JDK8之HashMap源码

JDK8的源码是Node数组+Node链表+TreeNode组成

常量解释

static final int DEFAULT_INITIAL_CAPACITY = 1 << 4; // aka 16 //Node数组默认长度

static final int MAXIMUM_CAPACITY = 1 << 30; //Node数组最大长度

static final float DEFAULT_LOAD_FACTOR = 0.75f; //扩容因子

static final int TREEIFY_THRESHOLD = 8; //有一个Node链表长度大于8 则有可能转化为TreeNode

static final int UNTREEIFY_THRESHOLD = 6; //在Hash表扩容时候,如果发现当前链表长度小于6了则重新退化为Node链表

//在转为TreeNode之前还会有一次会比较Node数组的长度,如果<64则Hash表仅是扩容,这样做的目的是,如果多个K/V恰好在同一个Node链表上导致的不必要的转换
static final int MIN_TREEIFY_CAPACITY = 64;
transient int size;//Hash表中的K-V数量

transient int modCount;//记录Hash表修改的次数,增 删 改 都会+1

int threshold;//可以理解为下一次扩容的阀值
final float loadFactor; //Hash表的实际扩容因子,默认值(0.75)或者自己定义

初始化

HashMap有三个初始化方法

//默认长度16,扩容因子0.75
public HashMap() {
     this.loadFactor = DEFAULT_LOAD_FACTOR; // all other fields defaulted
}
//手动设置容量,默认0.75的扩容因子
public HashMap(int initialCapacity) {
        this(initialCapacity, DEFAULT_LOAD_FACTOR);
}
public HashMap(int initialCapacity, float loadFactor) {
     //手动设置容量<0抛出异常  
      if (initialCapacity < 0)
            throw new IllegalArgumentException("Illegal initial capacity: " +
                                               initialCapacity);
       //手动设置容量超过最大容量,为最大容量 
       if (initialCapacity > MAXIMUM_CAPACITY)
            initialCapacity = MAXIMUM_CAPACITY;
       //扩展因子<=0 或者 不合法 抛出异常    
        if (loadFactor <= 0 || Float.isNaN(loadFactor))
            throw new IllegalArgumentException("Illegal load factor: " +
                                               loadFactor);
        
        this.loadFactor = loadFactor;
        //计算Hash表的扩容阀值
        this.threshold = tableSizeFor(initialCapacity);
    }
/**
     * Returns a power of two size for the given target capacity.
     * 翻译:返回大于输入参数且最近的2的整数次幂的数,例如9 返回16 ,17返回32 18返回32
     */
    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;
    }

put数据

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) {
        //tab是Hash表的容量数组,p是当前key的计算后的索引值对应的Node节点,n是容器数组的长度,i是key值计算后的索引值
        Node<K,V>[] tab; Node<K,V> p; int n, i;
        if ((tab = table) == null || (n = tab.length) == 0)
            //如果tab为空,或者n==0 则执行首次扩容
            n = (tab = resize()).length;
        if ((p = tab[i = (n - 1) & hash]) == null)
            //当前key值计算后的索引值对应的Node为空,说明当前位置是首次添加
            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))))
                //如果当前key与查出来的Node的key hash值相同则直接覆盖老值
                e = p;
            else if (p instanceof TreeNode)
                //当前节点是树类型,树形结构添加节点
                e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value);
            else {
                //如果当前Node的next为空,则直接将put的值放在当前Node的next位置,并且要判断是否需要转为TreeNode
                //如果当前Node的next不为空就需要循环next一直找到next为空的位置。说明了HashMap的put操作的时间复杂度最好为O(1),最坏O(n)
                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;
            }
        }
        //修改次数+1
        ++modCount;
        //如果当前的K-V数量 > 阀值 执行扩容
        if (++size > threshold)
            resize();
        afterNodeInsertion(evict);
        return null;
    }

Node链表转为Tree

treeifyBin (Node转为TreeNode)

final void treeifyBin(Node<K,V>[] tab, int hash) {
        int n, index; Node<K,V> e;
        //容量数组为空或者容量数组长度  < 64 继续扩容,避免不必要的转换
        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 {
                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);
            if ((tab[index] = hd) != null)
                hd.treeify(tab);
        }
    }

扩容

final Node<K,V>[] resize() {
        Node<K,V>[] oldTab = table;
        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;
            }
            //容量扩容一倍,扩容阀值也是一倍
            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
            newCap = oldThr;
        else {               // zero initial threshold signifies using defaults
            //首次初始化,容量是默认值,扩容阀值是容量*扩容因子
            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);
        }
        //设置扩容阀值
        threshold = newThr;
        //new一个长度为newCap的Node数组
        @SuppressWarnings({"rawtypes","unchecked"})
            Node<K,V>[] newTab = (Node<K,V>[])new Node[newCap];
        table = newTab;
        if (oldTab != null) {
            for (int j = 0; j < oldCap; ++j) {
                Node<K,V> e;
                //将老的Node数组里的Node重新放到扩容之后的Node数组,分为3中情况,当前Node next为空,TreeNode节点,当前Node next不为空
                if ((e = oldTab[j]) != null) {
                    oldTab[j] = null; //释放老数组的引用
                    if (e.next == null)
                        newTab[e.hash & (newCap - 1)] = e;
                    else if (e instanceof TreeNode)
                        ((TreeNode<K,V>)e).split(this, newTab, j, oldCap);
                    else { // preserve order
                        //loHead用户存储低位(位置不变)key的链头,loTail用于指向链位位置。
                        Node<K,V> loHead = null, loTail = null;
                        //hiHead用户存储即将存储在高位的key的链头,hiTail用于指向链尾位置。
                        Node<K,V> hiHead = null, hiTail = null;
                        Node<K,V> next;
                        do {
                            next = e.next;
                           //与原数组长度相与后,得到的结果为0的,意味着在新数组中的位置是不变的,因此,将其组成一个链条
                           if ((e.hash & oldCap) == 0) {
                                if (loTail == null)
                                    loHead = e;
                                else
                                    loTail.next = e;
                                loTail = e;
                            }
                            else {
                                //对于非0的key,其在新数组中的位置是需要更新的,需要存储在新增的数组中的一个新的位置,将其形成一个链条。
                                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;
    }

扩容避免1.7的出现的环形队列

JDK1.7高并发中出现环形队列的代码

void transfer(Entry[] newTable, boolean rehash) {
    int newCapacity = newTable.length;
    for (Entry<K,V> e : table) {
      while(null != e) {
        Entry<K,V> next = e.next;
        if (rehash) {
          e.hash = null == e.key ? 0 : hash(e.key);
        }
        //以下代码容易出现环形队列
        int i = indexFor(e.hash, newCapacity);
        e.next = newTable[i];
        newTable[i] = e;
        e = next;
      }
    }
  }

1.8解决这个问题

1、首先改头插法为尾插法

2、使用高位和低位Node节点来放不同位置的Node

 

线程不安全

putVal()

if ((p = tab[i = (n - 1) & hash]) == null)
//高并发情况下,如果A线程执行完 if 语句,恰好CPU将资源给了B线程,这时候B也走到newNode这一行,那么就会覆盖线程A的值
 tab[i] = newNode(hash, key, value, null); 

resize()

if (e.next == null)
//这里并没有判断当前索引位置是否存在节点,高并发情况下,假如put和resize同时进行,put的位置恰好是这个索引位置,那么oldNode就会覆盖这个新put的值
    newTab[e.hash & (newCap - 1)] = e;
原文地址:https://www.cnblogs.com/gyjx2016/p/12567703.html