Map

HashMap（底层是数组+链表/红黑树，无序键值对集合，非线程安全)

• 基于哈希表实现，链地址法。
• loadFactor默认为0.75，threshold（阈)为12，并创建一个大小为16的Entry数组。
• 在遍历时是无序的，如需有序，建议使用TreeMap。
• 采用数组方式存储key、value构成的Entry对象，无容量限制。
• 基于key hash寻找Entry对象存放在数组中的位置，对于hash冲突采用链表/红黑树的方式来解决。
• HashMap在插入元素时可能会扩大数组的容量，在扩大容量时需要重新计算hash，并复制对象到新的数组中。
• 是非线程安全的。
• 哈希冲突时采用链表法的类，一个哈希桶多于8个元素改为TreeNode
• 哈希冲突时采用红黑树存储的类，一个哈希桶少于6个元素改为Node
• 某个桶对应的链表过长的话搜索效率低，改为红黑树效率会提高。
• 为何按位与而不是取摸 hashmap的iterator读取时是否会读到另一个线程put的数据 红黑树；hashmap报ConcurrentModificationException的情况
• Hash冲突中链表结构的数量大于8个，则调用树化转为红黑树结构，红黑树查找稍微快些；红黑树结构的数量小于6个时，则转为链表结构
• 如果加载因子越大，对空间的利用更充分，但是查找效率会降低（链表长度会越来越长)；如果加载因子太小，那么表中的数据将过于稀疏（很多空间还没用，就开始扩容了)，对空间造成严重浪费。如果我们在构造方法中不指定，则系统默认加载因子为0.75，这是一个比较理想的值，一般情况下我们是无需修改的。
  • 一般对哈希表的散列很自然地会想到用hash值对length取模（即除法散列法)，Hashtable中也是这样实现的，这种方法基本能保证元素在哈希表中散列的比较均匀，但取模会用到除法运算，效率很低，HashMap中则通过h&(length-1)的方法来代替取模，同样实现了均匀的散列，但效率要高很多，这也是HashMap对Hashtable的一个改进。
  • 哈希表的容量一定要是2的整数次幂。首先，length为2的整数次幂的话，h&(length-1)就相当于对length取模，这样便保证了散列的均匀，同时也提升了效率；其次，length为2的整数次幂的话，为偶数，这样length-1为奇数，奇数的最后一位是1，这样便保证了h&(length-1)的最后一位可能为0，也可能为1（这取决于h的值)，即与后的结果可能为偶数，也可能为奇数，这样便可以保证散列的均匀性，而如果length为奇数的话，很明显length-1为偶数，它的最后一位是0，这样h&(length-1)的最后一位肯定为0，即只能为偶数，这样任何hash值都只会被散列到数组的偶数下标位置上，这便浪费了近一半的空间，因此，length取2的整数次幂，是为了使不同hash值发生碰撞的概率较小，这样就能使元素在哈希表中均匀地散列。

Map#Entry（接口)

interface Entry {
    K getKey();

    V getValue();

    V setValue(V value);

    boolean equals(Object o);
    int hashCode();
    public static , V> Comparator> comparingByKey() {
        return (Comparator> & Serializable)
            (c1, c2) -> c1.getKey().compareTo(c2.getKey());
    }

    public static > Comparator> comparingByValue() {
        return (Comparator> & Serializable)
            (c1, c2) -> c1.getValue().compareTo(c2.getValue());
    }

    public static  Comparator> comparingByKey(Comparator cmp) {
        Objects.requireNonNull(cmp);
        return (Comparator> & Serializable)
            (c1, c2) -> cmp.compare(c1.getKey(), c2.getKey());
    }

    public static  Comparator> comparingByValue(Comparator cmp) {
        Objects.requireNonNull(cmp);
        return (Comparator> & Serializable)
            (c1, c2) -> cmp.compare(c1.getValue(), c2.getValue());
    }
}
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HashMap#Node（Map.Entry的实现，链表的基本元素)

static class Node implements Map.Entry {
    final int hash;
    final K key;
    V value;
    Node next;

    Node(int hash, K key, V value, Node next) {
        this.hash = hash;
        this.key = key;
        this.value = value;
        this.next = next;
    }

    public final K getKey()        { return key; }
    public final V getValue()      { return value; }
    public final String toString() { return key + "=" + value; }

    public final int hashCode() {
        return Objects.hashCode(key) ^ Objects.hashCode(value);
    }

    public final V setValue(V newValue) {
        V oldValue = value;
        value = newValue;
        return oldValue;
    }

    public final boolean equals(Object o) {
        if (o == this)
            return true;
        if (o instanceof Map.Entry) {
            Map.Entry e = (Map.Entry)o;
            if (Objects.equals(key, e.getKey()) &&
                Objects.equals(value, e.getValue()))
                return true;
        }
        return false;
    }
}
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HashMap#TreeNode（Map.Entry的实现，红黑树的基本元素)

 static final class TreeNode extends LinkedHashMap.Entry {
    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) {
        super(hash, key, val, next);
    }
      //...
 }

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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 default initial capacity - MUST be a power of two.
 */
static final int DEFAULT_INITIAL_CAPACITY = 1 << 4; // aka 16

/**
 * The maximum capacity, used if a higher value is implicitly specified
 * by either of the constructors with arguments.
 * MUST be a power of two <= 1<<30.
 */
static final int MAXIMUM_CAPACITY = 1 << 30;

/**
 * The load factor used when none specified in constructor.
 */
static final float DEFAULT_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.)
 * Should be at least 4 * TREEIFY_THRESHOLD to avoid conflicts
 * between resizing and treeification thresholds.
 */
static final int MIN_TREEIFY_CAPACITY = 64; 
/**
 * The table, initialized on first use, and resized as
 * necessary. When allocated, length is always a power of two.
 * (We also tolerate length zero in some operations to allow
 * bootstrapping mechanics that are currently not needed.)
 */
transient Node[] table;

/**
 * Holds cached entrySet(). Note that AbstractMap fields are used
 * for keySet() and values().
 */
transient Set> entrySet;

/**
 * The number of key-value mappings contained in this map.
 */
transient int size;

/**
 * The number of times this HashMap has been structurally modified
 * Structural modifications are those that change the number of mappings in
 * the HashMap or otherwise modify its internal structure (e.g.,
 * rehash).  This field is used to make iterators on Collection-views of
 * the HashMap fail-fast.  (See ConcurrentModificationException).
 */
transient int modCount;

/**
 * The next size value at which to resize (capacity * load factor).
 *
 * @serial
 */
// (The javadoc description is true upon serialization.
// Additionally, if the table array has not been allocated, this
// field holds the initial array capacity, or zero signifying
// DEFAULT_INITIAL_CAPACITY.) 
// HashMap的阈值，用于判断是否需要调整HashMap的容量（threshold = 容量*装载因子)
int threshold;

/**
 * The load factor for the hash table.
 *
 * @serial
 */
final float loadFactor;

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构造方法

注意哪怕是指定了初始容量，也不会直接初始化table，而是在第一次put时调用resize来初始化table，resize里会将threshold视为初始容量。

public HashMap(int initialCapacity, float loadFactor) {
    if (initialCapacity < 0)
        throw new IllegalArgumentException("Illegal initial capacity: " +
                                           initialCapacity);
    if (initialCapacity > MAXIMUM_CAPACITY)
        initialCapacity = MAXIMUM_CAPACITY;
    if (loadFactor <= 0 || Float.isNaN(loadFactor))
        throw new IllegalArgumentException("Illegal load factor: " +
                                           loadFactor);
    this.loadFactor = loadFactor; 
    // 阈值为不小于容量的2的幂次
    this.threshold = tableSizeFor(initialCapacity);
}

public HashMap(int initialCapacity) {
    this(initialCapacity, DEFAULT_LOAD_FACTOR);
}

/**
 * Constructs an empty HashMap with the default initial capacity
 * (16) and the default load factor (0.75).
 */
public HashMap() {
    this.loadFactor = DEFAULT_LOAD_FACTOR; // all other fields defaulted
}
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tableSizeFor（找到大于等于initialCapacity的最小的2的幂次以及原因)

/**
 * Returns a power of two size for the given target capacity.
 */
static final int tableSizeFor(int cap) {
    int n = cap - 1;
    n |= n >>> 1;
    n |= n >>> 2;
    n |= n >>> 4;
    n |= n >>> 8;
    n |= n >>> 16;
    return (n < 0) ? 1 : (n >= MAXIMUM_CAPACITY) ? MAXIMUM_CAPACITY : n + 1;
}
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hash（hash算法，算法比较高效、均匀)

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

• key的hash值高16位不变，低16位与高16位异或作为key的最终hash值。（h >>> 16，表示无符号右移16位，高位补0，任何数跟0异或都是其本身，因此key的hash值高16位不变。)
• 保证了对象的hashCode的高16位的变化能反应到低16位中，

hash to index

• 如何根据hash值计算index？（put和get中的代码)
• n = table.length;
  • index = (n-1)& hash;
  • 当n总是2的n次方时，hash & (n-1)运算等价于h%n，但是&比%具有更高的效率。

put

public V put(K key, V value) {
    return putVal(hash(key), key, value, false, true);
}
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• onlyIfAbsent如果为true，只有在hashmap没有该key的时候才添加
• evict如果为false，hashmap为创建模式；只有在使用Map集合作为构造器创建LinkedHashMap或HashMap时才会为false。
• 这两个参数均为实现java8的新接口而设置

  Node newNode(int hash, K key, V value, Node next) {
    return new Node<>(hash, key, value, next);
}
  

 final V putVal(int hash, K key, V value, boolean onlyIfAbsent,
               boolean evict) {
    Node[] tab; // table
 Node p;  // node pointer
 int n, i; // n 为length, i 为 node index
    if ((tab = table) == null || (n = tab.length) == 0)
        n = (tab = resize()).length;
     // index处没有元素，则直接放入新节点
    if ((p = tab[i = (n - 1) & hash]) == null)
        tab[i] = newNode(hash, key, value, null);
    else {
  // index处有元素
        Node e; 
        if (p.hash == hash &&
            ((k = p.key) == key || (key != null && key.equals(k))))
 // 假如key是相同的，那么替换value即可
            e = p;
        else if (p instanceof TreeNode)
 // key不同，但如果p是红黑树根节点，那么将新节点放入红黑树
            e = ((TreeNode)p).putTreeVal(this, tab, hash, key, value);
        else {
 // key不同，但如果p是链表头节点，那么判断链表中是否有该节点，如没有，则将新节点插入到链表尾部
            for (int binCount = 0; ; ++binCount) {
                if ((e = p.next) == null) {
                    p.next = newNode(hash, key, value, null);
     // 插入后如果发现已经链表长度已经适合转为红黑树了，则转换
                    if (binCount >= TREEIFY_THRESHOLD - 1) // -1 for 1st
                        treeifyBin(tab, hash);
                    break;
                }
                // 链表中某元素key和key相同，则替换value即可
                if (e.hash == hash &&
                    ((k = e.key) == key || (key != null && key.equals(k))))
                    break;
                p = e;
            }
        }
        if (e != null) { // existing mapping for key
            V oldValue = e.value;
            if (!onlyIfAbsent || oldValue == null)
                e.value = value;
            afterNodeAccess(e);
            return oldValue;
        }
    }
    ++modCount; 
    if (++size > threshold)
        resize();
    afterNodeInsertion(evict);
    return null;
}

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扩容 resize

• 扩容函数，如果hash桶为空，初始化默认大小，否则双倍扩容
• 注意！！因为扩容为2的倍数，根据hash桶的计算方法，元素哈希值不变
• 所以元素在新的hash桶的下标，要不跟旧的hash桶下标一致，要不增加1倍。
• cap：capacity
• thr：threshold

    - final Node[] resize() {
    Node[] oldTab = table;
    int oldCap = (oldTab == null) ? 0 : oldTab.length;
    int oldThr = threshold;
    int newCap, newThr = 0;
    if (oldCap > 0) {
        if (oldCap >= MAXIMUM_CAPACITY) {
            threshold = Integer.MAX_VALUE;
            return oldTab;
        }
        else if ((newCap = oldCap << 1) < MAXIMUM_CAPACITY &&
                 oldCap >= DEFAULT_INITIAL_CAPACITY)
            newThr = oldThr << 1; // double threshold
    }
    else if (oldThr > 0) // initial capacity was placed in threshold
        newCap = oldThr;
    else {               // zero initial threshold signifies using defaults
        newCap = DEFAULT_INITIAL_CAPACITY;
        newThr = (int)(DEFAULT_LOAD_FACTOR * DEFAULT_INITIAL_CAPACITY);
    }
    if (newThr == 0) {
        float ft = (float)newCap * loadFactor;
        newThr = (newCap < MAXIMUM_CAPACITY && ft < (float)MAXIMUM_CAPACITY ?
                  (int)ft : Integer.MAX_VALUE);
    }
    threshold = newThr;
    Node[] newTab = (Node[])new Node[newCap];
    table = newTab;
- 

- 	if (oldTab != null) {
        for (int j = 0; j < oldCap; ++j) {
            Node e;
            if ((e = oldTab[j]) != null) {
-  j位置原本元素存在
                oldTab[j] = null;
                if (e.next == null)
-  如果该位置没有形成链表，则再次计算index，放入新table
-  假设扩容前的table大小为2的N次方，有上述put方法解析可知，元素的table索引为其hash值的后N位确定
- 那么扩容后的table大小即为2的N+1次方，则其中元素的table索引为其hash值的后N+1位确定，比原来多了一位
- 因此，table中的元素只有两种情况：
- 元素hash值第N+1位为0：不需要进行位置调整
    - 元素hash值第N+1位为1：调整至原索引的两倍位置
                    newTab[e.hash & (newCap - 1)] = e;
                else if (e instanceof TreeNode)
-  如果该位置形成了红黑树，则split
                    ((TreeNode)e).split(this, newTab, j, oldCap);
                else { // preserve order
-  如果该位置形成了链表，则分成两个链表，分别放在0~oldCap,oldCap~oldCap*2位置处
                    Node loHead = null, loTail = null;
                    Node hiHead = null, hiTail = null;
                    Node next;
                    do {
                        next = e.next;
//  用于确定元素hash值第N+1位是否为0：
// 若为0，则使用loHead与loTail，将元素移至新table的原索引处
// 若不为0，则使用hiHead与hiHead，将元素移至新table的两倍索引处
                        if ((e.hash & oldCap) == 0) {
                            if (loTail == null)
                                loHead = e;
                            else
                                loTail.next = e;
                            loTail = e;
                        }
                        else {
                            if (hiTail == null)
                                hiHead = e;
                            else
                                hiTail.next = e;
                            hiTail = e;
                        }
                    } while ((e = next) != null);
                    if (loTail != null) {
                        loTail.next = null;
                        newTab[j] = loHead;
                    }
                    if (hiTail != null) {
                        hiTail.next = null;
                        newTab[j + oldCap] = hiHead;
                    }
                }
            }
        }
    }
    return newTab;
}
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get（O(logn))

public V get(Object key) {
    Node e;
    return (e = getNode(hash(key), key)) == null ? null : e.value;
}


  final Node getNode(int hash, Object key) {
    Node[] tab; Node first, e; int n; K k;
    if ((tab = table) != null && (n = tab.length) > 0 &&
        (first = tab[(n - 1) & hash]) != null) {
//  table不为空，且hash对应index元素不为空
//  如果index位置就是我们要找的key，则直接返回
        if (first.hash == hash && // always check first node
            ((k = first.key) == key || (key != null && key.equals(k))))
            return first;
//  如果不是，则从链表或红黑树的角度继续找
        if ((e = first.next) != null) {
            if (first instanceof TreeNode)
                return ((TreeNode)first).getTreeNode(hash, key);
            do {
                if (e.hash == hash &&
                    ((k = e.key) == key || (key != null && key.equals(k))))
                    return e;
            } while ((e = e.next) != null);
        }
    }
    return null;
}

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remove

public V remove(Object key) {
    Node e;
    return (e = removeNode(hash(key), key, null, false, true)) == null ?
        null : e.value;
}
// value=null,matchValue=false,movable=true
    final Node removeNode(int hash, Object key, Object value,
                           boolean matchValue, boolean movable) {
    Node[] tab; Node p; int n, index;
    if ((tab = table) != null && (n = tab.length) > 0 &&
        (p = tab[index = (n - 1) & hash]) != null) {
        Node node = null, e; K k; V v;
     // 1) 如果hash 对应index即为我们要找的key，则找到
        if (p.hash == hash &&
            ((k = p.key) == key || (key != null && key.equals(k))))
            node = p;
     // 2) 从链表或红黑树的角度继续找
        else if ((e = p.next) != null) {
            if (p instanceof TreeNode)
                node = ((TreeNode)p).getTreeNode(hash, key);
            else {
                do {
                    if (e.hash == hash &&
                        ((k = e.key) == key ||
                         (key != null && key.equals(k)))) {
                        node = e;
                        break;
                    }
                    p = e;
                } while ((e = e.next) != null);
            }
        }
// 找到后，根据找到的位置不同 相应地进行删除
        if (node != null && (!matchValue || (v = node.value) == value ||
                             (value != null && value.equals(v)))) {
            if (node instanceof TreeNode)
                ((TreeNode)node).removeTreeNode(this, tab, movable);
            else if (node == p)
                tab[index] = node.next;
            else
                p.next = node.next;
            ++modCount;
            --size;
            afterNodeRemoval(node);
            return node;
        }
    }
    return null;
}
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containsKey

public boolean containsKey(Object key) {
    return getNode(hash(key), key) != null;
}
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containsValue

public boolean containsValue(Object value) {
    Node[] tab; V v;
    if ((tab = table) != null && size > 0) {
        for (int i = 0; i < tab.length; ++i) {
            for (Node e = tab[i]; e != null; e = e.next) {
                if ((v = e.value) == value ||
                    (value != null && value.equals(v)))
                    return true;
            }
        }
    }
    return false;
}
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a)链表转红黑树 treeifyBin

/**
 * Replaces all linked nodes in bin at index for given hash unless
 * table is too small, in which case resizes instead.
 */
final void treeifyBin(Node[] tab, int hash) {
    int n, index; Node e;
    if (tab == null || (n = tab.length) < MIN_TREEIFY_CAPACITY)
        resize();
    else if ((e = tab[index = (n - 1) & hash]) != null) {
        TreeNode hd = null, tl = null;
        do {
            TreeNode p = replacementTreeNode(e, null);
            if (tl == null)
                hd = p;
            else {
                p.prev = tl;
                tl.next = p;
            }
            tl = p;
        } while ((e = e.next) != null);
        if ((tab[index] = hd) != null)
            hd.treeify(tab);
    }
}
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红黑树转链表 TreeNode#untreeify

// final Node untreeify(HashMap map) {
    Node hd = null, tl = null;
    for (Node q = this; q != null; q = q.next) {
        Node p = map.replacementNode(q, null);
        if (tl == null)
            hd = p;
        else
            tl.next = p;
        tl = p;
    }
    return hd;
}

### c)红黑树 查找 
final TreeNode getTreeNode(int h, Object k) {
    return ((parent != null) ? root() : this).find(h, k, null);
}


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/**

• Finds the node starting at root p with the given hash and key.
• The kc argument caches comparableClassFor(key) upon first use
• comparing keys.
  */
  final TreeNode find(int h, Object k, Class kc) {
  TreeNode p = this;
  do {
  int ph, dir; K pk;
  TreeNode pl = p.left, pr = p.right, q;
  if ((ph = p.hash) > h)
  p = pl;
  else if (ph < h)
  p = pr;
  else if ((pk = p.key) == k || (k != 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.find(h, k, kc)) != null)
  return q;
  else
  p = pl;
  } while (p != null);
  return null;
  }

### d)红黑树 添加
- final TreeNode putTreeVal(HashMap map, Node[] tab,
                               int h, K k, V v) {
    Class kc = null;
    boolean searched = false;
    TreeNode root = (parent != null) ? root() : this;
    for (TreeNode p = root;;) {
        int dir, ph; K pk;
        if ((ph = p.hash) > h)
            dir = -1;
        else if (ph < h)
            dir = 1;
        else if ((pk = p.key) == k || (k != null && k.equals(pk)))
            return p;
        else if ((kc == null &&
                  (kc = comparableClassFor(k)) == null) ||
                 (dir = compareComparables(kc, k, pk)) == 0) {
            if (!searched) {
                TreeNode q, ch;
                searched = true;
                if (((ch = p.left) != null &&
                     (q = ch.find(h, k, kc)) != null) ||
                    ((ch = p.right) != null &&
                     (q = ch.find(h, k, kc)) != null))
                    return q;
            }
            dir = tieBreakOrder(k, pk);
        }

        TreeNode xp = p;
        if ((p = (dir <= 0) ? p.left : p.right) == null) {
            Node xpn = xp.next;
            TreeNode x = map.newTreeNode(h, k, v, xpn);
            if (dir <= 0)
                xp.left = x;
            else
                xp.right = x;
            xp.next = x;
            x.parent = x.prev = xp;
            if (xpn != null)
                ((TreeNode)xpn).prev = x;
            moveRootToFront(tab, balanceInsertion(root, x));
            return null;
        }
    }
}
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e)红黑树 删除

/**
 * Removes the given node, that must be present before this call.
 * This is messier than typical red-black deletion code because we
 * cannot swap the contents of an interior node with a leaf
 * successor that is pinned by "next" pointers that are accessible
 * independently during traversal. So instead we swap the tree
 * linkages. If the current tree appears to have too few nodes,
 * the bin is converted back to a plain bin. (The test triggers
 * somewhere between 2 and 6 nodes, depending on tree structure).
 */
final void removeTreeNode(HashMap map, Node[] tab,
                          boolean movable) {
    int n;
    if (tab == null || (n = tab.length) == 0)
        return;
    int index = (n - 1) & hash;
    TreeNode first = (TreeNode)tab[index], root = first, rl;
    TreeNode succ = (TreeNode)next, pred = prev;
    if (pred == null)
        tab[index] = first = succ;
    else
        pred.next = succ;
    if (succ != null)
        succ.prev = pred;
    if (first == null)
        return;
    if (root.parent != null)
        root = root.root();
    if (root == null || root.right == null ||
        (rl = root.left) == null || rl.left == null) {
        tab[index] = first.untreeify(map);  // too small
        return;
    }
    TreeNode p = this, pl = left, pr = right, replacement;
    if (pl != null && pr != null) {
        TreeNode s = pr, sl;
        while ((sl = s.left) != null) // find successor
            s = sl;
        boolean c = s.red; s.red = p.red; p.red = c; // swap colors
        TreeNode sr = s.right;
        TreeNode pp = p.parent;
        if (s == pr) { // p was s's direct parent
            p.parent = s;
            s.right = p;
        }
        else {
            TreeNode sp = s.parent;
            if ((p.parent = sp) != null) {
                if (s == sp.left)
                    sp.left = p;
                else
                    sp.right = p;
            }
            if ((s.right = pr) != null)
                pr.parent = s;
        }
        p.left = null;
        if ((p.right = sr) != null)
            sr.parent = p;
        if ((s.left = pl) != null)
            pl.parent = s;
        if ((s.parent = pp) == null)
            root = s;
        else if (p == pp.left)
            pp.left = s;
        else
            pp.right = s;
        if (sr != null)
            replacement = sr;
        else
            replacement = p;
    }
    else if (pl != null)
        replacement = pl;
    else if (pr != null)
        replacement = pr;
    else
        replacement = p;
    if (replacement != p) {
        TreeNode pp = replacement.parent = p.parent;
        if (pp == null)
            root = replacement;
        else if (p == pp.left)
            pp.left = replacement;
        else
            pp.right = replacement;
        p.left = p.right = p.parent = null;
    }

    TreeNode r = p.red ? root : balanceDeletion(root, replacement);

    if (replacement == p) {  // detach
        TreeNode pp = p.parent;
        p.parent = null;
        if (pp != null) {
            if (p == pp.left)
                pp.left = null;
            else if (p == pp.right)
                pp.right = null;
        }
    }
    if (movable)
        moveRootToFront(tab, r);
}
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f)红黑树 遍历

• 使用next指针，类似链表方式，便可遍历红黑树。

遍历（先迭代table，再迭代bucket->链表/红黑树)

keySet

keySet().iterator()

public Set keySet() {
    Set ks = keySet;
    if (ks == null) {
        ks = new KeySet();
        keySet = ks;
    }
    return ks;
}
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final class KeySet extends AbstractSet {
    public final Iterator iterator()     { return new KeyIterator(); }
}
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KeyIterator实现了Iterator接口，并继承了HashIterator。前者仅适用于KeySet的迭代，后者适合所有基于HashMap的迭代。

HashMap#HashIterator

abstract class HashIterator {
    Node next;        // next entry to return
    Node current;     // current entry
    int expectedModCount;  // for fast-fail
    int index;             // current slot

    HashIterator() {
        expectedModCount = modCount;
        Node[] t = table;
        current = next = null;
        index = 0;
        if (t != null && size > 0) { // advance to first entry
            do {} while (index < t.length && (next = t[index++]) == null);
        }
    }

    public final boolean hasNext() {
        return next != null;
    }

    final Node nextNode() {
        Node[] t;
        Node e = next;
        if (modCount != expectedModCount)
            throw new ConcurrentModificationException();
        if (e == null)
            throw new NoSuchElementException();  
// next的next为空的话，则继续遍历table，否则就返回next的next（链表或红黑树的下一个节点)
        if ((next = (current = e).next) == null && (t = table) != null) {
            do {} while (index < t.length && (next = t[index++]) == null);
        }
        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;
    }
}
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HashMap#KeyIterator

final class KeyIterator extends HashIterator
    implements Iterator {
    public final K next() { return nextNode().key; }
}
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entrySet

public Set> entrySet() {
    Set> es;
    return (es = entrySet) == null ? (entrySet = new EntrySet()) : es;
}
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• 使用的是该迭代器：

final class EntryIterator extends HashIterator
    implements Iterator> {
    public final Map.Entry next() { return nextNode(); }
}
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多线程环境下的问题

• 1.8中hashmap的确不会因为多线程put导致死循环（1.7代码中会这样子)，但是依然有其他的弊端，比如数据丢失等等。因此多线程情况下还是建议使用ConcurrentHashMap。

• 数据丢失：当多线程put的时候，当index相同而又同时达到链表的末尾时，另一个线程put的数据会把之前线程put的数据覆盖掉，就会产生数据丢失。

if ((e = p.next) == null) {
                  p.next = newNode(hash, key, value, null);
 }

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Hashtable

• Hashtable同样是基于哈希表实现的，同样每个元素是一个key-value对，其内部也是通过单链表解决冲突问题，容量不足（超过了阈值)时，同样会自动增长。
• Hashtable也是JDK1.0引入的类，是线程安全的，能用于多线程环境中。
• Hashtable同样实现了Serializable接口，它支持序列化，实现了Cloneable接口，能被克隆。
• Hashtable#Entry

private static class Entry implements Map.Entry {
    final int hash;
    final K key;
    V value;
    Entry next;

    protected Entry(int hash, K key, V value, Entry next) {
        this.hash = hash;
        this.key =  key;
        this.value = value;
        this.next = next;
    }

    @SuppressWarnings("unchecked")
    protected Object clone() {
        return new Entry<>(hash, key, value,
                              (next==null ? null : (Entry) next.clone()));
    }

    // Map.Entry Ops

    public K getKey() {
        return key;
    }

    public V getValue() {
        return value;
    }

    public V setValue(V value) {
        if (value == null)
            throw new NullPointerException();

        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 (key==null ? e.getKey()==null : key.equals(e.getKey())) &&
           (value==null ? e.getValue()==null : value.equals(e.getValue()));
    }

    public int hashCode() {
        return hash ^ Objects.hashCode(value);
    }

    public String toString() {
        return key.toString()+"="+value.toString();
    }
}
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成员变量

/**
 * The hash table data.
 */
private transient Entry[] table;

/**
 * The total number of entries in the hash table.
 */
private transient int count;

/**
 * The table is rehashed when its size exceeds this threshold.  (The
 * value of this field is (int)(capacity * loadFactor).)
 *
 * @serial
 */
private int threshold;

/**
 * The load factor for the hashtable.
 *
 * @serial
 */
private float loadFactor;

/**
 * The number of times this Hashtable has been structurally modified
 * Structural modifications are those that change the number of entries in
 * the Hashtable or otherwise modify its internal structure (e.g.,
 * rehash).  This field is used to make iterators on Collection-views of
 * the Hashtable fail-fast.  (See ConcurrentModificationException).
 */
private transient int modCount = 0;
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构造方法

public Hashtable(int initialCapacity, float loadFactor) {
    if (initialCapacity < 0)
        throw new IllegalArgumentException("Illegal Capacity: "+
                                           initialCapacity);
    if (loadFactor <= 0 || Float.isNaN(loadFactor))
        throw new IllegalArgumentException("Illegal Load: "+loadFactor);

    if (initialCapacity==0)
        initialCapacity = 1;
    this.loadFactor = loadFactor;
    table = new Entry[initialCapacity];
    threshold = (int)Math.min(initialCapacity * loadFactor, MAX_ARRAY_SIZE + 1);
}

/**
 * Constructs a new, empty hashtable with the specified initial capacity
 * and default load factor (0.75).
 *
 * @param     initialCapacity   the initial capacity of the hashtable.
 * @exception IllegalArgumentException if the initial capacity is less
 *              than zero.
 */
public Hashtable(int initialCapacity) {
    this(initialCapacity, 0.75f);
}

/**
 * Constructs a new, empty hashtable with a default initial capacity (11)
 * and load factor (0.75).
 */
public Hashtable() {
    this(11, 0.75f);
}
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Hashtable 的容量增加逻辑是乘2+1，保证奇数。
在应用数据分布在等差数据集合(如偶数)上时，如果公差与桶容量有公约数n，则至少有(n-1)/n数量的桶是利用不到的。

hash to index

• int hash = key.hashCode();
  int index = (hash & 0x7FFFFFFF) % tab.length;
• 取与之后一定是一个非负数
• 0x7FFFFFFF is 0111 1111 1111 1111 1111 1111 1111 1111 : all 1 except the sign bit.
• (hash & 0x7FFFFFFF) will result in a positive integer.
• (hash & 0x7FFFFFFF) % tab.length will be in the range of the tab length.

put（有锁)

public synchronized V put(K key, V value) {
    // Make sure the value is not null
    if (value == null) {
        throw new NullPointerException();
    }

    // Makes sure the key is not already in the hashtable.
    Entry tab[] = table;
    int hash = key.hashCode();
    int index = (hash & 0x7FFFFFFF) % tab.length;
    @SuppressWarnings("unchecked")
    Entry entry = (Entry)tab[index];
    for(; entry != null ; entry = entry.next) {
        if ((entry.hash == hash) && entry.key.equals(key)) {
            V old = entry.value;
            entry.value = value;
            return old;
        }
    }

    addEntry(hash, key, value, index);
    return null;
}
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private void addEntry(int hash, K key, V value, int index) {
    modCount++;

    Entry tab[] = table;
    if (count >= threshold) {
        // Rehash the table if the threshold is exceeded
        rehash();

        tab = table;
        hash = key.hashCode();
        index = (hash & 0x7FFFFFFF) % tab.length;
    }

    // Creates the new entry.
    @SuppressWarnings("unchecked")
    Entry e = (Entry) tab[index];
    tab[index] = new Entry<>(hash, key, value, e);
    count++;
}
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扩容 rehash

protected void rehash() {
    int oldCapacity = table.length;
    Entry[] oldMap = table;

    // overflow-conscious code
    int newCapacity = (oldCapacity << 1) + 1;
    if (newCapacity - MAX_ARRAY_SIZE > 0) {
        if (oldCapacity == MAX_ARRAY_SIZE)
            // Keep running with MAX_ARRAY_SIZE buckets
            return;
        newCapacity = MAX_ARRAY_SIZE;
    }
    Entry[] newMap = new Entry[newCapacity];

    modCount++;
    threshold = (int)Math.min(newCapacity * loadFactor, MAX_ARRAY_SIZE + 1);
    table = newMap;

    for (int i = oldCapacity ; i-- > 0 ;) {
        for (Entry old = (Entry)oldMap[i] ; old != null ; ) {
            Entry e = old;
            old = old.next;
            // 所有元素重新散列
            int index = (e.hash & 0x7FFFFFFF) % newCapacity;
            e.next = (Entry)newMap[index];
            newMap[index] = e;
        }
    }
}
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get（有锁)

public synchronized V get(Object key) {
    Entry tab[] = table;
    int hash = key.hashCode();
    int index = (hash & 0x7FFFFFFF) % tab.length;
    for (Entry e = tab[index] ; e != null ; e = e.next) {
        if ((e.hash == hash) && e.key.equals(key)) {
            return (V)e.value;
        }
    }
    return null;
}
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remove（有锁)

public synchronized V remove(Object key) {
    Entry tab[] = table;
    int hash = key.hashCode();
    int index = (hash & 0x7FFFFFFF) % tab.length;
    @SuppressWarnings("unchecked")
    Entry e = (Entry)tab[index];
    for(Entry prev = null ; e != null ; prev = e, e = e.next) {
        if ((e.hash == hash) && e.key.equals(key)) {
            modCount++;
            if (prev != null) {
                prev.next = e.next;
            } else {
                tab[index] = e.next;
            }
            count--;
            V oldValue = e.value;
            e.value = null;
            return oldValue;
        }
    }
    return null;
}
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