简介
Hashtable since JDK1.0 ,比较老古董的玩意啦。跟早期版本的HashMap几乎一致,除了直接加 synchronized锁全表 来支持并发操作,并发高的情况下,性能较低。推荐ConcurrentHashMap,锁粒度更细,并发性能表现更优异。
数据结构
数组+链表。当key的hash值出现碰撞,也就是算出来的下标相同时,则用链表来存储数据。
源码
构造函数
可以指定初始容量、加载因子。默认初始容量11、加载因子0.75
public Hashtable() {
this(11, 0.75f);
}
public Hashtable(int initialCapacity) {
this(initialCapacity, 0.75f);
}
public Hashtable(int initialCapacity, float loadFactor) {
if (initialCapacity < 0)
throw new IllegalArgumentException("Illegal Capacity: "+
initialCapacity);
if (loadFactor <= 0 || Float.isNaN(loadFactor))
throw new IllegalArgumentException("Illegal Load: "+loadFactor);
if (initialCapacity==0)
initialCapacity = 1;
this.loadFactor = loadFactor;
// 初始化table
table = new Entry<?,?>[initialCapacity];
threshold = (int)Math.min(initialCapacity * loadFactor, MAX_ARRAY_SIZE + 1);
}
新增or修改
// synchronized 锁整个表
public synchronized V put(K key, V value) {
// 不允许value为空
// Make sure the value is not null
if (value == null) {
throw new NullPointerException();
}
// Makes sure the key is not already in the hashtable.
Entry<?,?> tab[] = table;
int hash = key.hashCode();
int index = (hash & 0x7FFFFFFF) % tab.length;
//存在则更新
@SuppressWarnings("unchecked")
Entry<K,V> entry = (Entry<K,V>)tab[index];
for(; entry != null ; entry = entry.next) {
if ((entry.hash == hash) && entry.key.equals(key)) {
V old = entry.value;
entry.value = value;
return old;
}
}
// 不存在则插入
addEntry(hash, key, value, index);
return null;
}
private void addEntry(int hash, K key, V value, int index) {
modCount++;
Entry<?,?> tab[] = table;
// 到达阀值
if (count >= threshold) {
// 扩容
// Rehash the table if the threshold is exceeded
rehash();
tab = table;
hash = key.hashCode();
index = (hash & 0x7FFFFFFF) % tab.length;
}
// 取出index的链表
// Creates the new entry.
@SuppressWarnings("unchecked")
Entry<K,V> e = (Entry<K,V>) tab[index];
// 创建Entry,并链接原链表。最后赋值tab[index]
tab[index] = new Entry<>(hash, key, value, e);
// 计数
count++;
}
查询节点
public synchronized V get(Object key) {
Entry<?,?> tab[] = table;
int hash = key.hashCode();
// 计算索引
int index = (hash & 0x7FFFFFFF) % tab.length;
// 遍历链表
for (Entry<?,?> e = tab[index] ; e != null ; e = e.next) {
if ((e.hash == hash) && e.key.equals(key)) {
return (V)e.value;
}
}
return null;
}
删除节点
public synchronized V remove(Object key) {
Entry<?,?> tab[] = table;
int hash = key.hashCode();
// 计算索引
int index = (hash & 0x7FFFFFFF) % tab.length;
@SuppressWarnings("unchecked")
Entry<K,V> e = (Entry<K,V>)tab[index];
// 遍历链表
for(Entry<K,V> prev = null ; e != null ; prev = e, e = e.next) {
if ((e.hash == hash) && e.key.equals(key)) {
modCount++;
// 链表断开删除节点的关联
if (prev != null) {
prev.next = e.next;
} else {
tab[index] = e.next;
}
count--;
V oldValue = e.value;
e.value = null;
// 返回删除节点的值
return oldValue;
}
}
// 不存在key的节点
return null;
}
扩容 rehash() 方法
protected void rehash() {
int oldCapacity = table.length;
Entry<?,?>[] oldMap = table;
// 新容量 = 2倍旧容量 + 1
// overflow-conscious code
int newCapacity = (oldCapacity << 1) + 1;
if (newCapacity - MAX_ARRAY_SIZE > 0) {
if (oldCapacity == MAX_ARRAY_SIZE)
// Keep running with MAX_ARRAY_SIZE buckets
return;
newCapacity = MAX_ARRAY_SIZE;
}
// 创建新容量表
Entry<?,?>[] newMap = new Entry<?,?>[newCapacity];
modCount++;
// 计算阀值
threshold = (int)Math.min(newCapacity * loadFactor, MAX_ARRAY_SIZE + 1);
table = newMap;
// 搬运旧表的数据到新表
for (int i = oldCapacity ; i-- > 0 ;) {
// 遍历链表
for (Entry<K,V> old = (Entry<K,V>)oldMap[i] ; old != null ; ) {
Entry<K,V> e = old;
old = old.next;
// 计算新表索引
int index = (e.hash & 0x7FFFFFFF) % newCapacity;
// hash冲突,转用链表存储
e.next = (Entry<K,V>)newMap[index];
newMap[index] = e;
}
}
}
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