JDK1.8 HashMap源码学习

时间:2020-07-12
本文章向大家介绍JDK1.8 HashMap源码学习,主要包括JDK1.8 HashMap源码学习使用实例、应用技巧、基本知识点总结和需要注意事项,具有一定的参考价值,需要的朋友可以参考一下。

HashMap

概念:key-value键值对,非线程安全,key可以为空,无序

底层:jdk1.7 数组+链表 jdk1.8数组+链表+红黑树

由来:数组的查找速度很快,但是插入和删除效率很低

链表的插入和删除的效率很低,但是查找速度很慢

HashMap,其查找速度近似O(1)。如何实现:使用了hash算法,将key映射成数组(桶bucket)下标。

key-hashCode-hash-i

如何解决hash碰撞(hash冲突)

  1. 增加扰动函数,减少冲突
  2. 冲突时,使用链地址法

 

源码学习

一些常量

    /**
     * The default initial capacity - MUST be a power of two.
     */
    //默认容量 
    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
    static final int MAXIMUM_CAPACITY = 1 << 30;

    /**
     * The load factor used when none specified in constructor.
     */
    //默认负载因子
    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.
     */
    //当链表长度大于8时,对链表进行树化
    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.
     */
    //当红黑树长度小于6时,将树转换为链表
    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.
     */
    // 链表树化时,hashmap的容量必须大于64
    static final int MIN_TREEIFY_CAPACITY = 64;/

  

hash函数

取key的hascCode,将低16位与高16位异或(相同为0,不同为1),增加hash的随机性,减少hash冲突,使key分布的更均匀

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

  

tableSizeFor

扩容时,计算hashMap容量的方法,计算hashmap的最小容量,hashmap的容量比为2的n次方

16-16

15-16

    /**
     * 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;
    }

  hashMap的内部变量

    /**
     * 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.)
     */
  //内部维护一个数组table,称作桶bucket。注意:不是所有元素都在table,存的是所有链表的头结点 transient Node<K,V>[] table; /** * Holds cached entrySet(). Note that AbstractMap fields are used * for keySet() and values(). */
  //所有元素 transient Set<Map.Entry<K,V>> entrySet; /** * The number of key-value mappings contained in this map. */
// hashMap的长度,区别与容量 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). */ 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.) int threshold; /** * The load factor for the hash table. * * @serial */ final float loadFactor;

  

hashMap的构造函数

典型的3个

  1. 指定容量和负载因子,阈值=大于容量的最小2的n次方
  2. 指定容量,负载因子=0.75f,阈值=大于容量的最小2的n次方
  3. 默认构造函数,负载因子=0.75。容量和阈值未初始化
    /**
     * 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
     */
    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);
    }

    /**
     * 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.
     */
    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).
     */
    public HashMap() {
        this.loadFactor = DEFAULT_LOAD_FACTOR; // all other fields defaulted
    }

  

根据key获取元素

 

tab[(n - 1) & hash通过hash计算元素在桶中的位置,比如容量n=16
hash = 1=>i=1
hash = 15=>i=15
hash = 16=>i=0
hash = 17=>i=1
first = tab[(n - 1) & hash = hash mod n
与操作效率大于mod操作,一个很小的优化
    public V get(Object key) {
        Node<K,V> e;
   //计算key的hash值 //根据key的hash值去table上遍历
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; if ((tab = table) != null && (n = tab.length) > 0 && //如果桶的第一元素的hash和key等于查找的元素,则返回 (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; //查找桶的下一个元素 if ((e = first.next) != null) { //first为树结构 if (first instanceof TreeNode) return ((TreeNode<K,V>)first).getTreeNode(hash, key); do { //first为链表,则查找链表 if (e.hash == hash && ((k = e.key) == key || (key != null && key.equals(k)))) return e; } while ((e = e.next) != null); } } return null; }

 插入元素

    public V put(K key, V value) {
        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;
//table为空,或者table长度为0,扩容 if ((tab = table) == null || (n = tab.length) == 0) n = (tab = resize()).length; //桶元素(数组上的第一个元素)为空,则直接新建一个Node并赋值到数组上 if ((p = tab[i = (n - 1) & hash]) == null) tab[i] = newNode(hash, key, value, null); else { Node<K,V> e; K k; //第一个元素不为空,但是hash和key值和插入元素相等,此时将第一个元素赋值给e if (p.hash == hash && ((k = p.key) == key || (key != null && key.equals(k)))) e = p; //第一个元素不为空,发生hash冲突,且第一个元素为树节点,此时将p节点插入到红黑树 else if (p instanceof TreeNode) e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value); else { //第一个元素不为空,发生hash冲突,且第一个元素为链表节点,此时将p节点插入到链表 for (int binCount = 0; ; ++binCount) { //不同于jdk1.7,这里使用尾插法,将p插入到链表的最后一个节点 if ((e = p.next) == null) { p.next = newNode(hash, key, value, null); //如果插入后,链表的长度>8(包括桶元素),则对链表进行树化 if (binCount >= TREEIFY_THRESHOLD - 1) // -1 for 1st treeifyBin(tab, hash); break; } //如果再链表中找到和插入元素相等的节点,则直接跳出循环 if (e.hash == hash && ((k = e.key) == key || (key != null && key.equals(k)))) break; p = e; } } //插入节点的Key在hashMap中已存在,则更新value if (e != null) { // existing mapping for key V oldValue = e.value; if (!onlyIfAbsent || oldValue == null) e.value = value; afterNodeAccess(e); return oldValue; } } ++modCount; //如果插入节点后,hashmap的容量大于阈值(13>12),则扩容 if (++size > threshold) resize(); afterNodeInsertion(evict); return null; }

  

扩容

    /**
     * Initializes or doubles table size.  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;
        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)
                newThr = oldThr << 1; // double threshold
        }
        else if (oldThr > 0) // initial capacity was placed in threshold
            newCap = oldThr;
        else {               // zero initial threshold signifies using defaults
            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"})
            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;
                if ((e = oldTab[j]) != null) {
                    oldTab[j] = null;
                    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
                        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;
    }

  

 

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