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The 30-Day .NET Challenge - Day 20: Task vs. ValueTaskby@ssukhpinder
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The 30-Day .NET Challenge - Day 20: Task vs. ValueTask

by Sukhpinder SinghApril 9th, 2024
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Heap allocations aren’t entirely bad but when an object is allocated on a heap it contributes to the garbage collection cycles which in turn reduces overall application performance. In case of excessive heap allocation, the garbage collector can lead to GC pauses. One approach to optimize resource usage in async code is by using ValueTask<T Result> syntax.
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Heap allocations aren’t entirely bad, but when an object is allocated on a heap, it contributes to the garbage collection cycles, which in turn reduces overall application performance.

Introduction

One approach to optimizing resource usage in async code is by using ValueTask<TResult> syntax to minimize heap allocations, which in turn reduces pressure on garbage collection and enhances overall performance.

Learning Objectives

  • The Problem with Heap Allocations
  • Optimizing with ValueTask<TResult>
  • When to Use ValueTask<TResult>

Prerequisites for Developers

  • Basic understanding of C# programming language.

Getting Started

Heap allocations aren’t entirely bad, but when an object is allocated on a heap, it contributes to the garbage collection cycles, which in turn reduces overall application performance. In the case of excessive heap allocation, the garbage collector can cause GC pauses.

Bad Practice: Excessive Use of Task<TResult>

Let’s consider a common asynchronous pattern that developers commonly use:

    public async Task<string> ReadDataAsync()
    {
        var data = await ReadFromStreamAsync(_stream);
        return ProcessData(data);
    }

If the above-mentioned method is called more frequently, each request results in a new Task instance being allocated on heap memory. Over time, it leads to increased garbage collection overhead.

Optimizing with ValueTask<TResult>

By changing the return type from Task<TResult> to ValueTask<TResult>, we can reduce heap allocations

    public async ValueTask<string> ReadDataAsync()
    {
        var data = await ReadFromStreamAsync(_stream);
        return ProcessData(data);
    }

The aforementioned optimization is beneficial for high-frequency async operations or methods that are expected to complete synchronously in a significant portion of time.

When to Use ValueTask<TResult>

  • High-frequency methods
  • Performance-sensitive code
  • Methods that often complete synchronously

Create another class named TaskVsValueTask and add the following code snippet

    public static class TaskVsValueTask
    {
        public static async Task<string> FetchDataAsync()
        {
            // Simulate a delay to mimic fetching data
            await Task.Delay(1000);
            return "Data fetched using Task";
        }
    
        public static async ValueTask<string> FetchDataValueTaskAsync()
        {
            // Simulate a delay to mimic fetching data
            await Task.Delay(1000); // Note: Use Task.Delay for the sake of example.
            return "Data fetched using ValueTask";
        }
    }

Execute from the main method as follows

    #region Day 20: Task vs. Value Task
    static async Task<string> ExecuteDay20()
    {
        Console.WriteLine("Fetching data with Task...");
        string result = await TaskVsValueTask.FetchDataAsync();
        Console.WriteLine(result);
    
        Console.WriteLine("Fetching data with ValueTask...");
        string resultValueTask = await TaskVsValueTask.FetchDataValueTaskAsync();
        Console.WriteLine(resultValueTask);
    
        return "Executed Day 20 successfully..!!";
    }
    #endregion

Console Output

    Fetching data with Task...
    Data fetched using Task
    Fetching data with ValueTask...
    Data fetched using ValueTask

Complete Code on GitHub

GitHub — ssukhpinder/30DayChallenge.Net

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