最近看了一下ConcurrentHashMap的相关代码,感觉JDK1.7和JDK1.8差别挺大的,这次先看下JDK1.7是怎么实现的吧
哈希(hash)
先了解一下啥是哈希(网上有很多介绍),是一种散列函数,简单来说就是将输入值转换为固定值的一种压缩映射,在Java中最常见的就是Object.hashCode(),通过固定算法计算出来的一个值
数据结构
ConcurrentHashMap主要结构是有Segment<K,V>以及HashEntry<K,V>链表组成的
我们先看一下HashEntry<K,V>的主要结构,还是单向链表的数据结构:
static final class HashEntry<K,V> {final int hash;//hash值final K key;//存储keyvolatile V value;//存储值volatile HashEntry<K,V> next;//指向下一个,单向链表HashEntry(int hash, K key, V value, HashEntry<K,V> next) {this.hash = hash;this.key = key;this.value = value;this.next = next;}//......}
再来看一下Segment<K,V>的数据结构,主要还是用到了HashEntry<K,V>数组:
static final class Segment<K,V> extends ReentrantLock implements Serializable {//数据储存数组transient volatile HashEntry<K,V>[] table;/*** The load factor for the hash table. Even though this value* is same for all segments, it is replicated to avoid needing* links to outer object.* @serial*///扩容因子,当Segment的数量大于initialCapacity* loadFactor就会扩容final float loadFactor;/*** The table is rehashed when its size exceeds this threshold.* (The value of this field is always <tt>(int)(capacity ** loadFactor)</tt>.)*///阈值,超出后就必须重新散列,就是扩容transient int threshold;Segment(float lf, int threshold, HashEntry<K,V>[] tab) {this.loadFactor = lf;this.threshold = threshold;this.table = tab;}//.....
}
接下来看一下ConcurrentHashMap的构造函数以及相关变量:
/*** The default initial capacity for this table,* used when not otherwise specified in a constructor.*///容器的默认大小static final int DEFAULT_INITIAL_CAPACITY = 16;/*** The default load factor for this table, used when not* otherwise specified in a constructor.*///用来调整大小的,就是扩容static final float DEFAULT_LOAD_FACTOR = 0.75f;/*** The default concurrency level for this table, used when not* otherwise specified in a constructor.*///并发时访问的线程数量static final int DEFAULT_CONCURRENCY_LEVEL = 16; final Segment<K,V>[] segments;//数据存储的数组//最大并发的线程数,不能超过65536static final int MAX_SEGMENTS = 1 << 16; // slightly conservative//最大容量数,不能超过2的30次方static final int MAXIMUM_CAPACITY = 1 << 30;public ConcurrentHashMap(int initialCapacity,float loadFactor, int concurrencyLevel) {if (!(loadFactor > 0) || initialCapacity < 0 || concurrencyLevel <= 0)throw new IllegalArgumentException();if (concurrencyLevel > MAX_SEGMENTS)concurrencyLevel = MAX_SEGMENTS;// Find power-of-two sizes best matching argumentsint sshift = 0;int ssize = 1;while (ssize < concurrencyLevel) {++sshift;ssize <<= 1;}this.segmentShift = 32 - sshift;this.segmentMask = ssize - 1;if (initialCapacity > MAXIMUM_CAPACITY)initialCapacity = MAXIMUM_CAPACITY;int c = initialCapacity / ssize;if (c * ssize < initialCapacity)++c;int cap = MIN_SEGMENT_TABLE_CAPACITY;while (cap < c)cap <<= 1;// create segments and segments[0]Segment<K,V> s0 =new Segment<K,V>(loadFactor, (int)(cap * loadFactor),(HashEntry<K,V>[])new HashEntry[cap]);Segment<K,V>[] ss = (Segment<K,V>[])new Segment[ssize];UNSAFE.putOrderedObject(ss, SBASE, s0); // ordered write of segments[0]this.segments = ss;}
在构造方法中可以看到,其实还是创建一个Segment的数组,默认的话长度为16,并且将s0变量赋值进去,s0中的HashEntry数组的大小默认为2。
接下来看一下我们经常用put()方法,源代码如下:
首先需要计算key值的hash值,计算方法是固定的算法,然后判断Segment数组中是否有这个hash值的数据,如果不存在的话,则进入扩容方法ensureSegment(j);在这个方法中可以看到扩容新数组的长度为table.length * loadFactor,即每次扩容为initialCapacity* loadFactor,只会扩容HashEntry数组,并非Segment数组;如果存在的话,则调用Segment的put()方法,这个方法总共有四个参数,最后一个参数是用于区别putIfAbsent()以及put(),这两个方法区别简单来说就是,判断当前key存不存在,如果存在的话put()方法就是覆盖,而putIfAbsent()就是不覆盖,并且这两个方法都会返回旧值,在下面的有Segment的put方法解析。
@SuppressWarnings("unchecked")public V put(K key, V value) {Segment<K,V> s;if (value == null)throw new NullPointerException();int hash = hash(key);int j = (hash >>> segmentShift) & segmentMask;if ((s = (Segment<K,V>)UNSAFE.getObject // nonvolatile; recheck(segments, (j << SSHIFT) + SBASE)) == null) // in ensureSegments = ensureSegment(j);return s.put(key, hash, value, false);}private int hash(Object k) {int h = hashSeed;if ((0 != h) && (k instanceof String)) {return sun.misc.Hashing.stringHash32((String) k);}h ^= k.hashCode();// Spread bits to regularize both segment and index locations,// using variant of single-word Wang/Jenkins hash.h += (h << 15) ^ 0xffffcd7d;h ^= (h >>> 10);h += (h << 3);h ^= (h >>> 6);h += (h << 2) + (h << 14);return h ^ (h >>> 16);}//扩容Segment的数组,private Segment<K,V> ensureSegment(int k) {final Segment<K,V>[] ss = this.segments;long u = (k << SSHIFT) + SBASE; // raw offsetSegment<K,V> seg;if ((seg = (Segment<K,V>)UNSAFE.getObjectVolatile(ss, u)) == null) {Segment<K,V> proto = ss[0]; // use segment 0 as prototypeint cap = proto.table.length;float lf = proto.loadFactor;int threshold = (int)(cap * lf);HashEntry<K,V>[] tab = (HashEntry<K,V>[])new HashEntry[cap];if ((seg = (Segment<K,V>)UNSAFE.getObjectVolatile(ss, u))== null) { // recheckSegment<K,V> s = new Segment<K,V>(lf, threshold, tab);while ((seg = (Segment<K,V>)UNSAFE.getObjectVolatile(ss, u))== null) {if (UNSAFE.compareAndSwapObject(ss, u, null, seg = s))break;}}}return seg;}//Segement中的put方法:可以看到,首先会先去获取锁final V put(K key, int hash, V value, boolean onlyIfAbsent) {HashEntry<K,V> node = tryLock() ? null :scanAndLockForPut(key, hash, value);V oldValue;try {HashEntry<K,V>[] tab = table;int index = (tab.length - 1) & hash;HashEntry<K,V> first = entryAt(tab, index);for (HashEntry<K,V> e = first;;) {//循环链表上的节点判断if (e != null) {K k;if ((k = e.key) == key ||(e.hash == hash && key.equals(k))) {oldValue = e.value;//返回旧值if (!onlyIfAbsent) {e.value = value;//如果是putIfAbsent()则不执行这段覆盖代码++modCount;}break;}e = e.next;//链表的下一个节点}else {//如果在对应的table数组中不存在则创建一个HashEntry节点,或者创建一个if (node != null)node.setNext(first);elsenode = new HashEntry<K,V>(hash, key, value, first);int c = count + 1;if (c > threshold && tab.length < MAXIMUM_CAPACITY)rehash(node);elsesetEntryAt(tab, index, node);++modCount;count = c;oldValue = null;break;}}} finally {unlock();//释放锁}return oldValue;
接下来看看get()方法,其实get()方法的现对来说较为简单,在定位segment和定位table后,依次扫描这个table元素下的的链表,要么找到元素,要么返回null。这里可能会有个并发问题如何获取是最新的,因为在HashEntry设计当中value属性的使用了 volatile保证了数据的可见性。但是在获取的时候并未上锁,所以在使用get()以及containsKey()方法会存在一致性问题,由于HashEntry是链表结构,所以在并发情况下如果其他线程进行修改HashEntry链表值的话(即会修改链表结构,导致链表的next节点地址错乱),返回值并非是实时数据。
public V get(Object key) {Segment<K,V> s; // manually integrate access methods to reduce overheadHashEntry<K,V>[] tab;int h = hash(key);long u = (((h >>> segmentShift) & segmentMask) << SSHIFT) + SBASE;if ((s = (Segment<K,V>)UNSAFE.getObjectVolatile(segments, u)) != null &&(tab = s.table) != null) {for (HashEntry<K,V> e = (HashEntry<K,V>) UNSAFE.getObjectVolatile(tab, ((long)(((tab.length - 1) & h)) << TSHIFT) + TBASE);e != null; e = e.next) {K k;if ((k = e.key) == key || (e.hash == h && key.equals(k)))return e.value;}}return null;}//获取containsKey的值public boolean containsKey(Object key) {Segment<K,V> s; // same as get() except no need for volatile value readHashEntry<K,V>[] tab;int h = hash(key);long u = (((h >>> segmentShift) & segmentMask) << SSHIFT) + SBASE;if ((s = (Segment<K,V>)UNSAFE.getObjectVolatile(segments, u)) != null &&(tab = s.table) != null) {for (HashEntry<K,V> e = (HashEntry<K,V>) UNSAFE.getObjectVolatile(tab, ((long)(((tab.length - 1) & h)) << TSHIFT) + TBASE);e != null; e = e.next) {K k;if ((k = e.key) == key || (e.hash == h && key.equals(k)))return true;}}return false;}
//所以在使用key为Object的时候需要重写一下equals以及hashCode方法
在使用size()时候,会进去两次统计,并且不是加锁统计,两次一致直接返回结果,不一致,重新加锁再次统计
public int size() {// Try a few times to get accurate count. On failure due to// continuous async changes in table, resort to locking.final Segment<K,V>[] segments = this.segments;int size;boolean overflow; // true if size overflows 32 bitslong sum; // sum of modCountslong last = 0L; // previous sumint retries = -1; // first iteration isn't retrytry {for (;;) {//第一次统计if (retries++ == RETRIES_BEFORE_LOCK) {for (int j = 0; j < segments.length; ++j)ensureSegment(j).lock(); // force creation}sum = 0L;size = 0;overflow = false;//第二次统计for (int j = 0; j < segments.length; ++j) {Segment<K,V> seg = segmentAt(segments, j);if (seg != null) {sum += seg.modCount;int c = seg.count;if (c < 0 || (size += c) < 0)overflow = true;}}if (sum == last)break;last = sum;}} finally {if (retries > RETRIES_BEFORE_LOCK) {for (int j = 0; j < segments.length; ++j)segmentAt(segments, j).unlock();}}return overflow ? Integer.MAX_VALUE : size;}
其他方法我就不介绍啦,下次再看一点JDK1.8的ConcurrentHashMap源代码,写的不是很好,不要见怪咯