JDK1.8 HashMap源码分析

一、HashMap概述

在JDK1.8之前，HashMap采用数组+链表实现，即使用链表处理冲突，同一hash值的链表都存储在一个链表里。但是当位于一个桶中的元素较多，即hash值相等的元素较多时，通过key值依次查找的效率较低。而JDK1.8中，HashMap采用数组+链表+红黑树实现，当链表长度超过阈值（8）时，将链表转换为红黑树，这样大大减少了查找时间。

下图中代表jdk1.8之前的hashmap结构，左边部分即代表哈希表，也称为哈希数组，数组的每个元素都是一个单链表的头节点，链表是用来解决冲突的，如果不同的key映射到了数组的同一位置处，就将其放入单链表中。（此图借用网上的图）

图一、jdk1.8之前hashmap结构图

jdk1.8之前的hashmap都采用上图的结构，都是基于一个数组和多个单链表，hash值冲突的时候，就将对应节点以链表的形式存储。如果在一个链表中查找其中一个节点时，将会花费O（n）的查找时间，会有很大的性能损失。到了jdk1.8，当同一个hash值的节点数不小于8时，不再采用单链表形式存储，而是采用红黑树，如下图所示（此图是借用的图）

图二、jdk1.8 hashmap结构图

二、重要的field

//table就是存储Node类的数组，就是对应上图中左边那一栏，
  /**
     * The table, initialized on first use, and resized as
     * necessary. When allocated, length is always a power of two.
     * (We also tolerate length zero in some operations to allow
     * bootstrapping mechanics that are currently not needed.)
  */
transient Node<K,V>[] table;

/**
     * The number of key-value mappings contained in this map.
*  记录hashmap中存储键-值对的数量
  */
transient int size;

/**
  * hashmap结构被改变的次数，fail-fast机制
  */
transient int modCount;

    /**
     * The next size value at which to resize (capacity * load factor).
     * 扩容的门限值，当size大于这个值时，table数组进行扩容
     */
    int threshold;

    /**
     * The load factor for the hash table.
     *
     */
 float loadFactor;
/**
     * The default initial capacity - MUST be a power of two.
* 默认初始化数组大小为16
     */
    static final int DEFAULT_INITIAL_CAPACITY = 1 << 4; // aka 16

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

    /**
     * The load factor used when none specified in constructor.
* 默认装载因子，
     */
    static final float DEFAULT_LOAD_FACTOR = 0.75f;

    /**
     * The bin count threshold for using a tree rather than list for a
     * bin.  Bins are converted to trees when adding an element to a
     * bin with at least this many nodes. The value must be greater
     * than 2 and should be at least 8 to mesh with assumptions in
     * tree removal about conversion back to plain bins upon
     * shrinkage.
* 这是链表的最大长度，当大于这个长度时，链表转化为红黑树
     */
    static final int TREEIFY_THRESHOLD = 8;

    /**
     * The bin count threshold for untreeifying a (split) bin during a
     * resize operation. Should be less than TREEIFY_THRESHOLD, and at
     * most 6 to mesh with shrinkage detection under removal.
     */
    static final int UNTREEIFY_THRESHOLD = 6;

    /**
     * The smallest table capacity for which bins may be treeified.
     * (Otherwise the table is resized if too many nodes in a bin.)
     * Should be at least 4 * TREEIFY_THRESHOLD to avoid conflicts
     * between resizing and treeification thresholds.
     */
    static final int MIN_TREEIFY_CAPACITY = 64;

三、构造函数

//可以自己指定初始容量和装载因子
    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;
        //重新定义了扩容的门限
        this.threshold = tableSizeFor(initialCapacity);
}

/**
     * Returns a power of two size for the given target capacity.
     */
    static final int tableSizeFor(int cap) {
        int n = cap - 1;
        //先移位再或运算，最终保证返回值是2的整数幂
        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;
    }

    /**
     * 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.
     */
//当知道所要构建的数据容量的大小时，最好直接指定大小，提高效率
    public HashMap(int initialCapacity) {
        this(initialCapacity, DEFAULT_LOAD_FACTOR);
    }

    /**
     * Constructs an empty <tt>HashMap</tt> with the default initial capacity
     * (16) and the default load factor (0.75).
     */
    public HashMap() {
        this.loadFactor = DEFAULT_LOAD_FACTOR; // all other fields defaulted
    }

    //将map直接放入hashmap中
    public HashMap(Map<? extends K, ? extends V> m) {
        this.loadFactor = DEFAULT_LOAD_FACTOR;
        putMapEntries(m, false);
    }

final void putMapEntries(Map<? extends K, ? extends V> m, boolean evict) {
        int s = m.size();
        if (s > 0) {
            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);
            }
        }
}


/**
     * Basic hash bin node, used for most entries.  (See below for
     * TreeNode subclass, and in LinkedMyHashMap for its Entry subclass.)
     */
    在hashMap的结构图中，hash数组就是用Node型数组实现的，许多Node类通过next组成链表，key、value实际存储在Node内部类中。
    public static class Node<K,V> implements Map.Entry<K,V> {
        final int hash;
        final K key;
        V value;
        Node<K,V> next;

        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;
        }
    }

 

四、重要的方法分析

1.put方法

/**
     * Associates the specified value with the specified key in thismap.
     * If the map previously contained a mapping for the key, the old
     * value is replaced.
     *
*/
public V put(K key, V value) {
        return putVal(hash(key), key, value, false, true);
    }
static final int hash(Object key) {
        int h;
        //key的值为null时，hash值返回0，对应的table数组中的位置是0
        return (key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 16);
    }

/**
     * Implements Map.put and related methods
     *
     * @param hash hash for key
     * @param key the key
     * @param value the value to put
     * @param onlyIfAbsent if true, don't change existing value
     * @param evict if false, the table is in creation mode.
     * @return previous value, or null if none
 */
final V putVal(int hash, K key, V value, boolean onlyIfAbsent,
                   boolean evict) {
        Node<K,V>[] tab; Node<K,V> p; int n, i;
//先将table赋给tab，判断table是否为null或大小为0，若为真，就调用resize（）初始化
        if ((tab = table) == null || (n = tab.length) == 0)
            n = (tab = resize()).length;
//通过i = (n - 1) & hash得到table中的index值，若为null，则直接添加一个newNode
        if ((p = tab[i = (n - 1) & hash]) == null)
            tab[i] = newNode(hash, key, value, null);
        else {
        //执行到这里，说明发生碰撞，即tab[i]不为空，需要组成单链表或红黑树
            Node<K,V> e; K k;
            if (p.hash == hash &&
                ((k = p.key) == key || (key != null && key.equals(k))))
//此时p指的是table[i]中存储的那个Node，如果待插入的节点中hash值和key值在p中已经存在，则将p赋给e
                e = p;
//如果table数组中node类的hash、key的值与将要插入的Node的hash、key不吻合，就需要在这个node节点链表或者树节点中查找。
            else if (p instanceof TreeNode)
            //当p属于红黑树结构时，则按照红黑树方式插入
                e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value);
            else {
    //到这里说明碰撞的节点以单链表形式存储，for循环用来使单链表依次向后查找
                for (int binCount = 0; ; ++binCount) {
        //将p的下一个节点赋给e，如果为null，创建一个新节点赋给p的下一个节点
                    if ((e = p.next) == null) {
                        p.next = newNode(hash, key, value, null);
        //如果冲突节点达到8个，调用treeifyBin(tab, hash)，这个treeifyBin首先回去判断当前hash表的长度，如果不足64的话，实际上就只进行resize，扩容table，如果已经达到64，那么才会将冲突项存储结构改为红黑树。

                        if (binCount >= TREEIFY_THRESHOLD - 1) // -1 for 1st
                            treeifyBin(tab, hash);
                        break;
                    }
//如果有相同的hash和key，则退出循环
                    if (e.hash == hash &&
                        ((k = e.key) == key || (key != null && key.equals(k))))
                        break;
                    p = e;//将p调整为下一个节点
                }
            }
//若e不为null，表示已经存在与待插入节点hash、key相同的节点，hashmap后插入的key值对应的value会覆盖以前相同key值对应的value值，就是下面这块代码实现的
            if (e != null) { // existing mapping for key
                V oldValue = e.value;
        //判断是否修改已插入节点的value
                if (!onlyIfAbsent || oldValue == null)
                    e.value = value;
                afterNodeAccess(e);
                return oldValue;
            }
        }
        ++modCount;//插入新节点后，hashmap的结构调整次数+1
        if (++size > threshold)
            resize();//HashMap中节点数+1，如果大于threshold，那么要进行一次扩容
        afterNodeInsertion(evict);
        return null;
    }

2.扩容函数resize（）分析

/**
     * Initializes or doubles table size.  If null, allocates in
     * accord with initial capacity target held in field threshold.
     * Otherwise, because we are using power-of-two expansion, the
     * elements from each bin must either stay at same index, or move
     * with a power of two offset in the new table.
     *
     * @return the table
     */
    final Node<K,V>[] resize() {
        Node<K,V>[] oldTab = table;//定义临时Node数组型变量，作为hash table
        //读取hash table的长度
        int oldCap = (oldTab == null) ? 0 : oldTab.length;
        int oldThr = threshold;//读取扩容门限
        int newCap, newThr = 0;//初始化新的table长度和门限值
        if (oldCap > 0) {
            //执行到这里，说明table已经初始化
            if (oldCap >= MAXIMUM_CAPACITY) {
                threshold = Integer.MAX_VALUE;
                return oldTab;
            }
            //二倍扩容，容量和门限值都加倍
            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
        //用构造器初始化了门限值，将门限值直接赋给新table容量
            newCap = oldThr;
        else {
 // zero initial threshold signifies using defaults
//老的table容量和门限值都为0，初始化新容量，新门限值，在调用hashmap（）方式构造容器时，就采用这种方式初始化
            newCap = DEFAULT_INITIAL_CAPACITY;
            newThr = (int)(DEFAULT_LOAD_FACTOR * DEFAULT_INITIAL_CAPACITY);
        }
        if (newThr == 0) {
            //如果门限值为0，重新设置门限
            float ft = (float)newCap * loadFactor;
            newThr = (newCap < MAXIMUM_CAPACITY && ft < (float)MAXIMUM_CAPACITY ?
                      (int)ft : Integer.MAX_VALUE);
        }
        threshold = newThr;//更新新门限值为threshold
        @SuppressWarnings({"rawtypes","unchecked"})
       //初始化新的table数组
        Node<K,V>[] newTab = (Node<K,V>[])new Node[newCap];
        table = newTab;
        //当原来的table不为null时，需要将table[i]中的节点迁移
        if (oldTab != null) {
            for (int j = 0; j < oldCap; ++j) {
                Node<K,V> e;
                //取出链表中第一个节点保存，若不为null，继续下面操作
                if ((e = oldTab[j]) != null) {
                    oldTab[j] = null;//主动释放
                    if (e.next == null)
    //链表中只有一个节点，没有后续节点，则直接重新计算在新table中的index，并将此节点存储到新table对应的index位置处
                        newTab[e.hash & (newCap - 1)] = e;
                    else if (e instanceof TreeNode)
                    //若e是红黑树节点，则按红黑树移动
                        ((TreeNode<K,V>)e).split(this, newTab, j, oldCap);
                    else { // preserve order
                    //迁移单链表中的每个节点
                        Node<K,V> loHead = null, loTail = null;
                        Node<K,V> hiHead = null, hiTail = null;
                        Node<K,V> next;
                        do {
//下面这段暂时没有太明白，通过e.hash & oldCap将链表分为两队，参考知乎上的一段解释
/**
* 把链表上的键值对按hash值分成lo和hi两串，lo串的新索引位置与原先相同[原先位
* j]，hi串的新索引位置为[原先位置j+oldCap]；
* 链表的键值对加入lo还是hi串取决于 判断条件if ((e.hash & oldCap) == 0)，因为* capacity是2的幂，所以oldCap为10...0的二进制形式，若判断条件为真，意味着
* oldCap为1的那位对应的hash位为0，对新索引的计算没有影响（新索引
* =hash&(newCap-*1)，newCap=oldCap<<2）；若判断条件为假，则 oldCap为1的那位* 对应的hash位为1，
* 即新索引=hash&( newCap-1 )= hash&( (oldCap<<2) - 1)，相当于多了10...0，
* 即 oldCap

* 例子：
* 旧容量=16，二进制10000；新容量=32，二进制100000
* 旧索引的计算：
* hash = xxxx xxxx xxxy xxxx
* 旧容量-1 1111
* &运算 xxxx
* 新索引的计算：
* hash = xxxx xxxx xxxy xxxx
* 新容量-1 1 1111
* &运算 y xxxx
* 新索引 = 旧索引 + y0000，若判断条件为真，则y=0(lo串索引不变)，否则y=1(hi串
* 索引=旧索引+旧容量10000)
   */

                            next = e.next;
                            if ((e.hash & oldCap) == 0) {
                                if (loTail == null)
                                    loHead = e;
                                else
                                    loTail.next = e;
                                loTail = e;
                            }
                            else {
                                if (hiTail == null)
                                    hiHead = e;
                                else
                                    hiTail.next = e;
                                hiTail = e;
                            }
                        } while ((e = next) != null);
                        if (loTail != null) {
                            loTail.next = null;
                            newTab[j] = loHead;
                        }
                        if (hiTail != null) {
                            hiTail.next = null;
                            newTab[j + oldCap] = hiHead;
                        }
                    }
                }
            }
        }
        return newTab;
    }

3.get方法

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

    /**
     * Implements Map.get and related methods
     *
     * @param hash hash for key
     * @param key the key
     * @return the node, or null if none
     */
    final Node<K,V> getNode(int hash, Object key) {
        Node<K,V>[] tab; Node<K,V> first, e; int n; K k;
        if ((tab = table) != null && (n = tab.length) > 0 &&
            (first = tab[(n - 1) & hash]) != null) {
            if (first.hash == hash && // always check first node
                ((k = first.key) == key || (key != null && key.equals(k))))
                return first;
            if ((e = first.next) != null) {
           //分为红黑树和链表查找两种
                if (first instanceof TreeNode)
                    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);
            }
        }
        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;
    }

4.红黑树

/**
     * Entry for Tree bins. Extends LinkedMyHashMap.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);
        }

        //红黑树暂时还没有仔细研究，红黑树相关的增删改查操作后期再认真分析。

五、总结

仔细分析hashmap源码后，可以掌握很多常用的数据结构的用法。本次笔记只是记录了hashmap几个常用的方法，像红黑树、迭代器等还没有仔细研究，后面有时间会认真分析。

网友文章参考http://www.cnblogs.com/ToBeAProgrammer/p/4787761.html

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