JAVA读源码之-HashMap

JAVA读源码之-HashMap

提交于 2021-01-11
本篇文章是类似笔记的形式。文笔写不好,而且会大量摘抄别人的文章。

  • 参考视频 https://www.bilibili.com/video/BV1LJ411W7dP?p=6
  • 参考文档 https://gitee.com/gu_chun_bo/java-construct/blob/d466640dc977a61433fecbbb069ffe7a56d46d1a/java%E9%9B%86%E5%90%88/HashMap.md

底层结构

数组+ 链表+ 红黑树

image

类图

image
image

内部结构

Node

HashMap中元素是通过 Node数组、Node链表、红黑树存储的。 Node起到承载数据的作用,也是通过Node实现链表的。


 /**
     * Basic hash bin node, used for most entries.  (See below for
     * TreeNode subclass, and in LinkedHashMap for its Entry subclass.)
     */
    static class Node implements Map.Entry {
        //可以理解为Hash地址。不过是经过扰动的Hash地址
        final int hash;
        // 也就是Map的key
        final K key;
        // 也就是Map的value 
        V value;
        // 链表结构。hash碰撞出现的话。会存到next中。 可以看上面的示意图。
        Node next;

        Node(int hash, K key, V value, Node 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;
        }
    }

类定义

public class HashMap extends AbstractMap implements Map, Cloneable, Serializable {}

AbstractMap :   抽抽象类。提供方法封装。 不过HashMap把大部分方法重写了。就不一一列举了。
Cloneable   :   克隆。
     - cloneable其实就是一个标记接口,只有实现这个接口后,然后在类中重写Object中的clone方法,然后通过类调用clone方法才能克隆成功,如果不实现这个接口,则会抛出CloneNotSupportedException(克隆不被支持)异常。
     - 相关联的知识还有深克隆和浅克隆
     - 设计模式 `原型模式` 就是依据 cloneable 接口实现的。感兴趣的可以看一下。
Serializable:   序列化

代码分析

常量


 /**
     * The default initial capacity - MUST be a power of two.
     *
     * 缺省table大小
     */
    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.
     *
     * table最大长度
     */
    static final int MAXIMUM_CAPACITY = 1 << 30;

    /**
     * The load factor used when none specified in constructor.
     *
     * 缺省负载因子大小
     */
    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.
     *
     * 树化阈值
     * 插入数据时,如果链表过长时,将链表转化为红黑树
     * 具体算法看代码
     */
    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.
     *
     * 树降级称为链表的阈值
     */
    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.
     *
     * 树化的另一个参数,当哈希表中的所有元素个数超过64时,才会允许树化
     */
    static final int MIN_TREEIFY_CAPACITY = 64;

重点

  • 数化

Todo

成员变量

transient java关键字。表示不序列化 百度百科


 /* ---------------- Fields -------------- */

    /**
     * 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.)
     *
     * 哈希表
     *
     * 什么时候初始化?
     * //延迟初始化逻辑,第一次调用putVal时会初始化hashMap对象中的最耗费内存的散列表
     *  if ((tab = table) == null || (n = tab.length) == 0)
     *       n = (tab = resize()).length;
     *
     */
    transient Node[] table;

    /**
     * Holds cached entrySet(). Note that AbstractMap fields are used
     * for keySet() and values().
     */
    transient Set> entrySet;

    /**
     * The number of key-value mappings contained in this map.
     * 当前哈希表中元素个数
     */
    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).
     *
     * 当前哈希表结构修改次数
     */
    transient int modCount;

    /**
     * The next size value at which to resize (capacity * load factor).
     *
     * 扩容阈值,当你的哈希表中的元素超过阈值时,触发扩容
     * @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.
     *
     * 负载因子
     *
     * threshold = capacity * loadFactor
     *
     * @serial
     */
    final float loadFactor;

构造方法

 /* ---------------- Public operations -------------- */

    /**
     * Constructs an empty HashMap with the specified initial
     * capacity and load factor.
     *
     * @param  initialCapacity the initial capacity 初始容量
     * @param  loadFactor      the load factor 负载因子
     * @throws IllegalArgumentException if the initial capacity is negative
     *         or the load factor is nonpositive
     */
    public HashMap(int initialCapacity, float loadFactor) {

        //其实就是做了一些校验
        //capacity必须是大于0 ,最大值也就是 MAX_CAP
        if (initialCapacity < 0)
            throw new IllegalArgumentException("Illegal initial capacity: " +
                    initialCapacity);
        if (initialCapacity > MAXIMUM_CAPACITY)
            initialCapacity = MAXIMUM_CAPACITY;

        //loadFactor必须大于0
        if (loadFactor <= 0 || Float.isNaN(loadFactor))
            throw new IllegalArgumentException("Illegal load factor: " +
                    loadFactor);

        this.loadFactor = loadFactor;
        this.threshold = tableSizeFor(initialCapacity);
    }

    /**
     * Constructs an empty HashMap 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 HashMap with the default initial capacity
     * (16) and the default load factor (0.75).
     */
    public HashMap() {
        this.loadFactor = DEFAULT_LOAD_FACTOR; // all other fields defaulted
    }

    /**
     * Constructs a new HashMap with the same mappings as the
     * specified Map.  The HashMap is created with
     * default load factor (0.75) and an initial capacity sufficient to
     * hold the mappings in the specified Map.
     *
     * @param   m the map whose mappings are to be placed in this map
     * @throws  NullPointerException if the specified map is null
     */
    public HashMap(Map m) {
        this.loadFactor = DEFAULT_LOAD_FACTOR;
        putMapEntries(m, false);
    }

    /**
     * Implements Map.putAll and Map constructor.
     *
     * @param m the map
     * @param evict false when initially constructing this map, else
     * true (relayed to method afterNodeInsertion).
     */
    final void putMapEntries(Map 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 e : m.entrySet()) {
                K key = e.getKey();
                V value = e.getValue();
                putVal(hash(key), key, value, false, evict);
            }
        }
    }


tableSizeFor

位运算(二进制,说实话看不懂)

   /**
     * Returns a power of two size for the given target capacity.
     * 作用:返回一个大于等于当前值cap的一个数字,并且这个数字一定是2的次方数
     *
     * cap = 10
     * n = 10 - 1 => 9
     * 0b1001 | 0b0100 => 0b1101
     * 0b1101 | 0b0011 => 0b1111
     * 0b1111 | 0b0000 => 0b1111
     *
     * 0b1111 => 15
     *
     * return 15 + 1;
     *
     * cap = 16
     * n = 16;
     * 0b10000 | 0b01000 =>0b11000
     * 0b11000 | 0b00110 =>0b11110
     * 0b11110 | 0b00001 =>0b11111
     * =>0b11111 => 31
     * return 31 + 1;
     *
     * 0001 1101 1100 => 0001 1111 1111 + 1 => 0010 0000 0000 一定是2的次方数
     *
     */
    static final int tableSizeFor(int cap) {
        int n = cap;
        n |= n >>> 1;
        n |= n >>> 2;
        n |= n >>> 4;
        n |= n >>> 8;
        n |= n >>> 16;
        
        // 套娃三目运算
        return (n < 0) ? 1 : (n >= MAXIMUM_CAPACITY) ? MAXIMUM_CAPACITY : n + 1;
    }

put方法

image
/**
     * Associates the specified value with the specified key in this map.
     * If the map previously contained a mapping for the key, the old
     * value is replaced.
     *
     * @param key key with which the specified value is to be associated
     * @param value value to be associated with the specified key
     * @return the previous value associated with key, or
     *         null if there was no mapping for key.
     *         (A null return can also indicate that the map
     *         previously associated null with key.)
     *   返回先前key对应的value值(如果value为null,也返回null),如果先前不存在这个key,那么返回的就是null;
     */
    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) {
        //tab:表示当前hashMap的散列表
        //p:表示当前散列表的元素
        //n:表示散列表数组的长度
        //i:表示路由寻址 结果
        Node[] tab; Node p; int n, i;

        //延迟初始化逻辑,第一次调用putVal时会初始化hashMap对象中的最耗费内存的散列表
        if ((tab = table) == null || (n = tab.length) == 0)
            n = (tab = resize()).length;

        //最简单的一种情况:寻址找到的桶位 刚好是 null,这个时候,直接将当前k-v=>node 扔进去就可以了
        if ((p = tab[i = (n - 1) & hash]) == null)
            tab[i] = newNode(hash, key, value, null);

        else {
            //e:不为null的话,找到了一个与当前要插入的key-value一致的key的元素
            //k:表示临时的一个key
            Node e; K k;

            //表示桶位中的该元素,与你当前插入的元素的key完全一致,表示后续需要进行替换操作
            if (p.hash == hash &&
                    ((k = p.key) == key || (key != null && key.equals(k))))
                e = p;

            else if (p instanceof TreeNode)//红黑树,下期讲。进QQ群:865-373-238
                e = ((TreeNode)p).putTreeVal(this, tab, hash, key, value);
            else {
                //链表的情况,而且链表的头元素与我们要插入的key不一致。
                for (int binCount = 0; ; ++binCount) {
                    //条件成立的话,说明迭代到最后一个元素了,也没找到一个与你要插入的key一致的node
                    //说明需要加入到当前链表的末尾
                    if ((e = p.next) == null) {
                        p.next = newNode(hash, key, value, null);
                        //条件成立的话,说明当前链表的长度,达到树化标准了,需要进行树化
                        if (binCount >= TREEIFY_THRESHOLD - 1) // -1 for 1st
                            //树化操作
                            treeifyBin(tab, hash);
                        break;
                    }
                    //条件成立的话,说明找到了相同key的node元素,需要进行替换操作
                    if (e.hash == hash &&
                            ((k = e.key) == key || (key != null && key.equals(k))))
                        break;
                    p = e;
                }
            }

            //e不等于null,条件成立说明,找到了一个与你插入元素key完全一致的数据,需要进行替换
            if (e != null) { // existing mapping for key
                V oldValue = e.value;
                if (!onlyIfAbsent || oldValue == null)
                    e.value = value;
                afterNodeAccess(e);
                return oldValue;
            }
        }

        //modCount:表示散列表结构被修改的次数,替换Node元素的value不计数
        ++modCount;
        //插入新元素,size自增,如果自增后的值大于扩容阈值,则触发扩容。
        if (++size > threshold)
            resize();
        afterNodeInsertion(evict);
        return null;
    }


hash 方法

  • 小知识。 key是null的话。那它一定是放在第0位。 (key == null) ? 0 :
  • 这就是前面有说的扰动方法,让key值算出的hash值更均匀,减少hash碰撞的几率。也就提高了性能。 hash碰撞多了,就会加快数据向链表转化,向树转化。

    /**
     * Computes key.hashCode() and spreads (XORs) higher bits of hash
     * to lower.  Because the table uses power-of-two masking, sets of
     * hashes that vary only in bits above the current mask will
     * always collide. (Among known examples are sets of Float keys
     * holding consecutive whole numbers in small tables.)  So we
     * apply a transform that spreads the impact of higher bits
     * downward. There is a tradeoff between speed, utility, and
     * quality of bit-spreading. Because many common sets of hashes
     * are already reasonably distributed (so don't benefit from
     * spreading), and because we use trees to handle large sets of
     * collisions in bins, we just XOR some shifted bits in the
     * cheapest possible way to reduce systematic lossage, as well as
     * to incorporate impact of the highest bits that would otherwise
     * never be used in index calculations because of table bounds.
     *
     * 作用:让key的hash值的高16位也参与路由运算
     * 异或:相同则返回0,不同返回1
     *
     * h = 0b 0010 0101 1010 1100 0011 1111 0010 1110
     * 0b 0010 0101 1010 1100 0011 1111 0010 1110
     * ^
     * 0b 0000 0000 0000 0000 0010 0101 1010 1100
     * => 0010 0101 1010 1100 0001 1010 1000 0010
     */
    static final int hash(Object key) {
        int h;
        return (key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 16);
    }

resize方法

重新计算大小。会涉及到链表转换和树化。也就是咱们说的自动扩容

  //插入新元素,size自增,如果自增后的值大于扩容阈值,则触发扩容。
  if (++size > threshold)
     resize();

    /**
     * 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.
     *
     * 为什么需要扩容?
     * 为了解决哈希冲突导致的链化影响查询效率的问题,扩容会缓解该问题。
     *
     * @return the table
     */
    final Node[] resize() {
        //oldTab:引用扩容前的哈希表
        Node[] oldTab = table;
        //oldCap:表示扩容之前table数组的长度
        int oldCap = (oldTab == null) ? 0 : oldTab.length;
        //oldThr:表示扩容之前的扩容阈值,触发本次扩容的阈值
        int oldThr = threshold;
        //newCap:扩容之后table数组的大小
        //newThr:扩容之后,下次再次触发扩容的条件
        int newCap, newThr = 0;

        //条件如果成立说明 hashMap中的散列表已经初始化过了,这是一次正常扩容
        if (oldCap > 0) {
            //扩容之前的table数组大小已经达到 最大阈值后,则不扩容,且设置扩容条件为 int 最大值。
            if (oldCap >= MAXIMUM_CAPACITY) {
                threshold = Integer.MAX_VALUE;
                return oldTab;
            }

            //oldCap左移一位实现数值翻倍,并且赋值给newCap, newCap 小于数组最大值限制 且 扩容之前的阈值 >= 16
            //这种情况下,则 下一次扩容的阈值 等于当前阈值翻倍
            else if ((newCap = oldCap << 1) < MAXIMUM_CAPACITY &&
                    oldCap >= DEFAULT_INITIAL_CAPACITY)
                newThr = oldThr << 1; // double threshold
        }

        //oldCap == 0,说明hashMap中的散列表是null
        //1.new HashMap(initCap, loadFactor);
        //2.new HashMap(initCap);
        //3.new HashMap(map); 并且这个map有数据
        else if (oldThr > 0) // initial capacity was placed in threshold
            newCap = oldThr;

        //oldCap == 0,oldThr == 0
        //new HashMap();
        else {               // zero initial threshold signifies using defaults
            newCap = DEFAULT_INITIAL_CAPACITY;//16
            newThr = (int)(DEFAULT_LOAD_FACTOR * DEFAULT_INITIAL_CAPACITY);//12
        }

        //newThr为零时,通过newCap和loadFactor计算出一个newThr
        if (newThr == 0) {
            float ft = (float)newCap * loadFactor;
            newThr = (newCap < MAXIMUM_CAPACITY && ft < (float)MAXIMUM_CAPACITY ?
                    (int)ft : Integer.MAX_VALUE);
        }

        threshold = newThr;

        //创建出一个更长 更大的数组
        @SuppressWarnings({"rawtypes","unchecked"})
        Node[] newTab = (Node[])new Node[newCap];
        table = newTab;

        //说明,hashMap本次扩容之前,table不为null
        if (oldTab != null) {

            for (int j = 0; j < oldCap; ++j) {
                //当前node节点
                Node e;
                //说明当前桶位中有数据,但是数据具体是 单个数据,还是链表 还是 红黑树 并不知道
                if ((e = oldTab[j]) != null) {
                    //方便JVM GC时回收内存
                    oldTab[j] = null;

                    //第一种情况:当前桶位只有一个元素,从未发生过碰撞,这情况 直接计算出当前元素应存放在 新数组中的位置,然后
                    //扔进去就可以了
                    if (e.next == null)
                        newTab[e.hash & (newCap - 1)] = e;

                    //第二种情况:当前节点已经树化,本期先不讲,下一期讲,红黑树。QQ群:865-373-238
                    else if (e instanceof TreeNode)
                        ((TreeNode)e).split(this, newTab, j, oldCap);
                    else { // preserve order
                        //第三种情况:桶位已经形成链表

                        //低位链表:存放在扩容之后的数组的下标位置,与当前数组的下标位置一致。
                        Node loHead = null, loTail = null;
                        //高位链表:存放在扩容之后的数组的下表位置为 当前数组下标位置 + 扩容之前数组的长度
                        Node hiHead = null, hiTail = null;

                        Node next;
                        do {
                            next = e.next;
                            //hash-> .... 1 1111
                            //hash-> .... 0 1111
                            // 0b 10000

                            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;
    }

get方法


    /**
     * Returns the value to which the specified key is mapped,
     * or {@code null} if this map contains no mapping for the key.
     *
     * 

More formally, if this map contains a mapping from a key * {@code k} to a value {@code v} such that {@code (key==null ? k==null : * key.equals(k))}, then this method returns {@code v}; otherwise * it returns {@code null}. (There can be at most one such mapping.) * *

A return value of {@code null} does not necessarily * indicate that the map contains no mapping for the key; it's also * possible that the map explicitly maps the key to {@code null}. * The {@link #containsKey containsKey} operation may be used to * distinguish these two cases. * * @see #put(Object, Object) */ public V get(Object key) { Node e; 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 getNode(int hash, Object key) { //tab:引用当前hashMap的散列表 //first:桶位中的头元素 //e:临时node元素 //n:table数组长度 Node[] tab; Node first, e; int n; K k; if ((tab = table) != null && (n = tab.length) > 0 && (first = tab[(n - 1) & hash]) != null) { //第一种情况:定位出来的桶位元素 即为咱们要get的数据 if (first.hash == hash && // always check first node ((k = first.key) == key || (key != null && key.equals(k)))) return first; //说明当前桶位不止一个元素,可能 是链表 也可能是 红黑树 if ((e = first.next) != null) { //第二种情况:桶位升级成了 红黑树 if (first instanceof TreeNode)//下一期说 return ((TreeNode)first).getTreeNode(hash, key); //第三种情况:桶位形成链表 do { if (e.hash == hash && ((k = e.key) == key || (key != null && key.equals(k)))) return e; } while ((e = e.next) != null); } } return null; }

remove方法



    /**
     * Removes the mapping for the specified key from this map if present.
     *
     * @param  key key whose mapping is to be removed from the map
     * @return the previous value associated with key, or
     *         null if there was no mapping for key.
     *         (A null return can also indicate that the map
     *         previously associated null with key.)
     */
    public V remove(Object key) {
        Node e;
        return (e = removeNode(hash(key), key, null, false, true)) == null ?
                null : e.value;
    }

    /**
     * Implements Map.remove and related methods.
     *
     * @param hash hash for key
     * @param key the key
     * @param value the value to match if matchValue, else ignored
     * @param matchValue if true only remove if value is equal
     * @param movable if false do not move other nodes while removing
     * @return the node, or null if none
     */
    final Node removeNode(int hash, Object key, Object value,
                               boolean matchValue, boolean movable) {
        //tab:引用当前hashMap中的散列表
        //p:当前node元素
        //n:表示散列表数组长度
        //index:表示寻址结果
        Node[] tab; Node p; int n, index;

        if ((tab = table) != null && (n = tab.length) > 0 &&
                (p = tab[index = (n - 1) & hash]) != null) {
            //说明路由的桶位是有数据的,需要进行查找操作,并且删除

            //node:查找到的结果
            //e:当前Node的下一个元素
            Node node = null, e; K k; V v;

            //第一种情况:当前桶位中的元素 即为 你要删除的元素
            if (p.hash == hash &&
                    ((k = p.key) == key || (key != null && key.equals(k))))
                node = p;


            else if ((e = p.next) != null) {
                //说明,当前桶位 要么是 链表 要么 是红黑树

                if (p instanceof TreeNode)//判断当前桶位是否升级为 红黑树了
                    //第二种情况
                    //红黑树查找操作,下一期再说
                    node = ((TreeNode)p).getTreeNode(hash, key);
                else {
                    //第三种情况
                    //链表的情况
                    do {
                        if (e.hash == hash &&
                                ((k = e.key) == key ||
                                        (key != null && key.equals(k)))) {
                            node = e;
                            break;
                        }
                        p = e;
                    } while ((e = e.next) != null);
                }
            }


            //判断node不为空的话,说明按照key查找到需要删除的数据了
            if (node != null && (!matchValue || (v = node.value) == value ||
                    (value != null && value.equals(v)))) {

                //第一种情况:node是树节点,说明需要进行树节点移除操作
                if (node instanceof TreeNode)
                    ((TreeNode)node).removeTreeNode(this, tab, movable);

                //第二种情况:桶位元素即为查找结果,则将该元素的下一个元素放至桶位中
                else if (node == p)
                    tab[index] = node.next;

                else
                    //第三种情况:将当前元素p的下一个元素 设置成 要删除元素的 下一个元素。
                    p.next = node.next;

                ++modCount;
                --size;
                afterNodeRemoval(node);
                return node;
            }
        }
        return null;
    }


replace方法



    @Override
    public boolean replace(K key, V oldValue, V newValue) {
        Node e; V v;
        if ((e = getNode(hash(key), key)) != null &&
                ((v = e.value) == oldValue || (v != null && v.equals(oldValue)))) {
            e.value = newValue;
            afterNodeAccess(e);
            return true;
        }
        return false;
    }

    @Override
    public V replace(K key, V value) {
        Node e;
        if ((e = getNode(hash(key), key)) != null) {
            V oldValue = e.value;
            e.value = value;
            afterNodeAccess(e);
            return oldValue;
        }
        return null;
    }

中文注释后的源码

链接 》

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