C#Parallel库,XmlReader,XmlWriter

Question

我有一个用例,我需要:

• 遍历Xml文档中的每个Input节点
• 对每个输入执行时间密集的计算,并且
• 将结果写入XML文件.

输入看起来像这样:

<Root>
  <Input>
    <Case>ABC123</Case>
    <State>MA</State>
    <Investor>Goldman</Investor>
  </Input>
  <Input>
    <Case>BCD234</Case>
    <State>CA</State>
    <Investor>Goldman</Investor>
  </Input>
</Root>

和输出:

<Results>
  <Output>
    <Case>ABC123</Case>
    <State>MA</State>
    <Investor>Goldman</Investor>
    <Price>75.00</Price>
    <Product>Blah</Product>
  </Output>
  <Output>
    <Case>BCD234</Case>
    <State>CA</State>
    <Investor>Goldman</Investor>
    <Price>55.00</Price>
    <Product>Ack</Product>
  </Output>
</Results>

我想并行运行计算; 典型的输入文件可能有50,000个输入节点,没有线程的总处理时间可能是90分钟.大约90%的处理时间花在步骤#2(计算)上.

我可以很容易地并行迭代XmlReader:

static IEnumerable<XElement> EnumerateAxis(XmlReader reader, string axis)
{
  reader.MoveToContent();
  while (reader.Read())
  {
    switch (reader.NodeType)
    {
      case XmlNodeType.Element:
        if (reader.Name == axis)
        {
          XElement el = XElement.ReadFrom(reader) as XElement;
          if (el != null)
            yield return el;
        }
        break;
    }
  }
}
...
Parallel.ForEach(EnumerateAxis(reader, "Input"), node =>
{ 
  // do calc
  // lock the XmlWriter, write, unlock
});

我当前倾向于在写入XmlWriter时使用锁来确保线程安全.

在这种情况下,是否有更优雅的方式来处理XmlWriter？具体来说,我应该让Parallel.ForEach代码将结果传递回原始线程并让该线程处理XmlWriter,避免需要锁定吗？如果是这样,我不确定对此的正确方法.

Answer 1

这是我最喜欢的问题:一个可以用管道解决的问题.

请注意,根据您的具体情况,这种方法实际上可能会对性能产生负面影响,但是当您明确询问如何在专用线程上使用编写器时,下面的代码正好说明了这一点.

免责声明:理想情况下,你应该考虑TPL数据流,但这不是我精通的东西所以我只是采取熟悉的Task+ BlockingCollection<T>路线.

起初我打算建议一个3阶段的管道(读取,处理,写入),但后来我意识到你已经将前两个阶段与你在读取节点时"流"节点的方式结合起来了.把它们喂给你Parallel.ForEach(是的,你已经实施了一系列的管道).更好 - 减少线程同步.

考虑到这一点,代码现在变为:

public class Result
{
    public string Case { get; set; }
    public string State { get; set; }
    public string Investor { get; set; }
    public decimal Price { get; set; }
    public string Product { get; set; }
}

...

using (var reader = CreateXmlReader())
{
    // I highly doubt that this collection will
    // ever reach its bounded capacity since
    // the processing stage takes so long,
    // but in case it does, Parallel.ForEach
    // will be throttled.
    using (var handover = new BlockingCollection<Result>(boundedCapacity: 100))
    {
        var processStage = Task.Run(() =>
        {
            try
            {
                Parallel.ForEach(EnumerateAxis(reader, "Input"), node =>
                {
                    // Do calc.
                    Thread.Sleep(1000);

                    // Hand over to the writer.
                    // This handover is not blocking (unless our 
                    // blocking collection has reached its bounded
                    // capacity, which would indicate that the
                    // writer is running slower than expected).
                    handover.Add(new Result());
                });
            }
            finally
            {
                handover.CompleteAdding();
            }
        });

        var writeStage = Task.Run(() =>
        {
            using (var writer = CreateXmlReader())
            {
                foreach (var result in handover.GetConsumingEnumerable())
                {
                    // Write element.
                }
            }
        });

        // Note: the two stages are now running in parallel.
        // You could technically use Parallel.Invoke to
        // achieve the same result with a bit less code.
        Task.WaitAll(processStage, writeStage);
    }
}