C#异步编程(五)异步的同步构造

2021-07-13 00:07

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异步的同步构造

  任何使用了内核模式的线程同步构造,我都不是特别喜欢。因为所有这些基元都会阻塞一个线程的运行。创建线程的代价很大。创建了不用,这于情于理说不通。

  创建了reader-writer锁的情况,如果写锁被长时间占有,那么其他的读请求线程都会被阻塞,随着越来越多客户端请求到达,服务器创建了更多的线程,而他们被创建出来的目的就是让他们在锁上停止运行。更糟糕的是,一旦writer锁释放,所有读线程都同时解除阻塞并开始执行。现在,又变成大量的线程试图在相对数量很少的cpu上运行。所以,windows开始在线程之间不同的进行上下文切换,而真正的工作时间却很少。

       锁很流行,但长时间拥有会带来巨大的伸缩性问题。如果代码能通过异步的同步构造指出他想要一个锁,那么会非常有用。在这种情况下,如果线程得不到锁,可直接返回并执行其他工作,而不必在那里傻傻地阻塞。

       SemaphoreSlim通过waitAsync实现了这个思路

public Task WaitAsync(int millisecondsTimeout, CancellationToken cancellationToken);

使用await asynclock.WaitAsync()就可以实现刚才说的情境。

       但如果是reader-writer呢?.net framework提供了concurrentExclusiveSchedulerPair类。实例代码如下:

private static void ConcurrentExclusiveSchedulerDemo()
{
    var cesp = new ConcurrentExclusiveSchedulerPair();
    var tfExclusive = new TaskFactory(cesp.ExclusiveScheduler);
    var tfConcurrent = new TaskFactory(cesp.ConcurrentScheduler);

    for (int i = 0; i 5; i++)
    {
        var exclusive = i 2;
        (exclusive ? tfExclusive : tfConcurrent).StartNew(() =>
        {
            Console.WriteLine("{0} access",exclusive?"exclusive":"concurrent");
            //这里进行独占写入或者并发读取操作
        });
    }
}

       遗憾的是,framework没有提供鞠咏reader-writer语义的异步锁。所以我们可以自己构建一个,如下:

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public sealed class AsyncOneManyLock
{
    #region 锁的代码
    //自旋锁不要用readonly
    private SpinLock m_lock = new SpinLock(true);

    private void Lock()
    {
        bool taken = false;m_lock.Enter(ref taken);
    }
    private void Unlock()
    {
        m_lock.Exit();
    }

    #endregion

    #region 锁的状态和辅助方法

    private Int32 m_state = 0;
    private bool IsFree { get { return m_state == 0; } }
    private bool IsOwnedByWriter { get { return m_state == -1; } }
    private bool IsOwnedByReader { get { return m_state > 0; } }
    private Int32 AddReaders(Int32 count) { return m_state += count; }
    private Int32 SubtractReader() { return --m_state; }
    private void MakeWriter() { m_state = -1; }
    private void MakeFree() { m_state = 0; }

    #endregion

    //目的实在非竞态条件时增强性能和减少内存消耗
    private readonly Task m_noContentionAccessGranter;
    //每个等待的writer都通过他们在这里排队的TaskCompletionSource来唤醒
    private readonly Queue> m_qWaitingWriters = new Queueobject>>();
    //一个TaskCompletionSource收到信号,所有等待的reader都唤醒
    private TaskCompletionSource m_waitingReaderSignal = new TaskCompletionSourceobject>();
    private Int32 m_numWaitingReaders = 0;
    public AsyncOneManyLock()
    {
        //创建一个返回null的任务
        m_noContentionAccessGranter = Task.FromResult(null);
    }
    public Task WaitAsync(OneManyMode mode)
    {
        Task accressGranter = m_noContentionAccessGranter;//假定无竞争
        Lock () ;
        switch (mode)
        {
            case OneManyMode.Exclusive:
                if (IsFree)
                {
                    MakeWriter();//无竞争
                }
                else
                {
                    //有竞争
                    var tcs = new TaskCompletionSource();
                    m_qWaitingWriters.Enqueue(tcs);
                    accressGranter = tcs.Task;
                }
                break;
            case OneManyMode.Shared:
                if (IsFree||(IsOwnedByReader&&m_qWaitingWriters.Count==0))
                {
                    AddReaders(1);//无竞争
                }
                else
                {
                    //有竞争,递增等待的reader数量,并返回reader任务使reader等待。
                    m_numWaitingReaders++;
                    accressGranter = m_waitingReaderSignal.Task.ContinueWith(t => t.Result);
                }
                break;
        }
        Unlock();
        return accressGranter;
    }

    public void Release()
    {
        //嘉定没有代码被释放
        TaskCompletionSource accessGranter = null;
        Lock () ;
        if (IsOwnedByWriter)
        {
            MakeFree();
        }
        else
        {
            SubtractReader();
        }
        if (IsFree)
        {
            //如果自由,唤醒一个等待的writer或所有等待的readers
            if (m_qWaitingWriters.Count>0)
            {
                MakeWriter();
                accessGranter = m_qWaitingWriters.Dequeue();
            }
            else if (m_numWaitingReaders>0)
            {
                AddReaders(m_numWaitingReaders);
                m_numWaitingReaders = 0;
                accessGranter = m_waitingReaderSignal;
                //为将来需要等待的readers创建一个新的tcs
                m_waitingReaderSignal = new TaskCompletionSourceobject>();
            }
        }
        Unlock();
        //唤醒锁外面的writer/reader,减少竞争几率以提高性能
        if (accessGranter!=null)
        {
            accessGranter.SetResult(null);
        }
    }
}
AsyncOneManyLock

       上述代码永远不会阻塞线程。原因是内部没有没有很实用任何内核构造。这里确实使用了一个SpinLock,它在内部使用了用户模式构造。但是他的执行时间很短,WaitAsync方法里,只是一些整数计算和比较,这也符合只有执行时间很短的代码段才可以用自旋锁来保护。所以使用一个spinLock来保护对queue的访问,还是比较合适的。

并发集合类

       FCL自带4个线程安全的集合类,全部在System.Collections.Concurrent命名空间中定义。它们是ConcurrentStack、concurrentQueue、concurrentDictionary、concurrentBag。

所有这些集合都是“非阻塞”的,换而言之,如果一个线程试图提取一个不存在的元素(数据项),线程会立即返回;线程不会阻塞在那里,等着一个元素的出现。正是由于这个原因,所以如果获取了一个数据项,像tryDequeue,tryPop,tryTake和tryGetValue这样的方法全部返回true;否则返回false。

       一个集合“非阻塞”,并不意味着他就不需要锁了。concurrentDictionary类在内部使用了Monitor。但是,对集合中的项进行操作时,锁只被占有极短的时间。concurrentQueue和ConcurrentStack确实不需要锁;他们两个在内部都使用interlocked的方法来操纵集合。一个concurrentBag对象由大量迷你集合对象构成,每个线程一个。线程将一个项添加到bag中时,就用interlocked的方法将这个项添加到调用线程的迷你集合中。一个线程视图从bag中提取一个元素时,bag就检查调用线程的迷你集合,试图从中取出数据项。如果数据项在哪里,就用一个interlocked方法提取这个项。如果不在,就在内部获取一个monitor,以便从 线程的迷你集合提取一个项。这称为一个线程从另一个线程“窃取”一个数据项。

       注意,所有并发集合类都提供了getEnumerator方法,他一般用于C#的foreach语句,但也可用于Linq。对于concurrentQueue、ConcurrentStack和concurrentBag类,getEnumerator方法获取集合内容的一个“快照”,并从这个快照中返回元素;实际集合内容可能在使用快照枚举时发生改变。concurrentDictionary的getEnumerator的该方法不获取他内容的快照。因此,在枚举字典期间,字典的内容可能改变。还要注意,count属性返回的是查询时集合中的元素数量,如果其他线程同时正在集合中增删,这个计数可能马上就变得不正确。

       ConcurrentStack、concurrentQueue、concurrentBag都实现了IProducerConsumerCollection接口,实现了这个接口的任何类都能转变成一个阻塞集合,不过,尽量不使用这种阻塞集合。

       这里我们重点介绍下concurrentDictionary。

ConcurrentDictionary

       这里我对.net core中ConcurrentDictionary源码进行了分析,里面采用了Volatile.Read和write,然后也使用了lock这种混合锁,而且还定义了更细颗粒度的锁。所以多线程使用ConcurrentDictionary集合还是比较好的选择。

TryRemove

这个方法会调用内部私用的TryRemoveInternal

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private bool TryRemoveInternal(TKey key, out TValue value, bool matchValue, TValue oldValue)
{
    int hashcode = _comparer.GetHashCode(key);
    while (true)
    {
        Tables tables = _tables;
        int bucketNo, lockNo;
        //这里获取桶的索引和锁的索引,注意,锁的索引和桶未必是同一个值,具体算法看源码。
        GetBucketAndLockNo(hashcode, out bucketNo, out lockNo, tables._buckets.Length, tables._locks.Length);
        //这里锁住的只是对应这个index指向的锁,而不是所有锁。
        lock (tables._locks[lockNo])
        {
            //这里table可能被重新分配,所以这里再次获取,看得到的是不是同一个table
            // If the table just got resized, we may not be holding the right lock, and must retry.
            // This should be a rare occurrence.
            if (tables != _tables)
            {
                continue;
            }

            Node prev = null;
            //这里同一个桶,可能因为连地址,有很多值,所以要对比key
            for (Node curr = tables._buckets[bucketNo]; curr != null; curr = curr._next)
            {
                Debug.Assert((prev == null && curr == tables._buckets[bucketNo]) || prev._next == curr);
                //对比是不是要删除的的那个元素
                if (hashcode == curr._hashcode && _comparer.Equals(curr._key, key))
                {
                    if (matchValue)
                    {
                        bool valuesMatch = EqualityComparer.Default.Equals(oldValue, curr._value);
                        if (!valuesMatch)
                        {
                            value = default(TValue);
                            return false;
                        }
                    }
                    //执行删除,判断有没有上一个节点。然后修改节点指针或地址。
                    if (prev == null)
                    {
                        Volatile.Write(ref tables._buckets[bucketNo], curr._next);
                    }
                    else
                    {
                        prev._next = curr._next;
                    }

                    value = curr._value;
                    tables._countPerLock[lockNo]--;
                    return true;
                }
                prev = curr;
            }
        }
        value = default(TValue);
        return false;
    }
}
TryRemoveInternal

TryAdd

这个方法会调用内部私用的TryAddInternal

TryAddInternal(key, _comparer.GetHashCode(key), value, false, true, out dummy);

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/// 
/// Shared internal implementation for inserts and updates.
/// If key exists, we always return false; and if updateIfExists == true we force update with value;
/// If key doesn‘t exist, we always add value and return true;
/// 
private bool TryAddInternal(TKey key, int hashcode, TValue value, bool updateIfExists, bool acquireLock, out TValue resultingValue)
{
    Debug.Assert(_comparer.GetHashCode(key) == hashcode);
    while (true)
    {
        int bucketNo, lockNo;
        Tables tables = _tables;
//老方法了,不多说,获取hash索引和锁索引
        GetBucketAndLockNo(hashcode, out bucketNo, out lockNo, tables._buckets.Length, tables._locks.Length);
        bool resizeDesired = false;
        bool lockTaken = false;
        try
        {
            //这里都是true的,所以会获取锁
            if (acquireLock)
                Monitor.Enter(tables._locks[lockNo], ref lockTaken);

            // If the table just got resized, we may not be holding the right lock, and must retry.
            // This should be a rare occurrence.
            if (tables != _tables)
            {
                continue;
            }

            // Try to find this key in the bucket
            Node prev = null;
            //查看对应的桶里,
            for (Node node = tables._buckets[bucketNo]; node != null; node = node._next)
            {
                Debug.Assert((prev == null && node == tables._buckets[bucketNo]) || prev._next == node);
                //查看有没有相同的key值,有就返回false
                if (hashcode == node._hashcode && _comparer.Equals(node._key, key))
                {
                    // The key was found in the dictionary. If updates are allowed, update the value for that key.
                    // We need to create a new node for the update, in order to support TValue types that cannot
                    // be written atomically, since lock-free reads may be happening concurrently.
                    //这个应该是addorupdate使用的,存在就更新。
                    if (updateIfExists)
                    {
                        if (s_isValueWriteAtomic)
                        {
                            node._value = value;
                        }
                        else
                        {
                            Node newNode = new Node(node._key, value, hashcode, node._next);
                            if (prev == null)
                            {
                                Volatile.Write(ref tables._buckets[bucketNo], newNode);
                            }
                            else
                            {
                                prev._next = newNode;
                            }
                        }
                        resultingValue = value;
                    }
                    else
                    {
                        resultingValue = node._value;
                    }
                    return false;
                }
                prev = node;
            }
            
            // The key was not found in the bucket. Insert the key-value pair.
            Volatile.Write(ref tables._buckets[bucketNo], new Node(key, value, hashcode, tables._buckets[bucketNo]));
            //这里checked检查是否存在溢出。
            checked
            {
                tables._countPerLock[lockNo]++;
            }
            // If the number of elements guarded by this lock has exceeded the budget, resize the bucket table.
            // It is also possible that GrowTable will increase the budget but won‘t resize the bucket table.
            // That happens if the bucket table is found to be poorly utilized due to a bad hash function.
            // _budget是 The maximum number of elements per lock before a resize operation is triggered
            if (tables._countPerLock[lockNo] > _budget)
            {
                resizeDesired = true;
            }
        }
        finally
        {
            if (lockTaken)
                Monitor.Exit(tables._locks[lockNo]);
        }
        // The fact that we got here means that we just performed an insertion. If necessary, we will grow the table.
        //
        // Concurrency notes:
        // - Notice that we are not holding any locks at when calling GrowTable. This is necessary to prevent deadlocks.
        //As a result, it is possible that GrowTable will be called unnecessarily. But, GrowTable will obtain lock 0

        //   and then verify that the table we passed to it as the argument is still the current table.
        if (resizeDesired)
        {
            GrowTable(tables);
        }
//赋值
        resultingValue = value;
        return true;
    }
}
TryAddInternal

TryGetValue

TryGetValueInternal(key, _comparer.GetHashCode(key), out value);

 

private bool TryGetValueInternal(TKey key, int hashcode, out TValue value)
{
    Debug.Assert(_comparer.GetHashCode(key) == hashcode);
    //用本地变量保存这个table的快照。
    // We must capture the _buckets field in a local variable. It is set to a new table on each table resize.
    Tables tables = _tables;
    int bucketNo = GetBucket(hashcode, tables._buckets.Length);
    // We can get away w/out a lock here.
    // The Volatile.Read ensures that we have a copy of the reference to tables._buckets[bucketNo].
    // This protects us from reading fields (‘_hashcode‘, ‘_key‘, ‘_value‘ and ‘_next‘) of different instances.
Node n = Volatile.Read(ref tables._buckets[bucketNo]);
//如果key相符 ,赋值,不然继续寻找下一个。
    while (n != null)
    {
        if (hashcode == n._hashcode && _comparer.Equals(n._key, key))
        {
            value = n._value;
            return true;
        }
        n = n._next;
    }
    value = default(TValue);//没找到就赋默认值
    return false;
}

 

C#异步编程(五)异步的同步构造

标签:aac   dea   span   consumer   添加   result   伸缩性   display   free   

原文地址:https://www.cnblogs.com/qixinbo/p/9591333.html


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