2021-10-20-HashMap源码详解

本文基于1.8的源码说明

DEFAULT_INITIAL_CAPACITY：初始化大小：16

MAXIMUM_CAPACITY：最大数组大小（最接近int最大值的2的n次冥）：1<<30

DEFAULT_LOAD_FACTOR：负载因子（数组占用率达到多少开始扩容/并不绝对，具体取决于扩容阈值 threshold）：0.75f

TREEIFY_THRESHOLD：由链表转为红黑树的阈值：8

UNTREEIFY_THRESHOLD：由红黑树转为链表的阈值：6

MIN_TREEIFY_CAPACITY：转红黑树时判断数组容量是否大于这个值，大于则转红黑树，小于则不转：64

static final int hash(Object key) ：hash散列算法，计算key的哈希值

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

static Class comparableClassFor(Object x)：

static int compareComparables(Class kc, Object k, Object x)：

static final int tableSizeFor(int cap)：是返回大于输入参数且最近的2的整数次幂的数（第一次使用是在有参构造时）

 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;
    }

final void putMapEntries(Map m, boolean evict)：

public V get(Object key)：根据key获取value

	public V get(Object key) {
        Node e;
        return (e = getNode(hash(key), key)) == null ? null : e.value;
    }

final Node getNode(int hash, Object key)：根据节点hash和key获取节点

final Node getNode(int hash, Object key) {
        Node[] tab; Node first, e; int n; K k;
        //节点不为空
        if ((tab = table) != null && (n = tab.length) > 0 &&
            (first = tab[(n - 1) & hash]) != null) {
            //判断首个节点是否是我们要寻找的key
            if (first.hash == hash && // always check first node
                ((k = first.key) == key || (key != null && key.equals(k))))
                return first;
            //第一个节点不是，则往下寻找
            if ((e = first.next) != null) {
            	//红黑树则执行红黑树的查找方法
                if (first instanceof TreeNode)
                    return ((TreeNode)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;
    }

public boolean containsKey(Object key)：判断是否存在该key

public boolean containsKey(Object key) {
        return getNode(hash(key), key) != null;
    }

public V put(K key, V value)：往hashMap里面存入键值对

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)：往hashMap里面存入键值对

final V putVal(int hash, K key, V value, boolean onlyIfAbsent,boolean evict) {
        Node[] tab; Node p; int n, i;
        //如果数组为null或者长度为0则扩容（此时表示为初始化之后第一次put）
        if ((tab = table) == null || (n = tab.length) == 0)
        	//n赋值为扩容后数组的长度
            n = (tab = resize()).length;
        //如果该节点为空，则直接插入（(n - 1) & hash 为计算数组下标算法）
        if ((p = tab[i = (n - 1) & hash]) == null)
            tab[i] = newNode(hash, key, value, null);
        else {
        	//如果该节点不为空，则需要在链表或者树后面添加节点
            Node e; K k;
            //节点的hash值相同，并且key值相同或者equlse()返回true，表示该key值以存在
            if (p.hash == hash &&
                ((k = p.key) == key || (key != null && key.equals(k))))
                e = p;
            else if (p instanceof TreeNode)
            	//如果节点是树节点，则调用树节点的put方法、并返回
                e = ((TreeNode)p).putTreeval(this, tab, hash, key, value);
            else {
            	//循环链表节点
                for (int binCount = 0; ; ++binCount) {
                	//如果某节点的next为空，说明该节点不存在，并且需要插入在该节点的next位置
                    if ((e = p.next) == null) {
                    	//插入
                        p.next = newNode(hash, key, value, null);
                        //判断bincount和树化阈值，大于等于8就树化
                        if (binCount >= TREEIFY_THRESHOLD - 1) // -1 for 1st
                        	//树化
                            treeifyBin(tab, hash);
                        break;
                    }
                    //和上面一样，判断key值是否相等，相等则表示已存在，直接返回
                    if (e.hash == hash &&
                        ((k = e.key) == key || (key != null && key.equals(k))))
                        break;
                    p = e;
                }
            }
            //表示该key的节点存在、e为插入的新节点或者已存在的该key的节点
            if (e != null) { // existing mapping for key
                V oldValue = e.value;
                //如果key值已存在，则替换该key的value
                if (!onlyIfAbsent || oldValue == null)
                    e.value = value;
                afterNodeAccess(e);
                return oldValue;
            }
        }
        //fail fast机制的操作数+1（链表或者树后面增加节点，该值不增加，不会导致fail fast）
        ++modCount;
        //size+1 map的size+1 并判断是否需要扩容
        if (++size > threshold)
            resize();
        afterNodeInsertion(evict);
        return null;
    }

final Node[] resize()：扩容方法

final Node[] resize() {
        Node[] oldTab = table;
        int oldCap = (oldTab == null) ? 0 : oldTab.length;
        int oldThr = threshold;
        int newCap, newThr = 0;
        //判断原来的数组是否是第一次扩容、大于0则不是
        if (oldCap > 0) {
        	//是否大于最大长度，如果大于，则将扩容阈值增加打int最大值
            if (oldCap >= MAXIMUM_CAPACITY) {
                threshold = Integer.MAX_VALUE;
                return oldTab;
            }
            //如果不大于，并且数组大于等于默认容量 则正常扩容、扩容一倍
            //如果新容量等于最大值了并且数组大于等于默认容量，则不进行新阈值x2操作，此时newThr等于0，否则进行
            else if ((newCap = oldCap << 1) < MAXIMUM_CAPACITY &&
                     oldCap >= DEFAULT_INITIAL_CAPACITY)
                newThr = oldThr << 1; // double threshold
        }
        //如果是第一次扩容，则判断是否是有参构造，如果是有参构造，直接将扩容阈值设置为新容量
        else if (oldThr > 0) // initial capacity was placed in threshold
            newCap = oldThr;
        //这里表示是第一次扩容，并且是无参构造、则将新容量，新阈值设置为默认值
        else {               // zero initial threshold signifies using defaults
            newCap = DEFAULT_INITIAL_CAPACITY;
            newThr = (int)(DEFAULT_LOAD_FACTOR * DEFAULT_INITIAL_CAPACITY);
        }
        //如果新阈值没赋值，则进行赋值操作
        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[] newTab = (Node[])new Node[newCap];
        table = newTab;
        //原数组不为空
        if (oldTab != null) {
            for (int j = 0; j < oldCap; ++j) {
                Node e;
                if ((e = oldTab[j]) != null) {
                    oldTab[j] = null;
                    if (e.next == null)
                    	//如果是单节点，则直接重新执行散列算法插入赋值
                        newTab[e.hash & (newCap - 1)] = e;
                    //如果是树节点，则执行树节点的插入操作
                    else if (e instanceof TreeNode)
                        ((TreeNode)e).split(this, newTab, j, oldCap);
                    //这个分支表示为链表节点
                    else { // preserve order
                        Node loHead = null, loTail = null;
                        Node hiHead = null, hiTail = null;
                        Node next;
                        //将原来的链表拆分为高位和低位两个链表
                        do {
                        	//next指向下一个
                            next = e.next;
                            //等于0为低位、低位head为lohead，循环结束直接赋值为此节点，高位相同
                            if ((e.hash & oldCap) == 0) {
                                if (loTail == null)
                                    loHead = e;
                                else
                                    loTail.next = e;
                                loTail = e;
                            }
                            //否则为高位
                            else {
                                if (hiTail == null)
                                    hiHead = e;
                                else
                                    hiTail.next = e;
                                hiTail = e;
                            }
                        } while ((e = next) != null);
                        //判断不为空则赋值，注意低位的下标不变，高位的下标为原来的下标+原来的容量
                        if (loTail != null) {
                            loTail.next = null;
                            newTab[j] = loHead;
                        }
                        if (hiTail != null) {
                            hiTail.next = null;
                            newTab[j + oldCap] = hiHead;
                        }
                    }
                }
            }
        }
        return newTab;
    }

final void treeifyBin(Node[] tab, int hash)：判断链表是否需要树化

final void treeifyBin(Node[] tab, int hash) {
        int n, index; Node e;
        //如果数组为空或者数组长度小于64则直接扩容
        if (tab == null || (n = tab.length) < MIN_TREEIFY_CAPACITY)
            resize();
        //节点不为空，则转红黑树
        else if ((e = tab[index = (n - 1) & hash]) != null) {
            TreeNode hd = null, tl = null;
            //hd为红黑树根节点，循环完毕直接赋值
            do {
                TreeNode p = replacementTreeNode(e, null);
                if (tl == null)
                    hd = p;
                else {
                    p.prev = tl;
                    tl.next = p;
                }
                tl = p;
            } while ((e = e.next) != null);
            //平衡等一些列后续操作，后续再学习
            if ((tab[index] = hd) != null)
                hd.treeify(tab);
        }
    }

public V remove(Object key)：移除节点

  public V remove(Object key) {
        Node e;
        return (e = removeNode(hash(key), key, null, false, true)) == null ?
            null : e.value;
    }

public boolean containsValue(Object value)：判断是否存在value

 public boolean containsValue(Object value) {
        Node[] tab; V v;
        if ((tab = table) != null && size > 0) {
            for (int i = 0; i < tab.length; ++i) {
                for (Node e = tab[i]; e != null; e = e.next) {
                    if ((v = e.value) == value ||
                        (value != null && value.equals(v)))
                        return true;
                }
            }
        }
        return false;
    }

public Set keySet()：获得key集合

   public Set keySet() {
        Set ks = keySet;
        if (ks == null) {
            ks = new KeySet();
            keySet = ks;
        }
        return ks;
    }

public Collection values()：获取value集合

public Collection values() {
        Collection vs = values;
        if (vs == null) {
            vs = new Values();
            values = vs;
        }
        return vs;
    }

public Set> entrySet()：获取键值对集合

public Set> entrySet() {
        Set> es;
        return (es = entrySet) == null ? (entrySet = new EntrySet()) : es;
    }

final Node removeNode(int hash, Object key, Object value,boolean matchValue, boolean movable)：移除节点

final Node removeNode(int hash, Object key, Object value,
                               boolean matchValue, boolean movable) {
        Node[] tab; Node p; int n, index;
        //节点不为空
        if ((tab = table) != null && (n = tab.length) > 0 &&
            (p = tab[index = (n - 1) & hash]) != null) {
            Node node = null, e; K k; V v;
            //如果第一个是要删除的key，直接删除
            if (p.hash == hash &&
                ((k = p.key) == key || (key != null && key.equals(k))))
                node = p;
            else if ((e = p.next) != null) {
            	//执行树的查找方法
                if (p instanceof TreeNode)
                    node = ((TreeNode)p).getTreeNode(hash, key);
                //否则是链表查找
                else {
                    do {
                        if (e.hash == hash &&
                            ((k = e.key) == key ||
                             (key != null && key.equals(k)))) {
                            node = e;
                            break;
                        }
                        p = e;
                    } while ((e = e.next) != null);
                }
            }
            //如果查找的节点不为空
            if (node != null && (!matchValue || (v = node.value) == value ||
                                 (value != null && value.equals(v)))) {
                if (node instanceof TreeNode)
                    ((TreeNode)node).removeTreeNode(this, tab, movable);
                else if (node == p)
                    tab[index] = node.next;
                else
                    p.next = node.next;
                ++modCount;
                --size;
                afterNodeRemoval(node);
                return node;
            }
        }
        return null;
    }