扩容后的阀值,应该是现在容量的0.75倍
                    sizeCtl = (n << 1) - (n >>> 1);
                    return;
                }
                // 采用CAS算法更新SizeCtl,减一,表示有一个新的线程参与到扩容操作
         	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
                }
            }
            // CAS算法获取某一个数组的节点,为空就设为ForwordingNode
            else if ((f = tabAt(tab, i)) == null)
                advance = casTabAt(tab, i, null, fwd);
    // 如果这个节点的hash值是MOVED,就表示这个节点是ForwordingNode节点,就表示这个节点已经被处理过了,直接跳过
           else if ((fh = f.hash) == MOVED)
                advance = true; // already processed
            else {
                synchronized (f) {
                    if (tabAt(tab, i) == f) {
                        Node ln, hn;
                        if (fh >= 0) {
    //如果这个节点的确是链表节点,则拆分为两个子链表,存储到nextTable相应的两个位置
                            int runBit = fh & n;
                            Node lastRun = f;
                            for (Node 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;
                            }
                            for (Node 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(ph, pk, pv, ln);
                                else
                                    hn = new Node(ph, pk, pv, hn);
                            }
    // CAS存储在nextTable的i位置上
                            setTabAt(nextTab, i, ln);
    // CAS存储在nextTable的i+n位置上
                            setTabAt(nextTab, i + n, hn);
    // CAS在原table的i处设置forwordingNode节点,表示这个这个节点已经处理完毕
                            setTabAt(tab, i, fwd);
                            advance = true;
                        }
    // 如果这个节点是红黑树,则拆分为两颗子树,保存到nextTable相应的两个位置
                        else if (f instanceof TreeBin) {
                            TreeBin t = (TreeBin)f;
                            TreeNode lo = null, loTail = null;
                            TreeNode hi = null, hiTail = null;
                            int lc = 0, hc = 0;
                            for (Node e = t.first; e != null; e = e.next) {
                                int h = e.hash;
                                TreeNode p = new TreeNode
                                    (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;
                                }
                            }
    // 如果拆分后的树的节点数量已经少于6个就需要重新转化为链表
                            ln = (lc <= UNTREEIFY_THRESHOLD) ? untreeify(lo) :
                                (hc != 0) ? new TreeBin(lo) : t;
                            hn = (hc <= UNTREEIFY_THRESHOLD) ? untreeify(hi) :
                                (lc != 0) ? new TreeBin(hi) : t;
    // CAS存储在nextTable的i位置上
                            setTabAt(nextTab, i, ln);
    // CAS存储在nextTable的i+n位置上
                            setTabAt(nextTab, i + n, hn);
    // CAS在原table的i处设置forwordingNode节点,表示这个这个节点已经处理完毕
    setTabAt(tab, i, fwd);
                            advance = true;
                        }
                    }
                }
            }
        }
    }
    
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    helpTransfer

       final Node[] helpTransfer(Node[] tab, Node f) {
        Node[] nextTab; int sc;
        if (tab != null && (f instanceof ForwardingNode) &&
            (nextTab = ((ForwardingNode)f).nextTable) != null) {
            int rs = resizeStamp(tab.length);
            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)) {
    // 调用扩容方法
                    transfer(tab, nextTab);
                    break;
                }
            }
            return nextTab;
        }
        return table;
    }
    
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    get(无锁)

    public V get(Object key) {
        Node[] tab; Node e, p; int n, eh; K ek;
        int h = spread(key.hashCode());
        if ((tab = table) != null && (n = tab.length) > 0 &&
            (e = tabAt(tab, (n - 1) & h)) != null) {
            if ((eh = e.hash) == h) {
                // bucket中第一个结点就是我们要找的,直接返回
                if ((ek = e.key) == key || (ek != null && key.equals(ek)))
                    return e.val;
            }
            else if (eh < 0)
            	// bucket中第一个结点是红黑树根,则调用find方法去找
                return (p = e.find(h, key)) != null ? p.val : null;
            // bucket中第一个结点是链表,则遍历链表查找
            while ((e = e.next) != null) {
                if (e.hash == h &&
                    ((ek = e.key) == key || (ek != null && key.equals(ek))))
                    return e.val;
            }
        }
        return null;
    }
    
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    untreeify(无锁)

    static  Node untreeify(Node b) {
        Node hd = null, tl = null;
        for (Node q = b; q != null; q = q.next) {
            Node p = new Node(q.hash, q.key, q.val, null);
            if (tl == null)
                hd = p;
            else
                tl.next = p;
            tl = p;
        }
        return hd;
    }
    
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    remove(有锁)

    public boolean remove(Object key, Object value) {
        if (key == null)
            throw new NullPointerException();
        return value != null && replaceNode(key, null, value) != null;
    } 
    /**
     * Implementation for the four public remove/replace methods:
     * Replaces node value with v, conditional upon match of cv if
     * non-null.  If resulting value is null, delete.
     */
    final V replaceNode(Object key, V value, Object cv) {
        int hash = spread(key.hashCode());
        for (Node[] tab = table;;) {
            Node f; int n, i, fh;
            if (tab == null || (n = tab.length) == 0 ||
                (f = tabAt(tab, i = (n - 1) & hash)) == null)
                break;
            else if ((fh = f.hash) == MOVED)
    
    // 如果已经被移动,那么就帮助进行扩容
                tab = helpTransfer(tab, f);
            else {
                V oldVal = null;
                boolean validated = false;
                synchronized (f) {
                    if (tabAt(tab, i) == f) {
    // 如果是链表,则删除链表中的节点
                        if (fh >= 0) {
                            validated = true;
                            for (Node e = f, pred = null;;) {
                                K ek;
                                if (e.hash == hash &&
                                    ((ek = e.key) == key ||
                                     (ek != null && key.equals(ek)))) {
                                    V ev = e.val;
                                    if (cv == null || cv == ev ||
                                        (ev != null && cv.equals(ev))) {
                                        oldVal = ev;
                                        if (value != null)
                                            e.val = value;
                                        else if (pred != null)
                                            pred.next = e.next;
                                        else
                                            setTabAt(tab, i, e.next);
                                    }
                                    break;
                                }
                                pred = e;
                                if ((e = e.next) == null)
                                    break;
                            }
                        }
        // 如果是红黑树,则从红黑树中删除结点
                        else if (f instanceof TreeBin) {
                            validated = true;
                            TreeBin t = (TreeBin)f;
                            TreeNode r, p;
                            if ((r = t.root) != null &&
                                (p = r.findTreeNode(hash, key, null)) != null) {
                                V pv = p.val;
                                if (cv == null || cv == pv ||
                                    (pv != null && cv.equals(pv))) {
                                    oldVal = pv;
                                    if (value != null)
                                        p.val = value;
                                    else if (t.removeTreeNode(p))
                                        setTabAt(tab, i, untreeify(t.first));
                                }
                            }
                        }
                    }
                }
                if (validated) {
                    if (oldVal != null) {
                        if (value == null)
                            addCount(-1L, -1);
                        return oldVal;
                    }
                    break;
                }
            }
        }
        return null;
    }
    
    
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    containsKey

    public boolean containsKey(Object key) {
        return get(key) != null;
    }
    
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    containsValue

    public boolean containsValue(Object value) {
        if (value == null)
            throw new NullPointerException();
        Node[] t;
        if ((t = table) != null) {
            Traverser it = new Traverser(t, t.length, 0, t.length);
            for (Node p; (p = it.advance()) != null; ) {
                V v;
                if ((v = p.val) == value || (v != null && value.equals(v)))
                    return true;
            }
        }
        return false;
    } 
    static class Traverser {
        Node[] tab;        // current table; updated if resized
        Node next;         // the next entry to use
        TableStack stack, spare; // to save/restore on ForwardingNodes
        int index;              // index of bin to use next
        int baseIndex;          // current index of initial table
        int baseLimit;          // index bound for initial table
        final int baseSize;     // initial table size
    
        Traverser(Node[] tab, int size, int index, int limit) {
            this.tab = tab;
            this.baseSize = size;
            this.baseIndex = this.index = index;
            this.baseLimit = limit;
            this.next = null;
        }
    
        /**
         * Advances if possible, returning next valid node, or null if none.
         */
        final Node advance() {
            Node e;
            if ((e = next) != null)
                e = e.next;
            for (;;) {
                Node[] t; int i, n;  // must use locals in checks
                if (e != null)
                    return next = e;
                if (baseIndex >= baseLimit || (t = tab) == null ||
                    (n = t.length) <= (i = index) || i < 0)
                    return next = null;
                if ((e = tabAt(t, i)) != null && e.hash < 0) {
                    if (e instanceof ForwardingNode) {
                        tab = ((ForwardingNode)e).nextTable;
                        e = null;
                        pushState(t, i, n);
                        continue;
                    }
                    else if (e instanceof TreeBin)
                        e = ((TreeBin)e).first;
                    else
                        e = null;
                }
                if (stack != null)
                    recoverState(n);
                else if ((index = i + baseSize) >= n)
                    index = ++baseIndex; // visit upper slots if present
            }
        }
    
        /**
         * Saves traversal state upon encountering a forwarding node.
         */
        private void pushState(Node[] t, int i, int n) {
            TableStack s = spare;  // reuse if possible
            if (s != null)
                spare = s.next;
            else
                s = new TableStack();
            s.tab = t;
            s.length = n;
            s.index = i;
            s.next = stack;
            stack = s;
        }
    
        /**
         * Possibly pops traversal state.
         *
         * @param n length of current table
         */
        private void recoverState(int n) {
            TableStack s; int len;
            while ((s = stack) != null && (index += (len = s.length)) >= n) {
                n = len;
                index = s.index;
                tab = s.tab;
                s.tab = null;
                TableStack next = s.next;
                s.next = spare; // save for reuse
                stack = next;
                spare = s;
            }
            if (s == null && (index += baseSize) >= n)
                index = ++baseIndex;
        }
    }
    
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    遍历

    public Set> entrySet() {
        EntrySetView es;
        return (es = entrySet) != null ? es : (entrySet = new EntrySetView(this));
    } 
    public Iterator> iterator() {
        ConcurrentHashMap m = map;
        Node[] t;
        int f = (t = m.table) == null ? 0 : t.length;
        return new EntryIterator(t, f, 0, f, m);
    } 
    static class BaseIterator extends Traverser {
        final ConcurrentHashMap map;
        Node lastReturned;
        BaseIterator(Node[] tab, int size, int index, int limit,
                    ConcurrentHashMap map) {
            super(tab, size, index, limit);
            this.map = map;
            advance();
        }
    
        public final boolean hasNext() { return next != null; }
        public final boolean hasMoreElements() { return next != null; }
    
        public final void remove() {
            Node p;
            if ((p = lastReturned) == null)
                throw new IllegalStateException();
            lastReturned = null;
            map.replaceNode(p.key, null, null);
        }
    } 
    static final class EntryIterator extends BaseIterator
        implements Iterator> {
        EntryIterator(Node[] tab, int index, int size, int limit,
                      ConcurrentHashMap map) {
            super(tab, index, size, limit, map);
        }
    
        public final Map.Entry next() {
            Node p;
            if ((p = next) == null)
                throw new NoSuchElementException();
            K k = p.key;
            V v = p.val;
            lastReturned = p;
            advance();
            return new MapEntry(k, v, map);
        }
    }
    
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    1.7 分段锁实现

    • 采用 Segment + HashEntry的方式进行实现

    put

    • 当执行 put方法插入数据时,根据key的hash值,在 Segment数组中找到相应的位置,如果相应位置的 Segment还未初始化,则通过CAS进行赋值,接着执行 Segment对象的 put方法通过加锁机制插入数据,实现如下:
    • 场景:线程A和线程B同时执行相同 Segment对象的 put方法
    • 1、线程A执行 tryLock()方法成功获取锁,则把 HashEntry对象插入到相应的位置;
    • 2、线程B获取锁失败,则执行 scanAndLockForPut()方法,在 scanAndLockForPut方法中,会通过重复执行 tryLock()方法尝试获取锁,在多处理器环境下,重复次数为64,单处理器重复次数为1,当执行 tryLock()方法的次数超过上限时,则执行 lock()方法挂起线程B;
    • 3、当线程A执行完插入操作时,会通过 unlock()方法释放锁,接着唤醒线程B继续执行;

    size

    • 因为 ConcurrentHashMap是可以并发插入数据的,所以在准确计算元素时存在一定的难度,一般的思路是统计每个 Segment对象中的元素个数,然后进行累加,但是这种方式计算出来的结果并不一样的准确的,因为在计算后面几个 Segment的元素个数时,已经计算过的 Segment同时可能有数据的插入或则删除。
    • 先采用不加锁的方式,连续计算元素的个数,最多计算3次: 1、如果前后两次计算结果相同,则说明计算出来的元素个数是准确的; 2、如果前后两次计算结果都不同,则给每个 Segment进行加锁,再计算一次元素的个数;

    ConcurrentSkipListMap

    • ConcurrentSkipListMap有几个ConcurrentHashMap 不能比拟的优点:

    • 1、ConcurrentSkipListMap 的key是有序的。

    • 2、ConcurrentSkipListMap 支持更高的并发。ConcurrentSkipListMap 的存取时间是log(N),和线程数几乎无关。也就是说在数据量一定的情况下,并发的线程越多,ConcurrentSkipListMap越能体现出他的优势。

    • SkipList 跳表:

    • 跳表是平衡树的一种替代的数据结构,但是和红黑树不相同的是,跳表对于树的平衡的实现是基于一种随机化的算法的,这样也就是说跳表的插入和删除的工作是比较简单的。

    • 下面来研究一下跳表的核心思想:

    • 先从链表开始,如果是一个简单的链表,那么我们知道在链表中查找一个元素I的话,需要将整个链表遍历一次。

    • 如果是说链表是排序的,并且节点中还存储了指向前面第二个节点的指针的话,那么在查找一个节点时,仅仅需要遍历N/2个节点即可。

    • 这基本上就是跳表的核心思想,其实也是一种通过“空间来换取时间”的一个算法,通过在每个节点中增加了向前的指针,从而提升查找的效率。

    🚩 Map实现类之间的区别

    HashMap与ConcurrentHashMap区别

    • 1)前者允许key或value为null,后者不允许
    • 2)前者不是线程安全的,后者是

    HashMap、TreeMap与LinkedHashMap区别

    • 1)HashMap遍历时,取得数据的顺序是完全随机的;
    • TreeMap可以按照自然顺序或Comparator排序;
      • LinkedHashMap可以按照插入顺序或访问顺序排序,且get的效率(O(1))比TreeMap(O(logn))更高。
      • 2)HashMap底层基于哈希表,数组+链表/红黑树;
    • TreeMap底层基于红黑树
    • LinkedHashMap底层基于HashMap与环形双向链表
    • 3)就get和put效率而言,HashMap是最高的,LinkedHashMap次之,TreeMap最次。

    HashMap与Hashtable区别

      1. 扩容策略:Hashtable在不指定容量的情况下的默认容量为11,而HashMap为16,Hashtable不要求底层数组的容量一定要为2的整数次幂(*2+1),而HashMap则要求一定为2的整数次幂(*2)。
      1. 允许null:Hashtable中key和value都不允许为null,而HashMap中key和value都允许为null(key只能有一个为null,而value则可以有多个为null)。
      1. 线程安全:前者不是线程安全的,后者是;

    ConcurrentHashMap、Collections.synchronizedMap与Hashtable的异同

    • 它们都是同步Map,但三者实现同步的机制不同;后两者都是简单地在方法上加synchronized实现的,锁的粒度较大;前者是基于CAS和synchronized实现的,锁的粒度较小,大部分都是lock-free无锁实现同步的。
    • ConcurrentHashMap还提供了putIfAbsent同步方法。
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  • 原文地址:https://blog.csdn.net/qq_35530042/article/details/125898794