How to use the TPL Dataflow library to implement a producer-consumer pattern?

How to use the TPL Dataflow library to implement a producer-consumer pattern?

This document describes how to use the TPL Dataflow Library to implement a producer-consumer pattern. In this pattern, the producer sends messages to a message block, and the consumer reads messages from that block. The TPL Dataflow Library (the System.Threading.Tasks.Dataflow namespace) is not distributed with .NET.

How to install the TPL Dataflow library in Visual Studio?

The TPL Dataflow Library (the System.Threading.Tasks.Dataflow namespace) is not distributed with .NET. To install the System.Threading.Tasks.Dataflow namespace in Visual Studio, open your project, choose Manage NuGet Packages from the Project menu, and search online for the System.Threading.Tasks.Dataflow package.

How to queue producer and consumer in dataflow?

Our producer can just enqueue a sequence of values, and then mark the queue as complete: Similarly, the consumer can just await until a value is ready in the queue, and then add it to its collection of received values.

Why is TPL a good tool for parallel workflow?

The TPL DataFlow is a great tool for implementing this pattern, because it has intrinsic support for multiple readers and multiple writers concurrently, and it encourages a pipeline pattern of programming, with producers sending messages to decoupled consumers

How does the.NET Task Parallel Library ( TPL ) work?

The TPL DataFlow library eases concurrent processing and implements tailored asynchronous parallel workflow and batch queuing. Furthermore, it facilitates the implementation of sophisticated patterns based on combining multiple components that talk to each other by passing messages.

What does the TPL Dataflow bufferblock do?

The TPL DataFlow BufferBlock acts as a buffer for data. Such data is stored in a first in, first out (FIFO) order. In general, the BufferBlock is a great tool for enabling and implementing asynchronous Producer/Consumer patterns, where the internal message queue can be written to by multiple sources, or read from multiple targets.