转自：https://blog.csdn.net/caoxiaohong1005/article/details/79909083
1.特性分析
说明：因为LinkedHashMap单词太长，所以以下都用LHM替代
- 基本数据结构：数组＋双向链表＋红黑树
- 因为继承HashMap，故常用属性和HashMap都一样。
- 对于几个node指针的分析：
- HashMap中的Map.Entry：只有next
- LinkedHashMap中的Entry：before，after，next。其中next指针因为继承Map.Entry得到
- HashMap和LinkedHashMap公有的TreeNode：left，right，parent，pre，before，after，next，后三个因为继承LinkedHashMap.Entry得到。
- 对“哈希表和双向链表都实现了Map接口”的理解
因为LHM中每一个entry在内存中只有一个，所以针对某一个entry，无论是哈希表中的节点还是双向链表中的节点都用的是同一个entry。通过继承Map.Entry，并添加指针before，after从而获得LHM的entry。因此得到上述结论。 - 双向链表种entry的排序
- 域accessOrder进行控制。
- false：构造函数的默认值，表示按照entry的插入顺序进行排序 ，故每插入一个新的entry则添加到双向链表的尾部。(注意：如果插入entry的key之前就存在双向链表中，则此次插入操作只会更改value，不会更改原双向链表各个entry的顺序)
- true：表示按entry的访问顺序进行排序，根据LRU原则，最新访问的entry排列在双链表的尾部。
- 默认为：按entry的插入顺序进行排序，故后插入的entry在双链表的尾部。
- 域accessOrder进行控制。
- LHM和TreeMap都实现了entry的排序，有什么区别：
- TreeMap按照key排序，而LHM按照entry的插入or访问顺序排序。
- 因为LHM保持entry有序的方式是调整双向链表的before，after指针，而TreeMap保持entry有序的方式是对tree结构作调整，因此显然LHM的代价更小。
- 特殊的构造函数LinkedHashMap(int,float,boolean)
- boolean=true时，迭代器顺序遵循LRU规则，最近最少访问的entry会被最先遍历到。这种Map非常适合构建LRU缓存。
- removeEldestEntry(Map.Entry)
- 通过覆写，可以实现：当添加新的映射到map中时,强制自动移除过期的映射.
- 过期数据：
- 双向链表按插入entry排序，则为最早插入双向链表的entry。
- 双向链表按访问entry排序，则为最近最少访问的entry。
- 和HashMap的比较
- 常规操作，如add,contains,remove等，比HashMap稍微差一些，因为需要维护双向链表。
- 视图迭代器执行时间长短的影响因素
- LHM：和size成比例
- HashMap：和capacity成比例
- 因此HashMap相对比较费时,因为size<=capacity。
- 非线程安全，元素允许为null
- 关于结构修改定义
和HashMap相比，添加了一种规定：在访问有序的LinkedHashMap中,影响LinkedHashMap迭代顺序的操作。比如get方法的调用就是一种结构性的更改.(因为访问有序的LinkedHashMap,在get访问一个元素后,,会对元素在链表中的位置产生影响,故结构会更改) - 3个特殊回调方法
- afterNodeRemoval，删除节点后，双向链表中unlink
- afterNodeInsertion，插入节点后，是否删除eldest节点
- afterNodeAccess，访问节点后，是否调整当前访问节点的顺序
- 这3个方法保证了双向链表的有序性。在HashMap中方法体为空，此处是进行了覆写。
- 调用了afterNodeRemoval的方法：
remove - 调用了afterNodeInsertion的方法：
put，computeIfAbsent，compute，merge - 调用了afterNodeAccess的方法：
put，computeIfAbsent，compute，merge，replace ，get，getOrDefault - 除去afterNodeAccess中的get，getOrDefault两个方法是在LHM中定义的，其它都是在HashMap中定义的。
- 为了清晰理解LHM插入节点后的结构，给出一个例子
- hash函数为：h(key)=key%8
- 依次插入元素：(k,v)对依次为：(1,11)，(2,12)，(3,13)，(9,19)，(17,27)
- 给出结构图：(图中node节点未写出value，只写了key)
2.code分析
import java.io.IOException;
import java.io.InvalidObjectException;
import java.io.Serializable;
import java.lang.*;
import java.lang.reflect.ParameterizedType;
import java.lang.reflect.Type;
import java.util.*;
import java.util.function.*;
import java.util.function.BiFunction;
import java.util.function.Consumer;
/**
* Created by caoxiaohong on 17/11/9 20:30.
*/
/**
* HashMap是实现了Map接口的哈希表.HashMap实现了map所有该有的操作.并且key和value都允许为null.
* (HashMap和HashTable唯一不同的是:前者是非线程安全的,后者是线程安全的.因此除去线程安全这一点,我们可以粗略的认为HashMap
* 和HashTable是等价的.)
* HashMap存储的元素是没有顺序性的;特别是:不能保证现有的顺序随着时间的推移不会发生变化.
*
* 如果哈希函数能够把存储的元素均匀的分配到各个bucket里面,那么get和put操作的时间性能都是常数级别的.
* 关于HashMap的迭代器,它的执行时间和两个因素有关,且成比例增长:
* (1)当前HashMap实例有几个bucket.
* (2)当前HashMap实例究竟存储了几个元素.
* 所以,如果在一个应用中经常用到迭代器的话,那么将HashMap实例的capacity设置的太大(也就是负载因子过低),这是不合理的.因为这会严重影响其性能.
*
* 有两个参数会影响HashMap实例的性能:(1)初始化capacity的大小.(2)负载因子的大小.
* capacity是指:哈希表拥有的bucket的数量.而初始化的capacity就是哈希表创建时的capacity.
* 负载因子是指:它其实是HashMap实例的capacity自动增长的指标.
* 当哈希表的条目超过了负载因子和capacity二者的乘积,哈希表会被rehash(也就是说,哈希表的内部数据结构会被重建),这样才能保证哈希表的bucket
* 的个数大约增长为之前的2倍大小.
*
* 通用规则是:默认的负载因子大小为0.75.这个数字是在时间和空间的损耗上面做了一个平衡的值.较大的负载因子虽然会提升空间利用率,
* 但是却提升了查找成本(查找成本在HashMap类中主要体现的操作就是get和put).当初始化一个HashMap的capacity的时候,条目的个数和负载因子
* 这两个因素都应该被考虑进去,从而尽量减少rehash的次数.如果初始化的capacity比最多条目数除以负载因子的值还大,那么rehash的操作
* 绝不会出现.
*
* 如果我们确定一定会在HashMap实例中存储很多的条目,那么在HashMap初始化时设置一个比较大的capacity要比设置一个小的capacity而让其
* 后期自动增长的效率高得多.
*
* 注意:HashMap类是非线程安全的.
* 如果多个线程同时操作一个HashMap实例,并且至少一个线程修改了HashMap实例的结构,要想实现线程安全,那么必须要有额外的措施来保证这一点.
* (结构修改是指:为HashMap实例add或者delete一个或者多个映射;仅仅更改某个已经存在的key对应的value值,这并不是结构的改变.)
* 这通常是通过同步一些map已经封装的对象,来实现线程同步的.
*
* 如果找不到map已经封装好的对象,那么就需要使用Collections.synchronizedMap的方法来包装map.
* 这一包装操作最好在创建HashMap实例的时候就完成,以防止在操作map的时候发生一些偶然的非线程安全的问题.
* 创建时的包装方式如下:
* Map m = Collections.synchronizedMap(new HashMap(...));
*
* 所有通过这个类的"集合视图方法"返回的迭代器:(如果通过迭代器遍历的过程中遇到问题,)都会尽可能早的抛出异常的.
* 也就说:如果HashMap实例在创建完迭代器后,无论以何种方式,只要其结构发生了改变,迭代器都会抛出异常ConcurrentModificationException,
* 当然唯一例外的情况就是:迭代器自己的remove方法,虽然会改变HashMap实例的结构,但是这并不会导致迭代器抛出异常.(为什么呢?通过
* 后面的源码,我们自然可以理解到.因为迭代器自己的remove方法,始终删除的HashMap实例上一次刚刚访问的元素,而且更新了下一次访问的游标,所以
* 这就保证了不用抛出异常.)
*
* 注意:迭代器的尽可能早的抛出异常的功能,并不是完全得到保障的.一般来讲,在出现了非线程安全的修改问题时,没有硬性保障一定会抛出异常.
* 迭代器尽可能早的抛出异常是说:它只是会尽力做到这一点.
* 因此,如果一个程序完全依赖于这一异常的正确性,这可能会出现问题:迭代器的这一功能只能用来去查找一些bug.
*
* @see Object#hashCode()
* @see Collection
* @see Map
* @see TreeMap
* @see Hashtable
* @since 1.2
*/
/**
* 类名分析:
* (1)继承类:AbstractMap<K,V>
* (2)实现接口:
* Map<K,V>:
* Cloneable:表示这个类可以调用Object的clone()方法,但是这个接口里面并没有提供任何方法,所以要想实现对象HashMap的浅拷贝,则需要在此类中
* 手动写出clone()方法的拷贝过程.
* Serializable:表示HashMap可以序列化,反序列化.
*/
public class HashMap<K,V> extends AbstractMap<K,V>
implements Map<K,V>, Cloneable, Serializable {
private static final long serialVersionUID = 362498820763181265L;
/**
* 变量定义了:HashMap初始化容量的大小为:16.
* 变量定义的特征:
* 1.static final类型;
* 2.默认大小必须为2的整数次幂;
*/
static final int DEFAULT_INITIAL_CAPACITY = 1 << 4; // aka 16
/**
* 变量定义了:HashMap初始化最大的容量.这个变量什么时候起作用呢?就是在初始化HashMap时,如果传入构造器中的参数>(1<<30),则初始化
* HashMap时,不能使用传入参数,而使用变量MAXIMUM_CAPACITY.
* 变量定义特征:
* 1.static final类型;
* 2.1<<30==1073741824;
*
*/
static final int MAXIMUM_CAPACITY = 1 << 30;
/**
* HashMap初始化时的默认负载因子为:0.75;
* 当然负载因子也可以在构造器参数中进行指定.
* 变量定义特征:
* 1.static final类型;
* 2.(0,1)的取值范围;
*/
static final float DEFAULT_LOAD_FACTOR = 0.75f;
/**
* 将链表转为红黑树的阈值
* 当一个元素在被添加时,如果链表中node的个数已经达到了8个,链表将转为红黑树形式.
* 这个值的设定必须大于2,且至少为8,显然源码中已经设定为8.原因是:
*/
static final int TREEIFY_THRESHOLD = 8;
/**
* 将红黑树转为链表的阈值
* 红黑树中node个数必须小于阈值.
* 阈值最大为6,这里阈值设定为6
*/
static final int UNTREEIFY_THRESHOLD = 6;
/**
* 桶被转为树的最小容量.
* (桶的结构变化方式有两种:resize方式+转为树)
* 为了避免桶的机构在选择变化方式时产生冲突,这一容量的设定值至少为32,那么可以看到在源码中已经设定这个值为64.
*/
static final int MIN_TREEIFY_CAPACITY = 64;
/**
* Basic hash bin node, used for most entries. (See below for
* TreeNode subclass, and in LinkedHashMap for its Entry subclass.)
* 基本哈希bin节点,用于大多数条目.
*
*/
static class Node<K,V> implements Map.Entry<K,V> {
final int hash;
final K key;
V value;
Node<K,V> next;
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; }
//条目的哈希值=key和value的哈希值求异或
public final int hashCode() {
return Objects.hashCode(key) ^ Objects.hashCode(value);
}
public final V setValue(V newValue) {
V oldValue = value;
value = newValue;
return oldValue;
}
//equals方法还是正常的判定
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;
}
}
/* ---------------- Static utilities 静态工具类-------------- */
/**
* 计算key的哈希值h,再将h和(h无符号右移16位)进行异或.因为table使用了2的整数次幂的掩码,所以在当前
* 掩码二进制位处的哈希值集合,总会发生碰撞.(在已知的例子中是Float键的集合,在小table中保持连续的整数)
* 所以我们采取了h>>>>16的措施,使得这种影响从高位转移到低位.为什么选择右移16位,而不是18位等等,这其实是在速度,实用性,
* 性能方面作出的一个权衡.因为很多哈希集合已经分配的很合理了(这样的哈希集合是不会从h>>>16位得到好处的),同时,因为
* 我们使用红黑树来处理容器中大量集合的碰撞问题,为了降低系统损耗,我们采用了最廉价的方式,即对更改的二进制位进行了异或操作,
* 同时消除了由于表边界而不会用于索引计算的最高位的影响.
*/
static final int hash(Object key) {
int h;
return (key == null) ? 0 : (h = key.hashCode()) ^ (h >>> 16);
}
/**
* 如果传入参数x实现了Comparable接口,则返回类x,否则返回null.
*/
static Class<?> comparableClassFor(Object x) {
if (x instanceof java.lang.Comparable) {
Class<?> c; Type[] ts, as; Type t; ParameterizedType p;
//如果x是String类型,则返回String
if ((c = x.getClass()) == String.class) // bypass checks
return c;
//如果c实现的接口不为空
if ((ts = c.getGenericInterfaces()) != null) {
for (int i = 0; i < ts.length; ++i) { //对实现接口进行遍历
if (((t = ts[i]) instanceof ParameterizedType) &&
((p = (ParameterizedType)t).getRawType() ==
java.lang.Comparable.class) &&
(as = p.getActualTypeArguments()) != null &&
as.length == 1 && as[0] == c) // type arg is c
return c;
}
}
}
return null;
}
/**
* Returns k.compareTo(x) if x matches kc (k's screened comparable
* class), else 0.
* 如果x和kc类型相同,则返回k.compareTo(x)结果;否则返回0.
*/
@SuppressWarnings({"rawtypes","unchecked"}) // for cast to Comparable
static int compareComparables(Class<?> kc, Object k, Object x) {
return (x == null || x.getClass() != kc ? 0 :
((java.lang.Comparable)k).compareTo(x));
}
/**
* Returns a power of two size for the given target capacity.
* 返回一个2倍capacity的整数次幂.
* 这是一个static final类型的变量
*/
static final int tableSizeFor(int cap) {
int n = cap - 1;
n |= n >>> 1;
n |= n >>> 2;
n |= n >>> 4;
n |= n >>> 8;
n |= n >>> 16;
return (n < 0) ? 1 : (n >= MAXIMUM_CAPACITY) ? MAXIMUM_CAPACITY : n + 1;
}
/* ---------------- Fields 域-------------- */
/**
* table在第一次使用时,进行初始化,如果有必要会有resize的操作.
* 当分配好大小后,table的大小总是2的整数次幂.
* (我们还允许在某些操作中允许长度为零,以允许当前不需要的引导机制)
*
* transient类型变量,序列化时,table=null
*/
transient Node<K,V>[] table;
/**
* 保存缓存的entrySet（）。请注意，AbstractMap字段用于keySet（）和values（）
* 序列化时,entrySet=null
*/
transient Set<Map.Entry<K,V>> entrySet;
/**
* map中键值对的个数
* 序列化时,size没有值
*/
transient int size;
/**
* map结构的更改次数.结构更改是:键值对个数发生改变 or 其它改变map内部结构的操作,如resize时.
* 这又是一个transient类型的域
*/
transient int modCount;
/**
* 下一次resize的阈值大小:阈值=map容量*负载因子.(threshold=capacity*load factor)
*/
int threshold;
/**
* 哈希表的负载因子
* final类型字段,构造器给定后,不可更改
* @serial
*/
final float loadFactor;
/* ---------------- Public operations -------------- */
/**
* public实例构造器,参数指定了:map初始化时的容量+负载因子
*/
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);
}
/**
* public实例构造器,参数指定:初始容量.
* 通过调用上面的构造函数,负载因子为默认的0.75
*/
public HashMap(int initialCapacity) {
this(initialCapacity, DEFAULT_LOAD_FACTOR);
}
/**
* public实例构造器,无参数.
* 默认的初始化容量为16 && 负载因子为默认的0.75
*/
public HashMap() {
this.loadFactor = DEFAULT_LOAD_FACTOR; // all other fields defaulted
}
/**
* 创建一个新的HashMap,并用参数m来初始化其键值对.
* 这个新的map负载因子为0.75,容量大小:以足够存放键值对为目标.
*/
public HashMap(Map<? extends K, ? extends V> m) {
this.loadFactor = DEFAULT_LOAD_FACTOR;
putMapEntries(m, false);//调用的就是下面的方法
}
/**
* 这一方法实现了Map.putAll和Map构造器的功能.
* 当初始化map时,evict值为false,其它时候为true.
* 这是一个final类型的方法
*/
final void putMapEntries(Map<? extends K, ? extends V> m, boolean evict) {
//传入map中键值对的个数
int s = m.size();
//如果m中有键值对
if (s > 0) {
//如果table为null
if (table == null) { // pre-size
//初始化容量为ft=s/loadFactor+1.
float ft = ((float)s / loadFactor) + 1.0F;
//如果ft>MAXIMUM_CAPACITY,则令t=MAXIMUM_CAPACITY;否则令t=ft.
int t = ((ft < (float)MAXIMUM_CAPACITY) ?
(int)ft : MAXIMUM_CAPACITY);
//如果t>阈值,更改阈值.将阈值更改为2t的整数次幂.
if (t > threshold)
threshold = tableSizeFor(t);
}
//如果m中键值对个数>阈值
else if (s > threshold)
resize();
for (Map.Entry<? extends K, ? extends V> e : m.entrySet()) {
K key = e.getKey();
V value = e.getValue();
putVal(hash(key), key, value, false, evict);
}
}
}
//不解释
public int size() {
return size;
}
//不解释
public boolean isEmpty() {
return size == 0;
}
/**
* 就是map的get(key)方法.
* 返回结果2种情况:null 或者 某个具体值.
* 唯一需要注意的是:返回结果为null并不是说map中没有对应key的映射,因为HashMap中key和value都允许为null.
* 这可能key本来对应的value就是null.
* 如果区分到底是不存在这样的映射?还是说key对应的value就是null?-->containsKey()方法可以解决这个问题.
*/
public V get(Object key) {
Node<K,V> e;
//调用了getNode方法,参数为:key的哈希值和key
return (e = getNode(hash(key), key)) == null ? null : e.value;
}
/**
* 实现Map.get()及相关算法.
* final类型方法.包级私有
*/
final Node<K,V> getNode(int hash, Object key) {
Node<K,V>[] tab; Node<K,V> first, e; int n; K k;
//赋值:tab=table & n=tab.length & first=tab[(n - 1) & hash]]
//table不为空 & table长度>0 & table[(n - 1) & hash]]!=null
if ((tab = table) != null && (n = tab.length) > 0 &&
(first = tab[(n - 1) & hash]) != null) {
//总是先检查first节点是否符合条件,这是从性能角度出发的,这一点要注意
if (first.hash == hash && // always check first node
((k = first.key) == key || (key != null && key.equals(k))))
return first;
//e=first.next节点
//next节点不为空
if ((e = first.next) != null) {
//如果first节点为红黑树节点,则采用红黑树的查找方式去找key对应的value,并返回
if (first instanceof TreeNode)
return ((TreeNode<K,V>)first).getTreeNode(hash, key);
//如果first节点为链表节点,则顺序查找key对应的value.
do {
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k))))
return e;
} while ((e = e.next) != null);
}
}
return null;
}
/**
* 如果map中包含对应的映射,则返回true;否则false.
*/
public boolean containsKey(Object key) {
return getNode(hash(key), key) != null;
}
/**
* map的put操作,如果map中已经有了key,则key对应的原来的value会被替换掉.
* 调用了下面的final类型方法.
*/
public V put(K key, V value) {
return putVal(hash(key), key, value, false, true);
}
/**
* 实现了map.put()及其相关的方法.
* @param onlyIfAbsent 为true时,则不覆盖key对应的value值,但是put在调用这个方法时,赋值false,说明覆盖原始value.
* @param evict 为false时,table处于创建模式.
*/
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为null,或者table.length==0,通过调用resize()方法为table初始化大小.
* tab=table或者tab = resize();
* n=tab.length 或者 n=(tab = resize()).length
*/
if ((tab = table) == null || (n = tab.length) == 0)
n = (tab = resize()).length;
/**如果first节点为null,则为tab[first=i]赋值.
* p=tab[i = (n - 1) & hash]
*/
if ((p = tab[i = (n - 1) & hash]) == null)
tab[i] = newNode(hash, key, value, null);
else {
Node<K,V> e; K k;
//如果p节点和插入节点的hash和key相同,则e=p.
if (p.hash == hash &&
((k = p.key) == key || (key != null && key.equals(k))))
e = p;
//如果p是红黑树节点,调用红黑树节点插入法.
else if (p instanceof TreeNode)
e = ((TreeNode<K,V>)p).putTreeVal(this, tab, hash, key, value);
//如果p为链表节点
else {
for (int binCount = 0; ; ++binCount) {
//链表结尾处插入节点
if ((e = p.next) == null) {
p.next = newNode(hash, key, value, null);
//如果链表节点个数到达在插入新的节点后,达到转为红黑树的阈值,则还需要将此链表转为红黑树.
if (binCount >= TREEIFY_THRESHOLD - 1) // -1 for 1st
treeifyBin(tab, hash);
break;
}
//如果插入节点和原链表中的某个key具有相同的hash且key相同,停止查找.
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k))))
break;
p = e;
}
}
if (e != null) { // existing mapping for key
V oldValue = e.value;
//替换原value值
if (!onlyIfAbsent || oldValue == null)
e.value = value;
afterNodeAccess(e);
return oldValue;
}
}
//map结构更改次数+1
++modCount;
//键值对个数>阈值,更新table容量为原来2倍.这说明,HashMap扩容为原来2倍.
if (++size > threshold)
resize();
afterNodeInsertion(evict);
return null;
}
/**
* 初始化table的大小或者将table的大小增大为两倍.
* 如果table==null,将table的大小设置为指定阈值threshold大小;
* 否则,因为我们使用的增长策略是2的整数次幂方式,table的容量在更改时,同一元素在table中的索引要么不变,要么移动到相对原位置
* 而言,距离2的整数次幂的一个位置.
* 最终返回table.
*/
final Node<K,V>[] resize() {
Node<K,V>[] oldTab = table;
int oldCap = (oldTab == null) ? 0 : oldTab.length;
int oldThr = threshold;
int newCap, newThr = 0;
//如果原map容量>0
if (oldCap > 0) {
//如果原容量>=最大容量,更改阈值为Integer最大值,并返回原table,程序停止执行.
if (oldCap >= MAXIMUM_CAPACITY) {
threshold = Integer.MAX_VALUE;
return oldTab;
}
//为新阈值赋值:oldThr << 1
else if ((newCap = oldCap << 1) < MAXIMUM_CAPACITY &&
oldCap >= DEFAULT_INITIAL_CAPACITY)
newThr = oldThr << 1; // double threshold
}
//如果原阈值>0
else if (oldThr > 0) // initial capacity was placed in threshold
//新阈值=原阈值
newCap = oldThr;
else { // zero initial threshold signifies using defaults
newCap = DEFAULT_INITIAL_CAPACITY;
newThr = (int)(DEFAULT_LOAD_FACTOR * DEFAULT_INITIAL_CAPACITY);
}
//如果新阈值==0
if (newThr == 0) {
//ft为新阈值
float ft = (float)newCap * loadFactor;
//新阈值赋值
newThr = (newCap < MAXIMUM_CAPACITY && ft < (float)MAXIMUM_CAPACITY ?
(int)ft : Integer.MAX_VALUE);
}
//table阈值赋值
threshold = newThr;
@SuppressWarnings({"rawtypes","unchecked"})
Node<K,V>[] newTab = (Node<K,V>[])new Node[newCap];
//table赋值
table = newTab;
//如果原table不为null
if (oldTab != null) {
//遍历旧table各个bucket
for (int j = 0; j < oldCap; ++j) {
Node<K,V> e;
//如果原table[j]!=null
if ((e = oldTab[j]) != null) {
//将原table[j]处置为null,释放空间.
oldTab[j] = null;
//如果e无后继节点
if (e.next == null)
//将e值付给新table的e对应的first节点
newTab[e.hash & (newCap - 1)] = e;
//e如果为红黑树类型节点
else if (e instanceof TreeNode)
//重构红黑树结构,到新table中
((TreeNode<K,V>)e).split(this, newTab, j, oldCap);
//e如果为链表节点
else { // preserve order
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;
}
/**
* 将桶数组table转为红黑树.
*/
final void treeifyBin(Node<K,V>[] tab, int hash) {
int n, index; Node<K,V> e;
//如果table为空或者桶数组table太小,不符合转为红黑树的条件.
if (tab == null || (n = tab.length) < MIN_TREEIFY_CAPACITY)
//桶数组table扩容
resize();
//如果符合转为红黑树的条件,且hash对应的桶不为null
else if ((e = tab[index = (n - 1) & hash]) != null) {
TreeNode<K,V> hd = null, tl = null;
//遍历链表
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);
}
}
//将指定m中的键值对映射到调用putAll方法的map中.如果key有重复,则value值被覆盖.
public void putAll(Map<? extends K, ? extends V> m) {
putMapEntries(m, true);
}
//删除指定key的条目
public V remove(Object key) {
Node<K,V> e;
/**
* null:显然传入的value=null,说明需要忽略value,所以matchValue必定为false.
* true:删除当前节点时,会移动其它节点.
*/
return (e = removeNode(hash(key), key, null, false, true)) == null ?
null : e.value;
}
/**
* Map.remove方法及其相关方法的实现
* @param matchValue 如果为true,则删除一个node的条件是:key和value都一致,才删除.
* @param movable 如果为false,则删除当前节点时,不会移动其它节点.
*/
final Node<K,V> removeNode(int hash, Object key, Object value,
boolean matchValue, boolean movable) {
Node<K,V>[] tab; Node<K,V> p; int n, index;
/**如果table不为null 且 table.leng>0 且 table[first]!=null
* 赋值:tab=table & n=tab.length & p=tab[first] & index=first
* first=(n-1) & hash :这个索引到底是什么?其实就是key在table的下标.所以如果如果tab[index]=null,说明
* 这个索引值处没有存储元素,也就是table中未存储这个索引值的任何node,故不需要再往下查找啦,直接返回null.
*/
if ((tab = table) != null && (n = tab.length) > 0 &&
(p = tab[index = (n - 1) & hash]) != null) {
Node<K,V> node = null, e; K k; V v;
/**
* 这里的写法和插入node写法一致.首先检查bucket中第一个node是否符合条件,也就是检查p是否符合条件;
* 如果p(=tab[index])的hash和key都一致,则node=p;
*/
if (p.hash == hash &&
((k = p.key) == key || (key != null && key.equals(k))))
node = p;
//如果p后面有节点,即hash值相同的节点个数>1
else if ((e = p.next) != null) {
//如果p节点类型为红黑树节点,则调用红黑树节点的查找方法.
if (p instanceof TreeNode)
node = ((TreeNode<K,V>)p).getTreeNode(hash, key);
//如果p节点为链表节点,则顺序查找链表节点
else {
do {
if (e.hash == hash &&
((k = e.key) == key ||
(key != null && key.equals(k)))) {
node = e;
break;
}
p = e;
} while ((e = e.next) != null);
}
}
/**如果找到指定hash的node,且保证删除策略matchValue,则可以删除.
* 1.matchValue=true,需要根据value是否一致来确定是否删除;
* 2.matchValue=false,则删除.
*/
if (node != null && (!matchValue || (v = node.value) == value ||
(value != null && value.equals(v)))) {
//node类型为红黑树节点,调用红黑树节点删除方法.
if (node instanceof TreeNode)
((TreeNode<K,V>)node).removeTreeNode(this, tab, movable);
/**p:需要被删除节点node的前驱
* 如果p节点和node节点是同一个,更改bucket中的值/
* buckt=tab[index]=node--->node.next
*/
else if (node == p)
tab[index] = node.next;
//直接更改链接指针,则删除node节点.
else
p.next = node.next;
//结构更改次数+1
++modCount;
//键值对个数-1
--size;
//回调函数
afterNodeRemoval(node);
//返回删除节点
return node;
}
}
return null;
}
/**
* 删除map中所有的键值对.此方法调用后,map实例将为null,因为方法中对tab[i]=null的赋值
*/
public void clear() {
Node<K,V>[] tab;
modCount++;
if ((tab = table) != null && size > 0) {
size = 0;
//注意:tab[i]=null,则告诉jvm可以对table的内存进行回收,同时table也不再拥有其内存空间.
for (int i = 0; i < tab.length; ++i)
tab[i] = null;
}
}
/**
* 这个方法没啥好说的
*/
public boolean containsValue(Object value) {
Node<K,V>[] tab; V v;
if ((tab = table) != null && size > 0) {
for (int i = 0; i < tab.length; ++i) {
for (Node<K,V> e = tab[i]; e != null; e = e.next) {
if ((v = e.value) == value ||
(value != null && value.equals(v)))
return true;
}
}
}
return false;
}
/**
* 返回map中key的集合视图.
* 这一集合由map做后台支撑,因此map中key的更改会影响key的Set集合,反之亦然.
* 如果在key的集合迭代过程中,map中key被更改了,会产生什么结果并未定义.
* 这一set支持删除元素,通过Iterator.remove(), Set.remove(),
* removeAll(), retainAll(), clear()方法,会从map中删除整个条目.
* 这一set不支持add()和addAll()方法.
*/
public Set<K> keySet() {
Set<K> ks = keySet;
if (ks == null) {
ks = new KeySet();
keySet = ks;
}
return ks;
}
/**继承于set骨架实现的内部final类
*/
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(java.util.function.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();
}
}
}
/**
* 获取map中values的一个Collection视图.
* 这个collection是以map作为后台支撑的,所以map中value的更改会影响这个collection,反之亦然.
* 当迭代这个collection时,如果map发生了改变,迭代结果会受到什么影响并未定义.
* 这个collection支持元素的删除,通过Iterator.remove(),
* Collection.remove(), removeAll(),
* retainAll(),clear()方法,均可进行删除,此时删除的是一个条目.
* 这个collection不支持元素的添加,即为不支持add()和addAll()方法.
*/
public Collection<V> values() {
Collection<V> vs = values;
if (vs == null) {
vs = new Values();
values = vs;
}
return vs;
}
//继续collection骨架实现的内部final类
final class Values extends AbstractCollection<V> {
public final int size() { return size; }
public final void clear() { HashMap.this.clear(); }
public final Iterator<V> iterator() { return new ValueIterator(); }
public final boolean contains(Object o) { return containsValue(o); }
public final Spliterator<V> spliterator() {
return new ValueSpliterator<>(HashMap.this, 0, -1, 0, 0);
}
public final void forEach(java.util.function.Consumer<? super V> 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.value);
}
if (modCount != mc)
throw new ConcurrentModificationException();
}
}
}
/**
* 返回map中条目的一个set.
* 这个set后台由map支撑,故在结构上,二者互相影响.
* 支持删除操作,不支持添加操作.
*/
public Set<Map.Entry<K,V>> entrySet() {
Set<Map.Entry<K,V>> es;
return (es = entrySet) == null ? (entrySet = new EntrySet()) : es;
}
//继承set骨架实现的内部final类
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();
}
public final boolean contains(Object o) {
if (!(o instanceof Map.Entry))
return false;
Map.Entry<?,?> e = (Map.Entry<?,?>) o;
Object key = e.getKey();
Node<K,V> candidate = getNode(hash(key), key);
return candidate != null && candidate.equals(e);
}
public final boolean remove(Object o) {
if (o instanceof Map.Entry) {
Map.Entry<?,?> e = (Map.Entry<?,?>) o;
Object key = e.getKey();
Object value = e.getValue();
return removeNode(hash(key), key, value, true, true) != null;
}
return false;
}
public final Spliterator<Map.Entry<K,V>> spliterator() {
return new EntrySpliterator<>(HashMap.this, 0, -1, 0, 0);
}
public final void forEach(java.util.function.Consumer<? super Entry<K,V>> 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);
}
if (modCount != mc)
throw new ConcurrentModificationException();
}
}
}
// Overrides of JDK8 Map extension methods
/**
* 以下为:jdk8中map的扩展方法
*/
@Override
public V getOrDefault(Object key, V defaultValue) {
Node<K,V> e;
return (e = getNode(hash(key), key)) == null ? defaultValue : e.value;
}
@Override
public V putIfAbsent(K key, V value) {
return putVal(hash(key), key, value, true, true);
}
@Override
public boolean remove(Object key, Object value) {
return removeNode(hash(key), key, value, true, true) != null;
}
@Override
public boolean replace(K key, V oldValue, V newValue) {
Node<K,V> e; V v;
if ((e = getNode(hash(key), key)) != null &&
((v = e.value) == oldValue || (v != null && v.equals(oldValue)))) {
e.value = newValue;
afterNodeAccess(e);
return true;
}
return false;
}
@Override
public V replace(K key, V value) {
Node<K,V> e;
if ((e = getNode(hash(key), key)) != null) {
V oldValue = e.value;
e.value = value;
afterNodeAccess(e);
return oldValue;
}
return null;
}
@Override
public V computeIfAbsent(K key,
java.util.function.Function<? super K, ? extends V> mappingFunction) {
if (mappingFunction == null)
throw new NullPointerException();
int hash = hash(key);
Node<K,V>[] tab; Node<K,V> first; int n, i;
int binCount = 0;
TreeNode<K,V> t = null;
Node<K,V> old = null;
if (size > threshold || (tab = table) == null ||
(n = tab.length) == 0)
n = (tab = resize()).length;
if ((first = tab[i = (n - 1) & hash]) != null) {
if (first instanceof TreeNode)
old = (t = (TreeNode<K,V>)first).getTreeNode(hash, key);
else {
Node<K,V> e = first; K k;
do {
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k)))) {
old = e;
break;
}
++binCount;
} while ((e = e.next) != null);
}
V oldValue;
if (old != null && (oldValue = old.value) != null) {
afterNodeAccess(old);
return oldValue;
}
}
V v = mappingFunction.apply(key);
if (v == null) {
return null;
} else if (old != null) {
old.value = v;
afterNodeAccess(old);
return v;
}
else if (t != null)
t.putTreeVal(this, tab, hash, key, v);
else {
tab[i] = newNode(hash, key, v, first);
if (binCount >= TREEIFY_THRESHOLD - 1)
treeifyBin(tab, hash);
}
++modCount;
++size;
afterNodeInsertion(true);
return v;
}
public V computeIfPresent(K key,
java.util.function.BiFunction<? super K, ? super V, ? extends V> remappingFunction) {
if (remappingFunction == null)
throw new NullPointerException();
Node<K,V> e; V oldValue;
int hash = hash(key);
if ((e = getNode(hash, key)) != null &&
(oldValue = e.value) != null) {
V v = remappingFunction.apply(key, oldValue);
if (v != null) {
e.value = v;
afterNodeAccess(e);
return v;
}
else
removeNode(hash, key, null, false, true);
}
return null;
}
@Override
public V compute(K key,
java.util.function.BiFunction<? super K, ? super V, ? extends V> remappingFunction) {
if (remappingFunction == null)
throw new NullPointerException();
int hash = hash(key);
Node<K,V>[] tab; Node<K,V> first; int n, i;
int binCount = 0;
TreeNode<K,V> t = null;
Node<K,V> old = null;
if (size > threshold || (tab = table) == null ||
(n = tab.length) == 0)
n = (tab = resize()).length;
if ((first = tab[i = (n - 1) & hash]) != null) {
if (first instanceof TreeNode)
old = (t = (TreeNode<K,V>)first).getTreeNode(hash, key);
else {
Node<K,V> e = first; K k;
do {
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k)))) {
old = e;
break;
}
++binCount;
} while ((e = e.next) != null);
}
}
V oldValue = (old == null) ? null : old.value;
V v = remappingFunction.apply(key, oldValue);
if (old != null) {
if (v != null) {
old.value = v;
afterNodeAccess(old);
}
else
removeNode(hash, key, null, false, true);
}
else if (v != null) {
if (t != null)
t.putTreeVal(this, tab, hash, key, v);
else {
tab[i] = newNode(hash, key, v, first);
if (binCount >= TREEIFY_THRESHOLD - 1)
treeifyBin(tab, hash);
}
++modCount;
++size;
afterNodeInsertion(true);
}
return v;
}
@Override
public V merge(K key, V value,
java.util.function.BiFunction<? super V, ? super V, ? extends V> remappingFunction) {
if (value == null)
throw new NullPointerException();
if (remappingFunction == null)
throw new NullPointerException();
int hash = hash(key);
Node<K,V>[] tab; Node<K,V> first; int n, i;
int binCount = 0;
TreeNode<K,V> t = null;
Node<K,V> old = null;
if (size > threshold || (tab = table) == null ||
(n = tab.length) == 0)
n = (tab = resize()).length;
if ((first = tab[i = (n - 1) & hash]) != null) {
if (first instanceof TreeNode)
old = (t = (TreeNode<K,V>)first).getTreeNode(hash, key);
else {
Node<K,V> e = first; K k;
do {
if (e.hash == hash &&
((k = e.key) == key || (key != null && key.equals(k)))) {
old = e;
break;
}
++binCount;
} while ((e = e.next) != null);
}
}
if (old != null) {
V v;
if (old.value != null)
v = remappingFunction.apply(old.value, value);
else
v = value;
if (v != null) {
old.value = v;
afterNodeAccess(old);
}
else
removeNode(hash, key, null, false, true);
return v;
}
if (value != null) {
if (t != null)
t.putTreeVal(this, tab, hash, key, value);
else {
tab[i] = newNode(hash, key, value, first);
if (binCount >= TREEIFY_THRESHOLD - 1)
treeifyBin(tab, hash);
}
++modCount;
++size;
afterNodeInsertion(true);
}
return value;
}
@Override
public void forEach(BiConsumer<? super K, ? super V> 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, e.value);
}
if (modCount != mc)
throw new ConcurrentModificationException();
}
}
@Override
public void replaceAll(BiFunction<? super K, ? super V, ? extends V> function) {
Node<K,V>[] tab;
if (function == 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) {
e.value = function.apply(e.key, e.value);
}
}
if (modCount != mc)
throw new ConcurrentModificationException();
}
}
/* ------------------------------------------------------------ */
// clone和序列化实现
/**
* 返回map实例的浅拷贝:key和value本身不会被clone,因为key和value均为对象.
*/
@SuppressWarnings("unchecked")
@Override
public Object clone() {
HashMap<K,V> result;
try {
result = (HashMap<K,V>)super.clone();
} catch (CloneNotSupportedException e) {
// this shouldn't happen, since we are Cloneable
throw new InternalError(e);
}
//将result实例的一些域进行赋值,要么为null,要么为0.因为result和原map共享table,所以所有域的值都不再有任何意义.
result.reinitialize();
//使用map初始化result
result.putMapEntries(this, false);
return result;
}
//这些方法在序列化HasSet时,同样适用.
final float loadFactor() { return loadFactor; }
//如果table不为null,返回容量为table的长度;
//如果table为null,如果阈值>0,返回容量为阈值;如果阈值<=0,返回默认初始化容量.
final int capacity() {
return (table != null) ? table.length :
(threshold > 0) ? threshold :
DEFAULT_INITIAL_CAPACITY;
}
/**
* 保存当前HashMap实例到流中(如序列化时)
* 序列化数据格式:
* 1.HashMap的容量(=桶数组的长度).
* 2.size(键值对个数)
* 3.键值对(顺序不确定)
*/
private void writeObject(java.io.ObjectOutputStream s)
throws IOException {
int buckets = capacity();
// Write out the threshold, loadfactor, and any hidden stuff
//写入:阈值,负载因子,其它隐藏信息
s.defaultWriteObject();
//写入:bucket个数(容量)
s.writeInt(buckets);
//写入size
s.writeInt(size);
//写入:键值对
internalWriteEntries(s);
}
/**
* 从流重建HashMap(如反序列化时)
*/
private void readObject(java.io.ObjectInputStream s)
throws IOException, ClassNotFoundException {
//读取:阈值(忽略),负载因子,其它隐藏信息
s.defaultReadObject();
//初始化map,对HashMap的一些域初始化.
reinitialize();
//如果负载因子<=0 or 为非数字值,则抛出异常.
if (loadFactor <= 0 || Float.isNaN(loadFactor))
throw new InvalidObjectException("Illegal load factor: " +
loadFactor);
/**
*读取buckets值,且忽略.
* 忽略是什么意思?
* 因为stream的读取必须是一个个二进制位的读取,所以读入顺序同序列化顺序一致.比如,必须先读取bucket才能读取size.
* 所以虽然读取了bucket的值,但是只是为了整个流的读取,不会对这个值进行处理.
*/
s.readInt();
//读取size,并保存
int mappings = s.readInt();
//如果键值对个数<0,则抛出异常.
if (mappings < 0)
throw new InvalidObjectException("Illegal mappings count: " +
mappings);
//如果键值对个数>0
else if (mappings > 0) { // (if zero, use defaults)
// Size the table using given load factor only if within
// range of 0.25...4.0
//负载因子
float lf = Math.min(Math.max(0.25f, loadFactor), 4.0f);
//容量(必然大于键值对个数)
float fc = (float)mappings / lf + 1.0f;
//根据fc进一步确定容量cap
int cap = ((fc < DEFAULT_INITIAL_CAPACITY) ?
DEFAULT_INITIAL_CAPACITY :
(fc >= MAXIMUM_CAPACITY) ?
MAXIMUM_CAPACITY :
tableSizeFor((int)fc));
//阈值=容量*负载因子
float ft = (float)cap * lf;
//根据ft确定阈值
threshold = ((cap < MAXIMUM_CAPACITY && ft < MAXIMUM_CAPACITY) ?
(int)ft : Integer.MAX_VALUE);
//为table申请内存空间个数:cap
@SuppressWarnings({"rawtypes","unchecked"})
Node<K,V>[] tab = (Node<K,V>[])new Node[cap];
table = tab;
//table建好后,将键值对拷贝到table中.
for (int i = 0; i < mappings; i++) {
@SuppressWarnings("unchecked")
K key = (K) s.readObject();
@SuppressWarnings("unchecked")
V value = (V) s.readObject();
putVal(hash(key), key, value, false, false);
}
}
}
/* ------------------------------------------------------------ */
// hash迭代器
//抽象类
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;//保证了在map结构发生改变时,迭代器失效
Node<K,V>[] t = table;
current = next = null;
index = 0;
//找到迭代的第一个入口
if (t != null && size > 0) { // advance to first entry
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;
//map结构改变,抛出异常
if (modCount != expectedModCount)
throw new ConcurrentModificationException();
//节点为null,抛出异常
if (e == null)
throw new NoSuchElementException();
//如果当前节点e为最后一个节点,则再次为index赋值,找到迭代器的入口.注意此时next=null
if ((next = (current = e).next) == null && (t = table) != null) {
do {} while (index < t.length && (next = t[index++]) == null);
}
//返回节点
return e;
}
public final void remove() {
Node<K,V> p = current;
//节点为null,抛出异常
if (p == null)
throw new IllegalStateException();
//map结构改变,抛出异常
if (modCount != expectedModCount)
throw new ConcurrentModificationException();
//释放当前节点内存,通知jvm可以对其进行回收
current = null;
K key = p.key;
//删除节点
removeNode(hash(key), key, null, false, false);
//更新map结构更改次数.
expectedModCount = modCount;
}
}
//key迭代器,继承hash迭代器
final class KeyIterator extends HashIterator
implements Iterator<K> {
public final K next() { return nextNode().key; }
}
//value迭代器,继承hash迭代器
final class ValueIterator extends HashIterator
implements Iterator<V> {
public final V next() { return nextNode().value; }
}
//entry迭代器,继承hash迭代器
final class EntryIterator extends HashIterator
implements Iterator<Map.Entry<K,V>> {
public final Map.Entry<K,V> next() { return nextNode(); }
}
/* ------------------------------------------------------------ */
// spliterators分隔迭代器
static class HashMapSpliterator<K,V> {
final HashMap<K,V> map;
Node<K,V> current; // 当前节点
int index; // current index, modified on advance/split当前索引,在节点向前或者被分割时,值改变
int fence; // table最后一个索引值+1
int est; // 预估size大小
int expectedModCount; // 用于检查map结构是否更改的标准域
HashMapSpliterator(HashMap<K,V> m, int origin,
int fence, int est,
int expectedModCount) {
this.map = m;
this.index = origin;
this.fence = fence;
this.est = est;
this.expectedModCount = expectedModCount;
}
//第一次使用时,初始化fence和size的值
final int getFence() { // initialize fence and size on first use
int hi;
if ((hi = fence) < 0) {
HashMap<K,V> m = map;
est = m.size;
expectedModCount = m.modCount;
Node<K,V>[] tab = m.table;
//table=null,则fence=0;否则为table的length
hi = fence = (tab == null) ? 0 : tab.length;
}
return hi;
}
//获取size大小
public final long estimateSize() {
getFence(); // force init
return (long) est;
}
}
//static final类
//key分隔迭代器,继承hash分隔迭代器
static final class KeySpliterator<K,V>
extends HashMapSpliterator<K,V>
implements Spliterator<K> {
KeySpliterator(HashMap<K,V> m, int origin, int fence, int est,
int expectedModCount) {
super(m, origin, fence, est, expectedModCount);
}
//
public KeySpliterator<K,V> trySplit() {
int hi = getFence(), lo = index, mid = (lo + hi) >>> 1;
return (lo >= mid || current != null) ? null :
new KeySpliterator<>(map, lo, index = mid, est >>>= 1,
expectedModCount);
}
//对每一个key执行action接口定义的操作
public void forEachRemaining(java.util.function.Consumer<? super K> action) {
int i, hi, mc;
if (action == null)
throw new NullPointerException();
HashMap<K,V> m = map;
Node<K,V>[] tab = m.table;
if ((hi = fence) < 0) {
mc = expectedModCount = m.modCount;
hi = fence = (tab == null) ? 0 : tab.length;
}
else
mc = expectedModCount;
if (tab != null && tab.length >= hi &&
(i = index) >= 0 && (i < (index = hi) || current != null)) {
Node<K,V> p = current;
current = null;
do {
if (p == null)
p = tab[i++];
else {
//当前节点执行accept操作,就是你定义consumer接口中的操作.
action.accept(p.key);
p = p.next;
}
} while (p != null || i < hi);
//map结构改变,抛出异常.
if (m.modCount != mc)
throw new ConcurrentModificationException();
}
}
//查找table中第一个非空的bucket,如果有,则对其执行action中的操作,并返回true;否则返回false;
public boolean tryAdvance(java.util.function.Consumer<? super K> action) {
int hi;
if (action == null)
throw new NullPointerException();
Node<K,V>[] tab = map.table;
//hi=table.length
if (tab != null && tab.length >= (hi = getFence()) && index >= 0) {
while (current != null || index < hi) {
if (current == null)
current = tab[index++];
else {
K k = current.key;
current = current.next;
action.accept(k);
if (map.modCount != expectedModCount)
throw new ConcurrentModificationException();
return true;
}
}
}
return false;
}
//?
public int characteristics() {
return (fence < 0 || est == map.size ? Spliterator.SIZED : 0) |
Spliterator.DISTINCT;
}
}
//value分隔迭代器,继承自hashmap分隔迭代器,各个方法和key分隔迭代器一样,不解释
static final class ValueSpliterator<K,V>
extends HashMapSpliterator<K,V>
implements Spliterator<V> {
ValueSpliterator(HashMap<K,V> m, int origin, int fence, int est,
int expectedModCount) {
super(m, origin, fence, est, expectedModCount);
}
public ValueSpliterator<K,V> trySplit() {
int hi = getFence(), lo = index, mid = (lo + hi) >>> 1;
return (lo >= mid || current != null) ? null :
new ValueSpliterator<>(map, lo, index = mid, est >>>= 1,
expectedModCount);
}
public void forEachRemaining(java.util.function.Consumer<? super V> action) {
int i, hi, mc;
if (action == null)
throw new NullPointerException();
HashMap<K,V> m = map;
Node<K,V>[] tab = m.table;
if ((hi = fence) < 0) {
mc = expectedModCount = m.modCount;
hi = fence = (tab == null) ? 0 : tab.length;
}
else
mc = expectedModCount;
if (tab != null && tab.length >= hi &&
(i = index) >= 0 && (i < (index = hi) || current != null)) {
Node<K,V> p = current;
current = null;
do {
if (p == null)
p = tab[i++];
else {
action.accept(p.value);
p = p.next;
}
} while (p != null || i < hi);
if (m.modCount != mc)
throw new ConcurrentModificationException();
}
}
public boolean tryAdvance(java.util.function.Consumer<? super V> action) {
int hi;
if (action == null)
throw new NullPointerException();
Node<K,V>[] tab = map.table;
if (tab != null && tab.length >= (hi = getFence()) && index >= 0) {
while (current != null || index < hi) {
if (current == null)
current = tab[index++];
else {
V v = current.value;
current = current.next;
action.accept(v);
if (map.modCount != expectedModCount)
throw new ConcurrentModificationException();
return true;
}
}
}
return false;
}
public int characteristics() {
return (fence < 0 || est == map.size ? Spliterator.SIZED : 0);
}
}
//entry分隔迭代器,功能和key分隔迭代器,不解释
static final class EntrySpliterator<K,V>
extends HashMapSpliterator<K,V>
implements Spliterator<Map.Entry<K,V>> {
EntrySpliterator(HashMap<K,V> m, int origin, int fence, int est,
int expectedModCount) {
super(m, origin, fence, est, expectedModCount);
}
public EntrySpliterator<K,V> trySplit() {
int hi = getFence(), lo = index, mid = (lo + hi) >>> 1;
return (lo >= mid || current != null) ? null :
new EntrySpliterator<>(map, lo, index = mid, est >>>= 1,
expectedModCount);
}
public void forEachRemaining(java.util.function.Consumer<? super Entry<K,V>> action) {
int i, hi, mc;
if (action == null)
throw new NullPointerException();
HashMap<K,V> m = map;
Node<K,V>[] tab = m.table;
if ((hi = fence) < 0) {
mc = expectedModCount = m.modCount;
hi = fence = (tab == null) ? 0 : tab.length;
}
else
mc = expectedModCount;
if (tab != null && tab.length >= hi &&
(i = index) >= 0 && (i < (index = hi) || current != null)) {
Node<K,V> p = current;
current = null;
do {
if (p == null)
p = tab[i++];
else {
action.accept(p);
p = p.next;
}
} while (p != null || i < hi);
if (m.modCount != mc)
throw new ConcurrentModificationException();
}
}
public boolean tryAdvance(Consumer<? super Entry<K,V>> action) {
int hi;
if (action == null)
throw new NullPointerException();
Node<K,V>[] tab = map.table;
if (tab != null && tab.length >= (hi = getFence()) && index >= 0) {
while (current != null || index < hi) {
if (current == null)
current = tab[index++];
else {
Node<K,V> e = current;
current = current.next;
action.accept(e);
if (map.modCount != expectedModCount)
throw new ConcurrentModificationException();
return true;
}
}
}
return false;
}
public int characteristics() {
return (fence < 0 || est == map.size ? Spliterator.SIZED : 0) |
Spliterator.DISTINCT;
}
}
/* ------------------------------------------------------------ */
//支持LinkedHashMap功能
/*
* The following package-protected methods are designed to be
* overridden by LinkedHashMap, but not by any other subclass.
* Nearly all other internal methods are also package-protected
* but are declared final, so can be used by LinkedHashMap, view
* classes, and HashSet.
* 下面的包级私方法被设计为由LinkedHashMap重写,但不能由其它任何子类重写.
* 几乎所有其它的内部方法都是包级私有,但声明类型都为final,因此LinkedHashMap,视图类,HashSet都可以使用.
*/
//创建常规节点(即为链表节点,非红黑树节点)
Node<K,V> newNode(int hash, K key, V value, Node<K,V> next) {
return new Node<>(hash, key, value, next);
}
//从树节点转为普通节点
Node<K,V> replacementNode(Node<K,V> p, Node<K,V> next) {
return new Node<>(p.hash, p.key, p.value, next);
}
//创建红黑树节点
TreeNode<K,V> newTreeNode(int hash, K key, V value, Node<K,V> next) {
return new TreeNode<>(hash, key, value, next);
}
//普通节点转为红黑树节点
TreeNode<K,V> replacementTreeNode(Node<K,V> p, Node<K,V> next) {
return new TreeNode<>(p.hash, p.key, p.value, next);
}
/**
* 重置HashMap实例的一些域到默认状态.
* 这一方法只会被clone()和readObject()这两个方法调用.
*/
void reinitialize() {
table = null;
entrySet = null;
keySet = null;
values = null;
modCount = 0;
threshold = 0;
size = 0;
}
// 回调以允许LinkedHashMap后置操作(访问,插入,删除)
void afterNodeAccess(Node<K,V> p) { }
void afterNodeInsertion(boolean evict) { }
void afterNodeRemoval(Node<K,V> p) { }
// 仅从writeObject调用，以确保兼容的排序。
void internalWriteEntries(java.io.ObjectOutputStream s) throws IOException {
Node<K,V>[] tab;
if (size > 0 && (tab = table) != null) {
for (int i = 0; i < tab.length; ++i) {
for (Node<K,V> e = tab[i]; e != null; e = e.next) {
s.writeObject(e.key);
s.writeObject(e.value);
}
}
}
}
/* --------------红黑树--------------- */
/**
* 红黑树entry。扩展LinkedHashMap.Entry（反过来扩展节点),因此可以用作普通或扩展的链表节点。
*/
static final class TreeNode<K,V> extends LinkedHashMap.Entry<K,V> {
TreeNode<K,V> parent; //红黑树连接点
TreeNode<K,V> left; //左孩子
TreeNode<K,V> right; //右孩子
TreeNode<K,V> prev; //删除节点时,需要断开链接,这个节点记录了删除节点的前一个节点.
boolean red;
TreeNode(int hash, K key, V val, Node<K,V> next) {
super(hash, key, val, next);
}
/**
* 返回当前节点的树根节点.
*/
final TreeNode<K,V> root() {
for (TreeNode<K,V> r = this, p;;) {
//如果r无双亲节点,则r为根节点
if ((p = r.parent) == null)
return r;
r = p;
}
}
/**
* 确保root节点为tab中的第一个节点
* tab:root节点所在红黑树节点数组
* 说白了就3个任务:
* 1.root节点从原位置删除
* 2.root节点插入到tab[index]位置
* 3.root作为根节点,更改后继和前驱.
*/
static <K,V> void moveRootToFront(Node<K,V>[] tab, TreeNode<K,V> root) {
int n;
//如果root节点不为null & tab不为null && tab.length>0
//n=tab.length
if (root != null && tab != null && (n = tab.length) > 0) {
//获取第一个节点在tab中的索引
int index = (n - 1) & root.hash;
//获取tab[index]节点
TreeNode<K,V> first = (TreeNode<K,V>)tab[index];
//如果root节点不是first节点
if (root != first) {
Node<K,V> rn;
//root节点赋值给tab中第一个节点
tab[index] = root;
//保存root节点的前驱
TreeNode<K,V> rp = root.prev;
//如果root后继不为null
if ((rn = root.next) != null)
//root后继的前驱改为root的前驱,这样就把root从原位置移除掉了
((TreeNode<K,V>)rn).prev = rp;
//如果root节点前驱的后继不为null,则root前驱的后继指向root的后继.
if (rp != null)
rp.next = rn;
//如果first不为null,则让first的前驱指向root
if (first != null)
first.prev = root;
//root的后继指向first
root.next = first;
//此时root无前驱了,无设为null,完成root在tab中第一的位置.
root.prev = null;
}
assert checkInvariants(root);
}
}
/**
* Finds the node starting at root p with the given hash and key.
* The kc argument caches comparableClassFor(key) upon first use
* comparing keys.
* 根据给定的key和hash,从红黑树的root节点开始查找.
* kc参数存在的意义:第一次使用时,缓存可比较的key.这样下次一样的key,则可以迅速找到该节点(当然map不能改变)
* @param h hash值
* @param k 查找key
* @param kc
* @return
*/
final TreeNode<K,V> find(int h, Object k, Class<?> kc) {
TreeNode<K,V> p = this;
do {
int ph, dir; K pk;
TreeNode<K,V> pl = p.left, pr = p.right, q;
if ((ph = p.hash) > h)
p = pl;
else if (ph < h)
p = pr;
//hash,key都和当前节点p相同,则查找返回p~
else if ((pk = p.key) == k || (k != null && k.equals(pk)))
return p;
//左子树为null,则遍历节点转为右子树
else if (pl == null)
p = pr;
//右子树为null,则遍历节点转为左子树
else if (pr == null)
p = pl;
//缓存非空
else if ((kc != null ||
(kc = comparableClassFor(k)) != null) &&
(dir = compareComparables(kc, k, pk)) != 0)
p = (dir < 0) ? pl : pr;
//右子树递归
else if ((q = pr.find(h, k, kc)) != null)
return q;
else
p = pl;
} while (p != null);
return null;
}
/**
* 查找root节点时,本方法被调用.
*/
final TreeNode<K,V> getTreeNode(int h, Object k) {
return ((parent != null) ? root() : this).find(h, k, null);
}
/**
* Tie-breaking工具是为了插入元素具有相同的hash值且无法进行其它比较时,对插入顺序进行排序.
* 我们并不需要一个完全的排序,只需要一个一致的插入规则来维护等价重叠.
* 本方法比单纯的检测一个二进制位的方式更有必要.
*/
static int tieBreakOrder(Object a, Object b) {
int d;
//如果a和b中至少一个为null 或者 a和b类型相同
if (a == null || b == null ||
(d = a.getClass().getName().
compareTo(b.getClass().getName())) == 0)
//identityHashCode和hashCode返回相同值
d = (System.identityHashCode(a) <= System.identityHashCode(b) ?
-1 : 1);
return d;
}
/**
* 整理连接此节点的整棵红黑树上的所有节点.
* 此方法用法:在插入,删除节点后,红黑树性质被破坏时,进行结构的调整.
* @return 返回树根节点
*/
final void treeify(Node<K,V>[] tab) {
TreeNode<K,V> root = null;
for (TreeNode<K,V> x = this, next; x != null; x = next) {
next = (TreeNode<K,V>)x.next;
x.left = x.right = null;
if (root == null) {
x.parent = null;
x.red = false;
root = x;
}
else {
K k = x.key;
int h = x.hash;
Class<?> kc = null;
for (TreeNode<K,V> p = root;;) {
int dir, ph;
K pk = p.key;
if ((ph = p.hash) > h)
dir = -1;
else if (ph < h)
dir = 1;
else if ((kc == null &&
(kc = comparableClassFor(k)) == null) ||
(dir = compareComparables(kc, k, pk)) == 0)
dir = tieBreakOrder(k, pk);
TreeNode<K,V> xp = p;
if ((p = (dir <= 0) ? p.left : p.right) == null) {
x.parent = xp;
if (dir <= 0)
xp.left = x;
else
xp.right = x;
root = balanceInsertion(root, x);
break;
}
}
}
}
moveRootToFront(tab, root);
}
/**
* 返回非TreeNode节点的列表，替换那些从此节点链接的节点,此节点作为返回链表的头节点。
*/
final Node<K,V> untreeify(HashMap<K,V> map) {
Node<K,V> hd = null, tl = null;
for (Node<K,V> q = this; q != null; q = q.next) {
Node<K,V> p = map.replacementNode(q, null);
if (tl == null)
hd = p;
else
tl.next = p;
tl = p;
}
return hd;
}
/**
* Tree version of putVal.
*/
final TreeNode<K,V> putTreeVal(HashMap<K,V> map, Node<K,V>[] tab,
int h, K k, V v) {
Class<?> kc = null;
boolean searched = false;
TreeNode<K,V> root = (parent != null) ? root() : this;
for (TreeNode<K,V> p = root;;) {
int dir, ph; K pk;
if ((ph = p.hash) > h)
dir = -1;
else if (ph < h)
dir = 1;
else if ((pk = p.key) == k || (k != null && k.equals(pk)))
return p;
else if ((kc == null &&
(kc = comparableClassFor(k)) == null) ||
(dir = compareComparables(kc, k, pk)) == 0) {
if (!searched) {
TreeNode<K,V> q, ch;
searched = true;
if (((ch = p.left) != null &&
(q = ch.find(h, k, kc)) != null) ||
((ch = p.right) != null &&
(q = ch.find(h, k, kc)) != null))
return q;
}
//查找插入规则
dir = tieBreakOrder(k, pk);
}
TreeNode<K,V> xp = p;
if ((p = (dir <= 0) ? p.left : p.right) == null) {
Node<K,V> xpn = xp.next;
//生成新节点
TreeNode<K,V> x = map.newTreeNode(h, k, v, xpn);
if (dir <= 0)
xp.left = x;
else
xp.right = x;
xp.next = x;
x.parent = x.prev = xp;
if (xpn != null)
((TreeNode<K,V>)xpn).prev = x;
//插入节点后,将树根调整到bucket中
moveRootToFront(tab, balanceInsertion(root, x));
return null;
}
}
}
/**
* 移除红黑树中的参数节点node,要求在此方法调用前,这个节点必须存在.
* 这比典型的红黑删除代码更加混乱，因为我们不能将内部节点的内容与被可访问的,遍历期间独立的“下一个”指针固定的叶子后继交换.
* 相反,我们交换了树的连接(因为左旋或者右旋完成的就是改变子树间的连接)
* 删除节点后,如果当前红黑树中节点个数太少,到达6个后,就会转为普通链表存储.
* (红黑树到链表的转换节点个数标准为:2~6,这具体取决于红黑树结构)
*/
final void removeTreeNode(HashMap<K,V> map, Node<K,V>[] tab,
boolean movable) {
int n;
if (tab == null || (n = tab.length) == 0)
return;
int index = (n - 1) & hash;
TreeNode<K,V> first = (TreeNode<K,V>)tab[index], root = first, rl;
TreeNode<K,V> succ = (TreeNode<K,V>)next, pred = prev;
if (pred == null)
tab[index] = first = succ;
else
pred.next = succ;
if (succ != null)
succ.prev = pred;
if (first == null)
return;
if (root.parent != null)
root = root.root();
if (root == null || root.right == null ||
(rl = root.left) == null || rl.left == null) {
tab[index] = first.untreeify(map); // too small
return;
}
TreeNode<K,V> p = this, pl = left, pr = right, replacement;
if (pl != null && pr != null) {
TreeNode<K,V> s = pr, sl;
while ((sl = s.left) != null) // find successor
s = sl;
boolean c = s.red; s.red = p.red; p.red = c; // swap colors
TreeNode<K,V> sr = s.right;
TreeNode<K,V> pp = p.parent;
if (s == pr) { // p was s's direct parent
p.parent = s;
s.right = p;
}
else {
TreeNode<K,V> sp = s.parent;
if ((p.parent = sp) != null) {
if (s == sp.left)
sp.left = p;
else
sp.right = p;
}
if ((s.right = pr) != null)
pr.parent = s;
}
p.left = null;
if ((p.right = sr) != null)
sr.parent = p;
if ((s.left = pl) != null)
pl.parent = s;
if ((s.parent = pp) == null)
root = s;
else if (p == pp.left)
pp.left = s;
else
pp.right = s;
if (sr != null)
replacement = sr;
else
replacement = p;
}
else if (pl != null)
replacement = pl;
else if (pr != null)
replacement = pr;
else
replacement = p;
if (replacement != p) {
TreeNode<K,V> pp = replacement.parent = p.parent;
if (pp == null)
root = replacement;
else if (p == pp.left)
pp.left = replacement;
else
pp.right = replacement;
p.left = p.right = p.parent = null;
}
TreeNode<K,V> r = p.red ? root : balanceDeletion(root, replacement);
if (replacement == p) { // detach
TreeNode<K,V> pp = p.parent;
p.parent = null;
if (pp != null) {
if (p == pp.left)
pp.left = null;
else if (p == pp.right)
pp.right = null;
}
}
if (movable)
moveRootToFront(tab, r);
}
/**
* 将红黑树中的节点分隔为较低和较高的树形结构,如果树中节点个数为6,则将转为链表.
* 这一方法只在resize()时被调用.
* 可以查看上面关于分隔位和索引的讨论.
* @param index 用于分隔的table索引
* @param bit the bit of hash to split on
*/
final void split(HashMap<K,V> map, Node<K,V>[] tab, int index, int bit) {
TreeNode<K,V> b = this;
// Relink into lo and hi lists, preserving order
TreeNode<K,V> loHead = null, loTail = null;
TreeNode<K,V> hiHead = null, hiTail = null;
int lc = 0, hc = 0;
for (TreeNode<K,V> e = b, next; e != null; e = next) {
next = (TreeNode<K,V>)e.next;
e.next = null;
if ((e.hash & bit) == 0) {
if ((e.prev = loTail) == null)
loHead = e;
else
loTail.next = e;
loTail = e;
++lc;
}
else {
if ((e.prev = hiTail) == null)
hiHead = e;
else
hiTail.next = e;
hiTail = e;
++hc;
}
}
if (loHead != null) {
if (lc <= UNTREEIFY_THRESHOLD)
tab[index] = loHead.untreeify(map);
else {
tab[index] = loHead;
if (hiHead != null) // (else is already treeified)
loHead.treeify(tab);
}
}
if (hiHead != null) {
if (hc <= UNTREEIFY_THRESHOLD)
tab[index + bit] = hiHead.untreeify(map);
else {
tab[index + bit] = hiHead;
if (loHead != null)
hiHead.treeify(tab);
}
}
}
/* --------------------红黑树方法--------------------------------- */
// Red-black tree methods, all adapted from CLR
//左旋方法
static <K,V> TreeNode<K,V> rotateLeft(TreeNode<K,V> root, TreeNode<K,V> p) {
TreeNode<K,V> r, pp, rl;
//如果p不为null & p有孩子不为null
//r=p.right
//不平衡原因:在p的右孩子上面插入节点
if (p != null && (r = p.right) != null) {
//rl指向从r上面拿下的左子树
if ((rl = p.right = r.left) != null)
//rl双亲节点改为p
rl.parent = p;
//p为根节点时,r变为根节点,且更改颜色为黑色.
if ((pp = r.parent = p.parent) == null)
(root = r).red = false;
//p为内部节点,且为pp的左孩子
else if (pp.left == p)
pp.left = r;
//p为内部节,且为pp的右孩子
else
pp.right = r;
//r的左孩子指向p
r.left = p;
//p的双亲节点指向r
p.parent = r;
}
//返回根节点
return root;
}
//右旋方法
static <K,V> TreeNode<K,V> rotateRight(TreeNode<K,V> root,
TreeNode<K,V> p) {
TreeNode<K,V> l, pp, lr;
//如果p不为null且p的左孩子不为null
//红黑树不平衡原因:在p的左孩子上插入一个node
if (p != null && (l = p.left) != null) {
//l的右子树变为p的右子树
//lr指向p的左子树
if ((lr = p.left = l.right) != null)
//lr的双亲节点改为p
lr.parent = p;
//如果p为根节点
if ((pp = l.parent = p.parent) == null)
//l节点颜色改为黑色(因为红黑树根节点必须为黑色)
(root = l).red = false;
//如果p为内部节点,且p为右节点
else if (pp.right == p)
pp.right = l;
//p为左节点
else
pp.left = l;
//p为l的右子树
l.right = p;
//p的双亲节点为l
p.parent = l;
}
//返回根节点
return root;
}
//插入节点后,调整平衡(调用左旋+右旋方法+颜色调整)
static <K,V> TreeNode<K,V> balanceInsertion(TreeNode<K,V> root,
TreeNode<K,V> x) {
x.red = true;
for (TreeNode<K,V> xp, xpp, xppl, xppr;;) {
if ((xp = x.parent) == null) {
x.red = false;
return x;
}
else if (!xp.red || (xpp = xp.parent) == null)
return root;
if (xp == (xppl = xpp.left)) {
if ((xppr = xpp.right) != null && xppr.red) {
xppr.red = false;
xp.red = false;
xpp.red = true;
x = xpp;
}
else {
if (x == xp.right) {
root = rotateLeft(root, x = xp);
xpp = (xp = x.parent) == null ? null : xp.parent;
}
if (xp != null) {
xp.red = false;
if (xpp != null) {
xpp.red = true;
root = rotateRight(root, xpp);
}
}
}
}
else {
if (xppl != null && xppl.red) {
xppl.red = false;
xp.red = false;
xpp.red = true;
x = xpp;
}
else {
if (x == xp.left) {
root = rotateRight(root, x = xp);
xpp = (xp = x.parent) == null ? null : xp.parent;
}
if (xp != null) {
xp.red = false;
if (xpp != null) {
xpp.red = true;
root = rotateLeft(root, xpp);
}
}
}
}
}
}
//删除节点后,调整红黑树(左旋方法+右旋方法+颜色调整)
static <K,V> TreeNode<K,V> balanceDeletion(TreeNode<K,V> root,
TreeNode<K,V> x) {
for (TreeNode<K,V> xp, xpl, xpr;;) {
if (x == null || x == root)
return root;
else if ((xp = x.parent) == null) {
x.red = false;
return x;
}
else if (x.red) {
x.red = false;
return root;
}
else if ((xpl = xp.left) == x) {
if ((xpr = xp.right) != null && xpr.red) {
xpr.red = false;
xp.red = true;
root = rotateLeft(root, xp);
xpr = (xp = x.parent) == null ? null : xp.right;
}
if (xpr == null)
x = xp;
else {
TreeNode<K,V> sl = xpr.left, sr = xpr.right;
if ((sr == null || !sr.red) &&
(sl == null || !sl.red)) {
xpr.red = true;
x = xp;
}
else {
if (sr == null || !sr.red) {
if (sl != null)
sl.red = false;
xpr.red = true;
root = rotateRight(root, xpr);
xpr = (xp = x.parent) == null ?
null : xp.right;
}
if (xpr != null) {
xpr.red = (xp == null) ? false : xp.red;
if ((sr = xpr.right) != null)
sr.red = false;
}
if (xp != null) {
xp.red = false;
root = rotateLeft(root, xp);
}
x = root;
}
}
}
else { // symmetric
if (xpl != null && xpl.red) {
xpl.red = false;
xp.red = true;
root = rotateRight(root, xp);
xpl = (xp = x.parent) == null ? null : xp.left;
}
if (xpl == null)
x = xp;
else {
TreeNode<K,V> sl = xpl.left, sr = xpl.right;
if ((sl == null || !sl.red) &&
(sr == null || !sr.red)) {
xpl.red = true;
x = xp;
}
else {
if (sl == null || !sl.red) {
if (sr != null)
sr.red = false;
xpl.red = true;
root = rotateLeft(root, xpl);
xpl = (xp = x.parent) == null ?
null : xp.left;
}
if (xpl != null) {
xpl.red = (xp == null) ? false : xp.red;
if ((sl = xpl.left) != null)
sl.red = false;
}
if (xp != null) {
xp.red = false;
root = rotateRight(root, xp);
}
x = root;
}
}
}
}
}
/**
* 检查树是否符合红黑树定义
*/
static <K,V> boolean checkInvariants(TreeNode<K,V> t) {
TreeNode<K,V> tp = t.parent, tl = t.left, tr = t.right,
tb = t.prev, tn = (TreeNode<K,V>)t.next;
if (tb != null && tb.next != t)
return false;
if (tn != null && tn.prev != t)
return false;
if (tp != null && t != tp.left && t != tp.right)
return false;
if (tl != null && (tl.parent != t || tl.hash > t.hash))
return false;
if (tr != null && (tr.parent != t || tr.hash < t.hash))
return false;
if (t.red && tl != null && tl.red && tr != null && tr.red)
return false;
if (tl != null && !checkInvariants(tl))
return false;
if (tr != null && !checkInvariants(tr))
return false;
return true;
}
}
}