问题
I have implemented a producer..consumer pattern using TPL data flow. The use case is that code reads messages from the Kafka bus. For efficiency, we need to process messages in batches when going to the database.
Is there a way in TPL data flow to hold on to the message and fire whenever a size or duration threshold is hit?
Example, the current implementation post the message once it is pulled from the queue.
postedSuccessfully = targetBuffer.Post(msg.Value);
回答1:
Buffering by count and duration is already available through the System.Reactive and specifically, the Buffer operator. Buffer collects incoming events until either the desired count is reached or its timespan expires.
Dataflow blocks are designed to work with System.Reactive. Blocks can be converted to Observables and Observers by using the DataflowBlock.AsObservable() and AsObserver() extension methods.
This makes building a buffering block very easy :
public static IPropagatorBlock<TIn,IList<TIn>> CreateBuffer<TIn>(TimeSpan timeSpan,int count)
{
var inBlock = new BufferBlock<TIn>();
var outBlock = new BufferBlock<IList<TIn>>();
var outObserver=outBlock.AsObserver();
inBlock.AsObservable()
.Buffer(timeSpan, count)
.ObserveOn(TaskPoolScheduler.Default)
.Subscribe(outObserver);
return DataflowBlock.Encapsulate(inBlock, outBlock);
}
This method uses two buffer blocks to buffer inputs and outputs. Buffer() reads from the input block (the observable) and writes to the output block (the observer) when either the batch is full or the timespan expires.
By default, Rx works on the current thread. By calling ObserveOn(TaskPoolScheduler.Default) we tell it to process data on a Task pool thread.
Example
This code creates a buffer block for 5 items or 1 second. It starts by posting 7 items, waits 1.1 seconds then posts another 7 items. Each batch is written to the console together with the thread ID :
static async Task Main(string[] args)
{
//Build the pipeline
var bufferBlock = CreateBuffer<string>(TimeSpan.FromSeconds(1), 5);
var options = new DataflowLinkOptions { PropagateCompletion = true };
var printBlock = new ActionBlock<IList<string>>(items=>printOut(items));
bufferBlock.LinkTo(printBlock, options);
//Start the messages
Console.WriteLine($"Starting on {Thread.CurrentThread.ManagedThreadId}");
for (int i=0;i<7;i++)
{
bufferBlock.Post(i.ToString());
}
await Task.Delay(1100);
for (int i=7; i < 14; i++)
{
bufferBlock.Post(i.ToString());
}
bufferBlock.Complete();
Console.WriteLine($"Finishing");
await bufferBlock.Completion;
Console.WriteLine($"Finished on {Thread.CurrentThread.ManagedThreadId}");
Console.ReadKey();
}
static void printOut(IEnumerable<string> items)
{
var line = String.Join(",", items);
Console.WriteLine($"{line} on {Thread.CurrentThread.ManagedThreadId}");
}
The output is :
Starting on 1
0,1,2,3,4 on 4
5,6 on 8
Finishing
7,8,9,10,11 on 8
12,13 on 6
Finished on 6
回答2:
I guess you could use something like this, Basically its just BatchBlock with a Timeout all rolled in to one
BatchBlockEx
public sealed class BatchBlockEx<T> : IDataflowBlock, IPropagatorBlock<T, T[]>, ISourceBlock<T[]>, ITargetBlock<T>, IReceivableSourceBlock<T[]>
{
private readonly AsyncAutoResetEvent _asyncAutoResetEvent = new AsyncAutoResetEvent();
private readonly BatchBlock<T> _base;
private readonly CancellationToken _cancellationToken;
private readonly int _triggerTimeMs;
public BatchBlockEx(int batchSize, int triggerTimeMs)
{
_triggerTimeMs = triggerTimeMs;
_base = new BatchBlock<T>(batchSize);
PollReTrigger();
}
public BatchBlockEx(int batchSize, int triggerTimeMs, GroupingDataflowBlockOptions dataflowBlockOptions)
{
_triggerTimeMs = triggerTimeMs;
_cancellationToken = dataflowBlockOptions.CancellationToken;
_base = new BatchBlock<T>(batchSize, dataflowBlockOptions);
PollReTrigger();
}
public int BatchSize => _base.BatchSize;
public int OutputCount => _base.OutputCount;
public Task Completion => _base.Completion;
public void Complete() => _base.Complete();
void IDataflowBlock.Fault(Exception exception) => ((IDataflowBlock)_base).Fault(exception);
public IDisposable LinkTo(ITargetBlock<T[]> target, DataflowLinkOptions linkOptions) => _base.LinkTo(target, linkOptions);
T[] ISourceBlock<T[]>.ConsumeMessage(DataflowMessageHeader messageHeader, ITargetBlock<T[]> target, out bool messageConsumed) => ((ISourceBlock<T[]>)_base).ConsumeMessage(messageHeader, target, out messageConsumed);
void ISourceBlock<T[]>.ReleaseReservation(DataflowMessageHeader messageHeader, ITargetBlock<T[]> target) => ((ISourceBlock<T[]>)_base).ReleaseReservation(messageHeader, target);
bool ISourceBlock<T[]>.ReserveMessage(DataflowMessageHeader messageHeader, ITargetBlock<T[]> target) => ((ISourceBlock<T[]>)_base).ReserveMessage(messageHeader, target);
DataflowMessageStatus ITargetBlock<T>.OfferMessage(DataflowMessageHeader messageHeader, T messageValue, ISourceBlock<T> source, bool consumeToAccept)
{
_asyncAutoResetEvent.Set();
return ((ITargetBlock<T>)_base).OfferMessage(messageHeader, messageValue, source, consumeToAccept);
}
public bool TryReceive(Predicate<T[]> filter, out T[] item) => _base.TryReceive(filter, out item);
public bool TryReceiveAll(out IList<T[]> items) => _base.TryReceiveAll(out items);
public override string ToString() => _base.ToString();
public void TriggerBatch() => _base.TriggerBatch();
private void PollReTrigger()
{
async Task Poll()
{
try
{
while (!_cancellationToken.IsCancellationRequested)
{
await _asyncAutoResetEvent.WaitAsync()
.ConfigureAwait(false);
await Task.Delay(_triggerTimeMs, _cancellationToken)
.ConfigureAwait(false);
TriggerBatch();
}
}
catch (TaskCanceledException)
{
// nope
}
}
Task.Run(Poll, _cancellationToken);
}
}
AsyncAutoResetEvent
public class AsyncAutoResetEvent
{
private static readonly Task _completed = Task.FromResult(true);
private readonly Queue<TaskCompletionSource<bool>> _waits = new Queue<TaskCompletionSource<bool>>();
private bool _signaled;
public Task WaitAsync()
{
lock (_waits)
{
if (_signaled)
{
_signaled = false;
return _completed;
}
var tcs = new TaskCompletionSource<bool>();
_waits.Enqueue(tcs);
return tcs.Task;
}
}
public void Set()
{
TaskCompletionSource<bool> toRelease = null;
lock (_waits)
if (_waits.Count > 0)
toRelease = _waits.Dequeue();
else if (!_signaled)
_signaled = true;
toRelease?.SetResult(true);
}
}
回答3:
While there is no out of the box timeout you can wire up a timer to TriggerBatch whenever the downstream pipeline has waited long enough for a batch. Then reset the timer when ever a batch is flowed through. The BatchBlock will take care of the rest for you.
Now for example, this sample has been configure to cause a batch size of 1 everytime even though the batch block would normally be waiting for 10 elements. The timeout forces emptying whatever is currently stored in the BatchBlock
public class BatchBlockExample
{
[Test]
public async Task BatchBlockWithTimeOut()
{
var batchBlock = new BatchBlock<int>(10);
var timeOut = TimeSpan.FromSeconds(1);
var timeOutTimer = new System.Timers.Timer(timeOut.TotalMilliseconds);
timeOutTimer.Elapsed += (s, e) => batchBlock.TriggerBatch();
var actionBlock = new ActionBlock<IEnumerable<int>>(x =>
{
//Reset the timeout since we got a batch
timeOutTimer.Stop();
timeOutTimer.Start();
Console.WriteLine($"Batch Size: {x.Count()}");
});
batchBlock.LinkTo(actionBlock, new DataflowLinkOptions() { PropagateCompletion = true });
timeOutTimer.Start();
foreach(var item in Enumerable.Range(0, 5))
{
await Task.Delay(2000);
await batchBlock.SendAsync(item);
}
batchBlock.Complete();
await actionBlock.Completion;
}
}
Output:
Batch Size: 1
Batch Size: 1
Batch Size: 1
Batch Size: 1
Batch Size: 1
来源：https://stackoverflow.com/questions/52633346/tpl-dataflow-batching-on-duration-or-threshold