任务数据流，可以从完成状态更改数据块吗? [英] Task Dataflow, can a data block be changed from completion state?

问题描述

我想知道是否可以更改数据块的完成状态?

例如，我标记了一个 var block = new BufferBlock< int>(); 数据块，其中包含 block.Complete().该块链接到其他数据块.我想知道是否可以通过将 block 的完成状态更改回其原始！complete状态来使其再次运行.

如果不可能，那么如何执行多个运行(包括完成)，而不必a)取消链接所有块，b)重新实例化所有块，以及c)再次重新链接所有块?

有什么想法可以减轻运行数据流周期的任务，包括完成整个链下的每个块而不必重新创建整个框架?

谢谢

解决方案

不，您不能不完整"完成的数据流块.我认为您应该做的是在每条消息中添加一个标志，说明是否是运行中的最后一条消息.为了使使用起来更简单，您可以创建一组辅助方法，例如:

 公共静态TransformBlock< Tuple< TInput，bool>，Tuple< TOutput，bool>CreateEnhancedTransformBlock< TInput，TOutput>(Func< TInput，TOutput>变换){返回新的TransformBlock< Tuple< TInput，bool> ;, Tuple< TOutput，bool>(元组=>Tuple.Create(transform(tuple.Item1)，tuple.Item2));} 

这样，您输入一个仅处理 TInput 和 TOuput 的 transform 委托，并且标志与每个消息一起传输./p>

I would like to know whether it is possible to change the completion state of data blocks?

For example, I marked a var block = new BufferBlock<int>(); data block complete with block.Complete(). The block is linked to other data blocks. I would like to know whether I can make block run again by changing its completion state back to its original !complete state.

If that is not possible how could I perform multiple runs, including completion, without having to a) de-link all blocks, b) re-instantiate all blocks,and c) re-link all blocks again?

Any ideas which may ease the task of running data flow cycles including completing each block down the chain without having to re-create the whole framework?

Thanks

解决方案

No, you can't "uncomplete" a completed dataflow block. I think what you should do is to add a flag to each message that says whether it's last message in a run. To make it simpler to work with it, you could create set of helper methods like:

public static TransformBlock<Tuple<TInput, bool>, Tuple<TOutput, bool>>
    CreateEnhancedTransformBlock<TInput, TOutput>(Func<TInput, TOutput> transform)
{
    return new TransformBlock<Tuple<TInput, bool>, Tuple<TOutput, bool>>(
        tuple => Tuple.Create(transform(tuple.Item1), tuple.Item2));
}

This way, you enter a transform delegate that deals just with TInput and TOuput and the flag is transfered along with each message.

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