1. HashMap概览
- HashMap类定义
HashMap<K,V> extends AbstractMap<K,V> implements Map<K,V>
HashMap继承了AbstractMap同时实现了Map接口，说明HashMap同样具有2对修改操作 3个遍历操作，5个查询操作。本文的主要大概也将围绕这10个操作来讲解HashMap
- Node类
在Map接口中，定义了一个Entry
interface Entry<K,V> { K getKey(); V getValue(); V setValue(V value); }
在HashMap中定义了静态内部类Node来表示HashMap中键值对的数据结构
static class Node<K,V> implements Map.Entry<K,V> { final int hash;//key对应的hash值 final K key;//key是不可变的 V value; Node<K,V> next;//链表指向的下一个Node，是为了解决Hash冲突 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; } }
- HashMap内部数据结构
HashMap内部的基础数据结构是数组+链表/红黑树实现。数组的实现好处是支持随机访问，根据下标查询的时间复杂是o(1)。
transient Node<K,V>[] table;
4.根据key的hash值确定Node在table数组中的下标
计算hash值 static final int hash(Object key) { int h; return (key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 16); } 通过table的length&hash值确定下标 i = (n - 1) & hash]
2. Map接口详解
1. V put(K,V)
思路讲解
通过key计算hash值，并通过hash值确认在table数组中的位置i
如果table[i]==null,根据key value创建Node对象赋值给table[i]
如果table[i]!=null,通过next遍历table[i]上的Node。如果key相等替换Node，如果不相等，创建Node添加到链表最后面(这里不讲红黑树)
//V !!!!注意 返回的是原先的值 final V putVal(int hash, K key, V value, boolean onlyIfAbsent, boolean evict) { Node<K,V>[] tab; Node<K,V> p; int n, i; //如果table数组还没有初始化，通过resize()初始化 if ((tab = table) == null || (n = tab.length) == 0) n = (tab = resize()).length; //通过hash值定位到数组的下标，如果该位置上没有数据，创建node并赋值到该位置上 if ((p = tab[i = (n - 1) & hash]) == null) tab[i] = newNode(hash, key, value, null); else { //如果下标的位置上有数据 Node<K,V> e; K k; //如果位置上的hash值和key与要插入的Node相等，把节点赋值给e。后面会替换e的value if (p.hash == hash && ((k = p.key) == key || (key != null && key.equals(k)))) e = p; else if (p instanceof TreeNode) //如果节点已经红黑树化了，插入到红黑树中 e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value); else {//还是链表的形式存储 //遍历当前数组上的Node的链表 for (int binCount = 0; ; ++binCount) { //遍历到最后一个Node if ((e = p.next) == null) { //新建Node指向链表最后面 p.next = newNode(hash, key, value, null); //如果链表的长度超过了8 将链表红黑树化 if (binCount >= TREEIFY_THRESHOLD - 1) // -1 for 1st treeifyBin(tab, hash); break; } //如果遍历的过程发现了key相同的 if (e.hash == hash && ((k = e.key) == key || (key != null && key.equals(k)))) break; //条件不满足p指针往后移动 p = e; } } //对于已经存在的key替换value的值 if (e != null) { // existing mapping for key V oldValue = e.value; if (!onlyIfAbsent || oldValue == null) e.value = value; //afterNodeAccess(e)!!!注意这个方法LinkedHashMap会用到，在HashMap中是空实现 afterNodeAccess(e); return oldValue; } } ++modCount; //如果插入后数组大小超过设置的值 需要对数组扩容 if (++size > threshold) resize(); //hashMap是空实现 afterNodeInsertion(evict); return null; }
afterNodeAccess只在put后才会调整
红黑树化 这里暂时没看懂 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) //扩容 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);//双链表红黑树化 } }
2. V get(Object key)
思路讲解
通过key计算hash值,通过hash值获取数组的下标i
若果table[i]==null,返回null
如果table[i]!=null
判断table[i]的hash值和key是否和要查询的相等，如果相等返回。
如果不相等，如果节点是红黑树，通过红黑树遍历，如果是链表通过链表遍历。
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; }
3. int size()
public int size() { return size; }
4. boolean isEmpty()
public boolean isEmpty() { return size == 0; }
5. Set
public Set<Map.Entry<K,V>> entrySet() { Set<Map.Entry<K,V>> es; return (es = entrySet) == null ? (entrySet = new EntrySet()) : es; } final class EntrySet extends AbstractSet<Map.Entry<K,V>> { public final int size() { return size; } public final void clear() { HashMap.this.clear(); } public final Iterator<Map.Entry<K,V>> iterator() { return new EntryIterator();//主要是通过迭代器来实现遍历 } } final class EntryIterator extends HashIterator implements Iterator<Map.Entry<K,V>> { public final Map.Entry<K,V> next() { return nextNode(); } } abstract class HashIterator { Node<K,V> next; // next entry to return Node<K,V> current; // current entry int expectedModCount; // for fast-fail int index; // current slot HashIterator() { expectedModCount = modCount; Node<K,V>[] t = table; current = next = null; index = 0; if (t != null && size > 0) { // 遍历数组找到第一个不为null的Node do {} while (index < t.length && (next = t[index++]) == null); } } public final boolean hasNext() { return next != null; } final Node<K,V> nextNode() { Node<K,V>[] t; Node<K,V> e = next; if (modCount != expectedModCount) throw new ConcurrentModificationException(); if (e == null) throw new NoSuchElementException(); if ((next = (current = e).next) == null && (t = table) != null) {//先遍历链表,如果链表还有数据 do {} while (index < t.length && (next = t[index++]) == null);//再遍历数组 } return e; } public final void remove() { Node<K,V> p = current; if (p == null) throw new IllegalStateException(); if (modCount != expectedModCount) throw new ConcurrentModificationException(); current = null; K key = p.key; removeNode(hash(key), key, null, false, false); expectedModCount = modCount; } }
