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; } } }