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JDK1.7的ConcurrentHashMap源码解析

作者:努力的小强

这篇文章主要介绍了JDK1.7的ConcurrentHashMap源码解析,HashMap是非线程安全的,而HashTable是线程安全的,但是HashTable实现同步的方法比较暴力,即在所有的方法体上添加synchronized关键字,需要的朋友可以参考下

概述

HashMap是非线程安全的,而HashTable是线程安全的,但是HashTable实现同步的方法比较暴力,即在所有的方法体上添加synchronized关键字

相当于所有读写线程均去读取一把锁,从并发角度,HashTable其实无法满足较高的并发度。

另一种同步Map的方法是使用Collections工具类。

    public static <K,V> Map<K,V> synchronizedMap(Map<K,V> m) {
        return new SynchronizedMap<>(m);
    }
    /**
     * @serial include
     */
    private static class SynchronizedMap<K,V>
        implements Map<K,V>, Serializable {
        private static final long serialVersionUID = 1978198479659022715L;
        private final Map<K,V> m;     // Backing Map
        //互斥锁
        final Object      mutex;        // Object on which to synchronize
        SynchronizedMap(Map<K,V> m) {
            this.m = Objects.requireNonNull(m);
            mutex = this;
        }
        SynchronizedMap(Map<K,V> m, Object mutex) {
            this.m = m;
            this.mutex = mutex;
        }
        public int size() {
            synchronized (mutex) {return m.size();}
        }
        public boolean isEmpty() {
            synchronized (mutex) {return m.isEmpty();}
        }
        public boolean containsKey(Object key) {
            synchronized (mutex) {return m.containsKey(key);}
        }
        public boolean containsValue(Object value) {
            synchronized (mutex) {return m.containsValue(value);}
        }
        public V get(Object key) {
            synchronized (mutex) {return m.get(key);}
        }
        public V put(K key, V value) {
            synchronized (mutex) {return m.put(key, value);}
        }
        public V remove(Object key) {
            synchronized (mutex) {return m.remove(key);}
        }
        public void putAll(Map<? extends K, ? extends V> map) {
            synchronized (mutex) {m.putAll(map);}
        }
        public void clear() {
            synchronized (mutex) {m.clear();}
        }
        private transient Set<K> keySet;
        private transient Set<Map.Entry<K,V>> entrySet;
        private transient Collection<V> values;
        public Set<K> keySet() {
            synchronized (mutex) {
                if (keySet==null)
                    keySet = new SynchronizedSet<>(m.keySet(), mutex);
                return keySet;
            }
        }
        public Set<Map.Entry<K,V>> entrySet() {
            synchronized (mutex) {
                if (entrySet==null)
                    entrySet = new SynchronizedSet<>(m.entrySet(), mutex);
                return entrySet;
            }
        }
        public Collection<V> values() {
            synchronized (mutex) {
                if (values==null)
                    values = new SynchronizedCollection<>(m.values(), mutex);
                return values;
            }
        }
        public boolean equals(Object o) {
            if (this == o)
                return true;
            synchronized (mutex) {return m.equals(o);}
        }
        public int hashCode() {
            synchronized (mutex) {return m.hashCode();}
        }
        public String toString() {
            synchronized (mutex) {return m.toString();}
        }
        // Override default methods in Map
        @Override
        public V getOrDefault(Object k, V defaultValue) {
            synchronized (mutex) {return m.getOrDefault(k, defaultValue);}
        }
        @Override
        public void forEach(BiConsumer<? super K, ? super V> action) {
            synchronized (mutex) {m.forEach(action);}
        }
        @Override
        public void replaceAll(BiFunction<? super K, ? super V, ? extends V> function) {
            synchronized (mutex) {m.replaceAll(function);}
        }
        @Override
        public V putIfAbsent(K key, V value) {
            synchronized (mutex) {return m.putIfAbsent(key, value);}
        }
        @Override
        public boolean remove(Object key, Object value) {
            synchronized (mutex) {return m.remove(key, value);}
        }
        @Override
        public boolean replace(K key, V oldValue, V newValue) {
            synchronized (mutex) {return m.replace(key, oldValue, newValue);}
        }
        @Override
        public V replace(K key, V value) {
            synchronized (mutex) {return m.replace(key, value);}
        }
        @Override
        public V computeIfAbsent(K key,
                Function<? super K, ? extends V> mappingFunction) {
            synchronized (mutex) {return m.computeIfAbsent(key, mappingFunction);}
        }
        @Override
        public V computeIfPresent(K key,
                BiFunction<? super K, ? super V, ? extends V> remappingFunction) {
            synchronized (mutex) {return m.computeIfPresent(key, remappingFunction);}
        }
        @Override
        public V compute(K key,
                BiFunction<? super K, ? super V, ? extends V> remappingFunction) {
            synchronized (mutex) {return m.compute(key, remappingFunction);}
        }
        @Override
        public V merge(K key, V value,
                BiFunction<? super V, ? super V, ? extends V> remappingFunction) {
            synchronized (mutex) {return m.merge(key, value, remappingFunction);}
        }
        private void writeObject(ObjectOutputStream s) throws IOException {
            synchronized (mutex) {s.defaultWriteObject();}
        }
    }

这种方法与HashTable实现方式类似,也是锁住整表来实现同步的。而ConcurrentHashMap则避免了上述两种Map同步方式锁住全表的问题。

ConcurrentHashMap可以做到读取数据不加锁,并且其内部的结构可以让其在进行写操作的时候能够将锁的粒度保持尽量的小,不用对整个ConcurrentHashMap加锁。

ConcurrentHashMap内部结构

ConcurrentHashMap内部采用了一种叫segment的数据结构,很明显它就是一个哈希桶数组,数组的元素就是HashEntry。

在这里插入图片描述

ConcurrentHashMap比HashMap多了一次hash过程,第一次hash定位到Segment,第二次hash定位到HashEntry,然后链表搜索找到指定节点。

该实现方法的缺点是hash过程比普通的HashMap要长,但是优点也很明显,在进行写操作时,只需锁住写元素所在的Segment即可,其他Segment无需加锁,提高了并发读写的效率。

Segment

Segment继承了ReentrantLock并实现了序列化接口,说明Segment的锁是可以重入的。

在这里插入图片描述

    static final class Segment<K,V> extends ReentrantLock implements Serializable {
        transient volatile HashEntry<K,V>[] table;
        transient int count;
        transient int modCount;
        transient int threshold;
        final float loadFactor;

Segment的数据结构与普通的HashMap基本类似,只是通过继承ReentrantLock可实现线程安全的操作。

HashEntry

Segment中的元素是以HashEntry的形式存放在链表数组中的,其结构与普通HashMap的HashEntry基本一致,不同的是Segment的HashEntry的value由volatile修饰,以支持内存可见性,即写操作对其他读线程即时可见。

    static final class HashEntry<K,V> {
        final int hash;
        final K key;
        volatile V value;
        volatile HashEntry<K,V> next;
    }

ConcurrentHashMap构造器

//initialCapacity:初始容量
	//loadFactor:负载因子
	//concurrencyLevel:ConcurrentHashMap内部的Segment的数量
    public ConcurrentHashMap(int initialCapacity,
                             float loadFactor, int concurrencyLevel) {
        if (!(loadFactor > 0) || initialCapacity < 0 || concurrencyLevel <= 0)
            throw new IllegalArgumentException();
        //若concurrencyLevel大于MAX_SEGMENTS,则concurrencyLevel=MAX_SEGMENTS
        //保证最大并发不超过MAX_SEGMENTS(1<<16)
        if (concurrencyLevel > MAX_SEGMENTS)
            concurrencyLevel = MAX_SEGMENTS;
        //求解concurrencyLevel与2的几次方最近
        //如concurrencyLevel=5 则5与2^3=8最近 则sshift=8 ssize=3
        int sshift = 0;
        int ssize = 1;
        while (ssize < concurrencyLevel) {
            ++sshift;
            ssize <<= 1;
        }
        //segmentShift和segmentMask主要用于元素的hash
        this.segmentShift = 32 - sshift;
        this.segmentMask = ssize - 1;
        //ConcurrentHashMap初始容量不超过MAXIMUM_CAPACITY(1<<30)
        if (initialCapacity > MAXIMUM_CAPACITY)
            initialCapacity = MAXIMUM_CAPACITY;
        //根据ConcurrentHashMap总容量initialCapacity除以
        //Segment[]数组的长度得到单个分段锁segment中HashEntry[]的大小
        int c = initialCapacity / ssize;
        //保证分段锁segment的总容量c不小于初始的容量
        if (c * ssize < initialCapacity)
            ++c;
        int cap = MIN_SEGMENT_TABLE_CAPACITY;
        //cap为每个segment的初始容量,其值为离c天花板方向最近的2^n
        //例:c为5 cap为8 c为12 cap为16
        while (cap < c)
            cap <<= 1;
        // 创建Segment
        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;
    }

ConcurrentHashMap put()源码分析

put()方法向ConcurrentHashMap中添加元素

    public V put(K key, V value) {
        Segment<K,V> s;
        //value不能为空
        if (value == null)
            throw new NullPointerException();
        //计算key的hash值
        int hash = hash(key);
        //无符号右移segmentShift(默认16)位
        //然后& segmentMask(默认15)得到segment在内存中的位置
        int j = (hash >>> segmentShift) & segmentMask;
         如果Segment不存在,则调用ensureSegment方法
        if ((s = (Segment<K,V>)UNSAFE.getObject
             (segments, (j << SSHIFT) + SBASE)) == null) //  in ensureSegment
            //初始化segment
            s = ensureSegment(j);
        //放值
        return s.put(key, hash, value, false);
    }

Segment put()方法源码解析

        final V put(K key, int hash, V value, boolean onlyIfAbsent) {
        	// 尝试直接获取锁,获取到锁node为null,
        	//否则调用scanAndLockForPut方法
            HashEntry<K,V> node = tryLock() ? null :
                scanAndLockForPut(key, hash, value);
            V oldValue;
            try {
                HashEntry<K,V>[] tab = table;
                // 获取在tab数组中的位置
                int index = (tab.length - 1) & hash;
                // 得到链表的头节点
                HashEntry<K,V> first = entryAt(tab, index);
                // 遍历链表
                for (HashEntry<K,V> e = first;;) {
                    if (e != null) {
                        K k;
                        if ((k = e.key) == key ||
                            (e.hash == hash && key.equals(k))) {
                            oldValue = e.value;
                            if (!onlyIfAbsent) {
                                e.value = value;
                                ++modCount;
                            }
                            break;
                        }
                        e = e.next;
                    }
                    // 遍历到链表尾部,没有重复的key,则新插入
                    else {
                        if (node != null)
                        	// 头插法,将node节点设为链表头节点
                            node.setNext(first);
                        else
                        	// 为null,则新建一个节点
                            node = new HashEntry<K,V>(hash, key, value, first);
                        int c = count + 1;
                        // 若c超过阈值则扩容,并且数组长度小于MAXIMUM_CAPACITY = 1 << 30
                        if (c > threshold && tab.length < MAXIMUM_CAPACITY)
                        	// 扩容并进行重新hash
                            rehash(node);
                        else
                            setEntryAt(tab, index, node);
                        ++modCount;
                        count = c;
                        oldValue = null;
                        break;
                    }
                }
            } finally {
                unlock();
            }
            return oldValue;
        }

scanAndLockForPut

private HashEntry<K,V> scanAndLockForPut(K key, int hash, V value) {
	// 获取链表头结点
	HashEntry<K,V> first = entryForHash(this, hash);
	HashEntry<K,V> e = first;
	HashEntry<K,V> node = null;
	int retries = -1; // negative while locating node
	// 不断尝试获取锁
	while (!tryLock()) {
		HashEntry<K,V> f; // to recheck first below
		if (retries < 0) {
			// 链表的头结点为null,或者遍历到链表的尾部
			if (e == null) {
				// 这里加条件是因为,有可能已经初始化node节点了
				// 结果由于头结点改变重新遍历链表
				if (node == null) // speculatively create node
					node = new HashEntry<K,V>(hash, key, value, null);
				retries = 0;
			}
			// 找到相同key的节点
			else if (key.equals(e.key))
				retries = 0;
			// 没有找到key对应的节点,指向下一个节点
			else
				e = e.next;
		}
		// 可用处理器数量大于1,MAX_SCAN_RETRIES=64,否则为1
		else if (++retries > MAX_SCAN_RETRIES) {
			// 调用ReentrantLock中NonfairSync的lock()方法
			// 执行过程中有可能不阻塞获取到锁,也有可能被阻塞
			// 而不是之前的一直尝试直接获取锁
			lock();
			break;
		}
		// 链表的头结点发生变化,更新头结点,并重置retries值为-1
		else if ((retries & 1) == 0 &&
				 (f = entryForHash(this, hash)) != first) {
			e = first = f; // re-traverse if entry changed
			retries = -1;
		}
	}
	return node;
}

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