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        HaspMap是Java集合框架中最重要、最常用的数据结构之一。其基于哈希表实现了Map接口，在Java1.8的版本中，其采用了“数组+链表+红黑树”的混合结构，底层代码如下：

transient Node<K,V>[] table;  // 哈希桶数组
static class Node<K,V> implements Map.Entry<K,V> {final int hash;final K key;V value;Node<K,V> next;/***各种方法的实现*/
}

其有一些重要的参数，分别是：

        1.`DEFAULT_INITIAL_CAPACITY = 1 << 4`：默认容量，初始值通常为16
        2.`MAXIMUM_CAPACITY = 1 << 30`：最大容量
        3. `DEFAULT_LOAD_FACTOR = 0.75f`：默认负载因子
        4. `TREEIFY_THRESHOLD = 8`：链表转红黑树阈值
        5. `UNTREEIFY_THRESHOLD = 6`：红黑树转链表阈值
        6.`MIN_TREEIFY_CAPACITY = 64`：最小树化容量

其有一些核心的方法，如 hash计算方法，put放入方法， resize扩容方法，get获取方法，实现的底层代码如下：

//hash计算方法
static final int hash(Object key) {int h;return (key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 16);
}//put放入方法
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) {Node<K,V>[] tab; Node<K,V> p; int n, i;// 1. 表为空则初始化if ((tab = table) == null || (n = tab.length) == 0)n = (tab = resize()).length;// 2. 计算索引位置，如果该位置为空则直接插入if ((p = tab[i = (n - 1) & hash]) == null)tab[i] = newNode(hash, key, value, null);else {Node<K,V> e; K k;// 3. 节点key已存在，直接覆盖valueif (p.hash == hash && ((k = p.key) == key || (key != null && key.equals(k))))e = p;// 4. 判断是否为树节点else if (p instanceof TreeNode)e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value);else {// 5. 遍历链表for (int binCount = 0; ; ++binCount) {if ((e = p.next) == null) {p.next = newNode(hash, key, value, null);// 链表长度大于8转换为红黑树if (binCount >= TREEIFY_THRESHOLD - 1)treeifyBin(tab, hash);break;}if (e.hash == hash && ((k = e.key) == key || (key != null && key.equals(k))))break;p = e;}}// 6. 写入valueif (e != null) {V oldValue = e.value;if (!onlyIfAbsent || oldValue == null)e.value = value;afterNodeAccess(e);return oldValue;}}++modCount;// 7. 超过最大容量就扩容if (++size > threshold)resize();afterNodeInsertion(evict);return null;
}
// resize扩容方法
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; // 双倍扩容}else if (oldThr > 0) // 初始容量设为阈值newCap = oldThr;else {               // 使用默认值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 {// 链表优化重hashNode<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;elseloTail.next = e;loTail = e;}else {if (hiTail == null)hiHead = e;elsehiTail.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获取方法
public V get(Object key) {Node<K,V> e;return (e = getNode(hash(key), key)) == null ? null : e.value;
}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) {// 检查第一个节点if (first.hash == hash && ((k = first.key) == key || (key != null && key.equals(k))))return first;if ((e = first.next) != null) {// 如果是树节点if (first instanceof TreeNode)return ((TreeNode<K,V>)first).getTreeNode(hash, key);// 遍历链表do {if (e.hash == hash && ((k = e.key) == key || (key != null && key.equals(k))))return e;} while ((e = e.next) != null);}}return null;
}

        由于HashMap在在多线程环境下没有采取同步措施，导致多个线程同时访问或修改同一个HashMap实例时可能会引发并发问题，且在修改HashMap时，修改操作会导致其内部数据结构状态不一致从而引发程序崩溃的问题，所以其是非线程安全的，所以在使用时需要考虑是否为多线程环境，防止出现问题