Hashtable常用特点区分:
1、extends Dictionary ；
2、线程安全；
3、key和value！=null；
4、默认容量11；负载因子0.75；
5、容量扩展old<<2+1.
/**
*
源码浅析
*/
//继承Dictionary实现Map, Cloneable, java.io.Serializable
public class Hashtable<K,V>
extends Dictionary<K,V>
implements Map<K,V>, Cloneable, java.io.Serializable
//4个构造，同HashMap一样
//第一个构造传入容量和负载因子
public Hashtable(int initialCapacity, float loadFactor) {
//传入容量不能小于0，
if (initialCapacity < 0)
throw new IllegalArgumentException("Illegal Capacity: "+
initialCapacity);
//负载因子不能小于等于0或者是非数
if (loadFactor <= 0 || Float.isNaN(loadFactor))
throw new IllegalArgumentException("Illegal Load: "+loadFactor);
//如果容量为0，则置为1，容量最小就是1
if (initialCapacity==0)
initialCapacity = 1;
this.loadFactor = loadFactor;
//table是以容量大小为初始大小的数组
table = new Entry[initialCapacity];
//临界值计算=容量乘以负载因子和当前系统数组最大长度加1的最小值，当达到临界值就需要扩容
threshold = (int)Math.min(initialCapacity * loadFactor, MAX_ARRAY_SIZE + 1);
initHashSeedAsNeeded(initialCapacity);
}
// 添加初始的容量，负载因子默认0.75
public Hashtable(int initialCapacity) {
this(initialCapacity, 0.75f);
}
// 容器默认11，负载因子默认0.75
public Hashtable() {
this(11, 0.75f);
}
// 初始容器取map最大尺寸*2和11取大的，也就是最小也是11，负载因子0.75
public Hashtable(Map<? extends K, ? extends V> t) {
this(Math.max(2*t.size(), 11), 0.75f);
//调用putAll将map中的数据加入hashtable中
putAll(t);
}
//Hashtable大部分方法属性都是加了同步锁,所以Hashtable是线程安全的
//返回所有key枚举对象
public synchronized Enumeration<K> keys() {
return this.<K>getEnumeration(KEYS);
}
//返回所有value枚举对象
public synchronized Enumeration<V> elements() {
return this.<V>getEnumeration(VALUES);
}
//判断Hashtable的值是否等于value
public synchronized boolean contains(Object value) {
/
/value不能等于null
if (value == null) {
throw new NullPointerException();
}
//遍历数组查找数组元素是否与value相等
Entry tab[] = table;
for (int i = tab.length ; i-- > 0 ;) {
for (Entry<K,V> e = tab[i] ; e != null ; e = e.next) {
if (e.value.equals(value)) {
return true;
}
}
}
return false;
}
//判断Hashtable是否包含传入key
public synchronized boolean containsKey(Object key) {
Entry tab[] = table;
//获取key的hash值
int hash = hash(key);
//计算在数组的索引
int index = (hash & 0x7FFFFFFF) % tab.length;
//找到key对应的链表,找出hash值和key值都相等的元素
for (Entry<K,V> e = tab[index] ; e != null ; e = e.next) {
if ((e.hash == hash) && e.key.equals(key)) {
return true;
}
}
return false;
}
//返回key对应的value,没有值得话返回null
public synchronized V get(Object key) {
Entry tab[] = table;
//计算key对应的hash值
int hash = hash(key);
//根据hash计算对应的索引
int index = (hash & 0x7FFFFFFF) % tab.length;
//根据索引找到对应的链表,在链表中查找hash值和key值都相等的元素
for (Entry<K,V> e = tab[index] ; e != null ; e = e.next) {
if ((e.hash == hash) && e.key.equals(key)) {
return e.value;
}
}
return null;
}
//调整Hashtable的长度,使其达到(oldCapacity << 1) + 1
protected void rehash() {
int oldCapacity = table.length;
Entry<K,V>[] oldMap = table;
// 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;
}
Entry<K,V>[] newMap = new Entry[newCapacity];
modCount++;
//临界值=新容量*负载因子和数组元素实际容量加1的min
threshold = (int)Math.min(newCapacity * loadFactor, MAX_ARRAY_SIZE + 1);
boolean rehash = initHashSeedAsNeeded(newCapacity);
table = newMap;
//将原有元素复制到新的Hashtable中
for (int i = oldCapacity ; i-- > 0 ;) {
for (Entry<K,V> old = oldMap[i] ; old != null ; ) {
Entry<K,V> e = old;
old = old.next;
if (rehash) {
e.hash = hash(e.key);
}
//计算新索引
int index = (e.hash & 0x7FFFFFFF) % newCapacity;
e.next = newMap[index];
newMap[index] = e;
}
}
}
//添加键值对
public synchronized V put(K key, V value) {
// value不等于null
if (value == null) {
throw new NullPointerException();
}
//若添加的key在Hashtable已经存在,则用新value覆盖原有的value
Entry tab[] = table;
int hash = hash(key);
int index = (hash & 0x7FFFFFFF) % tab.length;
for (Entry<K,V> e = tab[index] ; e != null ; e = e.next) {
if ((e.hash == hash) && e.key.equals(key)) {
V old = e.value;
e.value = value;
return old;
}
}
//若不存在键值等于key的键值对,+1
modCount++;
//如果Hashtable实际容量大于临界值,扩容
if (count >= threshold) {
// Rehash the table if the threshold is exceeded
rehash();
tab = table;
hash = hash(key);
index = (hash & 0x7FFFFFFF) % tab.length;
}
// Creates the new entry.
//将新的键值对插入对应数组索引为index的位置所在链表的表头.
Entry<K,V> e = tab[index];
tab[index] = new Entry<>(hash, key, value, e);
count++;
return null;
}
//删除键值为key的键值对
public synchronized V remove(Object key) {
Entry tab[] = table;
int hash = hash(key);
//计算索引
int index = (hash & 0x7FFFFFFF) % tab.length;
//因为是单链表,所以删除的时候要保留要删除节点的前一个节点
for (Entry<K,V> e = tab[index], prev = null ; e != null ; prev = e, e = e.next) {
if ((e.hash == hash) && e.key.equals(key)) {
modCount++;
if (prev != null) {
prev.next = e.next;
} else {
tab[index] = e.next;
}
count--;
V oldValue = e.value;
e.value = null;
return oldValue;
}
}
return null;
}
//多次调用put方法添加数据
public synchronized void putAll(Map<? extends K, ? extends V> t) {
for (Map.Entry<? extends K, ? extends V> e : t.entrySet())
put(e.getKey(), e.getValue());
}
//通过遍历数组的方式将数组元素key值置为null,value不理会
public synchronized void clear() {
Entry tab[] = table;
modCount++;
for (int index = tab.length; --index >= 0; )
tab[index] = null;
count = 0;
}
//克隆Hashtable
public synchronized Object clone() {
try {
//克隆一个相同的空Hashtable
Hashtable<K,V> t = (Hashtable<K,V>) super.clone();
t.table = new Entry[table.length];
//将原有元素一次克隆到相应位置
for (int i = table.length ; i-- > 0 ; ) {
t.table[i] = (table[i] != null)
? (Entry<K,V>) table[i].clone() : null;
}
//将延伸变量置空
t.keySet = null;
t.entrySet = null;
t.values = null;
t.modCount = 0;
return t;
} catch (CloneNotSupportedException e) {
// this shouldn't happen, since we are Cloneable
throw new InternalError();
}
}
//重写toString,遍历元素,生成{"key" = "value"},当长度达到最大值,结束
public synchronized String toString() {
int max = size() - 1;
if (max == -1)
return "{}";
StringBuilder sb = new StringBuilder();
Iterator<Map.Entry<K,V>> it = entrySet().iterator();
sb.append('{');
for (int i = 0; ; i++) {
Map.Entry<K,V> e = it.next();
K key = e.getKey();
V value = e.getValue();
sb.append(key == this ? "(this Map)" : key.toString());
sb.append('=');
sb.append(value == this ? "(this Map)" : value.toString());
if (i == max)
return sb.append('}').toString();
sb.append(", ");
}
}