HashMap的内部存储是以数组+链表+红黑树为组合的复合结构，数组(table)中元素是Entry，键值对(key-value)中key的hashCode值决定了Entry元素在数组中的位置，当发生hash冲突时，相同hash值的Entry元素组成链表，链表的长度是有定长的（TREEIFY_THRESHOLD=8），当链表触发链表树化，就会变成树形结构。 

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/**
     * 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.)
     */
    transient Node<K,V>[] table;
  • hash() 
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/**
     * 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.
     * 
     * 计算key.hashCode()并且移动高位到低位。由于数组使用2的幂次表示，变化仅仅在hash集合       
     * 的上方中这将总是发生碰撞（这其中的例子是Float的key集合在小的table中保持连续的数    
     * 字），所以我们应用高位向下移动的影响来作为转化。在速度、实用和为扩展上需要权衡，由于
     * 许多哈希集已经合理的分布（所以无需从移动位中受益），并且因为我们使用了树来处理容器中
     * 更大的冲突，因此我们仅以最简答单的方式对一些以为后的微bit进行XOR，以减少系统损耗，
     * 以及最高位的影响，否则由于table番位的限制，这些高位将永远不会在索引计算中使用。
     */
    static final int hash(Object key) {
        int h;
        return (key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 16);
    }

可以看到hash方法中将Object key计算出的hashCode右移了16位，这里的原因官方注释中已经很明了，这样做是为了将高位的信息在hash值进行计算索引中降低冲突的概率，因为在一些hash中低位可能会相同，所以这里移位来使得hash更加分布均匀。

  • 构造函数 
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/**
   * 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
  }

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

看到HashMap1.8中四个构造函数，主要就看第一个，两个入参initialCapacity是table数组的大小，默认值DEFAULT_INITIAL_CAPACITY=16，loadFactor负载因子用来控制扩容的阈值默认DEFAULT_LOAD_FACTOR=0.75f，就是当table的threshold到达0.75时触发table扩容。这里tableSizeFor(initialCapacity)方法是利用传入的初始化table容量转为2的幂次数。

  • put方法 
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/**
     * 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 <tt>key</tt>, or
     *         <tt>null</tt> if there was no mapping for <tt>key</tt>.
     *         (A <tt>null</tt> return can also indicate that the map
     *         previously associated <tt>null</tt> with <tt>key</tt>.)
     */
    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;
        if ((tab = table) == null || (n = tab.length) == 0)//（1）
            n = (tab = resize()).length;
        if ((p = tab[i = (n - 1) & hash]) == null)//（2）
            tab[i] = newNode(hash, key, value, null);
        else {//（3）
            Node<K,V> e; K k;
            if (p.hash == hash &&
                ((k = p.key) == key || (key != null && key.equals(k))))//（4）
                e = p;
            else if (p instanceof TreeNode)//（5）
                e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value);
            else {//（6）
                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))))//（7）
                        break;
                    p = e;
                }
            }
            if (e != null) { // existing mapping for key
                V oldValue = e.value;//（8）
                if (!onlyIfAbsent || oldValue == null)
                    e.value = value;
                afterNodeAccess(e);
                return oldValue;
            }
        }
        ++modCount;//（9）
        if (++size > threshold)//(10)
            resize();
        afterNodeInsertion(evict);
        return null;
    }

这里主要看putVal()方法。
（1）这里第一个if判断table是否为空，为空就利用resize方法初始化；
（2）第二个if判断如果当前根据hash跟到的table索引下为空就直接将Node对象放入table中；
（3）else下是hash发生碰撞；
（4）首先第一个if判断的是如果NewNode和table中位置的Node hash值和key都相同就直接可以看作是同一个Node，这里还有个场景是否用新put的values覆盖老的value，onlyIfAbsent为false或者老的value为空就要覆盖掉老值；
（5）else if判断如果是一个树结点就调用putTreeVal插入元素；
（6）else下循环遍历将p添加到链表尾部，如果这时达到链表最大阈值就需要调用treeifyBin方法进行树化；
（7）如果已经在链表中就braek掉；
（8）这里判断是否需要覆盖老数据。
（9）modCount保证并发访问，这里的put方法是线程不安全的，所以当modCount发现变化不一致就会抛出ConcurrentModificationException。 

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  final class KeySet extends AbstractSet<K> {
        public final int size()                 { return size; }
        public final void clear()               { HashMap.this.clear(); }
        public final Iterator<K> iterator()     { return new KeyIterator(); }
        public final boolean contains(Object o) { return containsKey(o); }
        public final boolean remove(Object key) {
            return removeNode(hash(key), key, null, false, true) != null;
        }
        public final Spliterator<K> spliterator() {
            return new KeySpliterator<>(HashMap.this, 0, -1, 0, 0);
        }
        public final void forEach(Consumer<? super K> action) {
            Node<K,V>[] tab;
            if (action == null)
                throw new NullPointerException();
            if (size > 0 && (tab = table) != null) {
                int mc = modCount;
                for (int i = 0; i < tab.length; ++i) {
                    for (Node<K,V> e = tab[i]; e != null; e = e.next)
                        action.accept(e.key);
                }
                if (modCount != mc)
                    throw new ConcurrentModificationException();
            }
        }
    }
```        

(10)这里对table扩容。

* resize方法  

``` java
/**
     * 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
     * 
     * 初始化或增加成两倍大的table，如果为空，则根据字段阈值中保持的初始容量目标进行分配。
     * 否则，因为我们使用的是2的幂，所以每个bin中的元素必须保持相同的索引，或者在新表中以2
     * 的幂偏移。
     */
    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) {//（1）
                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
                    //（2）
                        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;
    }

上面的代码基本都很好理解的，这里主要说两个点：
（1）这个位置是table变成两倍table的元素移动的操作，e.nex=null说明它就是一个元素不存在链和树直接根据e.hash & (newCap - 1)计算出它在新table中的位置并赋值；如果是树通过split方法复制树；
（2）这里比较重要的操作。这里是链表复制的过程，这里链表上的Node位置有两个场景，一种是不需要移动的Node形成链表还在老的index下，另一种是需要我们移动位置的Node形成新的链表复制到新的index下。这里为什么会有这个操作，因为index值的确定是根据Node.hash和cap-1取与获得的，那么在变成两倍table后讲道理每一个index都需要重新取计算，但是这里观察变成两倍table的原理其实每次threshold<<1（也就是二进制高位变成1），那么这样Node.hash和cap-1取与过程中发生变化的就只有高位是1的所以这里(e.hash & oldCap) == 0表示在变成两倍table后index不需要变化，如果需要变化那么index=老idnex+oldCap。

  • get方法 
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/**
     * Returns the value to which the specified key is mapped,
     * or {@code null} if this map contains no mapping for the key.
     *
     * <p>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.)
     *
     * <p>A return value of {@code null} does not <i>necessarily</i>
     * 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<K,V> 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<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;
    }

get方法相对简单直接通过key和hash取查找元素，如果是table中的first直接返回如果是tree从tree遍历g得到，如果是链表遍历拿到。

  • 总结
    hash()方法的关键是高位右移的操作，目的是为了使得hash趋于均匀分布，避免hash冲突（碰撞），在与table.length取与获得index时尽降低形成链
    put()方法完成table创建和初始化和新增Node，新增Node分三个场景直接放置在table[index]位置；形成链表的插入链表中，链表达到阈值形成红黑树
    resize()方法完成 两倍扩展以及扩展后的Node的重新放置，这里重要是巧妙的使用 (e.hash & oldCap) == 0来作为是否将老链表数据分开放置的处理，利用扩容和2的幂的关系进行操作