Exploring .NET 7’s Pipelines API for High-Performance IO

Quick Overview:
The growing tech development marketplace along with the growing competition requires the need for developing high-performance and efficient applications to survive the market and stay ahead of the competition. The IO or input/output operations here come to the rescue within the modern software development domain, as efficient handling of IO can help improve the overall performance of your .NET 7 app. The framework had introduced the Pipelines API within it for efficient handling of the IO operations.

The Pipelines API in DotNET 7 allows a streamlined approach to managing the IO operations to reduce memory allocations and improve the throughput. In this blog post, we will look into the details of the Pipelines API, take a glimpse at its benefits, and consider a few real-life implementations along with the performance advantages of Pipelines API.

Understanding the IO Performance Challenges

For businesses dealing with IO-intensive applications, there is a significant possibility to come across performance degrades under circumstances of high load on the disks. It is one of the most common challenges with traditional IO operations which often face the issue of latency and throughput issues, especially when dealing with large volumes of data or high-frequency operations.

The Blocking IO operations lead to significant delays whereas, the non-blocking operations, through more effective comparatively lead to complexities such as context switching, which can affect the performance.

The .NET framework offers a conventional approach to the IO which involves stream-based operations and asynchronous programming using the async/await. These methods have their perks but often lead to certain limitations in terms of efficiency and memory usage.

Before Pipelines, .NET developers initially were dependent on Stream class for IO operations. While the functional Stream required a complex boilerplate code, precisely when dealing with the fragmented data streams. To parse the data effectively complex logic was needed to handle the scenarios where a complete message was often not received in a single Read call. This led to issues in maintainability and performance.

Also Read: Difference Between .NET 7 and .NET 8

Introduction To Pipelines API

The Pipelines API turned out to be a fresh alternative to the traditional approach. It abstracts the complexities of data streams and presents an efficient and manageable approach to the IO. The Pipelines operate on sequences of memory segments, allowing your development team to process the data incrementally as it arrives. This frees you from the preallocation of large buffers and simplifies the handling of the fragmented data.

Advantages of Pipelines API

The Pipelines API presents a set of advantages for your development teams who aim for more control that are as follows:

• Performance Improvement: The optimized data processing and reduced context switching due to Pipeline API minimizes unnecessary memory allocations, improving the overall throughput and leading to performance gains.
• Asynchronous Operations: The Pipelines seamlessly integrate with the asynchronous programming paradigms, allowing your development teams to write non-blocking and efficient IO code.
• Reduced Allocations: The Pipelines reduce the memory allocations, thereby, reducing the amount of code required for the complex IO operations associated with managing the high volumes of data. This leads to a cleaner and more maintainable code.
• Flexibility: The Pipeline API offers a versatile foundation for building custom data processing pipelines tailored to your precise application development needs.

When To Use High-Performance Pipelines API in .NET 7

As the name suggests the high-performance Pipelines API is designed for performance-critical applications. However, there are other scenarios where these APIs can be efficiently used for sufficient and scalable processing of the data streams. The specific scenarios and considerations for using the High-Performance Pipelines API include:

• Performance-Centric Applications: For the apps that need real-time or near real-time data processing such as financial trading systems, telemetry, or analytics pipelines. Also, when building systems where low latency is crucial like high-frequency trading platforms or interactive applications, again an ideal use case for Pipelines API.
• IO Bound Applications: For apps that need to process large amounts of data or files efficiently, like log processing, media processing, or data import/export tasks. Also, the Pipelines API is a great choice when working with networks or file streams where you need to manage large data volumes with low latency.
• Memory Management: For applications requiring sensitivity to garbage collection, minimizing the heap allocations to improve performance. When you look for further control over buffer management to optimize performance like reusing the buffers to avoid unnecessary allocations.
• Custom Protocols and Data Formats: When you want to implement the custom serialization and deserialization routines for the proprietary data formats. For parsing the complex data structures efficiently from a byte stream.
• Networking Apps: For the servers you need to handle a large number of simultaneous connections like web servers, game servers, or chat apps. When implementing the protocols you need to read and write to the socket with minimal overhead, making the Pipelines API a great choice for networking applications.

When Not To Use Pipelines API

The Pipelines API is ideal when it comes to achieving peak performance with your business applications. However, there are certain cases when it is not advisable to use, these are as follows:

• Simple Apps: When you are building simple applications that are not performance-centric or are required to manage only small amounts of data, Pipelines API might be an overkill.
• High-Level Abstractions: For applications where the high-level abstractions such as ‘Stream’ and ‘HttpClient’ are efficient and performance is not an issue, Pipelines API is not a viable option.

Examples and Use Cases of .NET 7 Pipelines API

Below are a few use cases where using the .NET 7 Pipelines API for High-Performance IO can be of high efficiency.

Basic Data Processing Pipeline

In the below example, we will create a simple data processing pipeline that reads data from a source, processes it, and writes the processed data to a destination.

var pipe = new Pipe();
var writer = pipe.Writer;
var reader = pipe.Reader;

// Refer to the below code for Writer Task 
_ = Task.Run(async () =>
{
    for (int i = 0; i < 10; i++)
    {
        byte[] data = Encoding.UTF8.GetBytes($"Message {i}");
        await writer.WriteAsync(data);
    }
    writer.Complete();
});

// Below code is for the Reader Task
_ = Task.Run(async () =>
{
    while (true)
    {
        ReadResult result = await reader.ReadAsync();
        ReadOnlySequence<byte> buffer = result.Buffer;

        if (result.IsCompleted && buffer.Length == 0)
            break;

        foreach (var segment in buffer)
        {
            // The below code is to Process each segment
            Console.WriteLine(Encoding.UTF8.GetString(segment.Span));
        }

        reader.AdvanceTo(buffer.End);
    }
    reader.Complete();
});

File IO with Pipelines API

The example demonstrates how to read data from a file using the Pipelines API.

var pipe = new Pipe();
var writer = pipe.Writer;
var reader = pipe.Reader;

// Refer to the below code for Writer Task
_ = Task.Run(async () =>
{
    using (FileStream fs = new FileStream("input.txt", FileMode.Open, FileAccess.Read))
    {
        await fs.CopyToAsync(writer);
    }
    writer.Complete();
});

// Refer to the below code for Reader Task
_ = Task.Run(async () =>
{
    while (true)
    {
        ReadResult result = await reader.ReadAsync();
        ReadOnlySequence<byte> buffer = result.Buffer;

        if (result.IsCompleted && buffer.Length == 0)
            break;

        foreach (var segment in buffer)
        {
            // Refer to the below code to Process each segment
            Console.WriteLine(Encoding.UTF8.GetString(segment.Span));
        }

        reader.AdvanceTo(buffer.End);
    }
    reader.Complete();
});

Network IO with Pipelines API

In this code example, we will set up a simple server-client model using the Pipelines API to handle network streams.

var listener = new TcpListener(IPAddress.Any, 5000);
listener.Start();

_ = Task.Run(async () =>
{
    while (true)
    {
        var client = await listener.AcceptTcpClientAsync();
        _ = HandleClientAsync(client);
    }
});

async Task HandleClientAsync(TcpClient client)
{
    var pipe = new Pipe();
    var networkStream = client.GetStream();

    _ = FillPipeAsync(networkStream, pipe.Writer);
    await ReadPipeAsync(pipe.Reader);

    async Task FillPipeAsync(NetworkStream stream, PipeWriter writer)
    {
        while (true)
        {
            Memory<byte> memory = writer.GetMemory();
            int bytesRead = await stream.ReadAsync(memory);
            if (bytesRead == 0)
                break;

            writer.Advance(bytesRead);
            FlushResult result = await writer.FlushAsync();
            if (result.IsCompleted)
                break;
        }
        writer.Complete();
    }

    async Task ReadPipeAsync(PipeReader reader)
    {
        while (true)
        {
            ReadResult result = await reader.ReadAsync();
            ReadOnlySequence<byte> buffer = result.Buffer;

            if (result.IsCompleted && buffer.Length == 0)
                break;

            foreach (var segment in buffer)
            {
                // Refer to the below code to Process each segment
                Console.WriteLine(Encoding.UTF8.GetString(segment.Span));
            }

            reader.AdvanceTo(buffer.End);
        }
        reader.Complete();
    }
}

Conclusion

The .NET 7 Pipelines API presents a significant area for handling high-performance IO operations and achieving peak performance within the IO-bound applications. Reducing the memory allocations and optimizing the performance, the Pipelines API offers a powerful tool for developers to aim for building efficient, scalable applications. Embracing the Pipelines enables your development teams to craft cleaner, more efficient code while unlocking the full potential of your high-performance IO operations. As the .NET ecosystem is destined to grow within the market, the Pipelines are destined to become an indispensable tool for building performant and scalable .NET applications.