阿狗工具

核心成员变量

JDK7

• Entry[] table。Entry存储了HashMap的真正数据
• size大小，代表HashMap内存储了多少个键值对
• capacity容量。实际上HashMap中没有一个成员叫capacity，它是作为table这个数组的大小而隐式存在
• threshold阈值和loadFactor（默认0.75f）装载因子。threshold是通过capacity*loadFactor得到的。当size超过threshold时（刚好相等时不会扩容），HashMap扩容会再次计算每个元素的hash位置
• entrySet、keySet和values这三个都是一种试图，真正地数据都来自table

JDK8

• table。这个Node类型的数组存储了HashMap的真正数据 Node<K,V> implements Map.Entry<K,V>
• size大小，代表HashMap内存储了多少个键值对
• capacity容量。实际上HashMap中没有一个成员叫capacity，它是作为table这个数组的大小而隐式存在
• threshold阈值和loadFactor（默认0.75f）装载因子。threshold是通过capacity*loadFactor得到的。当size超过threshold时（刚好相等时不会扩容），HashMap会扩容（）
• entrySet、keySet和values这三个都是一种试图，真正地数据都来自table

JDK8阈值变化原因

到8转为红黑树

• TreeNode（红黑树中）占用空间是普通Node（链表中）的两倍，为了时间和空间的权衡
• 节点的分布频率会遵循泊松分布，链表长度达到8个元素的概率为0.00000006

到6转为链表

• 若是7，则当极端情况下（频繁插入和删除的都是同一个hash桶）对一个链表长度为8的hash桶进行频繁的删除和插入，同样也会导致频繁的树化<=>非树化

源码分析

put过程

JDK7

JDK8

put操作

// JDK7
public V put(K key, V value) {
    if (table == EMPTY_TABLE) {  // 表空进行初始化
        inflateTable(threshold);
    }
    if (key == null) // 键空
        return putForNullKey(value);
    int hash = hash(key);
    int i = indexFor(hash, table.length); // 计算bucket的位置
    for (Entry<K,V> e = table[i]; e != null; e = e.next) {
        Object k;
        // hash相同 equals 比较是真则替换返回旧值
        if (e.hash == hash && ((k = e.key) == key || key.equals(k))) {
            V oldValue = e.value;
            e.value = value;
            e.recordAccess(this);
            return oldValue;
        }
    }

    modCount++;
    addEntry(hash, key, value, i);  // 添加数据 这里包含hash冲突的处理
    return null;
}

void addEntry(int hash, K key, V value, int bucketIndex) {
    if ((size >= threshold) && (null != table[bucketIndex])) {
        // 扩容操作，将数据元素重新计算位置后放入newTable中，Hash位置会重新计算
        resize(2 * table.length);
        hash = (null != key) ? hash(key) : 0;
        bucketIndex = indexFor(hash, table.length);
    }

    createEntry(hash, key, value, bucketIndex);
}

void createEntry(int hash, K key, V value, int bucketIndex) {
    Entry<K,V> e = table[bucketIndex];
    // 根据头结点构建
    table[bucketIndex] = new Entry<>(hash, key, value, e);
    size++;
}

// JDK8
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;
    if ((tab = table) == null || (n = tab.length) == 0)
        n = (tab = resize()).length;
    if ((p = tab[i = (n - 1) & hash]) == null)
        tab[i] = newNode(hash, key, value, null);
    else {
        Node<K,V> e; K k;
        if (p.hash == hash &&
                ((k = p.key) == key || (key != null && key.equals(k))))
            e = p;
        else if (p instanceof TreeNode)
            e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value);
        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;
            if (!onlyIfAbsent || oldValue == null)
                e.value = value;
            afterNodeAccess(e);
            return oldValue;
        }
    }
    ++modCount;
    if (++size > threshold)
        resize();
    afterNodeInsertion(evict);
    return null;
}

hash算法

// JDK7
final int hash(Object k) {
    int h = hashSeed;
    if (0 != h && k instanceof String) {
        return sun.misc.Hashing.stringHash32((String) k);
    }

    h ^= k.hashCode();

    // This function ensures that hashCodes that differ only by
    // constant multiples at each bit position have a bounded
    // number of collisions (approximately 8 at default load factor).
    h ^= (h >>> 20) ^ (h >>> 12);
    return h ^ (h >>> 7) ^ (h >>> 4);
}

// JDK8
static final int hash(Object key) {
    int h;
    return (key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 16);
}

实体结构

// JDK7
static class Entry<K,V> implements Map.Entry<K,V> {
    final K key;
    V value;
    Entry<K,V> next;
    int hash;

    /**
     * Creates new entry.
     */
    Entry(int h, K k, V v, Entry<K,V> n) {
        value = v;
        next = n;
        key = k;
        hash = h;
    }
}

// JDK8
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;
    }
}

static class LinkedHashMap.Entry<K,V> extends HashMap.Node<K,V> {
    Entry<K,V> before, after;
    Entry(int hash, K key, V value, Node<K,V> next) {
        super(hash, key, value, next);
    }
}

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);
    }
}

get过程

JDK7

// JDK7
public V get(Object key) {
    if (key == null)
        return getForNullKey();
    Entry<K,V> entry = getEntry(key);

    return null == entry ? null : entry.getValue();
}

final Entry<K,V> getEntry(Object key) {
    if (size == 0) {
        return null;
    }

    int hash = (key == null) ? 0 : hash(key);
    for (Entry<K,V> e = table[indexFor(hash, table.length)];
         e != null;
         e = e.next) {
        Object k;
        if (e.hash == hash &&
                ((k = e.key) == key || (key != null && key.equals(k))))
            return e;
    }
    return null;
}

// JDK8
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) {
    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) {
            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;
}

JDK7&JDK8区别

• 底层结构
  JDK7是数组+链表 存储节点数据Entry
  JDK8是数组+链表+红黑树 存储节点数据Node。JDK8当链表长度大于8同时HashMap元素个数大于64则转换成红黑树
• 哈希表为空
  JDK7会先调用inflateTable初始化一个数组
  JDK8则直接调用热size扩容
• hash冲突时插入数据
  JDK7采用头插
  JDK8会将节点插入到链表尾部
• hash函数
  JDK7中的hash函数直接使用key的hashcode值进行5次异或和4次位移，扰动复杂
  JDK8中的hash函数采用key的hashcode值异或上key的hashcode无符号右移16位，扰动简单
• 扩容策略
  JDK7中会重新计算hash
  JDK8中不需要像JDK7那样重新计算hash，只需要看看原来的hash值新增的那个bit是1还是0就好了，是0的话索引没变，是1的话索引变成“原索引+oldCap”
  
  

  JDK8扩容