zoukankan      html  css  js  c++  java
  • HashMap源码

    继承类:AbstractMap
    实现接口:Map、Cloneable
    Map:将key-value映射为对象,接口取代了Dictionary类,
    AbstractMap实现了Map,减少实现Map接口时的工作量
    Cloneable实现此接口的类可以进行拷贝操作
     
    重要说明:
    1、异或操作:
    x是二进制数0101,y是二进制数1011;
    则x ^ y=1110
    2、每个键值对Node节点的hashCode=Objects.hashCode(key) ^ Objects.hashCode(value);(异或操作)
    3、判断两个键值Node节点相等的条件为:
    如果Node<K,V> A == Node<K,V> B,则返回true
    如果A节点继承了Map.Entry接口,并且A.key.equals(B.key) 并且A.value.equals(B.value) ,则返回true
     
    代码翻译:
    public class HashMap<K,V> extends AbstractMap<K,V>
        implements Map<K,V>, Cloneable, Serializable {
    
        初始大小16
        static final int DEFAULT_INITIAL_CAPACITY = 1 << 4; // aka 16
    
        最大容量2的30次方
        static final int MAXIMUM_CAPACITY = 1 << 30;
    
        容量扩大因子
        static final float DEFAULT_LOAD_FACTOR = 0.75f;
    
    
        哈希节点,节点中保存了key、value、hash、next节点值
        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;
            }
        }
    
        根据key计算hash值
        static final int hash(Object key) {
            int h;
            return (key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 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;
        }
    
        /* ---------------- Fields -------------- */
    
        初始化数组
        transient Node<K,V>[] table;
    
        已Set结构保存每个Map.Entry<K,V>节点
        transient Set<Map.Entry<K,V>> entrySet;
    
        Map大小
        transient int size;
    
        Map修改次数
        transient int modCount;
    
        size=(capacity * load factor)
        int threshold;
    
        哈希表的增长因子
        final float loadFactor;
    
    
        根据初始化容量以及增长因子构建空的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);
        }
    
        构建空的HasHMap,
        public HashMap(int initialCapacity) {
            this(initialCapacity, DEFAULT_LOAD_FACTOR);
        }
    
        构建空的HasHMap,增长因子=0.75
        public HashMap() {
            this.loadFactor = DEFAULT_LOAD_FACTOR; // all other fields defaulted
        }
    
        将指定Map对象保存到已存在的HashMap
        public HashMap(Map<? extends K, ? extends V> m) {
            this.loadFactor = DEFAULT_LOAD_FACTOR;
            putMapEntries(m, false);
        }
    
        将指定Map对象保存到已存在的HashMap
        final void putMapEntries(Map<? extends K, ? extends V> m, boolean evict) {
            int s = m.size();
            if (s > 0) {
                if (table == null) { // pre-size
                    float ft = ((float)s / loadFactor) + 1.0F;
                    int t = ((ft < (float)MAXIMUM_CAPACITY) ?
                             (int)ft : MAXIMUM_CAPACITY);
                    if (t > threshold)
                        threshold = tableSizeFor(t);
                }
                else if (s > threshold)
                    resize();
                for (Map.Entry<? extends K, ? extends V> e : m.entrySet()) {
                    K key = e.getKey();
                    V value = e.getValue();
                    putVal(hash(key), key, value, false, evict);
                }
            }
        }
    
    
        返回指定key的value或者返回null
        public V get(Object key) {
            Node<K,V> e;
            return (e = getNode(hash(key), key)) == null ? null : e.value;
        }
    
        hash相同并且key相等,则返回Node节点
        先获得table数组,从数组0开始遍历,
        判断每个数组的hash值与传入的hash是否相等(优先判断),并且key相等,则数组节点
        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;
        }
        
        //根据保存key与value,如果key已经存在,则value替换oldvalue
        public V put(K key, V value) {
            return putVal(hash(key), key, value, false, true);
        }
    
        
        根据public V put(K key, V value)方法调用putVal(hash(key), key, value, false, true)进行说明
        //保存key与value,对传入参数进一步说明:
            hash:key的hash值
            key:key值
            value:key对应的需要保存的值
            onlyIfAbsent:如果为true,表示已经存在key,则不替换oldvalue,如果为false,表示如果key已经存在,可以使用newValue替换oldValue
            evict:(先不考虑)
        final V putVal(int hash, K key, V value, boolean onlyIfAbsent,
                       boolean evict) {
            Node<K,V>[] tab; Node<K,V> p; int n, i;
            //数组对象为空,或者数组长度为0,设置新数组的长度
            if ((tab = table) == null || (n = tab.length) == 0)
                n = (tab = resize()).length;
            //key,value、hash创建Node节点,设置在tab[i]数组上
            //上一步骤n = tab.length中,n获得了当前数组的长度,
            //如果table数据为空或者长度为0,则会根据调用resize()重新初始化一个数组
            //如果根据hash在数组上找不到索引,则新建一个NewNode节点,并把NewNode节点复制到数组节点上
            if ((p = tab[i = (n - 1) & hash]) == null)
                tab[i] = newNode(hash, key, value, null);
            else {
                Node<K,V> e; K k;
                //如果hash、key都相等,则设置e节点=数组中p节点
                if (p.hash == hash &&
                    ((k = p.key) == key || (key != null && key.equals(k))))
                    e = p;
                else if (p instanceof TreeNode)
                    //如果p节点是TreeNode类型的节点,则调用TreeNode类下的putTreeVal方法进行设置key、value
                    e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value);
                else {
                    //如果p节点即不是数组上的节点,也不是TreeNode类型的节点,表示p为数组链表中的节点,
                    //循环数组后的链表,查找要找的节点(hash、key都相等的节点)
                    for (int binCount = 0; ; ++binCount) {
                        //如果最后节点的next为空,表示没有其他节点了,则新建一个newNode节点
                        if ((e = p.next) == null) {
                            p.next = newNode(hash, key, value, null);
                            if (binCount >= TREEIFY_THRESHOLD - 1) // -1 for 1st
                                treeifyBin(tab, hash);
                            break;
                        }
                        //如果查找到了hash、key都相等的节点,则把查找到的节点e复制给p节点
                        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;
        }
    
        重新设置数组大小
        final Node<K,V>[] resize() {
            Node<K,V>[] oldTab = table;
            //获得原有数组长度
            int oldCap = (oldTab == null) ? 0 : oldTab.length;
            //获得 临界值
            int oldThr = threshold;
            int newCap, newThr = 0;
            //如果临界值大于0,则新的数组长度等于临界值
            if (oldCap > 0) {
            //如果原数组长度大于0,并且原数组长度>(1 << 30),则返回原数组长度,同时临界值设置为Integer.MAX_VALUE
                if (oldCap >= MAXIMUM_CAPACITY) {
                    threshold = Integer.MAX_VALUE;
                    return oldTab;
                }
            //如果原数组长度大于0,并且原数组长度*2 小于Integer.MAX_VALUE 并且 原数组长度大于默认长度16(1<<4),则设置新的数组长度为原数组长度*2
                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
                //如果以上都不符合,则新的数组长度为10,新的临界值为默认长度10 * 默认因子0.75
                newCap = DEFAULT_INITIAL_CAPACITY;
                newThr = (int)(DEFAULT_LOAD_FACTOR * DEFAULT_INITIAL_CAPACITY);
            }
            //如果新的临界值==0,则如果新的数组长度小于Integer.MAX_VALUE并且 新的数组长度*默认因子小于Integer.MAX_VALUE,则新的临界值设置为新的数组长度*默认因子,否则设置为nteger.MAX_VALUE
            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"})
            //根据新的数组长度定义数组
                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;
                        //设置数组上的节点
                        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;
                                //这个逻辑不会触发,如果(e.hash & oldCap) == 0为true,则oldCap=0,表示数组为空
                                if ((e.hash & oldCap) == 0) {
                                    if (loTail == null)
                                        loHead = e;
                                    else
                                        loTail.next = e;
                                    loTail = e;
                                }
                                else {
                                    //按顺序把原数组节点中每个链表都复制到新数组每个节点的链表
                                    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;
        }
    
        /**
         * Replaces all linked nodes in bin at index for given hash unless
         * table is too small, in which case resizes instead.
         */
        final void treeifyBin(Node<K,V>[] tab, int hash) {
            int n, index; Node<K,V> e;
            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);
            }
        }
    
    
        根据执行key删除节点对象
        public V remove(Object key) {
            Node<K,V> e;
            return (e = removeNode(hash(key), key, null, false, true)) == null ?
                null : e.value;
        }
    
        
        具体说明 public V remove(Object key)方法调用时传递的参数:removeNode(hash(key), key, null, false, true)
        根据具体的节点信息删除Node
        传入参数说明:
            hash:key的hash值
            key:key值
            value:如果matchValue=true,则删除时需要匹配value与根据key和hash取出的value相等才删除
            matchValue:控制是否匹配value,如果为true,则value相等则删除
            movable:如果为false时,删除时不移动其他节点,如果为true,则删除节点时需要移动其他节点
        final Node<K,V> removeNode(int hash, Object key, Object value,
                                   boolean matchValue, boolean movable) {
            Node<K,V>[] tab; Node<K,V> p; int n, index;
            if ((tab = table) != null && (n = tab.length) > 0 &&
                (p = tab[index = (n - 1) & hash]) != null) {
                Node<K,V> node = null, e; K k; V v;
                //获取hash获得数组对应的节点判断hash、key是否相等,如果相等则把查找到的节点复制给node
                if (p.hash == hash &&
                    ((k = p.key) == key || (key != null && key.equals(k))))
                    node = p;
                else if ((e = p.next) != null) {
                    //如果节点是TreeNode类型的对象,根据hash和key获得TreeNode节点信息,把查找到的节点复制给node
                    if (p instanceof TreeNode)
                        node = ((TreeNode<K,V>)p).getTreeNode(hash, key);
                    else {
                    //如果不相等则进行do while循环判断,如果相等则把查找到的节点复制给node
                        do {
                            if (e.hash == hash &&
                                ((k = e.key) == key ||
                                 (key != null && key.equals(k)))) {
                                node = e;
                                break;
                            }
                            p = e;
                        } while ((e = e.next) != null);
                    }
                }
                如果查找到的节点不为空,在根据参数matchValue来控制是否需要进行值的校验
                if (node != null && (!matchValue || (v = node.value) == value ||
                                     (value != null && value.equals(v)))) {
                    if (node instanceof TreeNode)//针对查找的node是TreeNode类型的节点,则使用TreeNode下的removeTreeNode方法删除节点
                        ((TreeNode<K,V>)node).removeTreeNode(this, tab, movable);
                    else if (node == p)//针对查找到的node节点 等于 数组节点的情况
                        //如果查找到的node节点 等于 数组节点,则把数组节点设置为node节点的下一个节点
                        tab[index] = node.next;
                    else
                        //如果不是以上两种情况,则p的next节点设置为node的next节点,这样node节点就不在数组节点后的链表中了
                        p.next = node.next;
                    ++modCount;//HashMap操作次数加一
                    --size;//HashMap数量减一
                    afterNodeRemoval(node);//
                    return node;//返回被删除节点,如果没有则返回null
                }
            }
            return null;
        }
    
        //清空table数组
        public void clear() {
            Node<K,V>[] tab;
            modCount++;
            if ((tab = table) != null && size > 0) {
                size = 0;
                for (int i = 0; i < tab.length; ++i)
                    tab[i] = null;
            }
        }
    
        根据key、value必须与HashMap中完全匹配才可以删除节点数据数据
        public boolean remove(Object key, Object value) {
            return removeNode(hash(key), key, value, true, true) != null;
        }
    
        
        克隆HashMap的镜像,值不会克隆
        @SuppressWarnings("unchecked")
        @Override
        public Object clone() {
            HashMap<K,V> result;
            try {
                result = (HashMap<K,V>)super.clone();
            } catch (CloneNotSupportedException e) {
                // this shouldn't happen, since we are Cloneable
                throw new InternalError(e);
            }
            result.reinitialize();
            result.putMapEntries(this, false);
            return result;
        }
    
    }
     
    收藏文章数量从多到少与“把书读薄”是一个道理
  • 相关阅读:
    如何突破单库性能瓶颈?
    高性能数据库表该如何设计?
    高性能索引该如何设计?(下)
    高性能索引该如何设计?(上)
    MySQL体系结构与存储引擎
    动态ViewPager导航页面
    ViewPager图片轮转带点的
    手动图片横向轮播
    安卓布局中下拉列表框的实现
    安卓中adapter的应用
  • 原文地址:https://www.cnblogs.com/use-D/p/9595760.html
Copyright © 2011-2022 走看看