jdk 集合大家族之Map

jdk 集合大家族之Map

前言：

之前章节复习了Collection接口相关，此次我们来一起回顾一下Map相关

。本文基于jdk1.8。

1. HashMap

1.1 概述

• HashMap相对于List的数据结构而言，它是键值对的集合。主要通过提供key值来取相对应的value的值。而不是通过遍历来查找所需要的值。
• key值允许一个为null value不限制
  • key通常使用String Integer这种不可变类作为key
• 通过数组加链表加红黑树来实现，如下图所示
  
  

1.2 源码分析

• 成员变量

/**
     * The default initial capacity - MUST be a power of two.
     */
     // 数组长度默认的容量为16  必须是2的幂
    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.
     */
    // 最大容量 为2^30
    static final int MAXIMUM_CAPACITY = 1 << 30;

    /**
     * The load factor used when none specified in constructor.
     */
    // 默认的负载因子，当构造时没有指定负载因子时使用此值
    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.
     */
    // 链表的长度大于8时转换为红黑树
    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.
     */
    // 链表中的长度小于6时从红黑树转换会链表
    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.
     */
    // 链表转换为红黑树也不是随便转换的，需要满足Map中最少有MIN_TREEIFY_CAPACITY个Node才能允许树形化(将链表转化为红黑树)。
    // 否则表中的过多节点会选择扩容
    // 为了避免扩容和树形化的冲突的选择冲突，此值最少为 4 * TREEIFY_THRESHOLD
    // 数组长度小于64也不会将链表转为红黑树（链表长度大于8但是小于64选择扩容数组，重新hash）
    static final int MIN_TREEIFY_CAPACITY = 64;
     /**
     * 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;

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

    /**
     * The number of key-value mappings contained in this map.
     */
    // Map中键值对的数量
    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).
     */
    // 修改次数
    transient int modCount;

    /**
     * The next size value at which to resize (capacity * load factor).
     *
     * @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.)
    // 下一次扩容的阈值 Map数组长度 * 负载因子
    int threshold;

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

• 构造函数

/**
     * 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
     */
    // 构造指定容量 指定负载因子的HashMap
    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); // tableSizeFor 在大于等于initialCapacity 范围内找最接近initialCapacity的2的n次幂
    }

    static final int tableSizeFor(int cap) {
        int n = cap - 1; // 防止cap为2的n次幂 造成翻倍现象
        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.
     */
    // 构造指定容量 负载因子为默认0.75的HashMap
    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).
     */
    // 构造默认容量为16 负载因子为默认0.75的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);
    }

• 内部键值对的存储 Node 和 TreeNode

     /**
     * Basic hash bin node, used for most entries.  (See below for
     * TreeNode subclass, and in LinkedHashMap for its Entry subclass.)
     */
    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;
        }
    }

     /**
     * Entry for Tree bins. Extends LinkedHashMap.Entry (which in turn
     * extends Node) so can be used as extension of either regular or
     * linked node.
     */
     // 继承了Node(LinkedHashMap.Entry继承了HashMap.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);
        }

    }

• 添加元素 put方法

//
public V put(K key, V value) {
        return putVal(hash(key), key, value, false, true);
}

// 计算hashcode 无符号右移16位然后做异或运算，比取余效率高
static final int hash(Object key) {
        int h;
        return (key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 16);
}

final V putVal(int hash, K key, V value, boolean onlyIfAbsent,
                   boolean evict) {
        Node<K,V>[] tab; Node<K,V> p; int n, i;
        // 为空 或者数组长度为0 进行扩容
        if ((tab = table) == null || (n = tab.length) == 0)
           n = (tab = resize()).length;
        // (n-1)&hash 对数组长度减一与运算计算map数组中的下表 位运算比取余效率高
        // 如果数组的桶为空则直接放到桶内
        if ((p = tab[i = (n - 1) & hash]) == null)
            tab[i] = newNode(hash, key, value, null);
        else { // 桶内已经有其他数据了，进行比较 扩容判断等操作
            // e用于原来的值的返回
            Node<K,V> e; K k;
            // p点为桶中第一个节点 如果与桶内第一个节点hash相同 ,判断是否key是否equals 相同则把原来的值赋值给它
            if (p.hash == hash &&
                ((k = p.key) == key || (key != null && key.equals(k))))
                e = p;
            else if (p instanceof TreeNode) // 如果是树节点则存入
                e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value);
            else { // 桶中为链表
                for (int binCount = 0; ; ++binCount) { // 遍历链表
                    if ((e = p.next) == null) { // 如果遍历到结尾了 则加到结尾
                        p.next = newNode(hash, key, value, null);
                        // 遍历到大于等于8时 进行转换红黑树
                        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)))) // 如果遍历到key hash相同 并且equals时跳出循环
                        break;
                    // 继续向后遍历
                    p = e;
                }
            }
            // 存在相同值的key 替换并返回旧的value
            if (e != null) { // existing mapping for key
                V oldValue = e.value;
                if (!onlyIfAbsent || oldValue == null)
                    e.value = value;
                // 默认为空实现，允许我们修改完成后做一些操作
                afterNodeAccess(e);
                return oldValue;
            }
        }
        ++modCount;
        // 达到 负载因子*capacity 进行扩容
        if (++size > threshold)
            resize();
        // 默认也是空实现，允许我们插入完成后做一些操作
        afterNodeInsertion(evict);
        return null;
    }

• 转换成树

 final void treeifyBin(Node<K,V>[] tab, int hash) {
        int n, index; Node<K,V> e;
        // 此处如果数组的长度小于64 只是进行扩容 rehash 并未进行红黑树操作
        if (tab == null || (n = tab.length) < MIN_TREEIFY_CAPACITY)
            resize();
        else if ((e = tab[index = (n - 1) & hash]) != null) {
            TreeNode<K,V> hd = null, tl = null;
            do { // 将节点的数据结构转成TreeNode 形成一个新的链表
                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);
            // 将新的树结点链表赋给第index个桶
            if ((tab[index] = hd) != null)
                // 真正的转成红黑树
                hd.treeify(tab);
        }
    }

     final void treeify(Node<K,V>[] tab) {
            TreeNode<K,V> root = null;
            // 遍历链表中的每一个TreeNode 当前的节点为x
            for (TreeNode<K,V> x = this, next; x != null; x = next) {
                next = (TreeNode<K,V>)x.next;
                x.left = x.right = null;
                // 当root为空 当前节点设置成根节点 根节点设置成黑色(x.red=false)
                if (root == null) {
                    x.parent = null;
                    x.red = false;
                    root = x;
                }
                else {
                    K k = x.key;
                    int h = x.hash;
                    Class<?> kc = null;
                    // 从根节点开始遍历 找到x插入的位置
                    for (TreeNode<K,V> p = root;;) {
                        int dir, ph;
                        K pk = p.key;
                        // 如果当前结点的hash值小于根结点的hash值，方向dir = -1；
                        if ((ph = p.hash) > h)
                            dir = -1;
                        // 如果当前结点的hash值大于根结点的hash值，方向dir = 1；
                        else if (ph < h)
                            dir = 1;
                        // 如果x结点的key没有实现comparable接口，或者其key和根结点的key相等（k.compareTo(x) == 0）仲裁插入规则
                        // 只有k的类型K直接实现了Comparable<K>接口，才返回K的class，否则返回null，间接实现也不行。
                        else if ((kc == null &&
                                  (kc = comparableClassFor(k)) == null) ||
                                 (dir = compareComparables(kc, k, pk)) == 0)
                            // 仲裁插入规则
                            dir = tieBreakOrder(k, pk);

                        TreeNode<K,V> xp = p;
                        // 如果p的左右结点都不为null，继续for循环，否则执行插入
                        if ((p = (dir <= 0) ? p.left : p.right) == null) {
                            x.parent = xp;
                            if (dir <= 0)
                                xp.left = x;
                            else
                                xp.right = x;
                            // 插入后进行树的调整
                            root = balanceInsertion(root, x);
                            break;
                        }
                    }
                }
            }
            moveRootToFront(tab, root);
        }

其他map相关集合的如下图所示，concurrentHashMap 更高性能的支持并发，可以单独讲一篇。

LinkdedHashMap

LinkedHashMap保存了记录的插入顺序，在用Iteraor遍历LinkedHashMap时，先得到的记录肯定是先插入的，在遍历的时候会比HashMap慢，有HashMap的全部特性。

TreeMap

TreeMap将存储的键值对进行默认排序，并且还能够指定排序的比较器，是线程不安全的。TreeMap不允许键值为null

Hashtable

是线程安全的HashMap 但是他的线程安全控制是通过任意一个线程只能有一个线程写Hashtable,所以并发性不是很好。相比于ConcurrentHashMap使用的是分段锁，并发性更好。所以推荐使用ConcurrentHashMap。

参考资料

• https://www.cnblogs.com/rjzheng/p/11302835.html
• https://www.jianshu.com/p/309ea054cbc9