Скачать или смотреть Improving Performance with Parallel Processing of Async Tasks in C#

Discover how to efficiently process multiple async tasks simultaneously in C-, enhancing performance and reducing refresh times with our comprehensive guide!
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Mastering Concurrent Async Processing in C-: A Guide for Developers

In modern application development, particularly with C-, performance is a key factor that can significantly influence the user experience. For developers working with asynchronous programming, there are times when you might find your application sluggish, especially when waiting for one task to complete before starting another. A common scenario is processing multiple tasks within a foreach loop, which can feel painfully slow. Let's explore how to enhance this process by allowing tasks to be executed concurrently.

The Problem: Inefficient Async Processing

While implementing asynchronous methods can lead to better performance, mistakenly calling the await operator in your loops may inadvertently require tasks to complete one at a time, essentially negating the benefits of asynchronous programming. For instance, in the following code snippet, the application waits for GetIsConnected to resolve before checking if the item is connected and subsequently fetching additional details.

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In the code above, the Refresh function becomes slow because it waits for each item’s connection check to complete before processing the next item.

The Solution: Parallel Processing with Task Parallel Library

To tackle this inefficiency, we can leverage the Task Parallel Library (TPL) in C-. This allows us to run tasks concurrently rather than sequentially, significantly improving the overall refresh time of our application.

Step 1: Create a List for Tasks

First, we will set up a List to hold our tasks. During the iteration over the collection, rather than awaiting each operation, we will simply add them to this list.

Step 2: Await All Tasks Simultaneously

After adding all tasks to the list, we will call Task.WhenAll to await their completion collectively instead of individually. This change will boost performance by running these checks simultaneously.

The Refactored Code

Here’s the refactored code implementing the above improvements:

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Important Changes Explained

Return Type Change: The Refresh method is updated from async void to async Task. This change is recommended unless it is an event handler to ensure proper exception handling.

Task Creation: Each method call that requires awaiting is delegated to a separate method (GetCarDetails). This keeps the code organized and improves readability.

Using Task.WhenAll: By awaiting the collection of tasks (listOfTasks), you ensure that all operations complete before moving on, thereby allowing your application to manage multiple tasks in parallel effectively.

Conclusion

By implementing these strategies, not only do you improve the performance of your application, but you also maintain a clean and manageable code structure. Parallel processing of async tasks empowers developers to write efficient, responsive applications that provide a better user experience. Whether you're building a console application, a desktop app, or a web service, mastering async and concurrency will keep your applications running smoothly. Happy coding!