Java集合类之HashMap学习

[TOC]

文章参考 https://tech.meituan.com/2016/06/24/java-hashmap.html

文章参考：https://mp.weixin.qq.com/s/h5SJ1yuiqGVjfKqExQ3Zng

开始文章之前，我们先来思考几个问题：

1、初始化的容量为什么是16？
2、存储元素的数组的长度为什么都是2的幂次倍？
3、JDK7之后，为什么引入了红黑树？？引入红黑树有什么作用？？
3、红黑树的转化策略
4、HashMap的树形化的阈值为什么是8。列表化的阈值为什么是6.
5、HashMap的树形化的时机，还有什么限制？？

以上这个问题的答案：肯定都是为了性能撒！！

概述

HashMap是基于拉链法实现的一个散列表，它存储的内容是键值对(key-value)映射,内部由数组和链表和红黑树实现。

HashMap 继承于AbstractMap，实现了Map、Cloneable、java.io.Serializable接口。
HashMap 的实现不是同步的，这意味着它不是线程安全的。如果我们想要保证同步，可以考虑使用HashTable或者是ConcurrentHashMap。

HashMap的key、value都可以为null。此外，HashMap中的映射不是有序的。

在JDK1.7中和JDK1.8中有所区别：

在JDK1.7中，由”数组+链表“组成，数组是HashMap的主体，链表则是主要为了解决哈希冲突而存在的。

在JDK1.8中，有“数组+链表+红黑树”组成。当链表过长，则会严重影响HashMap的性能，红黑树搜索时间复杂度是O(logn)，而链表是O(n)。因此，JDK1.8对数据结构做了进一步的优化，引入了红黑树，链表和红黑树在达到一定条件会进行转换：

• 当链表超过8且数组长度(数据总量)超过64才会转为红黑树
• 将链表转换成红黑树前会判断，如果当前数组的长度小于64，那么会选择先进行数组扩容，而不是转换为红黑树，以减少搜索时间。

下面我们来对照源码类分析一下Hashmap的源码，来分析HashMap的工作原理。

首先，我们来看一下，HashMap的构造函数

/**
 * 默认的加载因子
 */
static final float DEFAULT_LOAD_FACTOR = 0.75f;

// 无参构造函数
public HashMap() {
    // 初始化填充因子.默认为0.75f
    this.loadFactor = DEFAULT_LOAD_FACTOR;
}

// 传入初始化容量的含参构造函数
public HashMap(int initialCapacity) {
    // 调用HashMap(int, float)型构造函数
    this(initialCapacity, DEFAULT_LOAD_FACTOR);
}

// 自定义初始化容量和默认填充因子的构造函数
public HashMap(int initialCapacity, float loadFactor) {
    // 初始容量不能小于0，否则报错
    if (initialCapacity < 0)
        throw new IllegalArgumentException("Illegal initial capacity: " +
                                            initialCapacity);
    // 初始容量不能大于最大值，否则为最大值
    if (initialCapacity > MAXIMUM_CAPACITY)
        initialCapacity = MAXIMUM_CAPACITY;
    // 填充因子不能小于或等于0，不能为非数字
    if (loadFactor <= 0 || Float.isNaN(loadFactor))
        throw new IllegalArgumentException("Illegal load factor: " +
                                            loadFactor);
    // 初始化填充因子
    this.loadFactor = loadFactor;
    /// 这个方法可以将任意一个整数转换大约的最小成2的幂次方。
    // 例如输入10，则会返回16。
    // 另外，有人可能疑惑，不是说threshold是 数组容量 * loadFactor得到的吗？
    // 是的，但是在第一次put操作，扩充数组时，会将这个threshold作为数组容量，然后再重新计算这个值。
    // 这个方法的具体实现我们下面解析
    this.threshold = tableSizeFor(initialCapacity);
}

// 以Map作为参数的构造函数
public HashMap(Map<? extends K, ? extends V> m) {
    // 初始化填充因子
    this.loadFactor = DEFAULT_LOAD_FACTOR;
    // 将m中的所有元素添加至HashMap中，这个方法我们下面分析
    putMapEntries(m, false);
}

下面我们来看一下类的属性

// 默认的初始容量是16,为什么默认是16，后面我们会解释道
static final int DEFAULT_INITIAL_CAPACITY = 1 << 4;
// 最大容量 2的30次幂
static final int MAXIMUM_CAPACITY = 1 << 30; 
// 默认的填充因子
static final float DEFAULT_LOAD_FACTOR = 0.75f;
// 当桶(bucket)上的结点数大于这个值时会转成红黑树
static final int TREEIFY_THRESHOLD = 8;
// 当桶(bucket)上的结点数小于这个值时树转链表
static final int UNTREEIFY_THRESHOLD = 6;

// 桶中结构转化为红黑树对应的table的最小大小
static final int MIN_TREEIFY_CAPACITY = 64;
// 存储元素的数组，总是2的幂次倍。Node则是链表节点对象。
transient Node<k,v>[] table;
// 存放具体元素的集
transient Set<map.entry<k,v>> entrySet;
// 存放元素的个数，注意这个不等于数组的长度。
transient int size;
// 每次扩容和更改map结构的计数器
transient int modCount;
// 临界值 当实际大小(容量*填充因子，但是第一次不是)超过临界值时，会进行扩容
int threshold;
// 填充因子
final float loadFactor;

4、Hasp的重点方法解析
请注意。我们是以JDK1.8.0_181版本来分析的。不同的JDK版本可能在实现有不同，但是基本思想都是一致的。
4.1、HashMap的put() 存放元素

• 这个是非常重要的方法！！！

• 所以我们着重分析一下

• 这个方法是将对应的value与对应的key进行关联，存放到Map中

• 如果原来Map中有对应key的value.那么便会更新为入参value

   * */
     public V put(K key, V value) {
     // 这个方法调用了putVal()。入参的时候调用hash(key)这个方法代码中有讲解
     return putVal(hash(key), key, value, false, true);
     }
  
  /**

• 从上面我们可以看到put()方法调用了这个方法。

• onlyIfAbsent：当存入键值对时，如果该key已存在，是否覆盖它的value。false为覆盖，true为不覆盖 *参考putIfAbsent()方法。

• evict：用于子类LinkedHashMap。 也就是说在hashmap是没有用的

• 下面我们简单介绍一下这个方法：

•      1.检查数组是否为空，执行resize()扩充；
  

•      2.通过hash值计算数组索引，获取该索引位的首节点。 
  

•      3.如果首节点为null（没发生碰撞） ，
  

•      直接添加节点到该索引位 (bucket) 。 
  

•      4.如果首节点不为null （发生碰撞） ，
  

•      那么有3种情况 ：
  

•          ① key和首节点的key相同，覆盖old value （保证key的唯一性） ；
  

•      否则执行②或③ 
  

•          ② 如果首节点是红黑树节点（TreeNode），将键值对添加到红黑树。 
  

•          ③ 如果首节点是链表，将键值对添加到链表。添加之后会判断链表长度是否到达TREEIFY_THRESHOLD - 1这个阈值，“尝试”将链表转换成红黑树。 
  

• 5.最后判断当前元素个数是否大于threshold，扩充数组。

• 我们根据key来获取Node的节点数据
  */
  public V get(Object key) {
  Node<K,V> e;
  // 根据key来计算对应的Hash值，通过key的hash值和key来获取对应的Value
  // 下面我们来看getNode方法
  return (e = getNode(hash(key), key)) == null ? null : e.value;
  }

/**

• 获取HashMap的Node节点
  */
  final Node<K,V> getNode(int hash, Object key) {
  //tab：内部数组 first: 索引位首节点 n: 数组长度 k: 索引位首节点的key
  Node<K,V>[] tab; Node<K,V> first, e; int n; K k;

  //数组不为null 数组长度大于0 定位到数组中的索引处。并判断索引位首节点不为null
  if ((tab = table) != null && (n = tab.length) > 0 &&

  // i = (n - 1) & hash ，n是数组长度，hash就是通过hash()方法进行高低位异或运算得出来的hash值。 //这个表达式就是hash值的取模运算，上面已经说过当除数为2的次方时，可以用与运算提高性能。
  // 所以这里也就是解决了我们为什么要将数组长度取2的N次方
  
  (first = tab[(n - 1) & hash]) != null) {
  
  // 如果索引位首节点的hash==key的hash 或者 key和索引位首节点的k相同
  if (first.hash == hash && // always check first node
      ((k = first.key) == key || (key != null && key.equals(k))))
       // 返回索引位首节点(值对象)
      return first;
  //  
  if ((e = first.next) != null) {
      if (first instanceof TreeNode)
          // 如果是红黑色则到红黑树中查找.
          // getNode的方法比较简单，下面我们就来看getTreeNode的方法实现
          return ((TreeNode<K,V>)first).getTreeNode(hash, key);
      // 否则就在链表中进行遍历朝朝。找到就返回e    
      do {
          if (e.hash == hash &&
              ((k = e.key) == key || (key != null && key.equals(k))))
              return e;
      } while ((e = e.next) != null);
  }

  }
  return null;
  }
  4.3 resize() 数组扩容

  // 遍历原数组
  for (int j = 0; j < oldCap; ++j) {
  // 取出首节点
  HashMap.Node<K,V> e;
  if ((e = oldTab[j]) != null) {
  oldTab[j] = null;
  // 如果链表只有一个节点，那么直接重新计算索引存入新数组。
  if (e.next == null)
  newTab[e.hash & (newCap - 1)] = e;
  // 如果该节点是红黑树，执行split方法，和链表类似的处理。
  else if (e instanceof HashMap.TreeNode)
  ((HashMap.TreeNode<K,V>)e).split(this, newTab, j, oldCap);
  
  // 此时节点是链表
  else { // preserve order
  // loHead，loTail为原链表的节点，索引不变。
  HashMap.Node<K,V> loHead = null, loTail = null;
  // hiHeadm, hiTail为新链表节点，原索引 + 原数组长度。
  HashMap.Node<K,V> hiHead = null, hiTail = null;
  HashMap.Node<K,V> next;
  
  // 遍历链表
  do {
  next = e.next;
  // 新增bit为0的节点，存入原链表。
  if ((e.hash & oldCap) == 0) {
  if (loTail == null)
  loHead = e;
  else
  loTail.next = e;
  loTail = e;
  }
  // 新增bit为1的节点，存入新链表。
  else {
  if (hiTail == null)
  hiHead = e;
  else
  hiTail.next = e;
  hiTail = e;
  }
  } while ((e = next) != null);
  // 原链表存回原索引位
  if (loTail != null) {
  loTail.next = null;
  newTab[j] = loHead;
  }
  // 新链表存到：原索引位 + 原数组长度
  if (hiTail != null) {
  hiTail.next = null;
  newTab[j + oldCap] = hiHead;
  }
  }
  }
  }
  }
  return newTab;
  }
  扩充数组不单单只是让数组长度翻倍，将原数组中的元素直接存入新数组中这么简单。
  因为元素的索引是通过hash&(n - 1)得到的，那么数组的长度由n变为2n，重新计算的索引就可能和原来的不一样了。
  在jdk1.7中，是通过遍历每一个元素，每一个节点，重新计算他们的索引值，存入新的数组中，称为rehash操作。

而java1.8对此进行了一些优化，没有了rehash操作。因为当数组长度是通过2的次方扩充的，那么会发现以下规律：

元素的位置要么是在原位置，要么是在原位置再移动2次幂的位置。因此，在扩充HashMap的时候，不需要像JDK1.7的实现那样重新计算hash，只需要看看原来的hash值新增的那个bit是1还是0就好了，是0的话索引没变，是1的话索引变成“原索引+oldCap”。

先计算新数组的长度和新的阈值（threshold），然后将旧数组的内容迁移到新数组中，和1.7相比不需要执行rehash操作。因为以2次幂扩展的数组可以简单通过新增的bit判断索引位。

4.4、树形化的treeifyBin() 方法。
Code
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// 把链表转换为红黑树
final void treeifyBin(Node<K,V>[] tab, int hash) {
int n, index; Node<K,V> e;
// 如果当前数组容量太小（小于64），放弃转换，扩充数组。
if (tab == null || (n = tab.length) < MIN_TREEIFY_CAPACITY)
resize();
} else if ((e = tab[index = (n - 1) & hash]) != null) {
// 将链表转成红黑树…
}
}
HashMap在jdk1.8之后引入了红黑树的概念，表示若桶中链表元素超过8时，会自动转化成红黑树；若桶中元素小于等于6时，树结构还原成链表形式。
红黑树的平均查找长度是log(n)，长度为8，查找长度为log(8)=3，链表的平均查找长度为n/2，当长度为8时，平均查找长度为8/2=4，这才有转换成树的必要；链表长度如果是小于等于6，6/2=3，虽然速度也很快的，但是转化为树结构和生成树的时间并不会太短。

五、HashMap的源码分析

public class HashMap<K,V> extends AbstractMap<K,V>
    implements Map<K,V>, Cloneable, Serializable {
private static final long serialVersionUID = 362498820763181265L;

/**
 * 默认的初始化容量是16，必须是2的幂次方（只有为什么我们下面会讲）。
 */
static final int DEFAULT_INITIAL_CAPACITY = 1 << 4; // aka 16

/**
 * 容量最大为2的30次方
 */
static final int MAXIMUM_CAPACITY = 1 << 30;

/**
 * The load factor used when none specified in constructor.
 * 如果未特殊指定加载因子的话，默认为0.75.
 * 至于为什么是0.75f。这是时间与空间综合考虑的经验值
 */
static final float DEFAULT_LOAD_FACTOR = 0.75f;

/**
 *  树形化阈值，当桶(bucket)上的结点数大于这个值时会转成红黑树
 */
static final int TREEIFY_THRESHOLD = 8;

/**
 *  解除树形化阈值，当桶(bucket)上的结点数小于这个值时树转链表
 */
static final int UNTREEIFY_THRESHOLD = 6;

/**
 * 树形化阈值的第二条件。当数组的长度小于这个值时，
 * 就算树形化阈达标，链表也不会转化为红黑树，而是优先扩容数组resize()。
 */
static final int MIN_TREEIFY_CAPACITY = 64;

/**
 * HashMap的数据存储Key-Value的节点对象。
 */
static class Node<K,V> implements Map.Entry<K,V> {
    final int hash;
    final K key;
    V value;
    // 链表的下一个节点
    Node<K,V> next;
    // 节点的构造函数
    Node(int hash, K key, V value, Node<K,V> 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;
    }
}

/* ---------------- Static utilities -------------- */

/**
 * 上面的代码只是用hashCode的高16位与低16位进行异或运算。 
 * hash() 方法就是将hashCode进一步的混淆，增加其 “随机度” ，试图减少插入HashMap时的hash冲突 。
 * 计算HashMap的key的hashCode的值。至于计算这个Key的hash的值的算法
 * 我们可以理解为这是考虑到位扩展的速度、实用性以及尽量让hash散列集合理分布
 * 这些因素之后的权衡做法
 */
static final int hash(Object key) {
    int h;
    return (key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 16);
}

/**
 * Returns x's Class if it is of the form "class C implements
 * Comparable<C>", else null.
 */
static Class<?> comparableClassFor(Object x) {
    if (x instanceof Comparable) {
        Class<?> c; Type[] ts, as; Type t; ParameterizedType p;
        if ((c = x.getClass()) == String.class) // bypass checks
            return c;
        if ((ts = c.getGenericInterfaces()) != null) {
            for (int i = 0; i < ts.length; ++i) {
                if (((t = ts[i]) instanceof ParameterizedType) &&
                    ((p = (ParameterizedType)t).getRawType() ==
                     Comparable.class) &&
                    (as = p.getActualTypeArguments()) != null &&
                    as.length == 1 && as[0] == c) // type arg is c
                    return c;
            }
        }
    }
    return null;
}

/**
 * Returns k.compareTo(x) if x matches kc (k's screened comparable
 * class), else 0.
 */
@SuppressWarnings({"rawtypes","unchecked"}) // for cast to Comparable
static int compareComparables(Class<?> kc, Object k, Object x) {
    return (x == null || x.getClass() != kc ? 0 :
            ((Comparable)k).compareTo(x));
}

/**
 * 返回给定大于容量值的最小2次幂。用来计算扩容的临界值
 * 跟大神学习了。用位运算代替取模预算(据说提升了5~8倍)。
 * 我们可以通过位运算来计算大约某个数的最小二次幂。
 *  >>> : 无符号右移，忽略符号位，空位都以0补齐
 * 
 */
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;
}

/* ---------------- Fields -------------- */

/**
 * HashMap的节点数组，当我们第一次使用的时候初始化大小
 * 当需要的时候，我们会进行扩容
 */
transient Node<K,V>[] table;

/**
 * Holds cached entrySet(). Note that AbstractMap fields are used
 * for keySet() and values().
 */
transient Set<Map.Entry<K,V>> entrySet;

// HashMap中键值对的数目
transient int size;

/**
 * HashMap结构被修改的次数。
 * 结构修改是指改变HashMap中映射的数量或修改其内部结构的次数(例如，rehash)。
 */
transient int modCount;

/**
 * 数组扩容阈值。即：HashMap数组总容量 * 加载因子。当前容量大于或等于该值时会执行扩容** resize() **。
 * 扩容的容量为当前 * HashMap 总容量的两倍。比如，当前 HashMap 的总容量为 16 ，那么扩容之后为 32 。
 */需要调整大小的阈值。容量*加载因子
int threshold;

/**
 * 加载因子
 */
final float loadFactor;

/* ---------------- Public operations -------------- */

/**
 * 这个方法是map作为参数的构造方法里面调用(clone方法也有调用)
 */
final void putMapEntries(Map<? extends K, ? extends V> m, boolean evict) {
    // 传入的Map的元素个数
    int s = m.size();
    // 元素个数大于0，我们开始执行下面的操作
    if (s > 0) {
        // 如果Hash桶的数组为null
        if (table == null) { // pre-size
            float ft = ((float)s / loadFactor) + 1.0F;
            int t = ((ft < (float)MAXIMUM_CAPACITY) ?
                     (int)ft : MAXIMUM_CAPACITY);
            if (t > threshold)
                threshold = tableSizeFor(t);
        }
        else if (s > threshold)
            resize();
        for (Map.Entry<? extends K, ? extends V> e : m.entrySet()) {
            K key = e.getKey();
            V value = e.getValue();
            putVal(hash(key), key, value, false, evict);
        }
    }
}

/**
 * Returns the number of key-value mappings in this map.
 *
 * @return the number of key-value mappings in this map
 */
public int size() {
    return size;
}

/**
 * Returns <tt>true</tt> if this map contains no key-value mappings.
 *
 * @return <tt>true</tt> if this map contains no key-value mappings
 */
public boolean isEmpty() {
    return size == 0;
}

/**
 * 我们根据key来获取Node的节点数据
 */
public V get(Object key) {
    Node<K,V> e;
    // 根据key来计算对应的Hash值，通过key的hash值和key来获取对应的Value
    // 下面我们来看getNode方法
    return (e = getNode(hash(key), key)) == null ? null : e.value;
}

/**
 * 获取HashMap的Node节点
 */
final Node<K,V> getNode(int hash, Object key) {
    //tab：内部数组  first: 索引位首节点 n: 数组长度 k: 索引位首节点的key
    Node<K,V>[] tab; Node<K,V> first, e; int n; K k;
    
    //数组不为null 数组长度大于0 定位到数组中的索引处。并判断索引位首节点不为null
    if ((tab = table) != null && (n = tab.length) > 0 &&
       
        // i = (n - 1) & hash ，n是数组长度，hash就是通过hash()方法进行高低位异或运算得出来的hash值。 //这个表达式就是hash值的取模运算，上面已经说过当除数为2的次方时，可以用与运算提高性能。
        // 所以这里也就是解决了我们为什么要将数组长度取2的N次方
        
        (first = tab[(n - 1) & hash]) != null) {
        
        // 如果索引位首节点的hash==key的hash 或者 key和索引位首节点的k相同
        if (first.hash == hash && // always check first node
            ((k = first.key) == key || (key != null && key.equals(k))))
             // 返回索引位首节点(值对象)
            return first;
        //  
        if ((e = first.next) != null) {
            if (first instanceof TreeNode)
                // 如果是红黑色则到红黑树中查找.
                // getNode的方法比较简单，下面我们就来看getTreeNode的方法实现
                return ((TreeNode<K,V>)first).getTreeNode(hash, key);
            // 否则就在链表中进行遍历朝朝。找到就返回e    
            do {
                if (e.hash == hash &&
                    ((k = e.key) == key || (key != null && key.equals(k))))
                    return e;
            } while ((e = e.next) != null);
        }
    }
    return null;
}

/**
 * Returns <tt>true</tt> if this map contains a mapping for the
 * specified key.
 *
 * @param   key   The key whose presence in this map is to be tested
 * @return <tt>true</tt> if this map contains a mapping for the specified
 * key.
 */
public boolean containsKey(Object key) {
    return getNode(hash(key), key) != null;
}

/**
 * 这个是非常重要的方法！！！
 * 所以我们着重分析一下
 * 这个方法是将对应的value与对应的key进行关联，存放到Map中
 * 如果原来Map中有对应key的value.那么便会更新为入参value
 */
public V put(K key, V value) {
    // 这个方法调用了putVal()。入参的时候调用hash(key)这个方法代码中有讲解
    return putVal(hash(key), key, value, false, true);
}

/**
 * 从上面我们可以看到put()方法调用了这个方法。
 * onlyIfAbsent：当存入键值对时，如果该key已存在，是否覆盖它的value。false为覆盖，true为不覆盖 *参考putIfAbsent()方法。
 * evict：用于子类LinkedHashMap。 也就是说在hashmap是没有用的

​
​ * 下面我们简单介绍一下这个方法：
​ * 1.检查数组是否为空，执行resize()扩充；
​ * 2.通过hash值计算数组索引，获取该索引位的首节点。
​ * 3.如果首节点为null（没发生碰撞） ，
​ * 直接添加节点到该索引位 (bucket) 。
​ * 4.如果首节点不为null （发生碰撞） ，
​ * 那么有3种情况 ：
​ * ① key和首节点的key相同，覆盖old value （保证key的唯一性） ；
​ * 否则执行②或③
​ * ② 如果首节点是红黑树节点（TreeNode），将键值对添加到红黑树。
​ * ③ 如果首节点是链表，将键值对添加到链表。添加之后会判断链表长度是否到达TREEIFY_THRESHOLD - 1这个阈值，“尝试”将链表转换成红黑树。
​ * 5.最后判断当前元素个数是否大于threshold，扩充数组。
​ */
​ final V putVal(int hash, K key, V value, boolean onlyIfAbsent,
​ boolean evict) {
​ // 声明hash桶的内部数组临时变量tab
​ // p：hash对应的索引位中的首节点
​ // n：内部数组的长度 i：hash对应的索引位
​ Node<K,V>[] tab; Node<K,V> p; int n, i;
​ // 条件一:table为null 或者table数组长度为0。
​ if ((tab = table) == null || (n = tab.length) == 0)
​ n = (tab = resize()).length; // 执行扩容操作，并计算数组长度
​ // i = (n-1)&hash 计算index值。所以当我们取值的时候，也是从这个Index
​ // 如果为null 那么通过newNode来构建hash桶的这个节点
​ if ((p = tab[i = (n - 1) & hash]) == null)
​ // 创建一个新的节点
​ tab[i] = newNode(hash, key, value, null);
​ else {
​ Node<K,V> e; K k;
​ //节点key存在，直接覆盖value
​ if (p.hash == hash &&
​ ((k = p.key) == key || (key != null && key.equals(k))))
​ e = p;
​ // 如果判断当前链是红黑树
​ else if (p instanceof TreeNode)
​ // 则执行红黑树的插入值的相关操作
​ e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value);
​ // 此时首节点为链表，如果链表中存在该键值对，直接覆盖value。
​ // 如果不存在，则在末端插入键值对。然后判断链表是否大于等于7，尝试转换成红黑树。
​ // 注意此处使用“尝试”，因为在treeifyBin方法中还会判断当前数组容量是否到达64，
​ // 否则会放弃次此转换，优先扩充数组容量。
​ else {
​ // 如果p节点不是为空，也不是为红黑树，那就是普通的链表
​ // 走到这里，hash碰撞了。检查链表中是否包含key，或将键值对添加到链表末尾
​ for (int binCount = 0; ; ++binCount) {
​ // p.next == null，到达链表末尾，添加新节点，如果长度足够，转换成树结构。
​ if ((e = p.next) == null) {
​ p.next = newNode(hash, key, value, null);
​ //链表长度大于7转换为红黑树进行处理（大于等于7）
​ if (binCount >= TREEIFY_THRESHOLD - 1) // -1 for 1st
​ treeifyBin(tab, hash);
​ break;
​ }
​ // 如果对应的Key已经存在则直接覆盖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;
​ // 如果超过最大的扩容林接着，则进行扩容
​ if (++size > threshold)
​ resize();
​ afterNodeInsertion(evict);
​ return null;
​ }

final HashMap.Node<K,V>[] resize() {
HashMap.Node<K,V>[] oldTab = table;
int oldCap = (oldTab == null) ? 0 : oldTab.length;
int oldThr = threshold;
int newCap, newThr = 0;
if (oldCap > 0) {
// 如果数组已经是最大长度，不进行扩充。
if (oldCap >= MAXIMUM_CAPACITY) {
threshold = Integer.MAX_VALUE;
return oldTab;
}
// 否则数组容量扩充一倍。（2的N次方）
else if ((newCap = oldCap << 1) < MAXIMUM_CAPACITY &&
oldCap >= DEFAULT_INITIAL_CAPACITY)
newThr = oldThr << 1; // double threshold
}
// 如果数组还没创建，但是已经指定了threshold（这种情况是带参构造创建的对象），threshold的值为数组长度
// 在 “构造函数” 那块内容进行过说明。
else if (oldThr > 0) // initial capacity was placed in threshold
newCap = oldThr;
// 这种情况是通过无参构造创建的对象
else { // zero initial threshold signifies using defaults
newCap = DEFAULT_INITIAL_CAPACITY;
newThr = (int)(DEFAULT_LOAD_FACTOR * DEFAULT_INITIAL_CAPACITY);
}
// 可能是上面newThr = oldThr << 1时，最高位被移除了，变为0。
if (newThr == 0) {
float ft = (float)newCap * loadFactor;
newThr = (newCap < MAXIMUM_CAPACITY && ft < (float)MAXIMUM_CAPACITY ?
(int)ft : Integer.MAX_VALUE);
}
threshold = newThr;

// 到了这里，新的数组长度已经被计算出来，创建一个新的数组。
@SuppressWarnings({"rawtypes","unchecked"})
HashMap.Node<K,V>[] newTab = (HashMap.Node<K,V>[])new HashMap.Node[newCap];
table = newTab;

// 下面代码是将原来数组的元素转移到新数组中。问题在于，数组长度发生变化。 
// 那么通过hash%数组长度计算的索引也将和原来的不同。
// jdk 1.7中是通过重新计算每个元素的索引，重新存入新的数组，称为rehash操作。
// 这也是hashMap无序性的原因之一。而现在jdk 1.8对此做了优化，非常的巧妙。
if (oldTab != null) {
    
    // 遍历原数组
    for (int j = 0; j < oldCap; ++j) {
        // 取出首节点
        HashMap.Node<K,V> e;
        if ((e = oldTab[j]) != null) {
            oldTab[j] = null;
            // 如果链表只有一个节点，那么直接重新计算索引存入新数组。
            if (e.next == null)
                newTab[e.hash & (newCap - 1)] = e;
            // 如果该节点是红黑树，执行split方法，和链表类似的处理。
            else if (e instanceof HashMap.TreeNode)
                ((HashMap.TreeNode<K,V>)e).split(this, newTab, j, oldCap);
            
            // 此时节点是链表
            else { // preserve order
                // loHead，loTail为原链表的节点，索引不变。
                HashMap.Node<K,V> loHead = null, loTail = null;
                // hiHeadm, hiTail为新链表节点，原索引 + 原数组长度。
                HashMap.Node<K,V> hiHead = null, hiTail = null;
                HashMap.Node<K,V> next;
                
               // 遍历链表
                do {
                    next = e.next;
                    // 新增bit为0的节点，存入原链表。
                    if ((e.hash & oldCap) == 0) {
                        if (loTail == null)
                            loHead = e;
                        else
                            loTail.next = e;
                        loTail = e;
                    }
                    // 新增bit为1的节点，存入新链表。
                    else {
                        if (hiTail == null)
                            hiHead = e;
                        else
                            hiTail.next = e;
                        hiTail = e;
                    }
                } while ((e = next) != null);
                // 原链表存回原索引位
                if (loTail != null) {
                    loTail.next = null;
                    newTab[j] = loHead;
                }
                // 新链表存到：原索引位 + 原数组长度
                if (hiTail != null) {
                    hiTail.next = null;
                    newTab[j + oldCap] = hiHead;
                }
            }
        }
    }
}
return newTab;

}

/**
 * 这个方法是将链表转化为红黑树
 *      如果当前数组容量太小（小于64），放弃转换，扩充数组。
 */
final void treeifyBin(Node<K,V>[] tab, int hash) {
    int n, index; Node<K,V> e;
    // 如果当前数组容量太小（小于64），放弃转换，扩充数组。
    if (tab == null || (n = tab.length) < MIN_TREEIFY_CAPACITY)
        resize();
    else if ((e = tab[index = (n - 1) & hash]) != null) {
        // 将链表转化为红黑树
        TreeNode<K,V> hd = null, tl = null;
        do {
            TreeNode<K,V> p = replacementTreeNode(e, null);
            if (tl == null)
                hd = p;
            else {
                p.prev = tl;
                tl.next = p;
            }
            tl = p;
        } while ((e = e.next) != null);
        if ((tab[index] = hd) != null)
            hd.treeify(tab);
    }
}

/**
 * Copies all of the mappings from the specified map to this map.
 * These mappings will replace any mappings that this map had for
 * any of the keys currently in the specified map.
 *
 * @param m mappings to be stored in this map
 * @throws NullPointerException if the specified map is null
 */
public void putAll(Map<? extends K, ? extends V> m) {
    putMapEntries(m, true);
}

/**
 * Removes the mapping for the specified key from this map if present.
 *
 * @param  key key whose mapping is to be removed from the map
 * @return the previous value associated with <tt>key</tt>, or
 *         <tt>null</tt> if there was no mapping for <tt>key</tt>.
 *         (A <tt>null</tt> return can also indicate that the map
 *         previously associated <tt>null</tt> with <tt>key</tt>.)
 */
public V remove(Object key) {
    Node<K,V> e;
    return (e = removeNode(hash(key), key, null, false, true)) == null ?
        null : e.value;
}

/**
 * Implements Map.remove and related methods
 *
 * @param hash hash for key
 * @param key the key
 * @param value the value to match if matchValue, else ignored
 * @param matchValue if true only remove if value is equal
 * @param movable if false do not move other nodes while removing
 * @return the node, or null if none
 */
final Node<K,V> removeNode(int hash, Object key, Object value,
                           boolean matchValue, boolean movable) {
    Node<K,V>[] tab; Node<K,V> p; int n, index;
    if ((tab = table) != null && (n = tab.length) > 0 &&
        (p = tab[index = (n - 1) & hash]) != null) {
        Node<K,V> node = null, e; K k; V v;
        if (p.hash == hash &&
            ((k = p.key) == key || (key != null && key.equals(k))))
            node = p;
        else if ((e = p.next) != null) {
            if (p instanceof TreeNode)
                node = ((TreeNode<K,V>)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);
            }
        }
        if (node != null && (!matchValue || (v = node.value) == value ||
                             (value != null && value.equals(v)))) {
            if (node instanceof TreeNode)
                ((TreeNode<K,V>)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;
}

/**
 * Removes all of the mappings from this map.
 * The map will be empty after this call returns.
 */
public void clear() {
    Node<K,V>[] tab;
    modCount++;
    if ((tab = table) != null && size > 0) {
        size = 0;
        for (int i = 0; i < tab.length; ++i)
            tab[i] = null;
    }
}

/**
 * Returns <tt>true</tt> if this map maps one or more keys to the
 * specified value.
 *
 * @param value value whose presence in this map is to be tested
 * @return <tt>true</tt> if this map maps one or more keys to the
 *         specified value
 */
public boolean containsValue(Object value) {
    Node<K,V>[] tab; V v;
    if ((tab = table) != null && size > 0) {
        for (int i = 0; i < tab.length; ++i) {
            for (Node<K,V> e = tab[i]; e != null; e = e.next) {
                if ((v = e.value) == value ||
                    (value != null && value.equals(v)))
                    return true;
            }
        }
    }
    return false;
}

/**
 * Returns a {@link Set} view of the keys contained in this map.
 * The set is backed by the map, so changes to the map are
 * reflected in the set, and vice-versa.  If the map is modified
 * while an iteration over the set is in progress (except through
 * the iterator's own <tt>remove</tt> operation), the results of
 * the iteration are undefined.  The set supports element removal,
 * which removes the corresponding mapping from the map, via the
 * <tt>Iterator.remove</tt>, <tt>Set.remove</tt>,
 * <tt>removeAll</tt>, <tt>retainAll</tt>, and <tt>clear</tt>
 * operations.  It does not support the <tt>add</tt> or <tt>addAll</tt>
 * operations.
 *
 * @return a set view of the keys contained in this map
 */
public Set<K> keySet() {
    Set<K> ks = keySet;
    if (ks == null) {
        ks = new KeySet();
        keySet = ks;
    }
    return ks;
}

final class KeySet extends AbstractSet<K> {
    public final int size()                 { return size; }
    public final void clear()               { HashMap.this.clear(); }
    public final Iterator<K> iterator()     { return new KeyIterator(); }
    public final boolean contains(Object o) { return containsKey(o); }
    public final boolean remove(Object key) {
        return removeNode(hash(key), key, null, false, true) != null;
    }
    public final Spliterator<K> spliterator() {
        return new KeySpliterator<>(HashMap.this, 0, -1, 0, 0);
    }
    public final void forEach(Consumer<? super K> action) {
        Node<K,V>[] tab;
        if (action == null)
            throw new NullPointerException();
        if (size > 0 && (tab = table) != null) {
            int mc = modCount;
            for (int i = 0; i < tab.length; ++i) {
                for (Node<K,V> e = tab[i]; e != null; e = e.next)
                    action.accept(e.key);
            }
            if (modCount != mc)
                throw new ConcurrentModificationException();
        }
    }
}

/**
 * Returns a {@link Collection} view of the values contained in this map.
 * The collection is backed by the map, so changes to the map are
 * reflected in the collection, and vice-versa.  If the map is
 * modified while an iteration over the collection is in progress
 * (except through the iterator's own <tt>remove</tt> operation),
 * the results of the iteration are undefined.  The collection
 * supports element removal, which removes the corresponding
 * mapping from the map, via the <tt>Iterator.remove</tt>,
 * <tt>Collection.remove</tt>, <tt>removeAll</tt>,
 * <tt>retainAll</tt> and <tt>clear</tt> operations.  It does not
 * support the <tt>add</tt> or <tt>addAll</tt> operations.
 *
 * @return a view of the values contained in this map
 */
public Collection<V> values() {
    Collection<V> vs = values;
    if (vs == null) {
        vs = new Values();
        values = vs;
    }
    return vs;
}

final class Values extends AbstractCollection<V> {
    public final int size()                 { return size; }
    public final void clear()               { HashMap.this.clear(); }
    public final Iterator<V> iterator()     { return new ValueIterator(); }
    public final boolean contains(Object o) { return containsValue(o); }
    public final Spliterator<V> spliterator() {
        return new ValueSpliterator<>(HashMap.this, 0, -1, 0, 0);
    }
    public final void forEach(Consumer<? super V> action) {
        Node<K,V>[] tab;
        if (action == null)
            throw new NullPointerException();
        if (size > 0 && (tab = table) != null) {
            int mc = modCount;
            for (int i = 0; i < tab.length; ++i) {
                for (Node<K,V> e = tab[i]; e != null; e = e.next)
                    action.accept(e.value);
            }
            if (modCount != mc)
                throw new ConcurrentModificationException();
        }
    }
}

/**
 * Returns a {@link Set} view of the mappings contained in this map.
 * The set is backed by the map, so changes to the map are
 * reflected in the set, and vice-versa.  If the map is modified
 * while an iteration over the set is in progress (except through
 * the iterator's own <tt>remove</tt> operation, or through the
 * <tt>setValue</tt> operation on a map entry returned by the
 * iterator) the results of the iteration are undefined.  The set
 * supports element removal, which removes the corresponding
 * mapping from the map, via the <tt>Iterator.remove</tt>,
 * <tt>Set.remove</tt>, <tt>removeAll</tt>, <tt>retainAll</tt> and
 * <tt>clear</tt> operations.  It does not support the
 * <tt>add</tt> or <tt>addAll</tt> operations.
 *
 * @return a set view of the mappings contained in this map
 */
public Set<Map.Entry<K,V>> entrySet() {
    Set<Map.Entry<K,V>> es;
    return (es = entrySet) == null ? (entrySet = new EntrySet()) : es;
}

final class EntrySet extends AbstractSet<Map.Entry<K,V>> {
    public final int size()                 { return size; }
    public final void clear()               { HashMap.this.clear(); }
    public final Iterator<Map.Entry<K,V>> iterator() {
        return new EntryIterator();
    }
    public final boolean contains(Object o) {
        if (!(o instanceof Map.Entry))
            return false;
        Map.Entry<?,?> e = (Map.Entry<?,?>) o;
        Object key = e.getKey();
        Node<K,V> candidate = getNode(hash(key), key);
        return candidate != null && candidate.equals(e);
    }
    public final boolean remove(Object o) {
        if (o instanceof Map.Entry) {
            Map.Entry<?,?> e = (Map.Entry<?,?>) o;
            Object key = e.getKey();
            Object value = e.getValue();
            return removeNode(hash(key), key, value, true, true) != null;
        }
        return false;
    }
    public final Spliterator<Map.Entry<K,V>> spliterator() {
        return new EntrySpliterator<>(HashMap.this, 0, -1, 0, 0);
    }
    public final void forEach(Consumer<? super Map.Entry<K,V>> action) {
        Node<K,V>[] tab;
        if (action == null)
            throw new NullPointerException();
        if (size > 0 && (tab = table) != null) {
            int mc = modCount;
            for (int i = 0; i < tab.length; ++i) {
                for (Node<K,V> e = tab[i]; e != null; e = e.next)
                    action.accept(e);
            }
            if (modCount != mc)
                throw new ConcurrentModificationException();
        }
    }
}

// Overrides of JDK8 Map extension methods

@Override
public V getOrDefault(Object key, V defaultValue) {
    Node<K,V> e;
    return (e = getNode(hash(key), key)) == null ? defaultValue : e.value;
}

@Override
public V putIfAbsent(K key, V value) {
    return putVal(hash(key), key, value, true, true);
}

@Override
public boolean remove(Object key, Object value) {
    return removeNode(hash(key), key, value, true, true) != null;
}

@Override
public boolean replace(K key, V oldValue, V newValue) {
    Node<K,V> e; V v;
    if ((e = getNode(hash(key), key)) != null &&
        ((v = e.value) == oldValue || (v != null && v.equals(oldValue)))) {
        e.value = newValue;
        afterNodeAccess(e);
        return true;
    }
    return false;
}

@Override
public V replace(K key, V value) {
    Node<K,V> e;
    if ((e = getNode(hash(key), key)) != null) {
        V oldValue = e.value;
        e.value = value;
        afterNodeAccess(e);
        return oldValue;
    }
    return null;
}

@Override
public V computeIfAbsent(K key,
                         Function<? super K, ? extends V> mappingFunction) {
    if (mappingFunction == null)
        throw new NullPointerException();
    int hash = hash(key);
    Node<K,V>[] tab; Node<K,V> first; int n, i;
    int binCount = 0;
    TreeNode<K,V> t = null;
    Node<K,V> old = null;
    if (size > threshold || (tab = table) == null ||
        (n = tab.length) == 0)
        n = (tab = resize()).length;
    if ((first = tab[i = (n - 1) & hash]) != null) {
        if (first instanceof TreeNode)
            old = (t = (TreeNode<K,V>)first).getTreeNode(hash, key);
        else {
            Node<K,V> e = first; K k;
            do {
                if (e.hash == hash &&
                    ((k = e.key) == key || (key != null && key.equals(k)))) {
                    old = e;
                    break;
                }
                ++binCount;
            } while ((e = e.next) != null);
        }
        V oldValue;
        if (old != null && (oldValue = old.value) != null) {
            afterNodeAccess(old);
            return oldValue;
        }
    }
    V v = mappingFunction.apply(key);
    if (v == null) {
        return null;
    } else if (old != null) {
        old.value = v;
        afterNodeAccess(old);
        return v;
    }
    else if (t != null)
        t.putTreeVal(this, tab, hash, key, v);
    else {
        tab[i] = newNode(hash, key, v, first);
        if (binCount >= TREEIFY_THRESHOLD - 1)
            treeifyBin(tab, hash);
    }
    ++modCount;
    ++size;
    afterNodeInsertion(true);
    return v;
}

public V computeIfPresent(K key,
                          BiFunction<? super K, ? super V, ? extends V> remappingFunction) {
    if (remappingFunction == null)
        throw new NullPointerException();
    Node<K,V> e; V oldValue;
    int hash = hash(key);
    if ((e = getNode(hash, key)) != null &&
        (oldValue = e.value) != null) {
        V v = remappingFunction.apply(key, oldValue);
        if (v != null) {
            e.value = v;
            afterNodeAccess(e);
            return v;
        }
        else
            removeNode(hash, key, null, false, true);
    }
    return null;
}

@Override
public V compute(K key,
                 BiFunction<? super K, ? super V, ? extends V> remappingFunction) {
    if (remappingFunction == null)
        throw new NullPointerException();
    int hash = hash(key);
    Node<K,V>[] tab; Node<K,V> first; int n, i;
    int binCount = 0;
    TreeNode<K,V> t = null;
    Node<K,V> old = null;
    if (size > threshold || (tab = table) == null ||
        (n = tab.length) == 0)
        n = (tab = resize()).length;
    if ((first = tab[i = (n - 1) & hash]) != null) {
        if (first instanceof TreeNode)
            old = (t = (TreeNode<K,V>)first).getTreeNode(hash, key);
        else {
            Node<K,V> e = first; K k;
            do {
                if (e.hash == hash &&
                    ((k = e.key) == key || (key != null && key.equals(k)))) {
                    old = e;
                    break;
                }
                ++binCount;
            } while ((e = e.next) != null);
        }
    }
    V oldValue = (old == null) ? null : old.value;
    V v = remappingFunction.apply(key, oldValue);
    if (old != null) {
        if (v != null) {
            old.value = v;
            afterNodeAccess(old);
        }
        else
            removeNode(hash, key, null, false, true);
    }
    else if (v != null) {
        if (t != null)
            t.putTreeVal(this, tab, hash, key, v);
        else {
            tab[i] = newNode(hash, key, v, first);
            if (binCount >= TREEIFY_THRESHOLD - 1)
                treeifyBin(tab, hash);
        }
        ++modCount;
        ++size;
        afterNodeInsertion(true);
    }
    return v;
}

@Override
public V merge(K key, V value,
               BiFunction<? super V, ? super V, ? extends V> remappingFunction) {
    if (value == null)
        throw new NullPointerException();
    if (remappingFunction == null)
        throw new NullPointerException();
    int hash = hash(key);
    Node<K,V>[] tab; Node<K,V> first; int n, i;
    int binCount = 0;
    TreeNode<K,V> t = null;
    Node<K,V> old = null;
    if (size > threshold || (tab = table) == null ||
        (n = tab.length) == 0)
        n = (tab = resize()).length;
    if ((first = tab[i = (n - 1) & hash]) != null) {
        if (first instanceof TreeNode)
            old = (t = (TreeNode<K,V>)first).getTreeNode(hash, key);
        else {
            Node<K,V> e = first; K k;
            do {
                if (e.hash == hash &&
                    ((k = e.key) == key || (key != null && key.equals(k)))) {
                    old = e;
                    break;
                }
                ++binCount;
            } while ((e = e.next) != null);
        }
    }
    if (old != null) {
        V v;
        if (old.value != null)
            v = remappingFunction.apply(old.value, value);
        else
            v = value;
        if (v != null) {
            old.value = v;
            afterNodeAccess(old);
        }
        else
            removeNode(hash, key, null, false, true);
        return v;
    }
    if (value != null) {
        if (t != null)
            t.putTreeVal(this, tab, hash, key, value);
        else {
            tab[i] = newNode(hash, key, value, first);
            if (binCount >= TREEIFY_THRESHOLD - 1)
                treeifyBin(tab, hash);
        }
        ++modCount;
        ++size;
        afterNodeInsertion(true);
    }
    return value;
}

@Override
public void forEach(BiConsumer<? super K, ? super V> action) {
    Node<K,V>[] tab;
    if (action == null)
        throw new NullPointerException();
    if (size > 0 && (tab = table) != null) {
        int mc = modCount;
        for (int i = 0; i < tab.length; ++i) {
            for (Node<K,V> e = tab[i]; e != null; e = e.next)
                action.accept(e.key, e.value);
        }
        if (modCount != mc)
            throw new ConcurrentModificationException();
    }
}

@Override
public void replaceAll(BiFunction<? super K, ? super V, ? extends V> function) {
    Node<K,V>[] tab;
    if (function == null)
        throw new NullPointerException();
    if (size > 0 && (tab = table) != null) {
        int mc = modCount;
        for (int i = 0; i < tab.length; ++i) {
            for (Node<K,V> e = tab[i]; e != null; e = e.next) {
                e.value = function.apply(e.key, e.value);
            }
        }
        if (modCount != mc)
            throw new ConcurrentModificationException();
    }
}

/* ------------------------------------------------------------ */
// Cloning and serialization

/**
 * Returns a shallow copy of this <tt>HashMap</tt> instance: the keys and
 * values themselves are not cloned.
 *
 * @return a shallow copy of this map
 */
@SuppressWarnings("unchecked")
@Override
public Object clone() {
    HashMap<K,V> result;
    try {
        result = (HashMap<K,V>)super.clone();
    } catch (CloneNotSupportedException e) {
        // this shouldn't happen, since we are Cloneable
        throw new InternalError(e);
    }
    result.reinitialize();
    result.putMapEntries(this, false);
    return result;
}

// These methods are also used when serializing HashSets
final float loadFactor() { return loadFactor; }
final int capacity() {
    return (table != null) ? table.length :
        (threshold > 0) ? threshold :
        DEFAULT_INITIAL_CAPACITY;
}

/**
 * Save the state of the <tt>HashMap</tt> instance to a stream (i.e.,
 * serialize it).
 *
 * @serialData The <i>capacity</i> of the HashMap (the length of the
 *             bucket array) is emitted (int), followed by the
 *             <i>size</i> (an int, the number of key-value
 *             mappings), followed by the key (Object) and value (Object)
 *             for each key-value mapping.  The key-value mappings are
 *             emitted in no particular order.
 */
private void writeObject(java.io.ObjectOutputStream s)
    throws IOException {
    int buckets = capacity();
    // Write out the threshold, loadfactor, and any hidden stuff
    s.defaultWriteObject();
    s.writeInt(buckets);
    s.writeInt(size);
    internalWriteEntries(s);
}

/**
 * Reconstitute the {@code HashMap} instance from a stream (i.e.,
 * deserialize it).
 */
private void readObject(java.io.ObjectInputStream s)
    throws IOException, ClassNotFoundException {
    // Read in the threshold (ignored), loadfactor, and any hidden stuff
    s.defaultReadObject();
    reinitialize();
    if (loadFactor <= 0 || Float.isNaN(loadFactor))
        throw new InvalidObjectException("Illegal load factor: " +
                                         loadFactor);
    s.readInt();                // Read and ignore number of buckets
    int mappings = s.readInt(); // Read number of mappings (size)
    if (mappings < 0)
        throw new InvalidObjectException("Illegal mappings count: " +
                                         mappings);
    else if (mappings > 0) { // (if zero, use defaults)
        // Size the table using given load factor only if within
        // range of 0.25...4.0
        float lf = Math.min(Math.max(0.25f, loadFactor), 4.0f);
        float fc = (float)mappings / lf + 1.0f;
        int cap = ((fc < DEFAULT_INITIAL_CAPACITY) ?
                   DEFAULT_INITIAL_CAPACITY :
                   (fc >= MAXIMUM_CAPACITY) ?
                   MAXIMUM_CAPACITY :
                   tableSizeFor((int)fc));
        float ft = (float)cap * lf;
        threshold = ((cap < MAXIMUM_CAPACITY && ft < MAXIMUM_CAPACITY) ?
                     (int)ft : Integer.MAX_VALUE);

        // Check Map.Entry[].class since it's the nearest public type to
        // what we're actually creating.
        SharedSecrets.getJavaOISAccess().checkArray(s, Map.Entry[].class, cap);
        @SuppressWarnings({"rawtypes","unchecked"})
        Node<K,V>[] tab = (Node<K,V>[])new Node[cap];
        table = tab;

        // Read the keys and values, and put the mappings in the HashMap
        for (int i = 0; i < mappings; i++) {
            @SuppressWarnings("unchecked")
                K key = (K) s.readObject();
            @SuppressWarnings("unchecked")
                V value = (V) s.readObject();
            putVal(hash(key), key, value, false, false);
        }
    }
}

/* ------------------------------------------------------------ */
// iterators

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

    HashIterator() {
        expectedModCount = modCount;
        Node<K,V>[] 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<K,V> nextNode() {
        Node<K,V>[] t;
        Node<K,V> e = next;
        if (modCount != expectedModCount)
            throw new ConcurrentModificationException();
        if (e == null)
            throw new NoSuchElementException();
        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<K,V> 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 KeyIterator extends HashIterator
    implements Iterator<K> {
    public final K next() { return nextNode().key; }
}

final class ValueIterator extends HashIterator
    implements Iterator<V> {
    public final V next() { return nextNode().value; }
}

final class EntryIterator extends HashIterator
    implements Iterator<Map.Entry<K,V>> {
    public final Map.Entry<K,V> next() { return nextNode(); }
}

/* ------------------------------------------------------------ */
// spliterators

static class HashMapSpliterator<K,V> {
    final HashMap<K,V> map;
    Node<K,V> current;          // current node
    int index;                  // current index, modified on advance/split
    int fence;                  // one past last index
    int est;                    // size estimate
    int expectedModCount;       // for comodification checks

    HashMapSpliterator(HashMap<K,V> m, int origin,
                       int fence, int est,
                       int expectedModCount) {
        this.map = m;
        this.index = origin;
        this.fence = fence;
        this.est = est;
        this.expectedModCount = expectedModCount;
    }

    final int getFence() { // initialize fence and size on first use
        int hi;
        if ((hi = fence) < 0) {
            HashMap<K,V> m = map;
            est = m.size;
            expectedModCount = m.modCount;
            Node<K,V>[] tab = m.table;
            hi = fence = (tab == null) ? 0 : tab.length;
        }
        return hi;
    }

    public final long estimateSize() {
        getFence(); // force init
        return (long) est;
    }
}

static final class KeySpliterator<K,V>
    extends HashMapSpliterator<K,V>
    implements Spliterator<K> {
    KeySpliterator(HashMap<K,V> m, int origin, int fence, int est,
                   int expectedModCount) {
        super(m, origin, fence, est, expectedModCount);
    }

    public KeySpliterator<K,V> trySplit() {
        int hi = getFence(), lo = index, mid = (lo + hi) >>> 1;
        return (lo >= mid || current != null) ? null :
            new KeySpliterator<>(map, lo, index = mid, est >>>= 1,
                                    expectedModCount);
    }

    public void forEachRemaining(Consumer<? super K> action) {
        int i, hi, mc;
        if (action == null)
            throw new NullPointerException();
        HashMap<K,V> m = map;
        Node<K,V>[] tab = m.table;
        if ((hi = fence) < 0) {
            mc = expectedModCount = m.modCount;
            hi = fence = (tab == null) ? 0 : tab.length;
        }
        else
            mc = expectedModCount;
        if (tab != null && tab.length >= hi &&
            (i = index) >= 0 && (i < (index = hi) || current != null)) {
            Node<K,V> p = current;
            current = null;
            do {
                if (p == null)
                    p = tab[i++];
                else {
                    action.accept(p.key);
                    p = p.next;
                }
            } while (p != null || i < hi);
            if (m.modCount != mc)
                throw new ConcurrentModificationException();
        }
    }

    public boolean tryAdvance(Consumer<? super K> action) {
        int hi;
        if (action == null)
            throw new NullPointerException();
        Node<K,V>[] tab = map.table;
        if (tab != null && tab.length >= (hi = getFence()) && index >= 0) {
            while (current != null || index < hi) {
                if (current == null)
                    current = tab[index++];
                else {
                    K k = current.key;
                    current = current.next;
                    action.accept(k);
                    if (map.modCount != expectedModCount)
                        throw new ConcurrentModificationException();
                    return true;
                }
            }
        }
        return false;
    }

    public int characteristics() {
        return (fence < 0 || est == map.size ? Spliterator.SIZED : 0) |
            Spliterator.DISTINCT;
    }
}

static final class ValueSpliterator<K,V>
    extends HashMapSpliterator<K,V>
    implements Spliterator<V> {
    ValueSpliterator(HashMap<K,V> m, int origin, int fence, int est,
                     int expectedModCount) {
        super(m, origin, fence, est, expectedModCount);
    }

    public ValueSpliterator<K,V> trySplit() {
        int hi = getFence(), lo = index, mid = (lo + hi) >>> 1;
        return (lo >= mid || current != null) ? null :
            new ValueSpliterator<>(map, lo, index = mid, est >>>= 1,
                                      expectedModCount);
    }

    public void forEachRemaining(Consumer<? super V> action) {
        int i, hi, mc;
        if (action == null)
            throw new NullPointerException();
        HashMap<K,V> m = map;
        Node<K,V>[] tab = m.table;
        if ((hi = fence) < 0) {
            mc = expectedModCount = m.modCount;
            hi = fence = (tab == null) ? 0 : tab.length;
        }
        else
            mc = expectedModCount;
        if (tab != null && tab.length >= hi &&
            (i = index) >= 0 && (i < (index = hi) || current != null)) {
            Node<K,V> p = current;
            current = null;
            do {
                if (p == null)
                    p = tab[i++];
                else {
                    action.accept(p.value);
                    p = p.next;
                }
            } while (p != null || i < hi);
            if (m.modCount != mc)
                throw new ConcurrentModificationException();
        }
    }

    public boolean tryAdvance(Consumer<? super V> action) {
        int hi;
        if (action == null)
            throw new NullPointerException();
        Node<K,V>[] tab = map.table;
        if (tab != null && tab.length >= (hi = getFence()) && index >= 0) {
            while (current != null || index < hi) {
                if (current == null)
                    current = tab[index++];
                else {
                    V v = current.value;
                    current = current.next;
                    action.accept(v);
                    if (map.modCount != expectedModCount)
                        throw new ConcurrentModificationException();
                    return true;
                }
            }
        }
        return false;
    }

    public int characteristics() {
        return (fence < 0 || est == map.size ? Spliterator.SIZED : 0);
    }
}

static final class EntrySpliterator<K,V>
    extends HashMapSpliterator<K,V>
    implements Spliterator<Map.Entry<K,V>> {
    EntrySpliterator(HashMap<K,V> m, int origin, int fence, int est,
                     int expectedModCount) {
        super(m, origin, fence, est, expectedModCount);
    }

    public EntrySpliterator<K,V> trySplit() {
        int hi = getFence(), lo = index, mid = (lo + hi) >>> 1;
        return (lo >= mid || current != null) ? null :
            new EntrySpliterator<>(map, lo, index = mid, est >>>= 1,
                                      expectedModCount);
    }

    public void forEachRemaining(Consumer<? super Map.Entry<K,V>> action) {
        int i, hi, mc;
        if (action == null)
            throw new NullPointerException();
        HashMap<K,V> m = map;
        Node<K,V>[] tab = m.table;
        if ((hi = fence) < 0) {
            mc = expectedModCount = m.modCount;
            hi = fence = (tab == null) ? 0 : tab.length;
        }
        else
            mc = expectedModCount;
        if (tab != null && tab.length >= hi &&
            (i = index) >= 0 && (i < (index = hi) || current != null)) {
            Node<K,V> p = current;
            current = null;
            do {
                if (p == null)
                    p = tab[i++];
                else {
                    action.accept(p);
                    p = p.next;
                }
            } while (p != null || i < hi);
            if (m.modCount != mc)
                throw new ConcurrentModificationException();
        }
    }

    public boolean tryAdvance(Consumer<? super Map.Entry<K,V>> action) {
        int hi;
        if (action == null)
            throw new NullPointerException();
        Node<K,V>[] tab = map.table;
        if (tab != null && tab.length >= (hi = getFence()) && index >= 0) {
            while (current != null || index < hi) {
                if (current == null)
                    current = tab[index++];
                else {
                    Node<K,V> e = current;
                    current = current.next;
                    action.accept(e);
                    if (map.modCount != expectedModCount)
                        throw new ConcurrentModificationException();
                    return true;
                }
            }
        }
        return false;
    }

    public int characteristics() {
        return (fence < 0 || est == map.size ? Spliterator.SIZED : 0) |
            Spliterator.DISTINCT;
    }
}

/* ------------------------------------------------------------ */
// LinkedHashMap support

/*
 * The following package-protected methods are designed to be
 * overridden by LinkedHashMap, but not by any other subclass.
 * Nearly all other internal methods are also package-protected
 * but are declared final, so can be used by LinkedHashMap, view
 * classes, and HashSet.
 */

// Create a regular (non-tree) node
Node<K,V> newNode(int hash, K key, V value, Node<K,V> next) {
    return new Node<>(hash, key, value, next);
}

// For conversion from TreeNodes to plain nodes
Node<K,V> replacementNode(Node<K,V> p, Node<K,V> next) {
    return new Node<>(p.hash, p.key, p.value, next);
}

// Create a tree bin node
TreeNode<K,V> newTreeNode(int hash, K key, V value, Node<K,V> next) {
    return new TreeNode<>(hash, key, value, next);
}

// For treeifyBin
TreeNode<K,V> replacementTreeNode(Node<K,V> p, Node<K,V> next) {
    return new TreeNode<>(p.hash, p.key, p.value, next);
}

/**
 * Reset to initial default state.  Called by clone and readObject.
 */
void reinitialize() {
    table = null;
    entrySet = null;
    keySet = null;
    values = null;
    modCount = 0;
    threshold = 0;
    size = 0;
}

// Callbacks to allow LinkedHashMap post-actions
void afterNodeAccess(Node<K,V> p) { }
void afterNodeInsertion(boolean evict) { }
void afterNodeRemoval(Node<K,V> p) { }

// Called only from writeObject, to ensure compatible ordering.
void internalWriteEntries(java.io.ObjectOutputStream s) throws IOException {
    Node<K,V>[] tab;
    if (size > 0 && (tab = table) != null) {
        for (int i = 0; i < tab.length; ++i) {
            for (Node<K,V> e = tab[i]; e != null; e = e.next) {
                s.writeObject(e.key);
                s.writeObject(e.value);
            }
        }
    }
}

/* ------------------------------------------------------------ */
// Tree bins

/**
 * Entry for Tree bins. Extends LinkedHashMap.Entry (which in turn
 * extends Node) so can be used as extension of either regular or
 * linked node.
 */
static final class TreeNode<K,V> extends LinkedHashMap.Entry<K,V> {
    TreeNode<K,V> parent;  // red-black tree links
    TreeNode<K,V> left;
    TreeNode<K,V> right;
    TreeNode<K,V> prev;    // needed to unlink next upon deletion
    boolean red;
    TreeNode(int hash, K key, V val, Node<K,V> next) {
        super(hash, key, val, next);
    }

    /**
     * Returns root of tree containing this node.
     */
    final TreeNode<K,V> root() {
        for (TreeNode<K,V> r = this, p;;) {
            if ((p = r.parent) == null)
                return r;
            r = p;
        }
    }

    /**
     * Ensures that the given root is the first node of its bin.
     */
    static <K,V> void moveRootToFront(Node<K,V>[] tab, TreeNode<K,V> root) {
        int n;
        if (root != null && tab != null && (n = tab.length) > 0) {
            int index = (n - 1) & root.hash;
            TreeNode<K,V> first = (TreeNode<K,V>)tab[index];
            if (root != first) {
                Node<K,V> rn;
                tab[index] = root;
                TreeNode<K,V> rp = root.prev;
                if ((rn = root.next) != null)
                    ((TreeNode<K,V>)rn).prev = rp;
                if (rp != null)
                    rp.next = rn;
                if (first != null)
                    first.prev = root;
                root.next = first;
                root.prev = null;
            }
            assert checkInvariants(root);
        }
    }

    /**
     * 进行红黑树的遍历
     */
    final TreeNode<K,V> find(int h, Object k, Class<?> kc) {
        // 获取当前的节点
        TreeNode<K,V> p = this;
        do {
            // 定义节点hash值、节点key值
            int ph, dir; K pk;
            // 获取左右子节点
            TreeNode<K,V> pl = p.left, pr = p.right, q;
            // 获取节点hash值 若是大于传入的hash值。则
            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;
    }

    /**
     * Calls find for root node.
     * 这个就是进行红黑树遍历的逻辑。
     */
    final TreeNode<K,V> getTreeNode(int h, Object k) {
        // 如果parent不为null.调用获取root  若是根节点直接遍历
        return ((parent != null) ? root() : this).find(h, k, null);
    }

    /**
     * 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;
    }

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

                    TreeNode<K,V> xp = p;
                    if ((p = (dir <= 0) ? p.left : p.right) == null) {
                        x.parent = xp;
                        if (dir <= 0)
                            xp.left = x;
                        else
                            xp.right = x;
                        root = balanceInsertion(root, x);
                        break;
                    }
                }
            }
        }
        moveRootToFront(tab, root);
    }

    /**
     * Returns a list of non-TreeNodes replacing those linked from
     * this node.
     */
    final Node<K,V> untreeify(HashMap<K,V> map) {
        Node<K,V> hd = null, tl = null;
        for (Node<K,V> q = this; q != null; q = q.next) {
            Node<K,V> p = map.replacementNode(q, null);
            if (tl == null)
                hd = p;
            else
                tl.next = p;
            tl = p;
        }
        return hd;
    }

    /**
     * Tree version of putVal.
     * 如果该节点是红黑树，往红黑树插入数据
     * 参数：当前的hashMap hash桶数组。hash key value
     */
    final TreeNode<K,V> putTreeVal(HashMap<K,V> map, Node<K,V>[] tab,
                                   int h, K k, V v) {
        Class<?> kc = null;
        boolean searched = false;
        // 获取根节点
        TreeNode<K,V> root = (parent != null) ? root() : this;
        
        for (TreeNode<K,V> p = root;;) {
            int dir, ph; K pk;
            // 计算根节点的hash值
            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<K,V> 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<K,V> xp = p;
            if ((p = (dir <= 0) ? p.left : p.right) == null) {
                Node<K,V> xpn = xp.next;
                TreeNode<K,V> 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<K,V>)xpn).prev = x;
                moveRootToFront(tab, balanceInsertion(root, x));
                return null;
            }
        }
    }

    /**
     * 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<K,V> map, Node<K,V>[] tab,
                              boolean movable) {
        int n;
        if (tab == null || (n = tab.length) == 0)
            return;
        int index = (n - 1) & hash;
        TreeNode<K,V> first = (TreeNode<K,V>)tab[index], root = first, rl;
        TreeNode<K,V> succ = (TreeNode<K,V>)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<K,V> p = this, pl = left, pr = right, replacement;
        if (pl != null && pr != null) {
            TreeNode<K,V> 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<K,V> sr = s.right;
            TreeNode<K,V> pp = p.parent;
            if (s == pr) { // p was s's direct parent
                p.parent = s;
                s.right = p;
            }
            else {
                TreeNode<K,V> 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<K,V> 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<K,V> r = p.red ? root : balanceDeletion(root, replacement);

        if (replacement == p) {  // detach
            TreeNode<K,V> 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);
    }

    /**
     * Splits nodes in a tree bin into lower and upper tree bins,
     * or untreeifies if now too small. Called only from resize;
     * see above discussion about split bits and indices.
     *
     * @param map the map
     * @param tab the table for recording bin heads
     * @param index the index of the table being split
     * @param bit the bit of hash to split on
     */
    final void split(HashMap<K,V> map, Node<K,V>[] tab, int index, int bit) {
        TreeNode<K,V> b = this;
        // Relink into lo and hi lists, preserving order
        TreeNode<K,V> loHead = null, loTail = null;
        TreeNode<K,V> hiHead = null, hiTail = null;
        int lc = 0, hc = 0;
        for (TreeNode<K,V> e = b, next; e != null; e = next) {
            next = (TreeNode<K,V>)e.next;
            e.next = null;
            if ((e.hash & bit) == 0) {
                if ((e.prev = loTail) == null)
                    loHead = e;
                else
                    loTail.next = e;
                loTail = e;
                ++lc;
            }
            else {
                if ((e.prev = hiTail) == null)
                    hiHead = e;
                else
                    hiTail.next = e;
                hiTail = e;
                ++hc;
            }
        }

        if (loHead != null) {
            if (lc <= UNTREEIFY_THRESHOLD)
                tab[index] = loHead.untreeify(map);
            else {
                tab[index] = loHead;
                if (hiHead != null) // (else is already treeified)
                    loHead.treeify(tab);
            }
        }
        if (hiHead != null) {
            if (hc <= UNTREEIFY_THRESHOLD)
                tab[index + bit] = hiHead.untreeify(map);
            else {
                tab[index + bit] = hiHead;
                if (loHead != null)
                    hiHead.treeify(tab);
            }
        }
    }

    /* ------------------------------------------------------------ */
    // Red-black tree methods, all adapted from CLR

    static <K,V> TreeNode<K,V> rotateLeft(TreeNode<K,V> root,
                                          TreeNode<K,V> p) {
        TreeNode<K,V> r, pp, rl;
        if (p != null && (r = p.right) != null) {
            if ((rl = p.right = r.left) != null)
                rl.parent = p;
            if ((pp = r.parent = p.parent) == null)
                (root = r).red = false;
            else if (pp.left == p)
                pp.left = r;
            else
                pp.right = r;
            r.left = p;
            p.parent = r;
        }
        return root;
    }

    static <K,V> TreeNode<K,V> rotateRight(TreeNode<K,V> root,
                                           TreeNode<K,V> p) {
        TreeNode<K,V> l, pp, lr;
        if (p != null && (l = p.left) != null) {
            if ((lr = p.left = l.right) != null)
                lr.parent = p;
            if ((pp = l.parent = p.parent) == null)
                (root = l).red = false;
            else if (pp.right == p)
                pp.right = l;
            else
                pp.left = l;
            l.right = p;
            p.parent = l;
        }
        return root;
    }

    static <K,V> TreeNode<K,V> balanceInsertion(TreeNode<K,V> root,
                                                TreeNode<K,V> x) {
        x.red = true;
        for (TreeNode<K,V> xp, xpp, xppl, xppr;;) {
            if ((xp = x.parent) == null) {
                x.red = false;
                return x;
            }
            else if (!xp.red || (xpp = xp.parent) == null)
                return root;
            if (xp == (xppl = xpp.left)) {
                if ((xppr = xpp.right) != null && xppr.red) {
                    xppr.red = false;
                    xp.red = false;
                    xpp.red = true;
                    x = xpp;
                }
                else {
                    if (x == xp.right) {
                        root = rotateLeft(root, x = xp);
                        xpp = (xp = x.parent) == null ? null : xp.parent;
                    }
                    if (xp != null) {
                        xp.red = false;
                        if (xpp != null) {
                            xpp.red = true;
                            root = rotateRight(root, xpp);
                        }
                    }
                }
            }
            else {
                if (xppl != null && xppl.red) {
                    xppl.red = false;
                    xp.red = false;
                    xpp.red = true;
                    x = xpp;
                }
                else {
                    if (x == xp.left) {
                        root = rotateRight(root, x = xp);
                        xpp = (xp = x.parent) == null ? null : xp.parent;
                    }
                    if (xp != null) {
                        xp.red = false;
                        if (xpp != null) {
                            xpp.red = true;
                            root = rotateLeft(root, xpp);
                        }
                    }
                }
            }
        }
    }

    static <K,V> TreeNode<K,V> balanceDeletion(TreeNode<K,V> root,
                                               TreeNode<K,V> x) {
        for (TreeNode<K,V> xp, xpl, xpr;;)  {
            if (x == null || x == root)
                return root;
            else if ((xp = x.parent) == null) {
                x.red = false;
                return x;
            }
            else if (x.red) {
                x.red = false;
                return root;
            }
            else if ((xpl = xp.left) == x) {
                if ((xpr = xp.right) != null && xpr.red) {
                    xpr.red = false;
                    xp.red = true;
                    root = rotateLeft(root, xp);
                    xpr = (xp = x.parent) == null ? null : xp.right;
                }
                if (xpr == null)
                    x = xp;
                else {
                    TreeNode<K,V> sl = xpr.left, sr = xpr.right;
                    if ((sr == null || !sr.red) &&
                        (sl == null || !sl.red)) {
                        xpr.red = true;
                        x = xp;
                    }
                    else {
                        if (sr == null || !sr.red) {
                            if (sl != null)
                                sl.red = false;
                            xpr.red = true;
                            root = rotateRight(root, xpr);
                            xpr = (xp = x.parent) == null ?
                                null : xp.right;
                        }
                        if (xpr != null) {
                            xpr.red = (xp == null) ? false : xp.red;
                            if ((sr = xpr.right) != null)
                                sr.red = false;
                        }
                        if (xp != null) {
                            xp.red = false;
                            root = rotateLeft(root, xp);
                        }
                        x = root;
                    }
                }
            }
            else { // symmetric
                if (xpl != null && xpl.red) {
                    xpl.red = false;
                    xp.red = true;
                    root = rotateRight(root, xp);
                    xpl = (xp = x.parent) == null ? null : xp.left;
                }
                if (xpl == null)
                    x = xp;
                else {
                    TreeNode<K,V> sl = xpl.left, sr = xpl.right;
                    if ((sl == null || !sl.red) &&
                        (sr == null || !sr.red)) {
                        xpl.red = true;
                        x = xp;
                    }
                    else {
                        if (sl == null || !sl.red) {
                            if (sr != null)
                                sr.red = false;
                            xpl.red = true;
                            root = rotateLeft(root, xpl);
                            xpl = (xp = x.parent) == null ?
                                null : xp.left;
                        }
                        if (xpl != null) {
                            xpl.red = (xp == null) ? false : xp.red;
                            if ((sl = xpl.left) != null)
                                sl.red = false;
                        }
                        if (xp != null) {
                            xp.red = false;
                            root = rotateRight(root, xp);
                        }
                        x = root;
                    }
                }
            }
        }
    }

    /**
     * Recursive invariant check
     */
    static <K,V> boolean checkInvariants(TreeNode<K,V> t) {
        TreeNode<K,V> tp = t.parent, tl = t.left, tr = t.right,
            tb = t.prev, tn = (TreeNode<K,V>)t.next;
        if (tb != null && tb.next != t)
            return false;
        if (tn != null && tn.prev != t)
            return false;
        if (tp != null && t != tp.left && t != tp.right)
            return false;
        if (tl != null && (tl.parent != t || tl.hash > t.hash))
            return false;
        if (tr != null && (tr.parent != t || tr.hash < t.hash))
            return false;
        if (t.red && tl != null && tl.red && tr != null && tr.red)
            return false;
        if (tl != null && !checkInvariants(tl))
            return false;
        if (tr != null && !checkInvariants(tr))
            return false;
        return true;
    }
}
}

上面，我们已经分析完了HashMap的源码，所以我们来解答一下上面提出的几个问题：

提问一：通过HashMap的扩容方法resize()方法。我们发现为什么扩容一直2倍扩容。而HashMap的默认初始容量也是16(2的4次幂)？？

分析：肯定是为了性能撒！！！数组的初始容量为16，而容量是以2的次方扩充的，一是为了提高性能使用足够大的数组，二是为了能使用位运算代替取模预算(据说提升了5~8倍)。数组是否需要扩充是通过负载因子判断的，如果当前元素个数为数组容量的0.75时，就会扩充数组。这个0.75就是默认的负载因子，可由构造传入。我们也可以设置大于1的负载因子，这样数组就不会扩充，牺牲性能，节省内存。

提问二：JDK8中HashMap为什么引入了红黑树？？引入红黑树有什么作用？？

分析:肯定实为了性能撒！！！即使负载因子和Hash算法设计的再合理，也免不了会出现拉链过长的情况，一旦出现拉链过长，则会严重影响HashMap的性能。于是，在JDK1.8版本中，对数据结构做了进一步的优化，引入了红黑树。而当链表长度太长（默认超过8）时，链表就转换为红黑树，利用红黑树快速增删改查的特点提高HashMap的性能，其中会用到红黑树的插入、删除、查找等算法。
当插入新元素时，对于红黑树的判断如下：
判断table[i] 是否为treeNode，即table[i] 是否是红黑树，如果是红黑树，则直接在树中插入键值对，否则转向下面；
遍历table[i]，判断链表长度是否大于8，大于8的话把链表转换为红黑树，在红黑树中执行插入操作，否则进行链表的插入操作；遍历过程中若发现key已经存在直接覆盖value即可；

提问三：为什么当桶中链表长度大于等于8之后，才转化为红黑树。为什么当长度小于等于6之后转化成为链表

分析：肯定是为了性能撒！！！！
红黑树的平均查找长度是log(n)，长度为8，查找长度为log(8)=3，链表的平均查找长度为n/2，当长度为8时，平均查找长度为8/2=4，这才有转换成树的必要；链表长度如果是小于等于6，6/2=3，虽然速度也很快的，但是转化为树结构和生成树的时间并不会太短。
以6和8来作为平衡点是因为，中间有个差值7可以防止链表和树之间频繁的转换。假设，如果设计成链表个数超过8则链表转换成树结构，链表个数小于8则树结构转换成链表，如果一个HashMap不停的插入、删除元素，链表个数在8左右徘徊，就会频繁的发生树转链表、链表转树，效率会很低。

提问三：解决hash冲突的办法有哪些?HashMap用的哪种？

解决Hash冲突方法有：开放定址法、再哈希法、链地址法（HashMap中常见的拉链法）、简历公共溢出区。HashMap中采用的是链地址法。

开放定址法也称为再散列法，基本思想就是，如果p=H(key)出现冲突时，则以p为基础，再次hash，p1=H(p)，如果p1再次出现冲突，则以p1为基础，以此类推，直到找到一个不冲突的哈希地址pi。因此开放定址法所需要的hash表的长度要大于等于所需要存放的元素，而且因为存在再次hash，所以只能在删除的节点上做标记，而不能真正删除节点。

再哈希法（双重散列，多重散列），提供多个不同的hash函数，R1=H1(key1)发生冲突时，再计算R2=H2（key1），直到没有冲突为止。这样做虽然不易产生堆集，但增加了计算的时间。

链地址法（拉链法），将哈希值相同的元素构成一个同义词的单链表，并将单链表的头指针存放在哈希表的第i个单元中，查找、插入和删除主要在同义词链表中进行，链表法适用于经常进行插入和删除的情况。

建立公共溢出区，将哈希表分为公共表和溢出表，当溢出发生时，将所有溢出数据统一放到溢出区。

注意开放定址法和再哈希法的区别是：

开放定址法只能使用同一种hash函数进行再次hash，再哈希法可以调用多种不同的hash函数进行再次hash。

对于第三点补充说明，检查链表长度转换成红黑树之前，还会先检测当前数组数组是否到达一个阈值（64），如果没有到达这个容量，会放弃转换，先去扩充数组。所以上面也说了链表长度的阈值是7或8，因为会有一次放弃转换的操作。