HashMap源码解析_jdk1.8(二)

HashMap源码解析_jdk1.8(二)

构造函数

HashMap提供了如下几个构造函数:

/**
 * 构造一个具有指定初始容量和负载因子的空HashMap.
 *
 * @param  initialCapacity 初始容量
 * @param  loadFactor      负载因子
 * @throws IllegalArgumentException if the initial capacity is negative
 *         or the load factor is nonpositive
 */
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;
    // 如果用户通过构造函数指定了一个数字作为容量,那么Hash会选择大于该数字的第一个2的幂作为容量。(1->1、7->8、9->16)
    this.threshold = tableSizeFor(initialCapacity);
}

/**
 * 构造一个具有指定初始容量和默认负载因子(0.75)的空HashMap.
 *
 * @param  initialCapacity 初始容量
 * @throws IllegalArgumentException if the initial capacity is negative.
 */
public HashMap(int initialCapacity) {
    
    
    this(initialCapacity, DEFAULT_LOAD_FACTOR);
}

/**
 * 构造一个具有默认初始容量(16)和默认负载因子(0.75)的空HashMap.
 */
public HashMap() {
    
    
    this.loadFactor = DEFAULT_LOAD_FACTOR; // all other fields defaulted
}

/**
 * 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
 */
public HashMap(Map<? extends K, ? extends V> m) {
    
    
    this.loadFactor = DEFAULT_LOAD_FACTOR;
    putMapEntries(m, false);
}

如果用户通过构造函数指定了一个数字作为容量,那么Hash会选择大于该数字的第一个2的幂作为容量。(1->1、7->8、9->16)

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

从构造函数我们可以看出,在常规构造器中,没有为数组table分配内存空间(有一个入参为指定Map的构造器例外),而是在执行put操作的时候才真正构建table数组。

put方法

请添加图片描述

/**
 * 将指定的value与该map中的指定key相关联.
 * 如果map中已经包含指定key,key对应的value将会被新值覆盖
 *
 * @param key key with which the specified value is to be associated
 * @param value value to be associated with the specified key
 * @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 put(K key, V value) {
    
    
    // 根据key计算hash值
    return putVal(hash(key), key, value, false, true);
}

/**
 * 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;
    // 如果table为null或长度为0,为数组table分配内存空间
    if ((tab = table) == null || (n = tab.length) == 0)
        n = (tab = resize()).length;

    // 判断插入的位置是否是冲突的,如果不冲突就直接newNode,插入到数组中即可
    if ((p = tab[i = (n - 1) & hash]) == null)
        tab[i] = newNode(hash, key, value, null);
    else {
    
     // 如果插入的hash值冲突了
        Node<K,V> e; K k;

        // 判断table[i]中的元素是否与插入的key一样,若相同那就直接使用插入的值p替换掉旧的值e。
        if (p.hash == hash &&
            ((k = p.key) == key || (key != null && key.equals(k))))
            e = p;
        
        // 判断插入的数据结构是红黑树还是链表,在这里表示如果是红黑树,那就直接putTreeVal到红黑树中
        else if (p instanceof TreeNode)
            e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value);
        // 数据结构是链表
        else {
    
    
            // 遍历table数组是否存在
            for (int binCount = 0; ; ++binCount) {
    
    
                // 不存在直接newNode(hash, key, value, null)
                if ((e = p.next) == null) {
    
    
                    p.next = newNode(hash, key, value, null);
                    // 判断当前链表的长度是否大于阈值8,如果大于那就会把当前链表转变成红黑树
                    if (binCount >= TREEIFY_THRESHOLD - 1) // -1 for 1st
                        treeifyBin(tab, hash);
                    break;
                }
                // 如果存在了跳出循环
                if (e.hash == hash &&
                    ((k = e.key) == key || (key != null && key.equals(k))))
                    break;
                p = e;
            }
        }
        // 如果存在了,直接使用新的value替换掉旧的value
        if (e != null) {
    
     // existing mapping for key
            V oldValue = e.value;
            if (!onlyIfAbsent || oldValue == null)
                e.value = value;
            afterNodeAccess(e);
            return oldValue;
        }
    }
    ++modCount;
    // 插入成功,判断是否需要扩容
    if (++size > threshold)
        resize();
    afterNodeInsertion(evict);
    return null;
}

resize扩容方法

/**
 * table数组初始化或长度加倍.  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;
    // 扩容前table数组长度
    int oldCap = (oldTab == null) ? 0 : oldTab.length;
    int oldThr = threshold;
    int newCap, newThr = 0;
    if (oldCap > 0) {
    
    
        if (oldCap >= MAXIMUM_CAPACITY) {
    
    
            threshold = Integer.MAX_VALUE;
            return oldTab;
        }
        else if ((newCap = oldCap << 1) < MAXIMUM_CAPACITY &&
                    oldCap >= DEFAULT_INITIAL_CAPACITY)
            // 将阈值扩大为2倍
            newThr = oldThr << 1; // double threshold
    }
    // 阈值已经初始化了,就直接使用
    else if (oldThr > 0) // initial capacity was placed in threshold
        newCap = oldThr;
    else {
    
                   // zero initial threshold signifies using defaults
        // 没有初始化阈值那就初始化一个默认的容量和阈值
        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"})
    // 新建一个数组长度为原来2倍的数组
    Node<K,V>[] newTab = (Node<K,V>[])new Node[newCap];
    table = newTab;
    // 旧数据保存在新数组里面
    if (oldTab != null) {
    
    
        for (int j = 0; j < oldCap; ++j) {
    
    
            Node<K,V> e;
            if ((e = oldTab[j]) != null) {
    
    
                oldTab[j] = null;
                // 只有一个节点,通过索引位置直接映射
                if (e.next == null)
                    newTab[e.hash & (newCap - 1)] = e;
                // 如果是红黑树,需要进行树拆分然后映射
                else if (e instanceof TreeNode)
                    ((TreeNode<K,V>)e).split(this, newTab, j, oldCap);
                else {
    
     // preserve order
                    // 如果是多个节点的链表,将原链表拆分为两个链表
                    Node<K,V> loHead = null, loTail = null;
                    Node<K,V> hiHead = null, hiTail = null;
                    Node<K,V> next;
                    do {
    
    
                        next = e.next;
                        // 扩容后,若hash值新增参与运算的位=0,那么元素在扩容后的位置=原始位置
                        if ((e.hash & oldCap) == 0) {
    
    
                            if (loTail == null)
                                loHead = e;
                            else
                                loTail.next = e;
                            loTail = e;
                        }
                        // 扩容后,若hash值新增参与运算的位=1,那么元素在扩容后的位置=原始位置+oldCap
                        else {
    
    
                            if (hiTail == null)
                                hiHead = e;
                            else
                                hiTail.next = e;
                            hiTail = e;
                        }
                    } while ((e = next) != null);

                    // 链表1存于原索引
                    if (loTail != null) {
    
    
                        loTail.next = null;
                        newTab[j] = loHead;
                    }
                    // 链表2存于原索引加上原hash桶长度的偏移量
                    if (hiTail != null) {
    
    
                        hiTail.next = null;
                        newTab[j + oldCap] = hiHead;
                    }
                }
            }
        }
    }
    return newTab;
}

参考:
https://zhuanlan.zhihu.com/p/79219960
https://www.cnblogs.com/theRhyme/p/9404082.html#_lab2_1_1

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转载自blog.csdn.net/tracydragonlxy/article/details/134018150