HashMap源码分析-基于jdk1.8

HashMap

1. 初始化
   

描述 Hashmap构造方法一公共有4个，分别如下

/**
* 无参构造
*/
public HashMap() {
        //默认的加载因子 0.75
        this.loadFactor = DEFAULT_LOAD_FACTOR; // all other fields defaulted
}

 /**
 * 给定初始容量
 * @param initialCapacity
 */
public HashMap(int initialCapacity) {
    /*指定集合初始容量 加载因子按照默认的来 0.75f*/
    this(initialCapacity, DEFAULT_LOAD_FACTOR);
}

/**
 * 指定初始容量和加载因子
 * @param initialCapacity
 * @param loadFactor
 */
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);
}

/**
 * 基于已有的集合构建
 * @param m
 */
public HashMap(Map<? extends K, ? extends V> m) {
    /*默认的加载因子*/
    this.loadFactor = DEFAULT_LOAD_FACTOR;
    putMapEntries(m, false);
}

2.添加元素

描述 相对于查找来说要复杂很多

/**
 * 获取key的hash值
 * @param key
 * @return
 */
static final int hash(Object key) {
    int h;
    //key为null时 hash值为0 取key对应的hashcode  异或上 h无符号右移16位，为了防止实现较差的hashcode
    // 产生较大的碰撞概率，这里会对hash值做一个移位，让自己的高位和低位做异或，以此来加大hash值得随机性
    return (key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 16);
}

/**
 * 在map中加入元素
 * @param key
 * @param value
 * @return
 */
public V put(K key, V value) {
    return putVal(hash(key), key, value, false, true);
}

/**
 *
 * @param hash 元素的hash值
 * @param key 添加的数据的key
 * @param value 添加的数据的值
 * @param onlyIfAbsent 是否覆盖已存在的value
 * @param evict
 * @return
 */
final V putVal(int hash, K key, V value, boolean onlyIfAbsent,
               boolean evict) {
    Node<K,V>[] tab;
    Node<K,V> p;
    int n, i;

    /*这种情况说明集合刚刚初始化，还没有任何元素*/
    if ((tab = table) == null || (n = tab.length) == 0)
        //加入第一个元素的时候，需要初始化下
        n = (tab = resize()).length;
    /*这种情况说明数组对应的位置还没有数据，没有出现hash碰撞 直接将元素存入即可*/
    if ((p = tab[i = (n - 1) & hash]) == null)
        tab[i] = newNode(hash, key, value, null);
    else {
        /*进来说明数据已经在数组这个位置发生了碰撞，需要将元素添加到链表或者红黑树中*/
        Node<K,V> e; K k;
        /*这种说明存在相同的key,需要对旧值做是否覆盖处理*/
        if (p.hash == hash &&
            ((k = p.key) == key || (key != null && key.equals(k))))
            e = p;
        /*说明链表已经转成了红黑树，需要将数据插入到红黑树中*/
        else if (p instanceof TreeNode)
            e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value);
        else {
            /*对链表一直循环 直到后继节点为空为止*/
            for (int binCount = 0; ; ++binCount) {
                if ((e = p.next) == null) {
                    /*找到链表的尾部后 将新的数据构造成新的节点，插入到尾部*/
                    p.next = newNode(hash, key, value, null);
                    /*如果链表长度达到阈值，就转成红黑树*/
                    if (binCount >= TREEIFY_THRESHOLD - 1) // -1 for 1st
                        treeifyBin(tab, hash);
                    break;
                }
                /*key已存在则退出，对value做是否覆盖处理*/
                if (e.hash == hash &&
                    ((k = e.key) == key || (key != null && key.equals(k))))
                    break;
                p = e;
            }
        }
        /*e不为空说明key已经存在*/
        if (e != null) { // existing mapping for key
            V oldValue = e.value;
            /*如果onlyIfAbsent为false 则可以将新值覆盖旧值*/
            if (!onlyIfAbsent || oldValue == null)
                e.value = value;
            afterNodeAccess(e);
            return oldValue;
        }
    }
    ++modCount;
    /*元素个数超过阈值 则需要扩容*/
    if (++size > threshold)
        resize();
    afterNodeInsertion(evict);
    return null;
}

//重新计算数组大小
final Node<K,V>[] resize() {
    Node<K,V>[] oldTab = table;
    int oldCap = (oldTab == null) ? 0 : oldTab.length;
    int oldThr = threshold;
    int newCap, newThr = 0;
    //如果旧的容量大于0
    if (oldCap > 0) {
        //如果容量值大于最大容量值，则将阈值设置为最大值
        if (oldCap >= MAXIMUM_CAPACITY) {
            threshold = Integer.MAX_VALUE;
            //无法扩容啦 直接返回旧的数组
            return oldTab;
        }
        //设置新的容量为原容量的两倍 如果扩容两倍小于最大值，且 旧的值大于出事默认值 则设置新的threshold为旧值得两倍
        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
        //设置旧的阈值为新的容量
        newCap = oldThr;
    else {
        // zero initial threshold signifies using defaults
        //初始化为默认的容量与阈值 16 ，12
        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;
    //初始化一个新容量的数组
    @SuppressWarnings({"rawtypes","unchecked"})
    Node<K,V>[] newTab = (Node<K,V>[])new Node[newCap];
    //如果是多线程 这里肯定有问题 将新的数组赋值给数据存储的table
    table = newTab;
    if (oldTab != null) {
        //如果原来有值，这里需要处理，并把值拷贝到新数组里面
        for (int j = 0; j < oldCap; ++j) {
            Node<K,V> e;
            //获取数组元素e
            if ((e = oldTab[j]) != null) {
                //原数组数据置空，可以垃圾回收原数组，要不让有可达的引用，无法回收
                oldTab[j] = null;
                if (e.next == null)
                    //最简单的情况，没有后续的碰撞元素，直接赋值即可，rehash
                    newTab[e.hash & (newCap - 1)] = e;
                else if (e instanceof TreeNode)
                    //如果是treeNode的节点
                    ((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;
                        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;
}

/*构造一个链表节点的构造函数*/
Node(int hash, K key, V value, Node<K,V> next) {
    /*key对应的hash值*/
    this.hash = hash;
    /*key*/
    this.key = key;
    /*value*/
    this.value = value;
    /*后继节点*/
    this.next = next;
}

3.查找元素

描述

4.移除元素

描述

/**
 * 查找元素
 * @param key
 * @return
 */
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;
    /*数组不为空 并且 数组长度大于零 并且 根据hash算法定位到的数组内的链表的头元素不为空*/
    if ((tab = table) != null && (n = tab.length) > 0 &&
        (first = tab[(n - 1) & hash]) != null) {
        /*首节点是key对应的值则直接返回*/
        if (first.hash == hash && // always check first node
            ((k = first.key) == key || (key != null && key.equals(k))))
            return first;
        if ((e = first.next) != null) {
            /*如果是红黑树节点，则在红黑树中查找*/
            if (first instanceof TreeNode)
                return ((TreeNode<K,V>)first).getTreeNode(hash, key);
            do {
                /*遍历链表，查找元素*/
                if (e.hash == hash &&
                    ((k = e.key) == key || (key != null && key.equals(k))))
                    return e;
            } while ((e = e.next) != null);
        }
    }
    return null;
}

4.移除元素

描述 相对于查找来说要复杂很多，但是不需要考虑扩容

/**
 * 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;
    /*数组不为空 并且 数组长度大于零 并且 根据hash算法定位到的数组内的链表的头元素不为空*/
    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;
        /*首节点*/
        if (p.hash == hash &&
            ((k = p.key) == key || (key != null && key.equals(k))))
            node = p;
        else if ((e = p.next) != null) {
            /*在红黑树中找到节点*/
            if (p instanceof TreeNode)
                node = ((TreeNode<K,V>)p).getTreeNode(hash, key);
            else {
                /*遍历链表找到节点*/
                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)
                /*从红黑树中移除节点*/
                ((TreeNode<K,V>)node).removeTreeNode(this, tab, movable);
            else if (node == p)
                /*如果移除的是头结点，则将数组中元素指向移除元素的后继节点*/
                tab[index] = node.next;
            else
                /*将移除节点的前驱节点的后继节点设置为移除节点的后继节点*/
                p.next = node.next;
            ++modCount;
            --size;
            afterNodeRemoval(node);
            return node;
        }
    }
    return null;
}