HashMap源码分析之构造函数及部分数据操作相关方法

“在介绍HashMap之前,为了方便更清楚地理解源码,先大致说说HashMap的实现原理,
	 HashMap 是基于数组 + 链表实现的, 首先HashMap就是一个大数组,在这个数组中,通过hash值去寻对应位置的元素, 如果遇到多个元素的hash值一样,那么怎么保存,这就引入了链表,在同一个hash的位置,保存多个元素(通过链表关联起来)。HashMap 所实现的基于<key, value>的键值对形式,是由其内部内Entry实现。”

Entry,是一个静态类,实现Map.Entry< K ,V>,通过他可以构成一个单向链表,只是一个内部类。

HashMap类继承了AbstractMap父类,实现Map,Cloneable, Serializble接口。

public class HashMAp<K,V> extends AbstractMap<K,V>
	implements Map<K,V>, Cloneable, Serializable
  1. serialVersionUID叫序列化ID 先摆着:
    java对象序列化的意思就是将对象的状态转化成字节流,以后可以通过这些值再生成相同状态的对象。对象序列化是对象持久化的一种实现方法,它是将对象的属性和方法转化为一种序列化的形式用于存储和传输。反序列化就是根据这些保存的信息重建对象的过程。
    序列化:将java对象转化为字节序列的过程。
    反序列化:将字节序列转化为java对象的过程。
  2. 负载因子:
    会影响HashMap性能
    首先回忆HashMap的数据结构,
    1. 我们都知道有序数组存储数据,对数据的索引效率都很高,但是插入和删除就会有性能瓶颈(回忆ArrayList)
    2. 链表存储数据,要一次比较元素来检索出数据,所以索引效率低,但是插入和删除效率高(回忆LinkedList),
      两者取长补短就产生了哈希散列这种存储方式,也就是HashMap的存储逻辑.
      而负载因子表示一个散列表的空间的使用程度,有这样一个公式:initailCapacity*loadFactor=HashMap的容量。

所以负载因子越大则散列表的装填程度越高,也就是能容纳更多的元素,元素多了,链表大了,所以此时索引效率就会降低。
反之,负载因子越小则链表中的数据量就越稀疏,此时会对空间造成浪费,但是此时索引效率高。
官方操作一波0.75f,咱也不知道为啥哈哈哈,效率高呗。

JDK1.8 开始HashMap的实现是 数组+链表+红黑树

	//序列化ID
	private static final long serialVersionUID = 362498820763181265L;
	// 初始容量16
	static final int DEFAULT_INITIAL_CAPACITY = 1 << 4; 
    //最大容量2^30
    static final int MAXIMUM_CAPACITY = 1 << 30;  
    //默认负载因子
    static final float DEFAULT_LOAD_FACTOR = 0.75f;
    //当链表达到8时转化为红黑树
    static final int TREEIFY_THRESHOLD = 8;
	//当红黑树节点数小于6时,转化为链表
    static final int UNTREEIFY_THRESHOLD = 6;
   /**    
   * 这个字段决定了当hash表的至少大小为多少时,链表才能进行树化。这个设计时合理的,
   * 因为当hash表的大小很小时,这时候表所需的空间还不多,可以牺牲空间减少时间,所以这个情况下
   * 当存储的节点过多时,最好的办法是调整表的大小,使其增大,而不是将链表树化。
	*/
    static final int MIN_TREEIFY_CAPACITY = 64;

下面介绍键值在HashMap中的存储形式。

 static class Node<K,V> implements Map.Entry<K,V> {
        final int hash;			//hash的value
        final K key;			//key
        V value;				//value 的 value值
        Node<K,V> next;
        //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;
        }
//Entry的get方法、toString方法
        public final K getKey()        { return key; }
        public final V getValue()      { return value; }
        public final String toString() { return key + "=" + value; }

计算hashCode中key和value异或值,将value值更改,返回原来的值

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

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

判断地址值,判断o是否为Map.Entry的实例,判断类型和键值。

		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;
        }

hash(Object key)

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

先获取到key的hashCode,然后进行移位再进行异或运算,复杂操作原因为了减少hash冲突。
“ 如果恶意程序知道我们用的是Hash算法,则在纯链表情况下,它能够发送大量请求导致哈希碰撞,然后不停访问这些key导致HashMap忙于进行线性查找,最终陷入瘫痪,即形成了拒绝服务攻击(DoS)。
关于Java 8中的hash函数,原理和Java 7中基本类似。Java 8中这一步做了优化,只做一次16位右位移异或混合,而不是四次,但原理是不变的。”

comparableClassFor(Object x)

    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;
    }

comparableClassFor(Object x)方法,当x的类型为X,且X直接实现了Comparable接口(比较类型必须为X类本身)时,返回x的运行时类型;否则返回null。

compareComparables(Class<?> kc, Object k, Object x)

    @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));
    }

如果x的类型为kc,则返回k.compareTo(x),否则返回0.

tableSizeFor(int cap)

    static final int tableSizeFor(int cap) {
        int n = cap - 1;
        n |= n >>> 1; // 将n和n右移1位的值进行或运算,将结果赋值给n
        n |= n >>> 2;
        n |= n >>> 4;
        n |= n >>> 8;
        n |= n >>> 16;
        return (n < 0) ? 1 : (n >= MAXIMUM_CAPACITY) ? MAXIMUM_CAPACITY : n + 1;
    }

返回大于等于cap的最小的二次幂数值。

    /**
    存储键值对的数组,一般是2的幂
     * 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.)
     * 存储键值对的数组,一般是2的幂
     */
    transient Node<K,V>[] table;

    /**
     * Holds cached entrySet(). Note that AbstractMap fields are used
     * for keySet() and values().
     * 键值对缓存,它们的映射关系集合保存在entrySet中。
     * 即使Key在外部修改导致hashCode变化,缓存中还可以找到映射关系
     */
    transient Set<Map.Entry<K,V>> entrySet;

    /**
     * The number of key-value mappings contained in this map.
     * 键值对的实际个数
     */
    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).
     * 记录HashMap被修改结构的次数。
     * 修改包括改变键值对的个数或者修改内部结构,比如rehash
     * 这个域被用作HashMap的迭代器的fail-fast机制中
     * (参考ConcurrentModificationException)
     */
    transient int modCount;

    /**
     * The next size value at which to resize (capacity * load factor).
     * 扩容的临界值,通过capacity * load factor可以计算出来。超过这个值HashMap将进行扩容
     * @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.)
    int threshold;

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

public HashMap(int initialCapacity, float loadFactor)

	/**
     * Constructs an empty <tt>HashMap</tt> with the specified initial
     * capacity and load factor.
     *
     * @param  initialCapacity the initial capacity
     * @param  loadFactor      the load factor
     * @throws IllegalArgumentException if the initial capacity is negative
     *         or the load factor is nonpositive
     */
/**
 * 使用指定的初始化容量initial capacity 和负载因子load factor构造一个空HashMap
 *
 * @param  initialCapacity 初始化容量
 * @param  loadFactor      负载因子
 * @throws IllegalArgumentException 如果指定的初始化容量为负数或者加载因子为非正数。
 */     
    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;
        this.threshold = tableSizeFor(initialCapacity);
    }

如果初始化容量小于零,非法参数异常,大于最大容量,更新最大容量,判断负载因子异常。

public HashMap(int initialCapacity)

    /**
     * Constructs an empty <tt>HashMap</tt> with the specified initial
     * capacity and the default load factor (0.75).
     *
     * @param  initialCapacity the initial capacity.
     * @throws IllegalArgumentException if the initial capacity is negative.
     */
 /**
 * 使用指定的初始化容量initial capacity和默认负载因子DEFAULT_LOAD_FACTOR(0.75)构造一个空HashMap
 *
 * @param  initialCapacity 初始化容量
 * @throws IllegalArgumentException 如果指定的初始化容量为负数
 */
    public HashMap(int initialCapacity) {
        this(initialCapacity, DEFAULT_LOAD_FACTOR);
    }

public HashMap()

    /**
     * Constructs an empty <tt>HashMap</tt> with the default initial capacity
     * (16) and the default load factor (0.75).
     */
     /**
	 * 使用指定的初始化容量(16)和默认负载因子DEFAULT_LOAD_FACTOR(0.75)构造一个空HashMap
	 */
    public HashMap() {
        this.loadFactor = DEFAULT_LOAD_FACTOR; // all other fields defaulted
    }

public HashMap(Map<? extends K, ? extends V> m)

    /**
     * Constructs a new <tt>HashMap</tt> with the same mappings as the
     * specified <tt>Map</tt>.  The <tt>HashMap</tt> is created with
     * default load factor (0.75) and an initial capacity sufficient to
     * hold the mappings in the specified <tt>Map</tt>.
     *
     * @param   m the map whose mappings are to be placed in this map
     * @throws  NullPointerException if the specified map is null
     * *使用与

*指定的<tt>map.<tt>创建“hashmap”时

*默认荷载系数(0.75)和初始承载力足以

*将映射保存在指定的<tt>映射中。

*

*@param m要将其映射放置在此映射中的映射

*@如果指定的映射为空,则引发NullPointerException
     */
    public HashMap(Map<? extends K, ? extends V> m) {
        this.loadFactor = DEFAULT_LOAD_FACTOR;
        putMapEntries(m, false);
    

整个夜,疯狂挥霍。

final void final void putMapEntries(Map<? extends K, ? extends V> m, boolean evict) (Map<? extends K, ? extends V> m, boolean evict)

//将一个map即m放入当前实例的table中
    final void putMapEntries(Map<? extends K, ? extends V> m, boolean evict) {
        int s = m.size();
        if (s > 0) {
        //如果table没初始化,ft = 一个值
        //t = ft 与 最大mum容量比较 赋值
        //t > 阈值条件,赋值改变threshold
            if (tablet == 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);
            }
        }
    }

啊mdzz… 搞来搞去就是一顿操作改了threshold的值为tableSizeFor((map大小 / loadFactor) + 1.0F)

public int size()

    /**
     * Returns the number of key-value mappings in this map.
     *
     * @return the number of key-value mappings in this map
     */
     /**
     *返回此映射中的键值映射数
     *@返回此映射中的键值映射数
     */
    public int size() {
        return size;
    }

public boolean isEmpty()

    /**
     * Returns <tt>true</tt> if this map contains no key-value mappings.
     *
     * @return <tt>true</tt> if this map contains no key-value mappings
     */
     /**
     *如果此映射不包含键值映射,则返回<tt>true。
     *@如果此映射不包含键值映射,则返回<tt>true
     */
    public boolean isEmpty() {
        return size == 0;
    }

    /**
     * Returns the value to which the specified key is mapped,
     * or {@code null} if this map contains no mapping for the key.
     *
     * <p>More formally, if this map contains a mapping from a key
     * {@code k} to a value {@code v} such that {@code (key==null ? k==null :
     * key.equals(k))}, then this method returns {@code v}; otherwise
     * it returns {@code null}.  (There can be at most one such mapping.)
     *
     * <p>A return value of {@code null} does not <i>necessarily</i>
     * indicate that the map contains no mapping for the key; it's also
     * possible that the map explicitly maps the key to {@code null}.
     * The {@link #containsKey containsKey} operation may be used to
     * distinguish these two cases.
     *
     * @see #put(Object, Object)
     */
     /**
     *返回指定键映射到的值,
     *或者@code NULL如果此映射不包含键的映射。
     *<p>更正式地说,如果此映射包含来自键的映射
     *@code k到值@code v这样@code(key==null?K==空:
     *key.equals(k)),则此方法返回@code v,否则返回
     *返回@code空。(最多可以有一个这样的映射。)
     *<p>返回值@code null不一定<i>
     *指示映射不包含键的映射;它还
     *可能映射显式地将键映射到@code null。
     *@link containskey containskey操作可用于
     *区分这两种情况。
     * @see #put(Object, Object)
*/
    public V get(Object key) {
        Node<K,V> e;
        return (e = getNode(hash(key), key)) == null ? null : e.value;
    }

final Node<K,V> getNode(int hash, Object key)

    /**
     * Implements Map.get and related methods.
     *
     * @param hash hash for key
     * @param key the key
     * @return the node, or null if none
     */
     /**
     * 根据key的哈希值和key获取对应的节点
	 * 
	 * @param hash 指定参数key的哈希值
	 * @param key 指定参数key
	 * @return 返回node,如果没有则返回null
     */
   final Node<K,V> getNode(int hash, Object key) {
        Node<K,V>[] tab; Node<K,V> first, e; int n; K k;
        //表不为空、长度不为零且key对应value不空
        if ((tab = table) != null && (n = tab.length) > 0 &&
            (first = tab[(n - 1) & hash]) != null) {
            //如果桶中的第一个节点得哈希值就和指定参数hash对应
            if (first.hash == hash && // always check first node
                ((k = first.key) == key || (key != null && key.equals(k))))
                return first;
                //返回第一个节点
                //如果没匹配上
            if ((e = first.next) != null) {
            //第一节点属于树的实例
                if (first instanceof TreeNode)
                //当前桶用红黑树,调用红黑树get方法获取节点
                    return ((TreeNode<K,V>)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);
            }
        }
        //若为空,返回null
        return null;
    }

根据key的哈希值获取key对应节点。


public boolean containsKey(Object key)

    // 调用getNode方法来获取键值对,如果没有找到返回false,找到了就返回ture
    public boolean containsKey(Object key) {
        return getNode(hash(key), key) != null;
    }

  1. public V put(K key, V value)
  2. final V putVal(int hash, K key, V value, boolean onlyIfAbsent, boolean evict)
  3. final Node<K,V>[] resize()
    put方法首先检查HashMap是否为空,为空执行resize初始化map,若非空,计算tab数组下标[(n - 1) & hash],判断数组对象是否为空,为空时新建一个node节点。
public V put(K key, V value) {
        return putVal(hash(key), key, value, false, true);
    }
    
final V putVal(int hash, K key, V value, boolean onlyIfAbsent,
                   boolean evict) {
        Node<K,V>[] tab; Node<K,V> p; int n, i;
 //检查hashmap是否为空,为空的话执行resize,相当于初始化一个map  
        if ((tab = table) == null || (n = tab.length) == 0)
            n = (tab = resize()).length;
  //非空时,计算tab数组下标[(n - 1) & hash],判断数组对象是否为空,为空时新建一个node节点。      
        if ((p = tab[i = (n - 1) & hash]) == null)
            tab[i] = newNode(hash, key, value, null);
  //数组对象非空,tab[i]非空,
  //判断该节点的key与即将put的key值是否相同,相同的话先讲tab[i]对应的node存储起来。      
        else {
            Node<K,V> e; K k;
            if (p.hash == hash &&
                ((k = p.key) == key || (key != null && key.equals(k))))
                e = p;
     //判断tab[i]是否为红黑树对象,若tab节点为红黑树,则执行一次树对象put操作。
            else if (p instanceof TreeNode)
                e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value);
        //处理tab[i]节点为链表对象,通过一个计数器binCount统计链表长度。如果tab[i]对象p的next为null,则链表到头了,这个时候新建一个node<key,value>节点为p.next。
           //如果链表长度计数器binCount>7即TREEIFY_THRESHOLD - 1即8-1,即链表长度大于8时,则进行红黑树转换。如果不满足转换条件,链表种插入新节点完毕,无需其他操作
            else {
                for (int binCount = 0; ; ++binCount) {
                    if ((e = p.next) == null) {
                        p.next = newNode(hash, key, value, null);
                        if (binCount >= TREEIFY_THRESHOLD - 1) // -1 for 1st
                            treeifyBin(tab, hash);
                        break;
                    }
                    if (e.hash == hash &&
                        ((k = e.key) == key || (key != null && key.equals(k))))
                        break;
                    p = e;
                }
            }
            
            if (e != null) { // existing mapping for key
                V oldValue = e.value;
            //针对存在相同key的节点,执行value覆盖,并返回旧值。
                if (!onlyIfAbsent || oldValue == null)
                    e.value = value;
                afterNodeAccess(e);
                return oldValue;
            }
        }
        ++modCount;
        //若tab大小超过阈值(容量*负载因子),执行resize扩容操作,返回null。
        if (++size > threshold)
            resize();
        afterNodeInsertion(evict);
        return null;
    }

final Node<K,V>[] resize() {
        Node<K,V>[] oldTab = table;
        int oldCap = (oldTab == null) ? 0 : oldTab.length;
        int oldThr = threshold;
        int newCap, newThr = 0;
        if (oldCap > 0) {
        // 老容量超过最大容量,不进行扩容
            if (oldCap >= MAXIMUM_CAPACITY) {
                threshold = Integer.MAX_VALUE;
                return oldTab;
            }
            // 扩容两倍
            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;
        @SuppressWarnings({"rawtypes","unchecked"})
        // 新建扩容数组
        Node<K,V>[] newTab = (Node<K,V>[])new Node[newCap];
        table = newTab;
        if (oldTab != null) {
        // 遍历老数组
            for (int j = 0; j < oldCap; ++j) {
                Node<K,V> e;
                if ((e = oldTab[j]) != null) {
                    oldTab[j] = null;
                    // 老数组子节点为null,通过e.hash & (newCap - 1)获取数组下标,将节点填充到该数组对象中
                    
                    if (e.next == null)
                        newTab[e.hash & (newCap - 1)] = e;
                    else if (e instanceof TreeNode)
                         // 节点为红黑色时
                         ((TreeNode<K,V>)e).split(this, newTab, j, oldCap);
                    else { // preserve order
                        Node<K,V> loHead = null, loTail = null;
                        Node<K,V> hiHead = null, hiTail = null;
                        Node<K,V> next;
                        do {
                            next = e.next;
                            // 元素位置没有发生变化
                            // 原hash与原容量进行与运算,loHead、loTail位置不变时的头尾节点
                            if ((e.hash & oldCap) == 0) {
                                if (loTail == null)
                                    loHead = e;
                                else
                                    loTail.next = e;
                                loTail = e;
                            }
                            // 元素位置发生变化
                            // hiHead、hiTail位置变化后新的头节点和尾节点
 
                            else {
                                if (hiTail == null)
                                    hiHead = e;
                                else
                                    hiTail.next = e;
                                hiTail = e;
                            }
                        } while ((e = next) != null);
                         // 位置不变时,(e.hash & oldCap) == 0,数组当前下标指向loHead
                        if (loTail != null) {
                            loTail.next = null;
                            newTab[j] = loHead;
                        }
                         // 位置变化时,数组下标变为[j + oldCap],指向头节点
                        if (hiTail != null) {
                            hiTail.next = null;
                            newTab[j + oldCap] = hiHead;
                        }
                    }
                }
            }
        }
        return newTab;
    }
    

final void treeifyBin(Node<K,V>[] tab, int hash)树化

    /**
     * Replaces all linked nodes in bin at index for given hash unless
     * table is too small, in which case resizes instead.
     */
     
    /**
     * Replaces all linked nodes in bin at index for given hash unless
     * table is too small, in which case resizes instead.
     */
/**
*替换给定哈希的索引处bin中的所有链接节点,除非
*表太小,在这种情况下会调整大小。
*/
    final void treeifyBin(Node<K,V>[] tab, int hash) {
        int n, index; Node<K,V> e;
        //如果元素数组长度为空或者小于MIN_TREEIFY_CAPACITY,执行resize操作
        if (tab == null || (n = tab.length) < MIN_TREEIFY_CAPACITY)
            resize();
            //数组长度与hash值位运算,得到链表的首节点,hd是树首节点,tl是树尾结点
        else if ((e = tab[index = (n - 1) & hash]) != null) {
            TreeNode<K,V> hd = null, tl = null;
            do {
            //节点变成树节点
                TreeNode<K,V> p = replacementTreeNode(e, null);
                //如果尾结点为空,赋值给首节点,树的根结点
               //如果尾结点不为空,则是双向链表结构构成
                if (tl == null)
                    hd = p;
                else {
                //prev指向前一个节点尾结点
                    p.prev = tl;
                 //next指向当前节点   
                    tl.next = p;
                }
                //把当前节点设置为尾结点
                tl = p;
            } while ((e = e.next) != null);
            if ((tab[index] = hd) != null)
                hd.treeify(tab);
                //转换成红黑树
        }
    }

public void putAll(Map<? extends K, ? extends V> m)

/**
     * 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) {
    //调用putMapEntries
        putMapEntries(m, true);
    }


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