Are you looking to optimize your ASP.NET Core API’s performance and make it more responsive? If you’re using Dapper as your ORM (Object-Relational Mapping) library, there’s a powerful feature in C# 8 that you can leverage to achieve this: IAsyncEnumerable. In this blog post, we’ll explore how you can use IAsyncEnumerable with Dapper to improve the streaming of data in your API endpoints.
Introduction
Recently, we migrated our ASP.NET Core API to .NET Core 3.1 and took the opportunity to explore the latest features available. One such feature that caught our attention was IAsyncEnumerable, introduced in C# 8. This interface allows you to work with asynchronous streams of data, which can be particularly beneficial when dealing with large datasets or slow database operations.
The Challenge: Dapper and IEnumerable
Dapper is a popular lightweight ORM library that provides fast and efficient data access for .NET applications. However, by default, Dapper returns data as IEnumerable, which is synchronous and not ideal for streaming large datasets. This limitation prompted us to investigate whether we could utilize IAsyncEnumerable to enhance the streaming capabilities of Dapper.
The Solution: Leveraging IAsyncEnumerable
Fortunately, with a few modifications to our code, we were able to leverage IAsyncEnumerable and streamline the streaming process in our API. Let’s walk through the necessary steps to achieve this.
Import the System.Linq.Async NuGet Package
To use IAsyncEnumerable, you’ll need to import the System.Linq.Async NuGet package into your project. This package extends the functionality of LINQ (Language Integrated Query) to support asynchronous operations.
Update Your Endpoint Method
In your API endpoint method, where you retrieve data using Dapper, modify the method signature to return IAsyncEnumerable instead of Task<IEnumerable>. This change signals that the method will now stream data asynchronously.
Update the Streaming Code
Inside the modified method, after retrieving the data using Dapper’s QueryMultipleAsync method, we’ll need to make a few adjustments to enable the streaming. First, ensure that you retrieve the data in an unbuffered manner by setting the buffered parameter to false in the ReadAsync method.
Next, instead of using the IEnumerable returned by Dapper, we’ll convert it to an IAsyncEnumerable using the ToAsyncEnumerable extension method provided by the System.Linq.Async package. This conversion is necessary to enable the asynchronous streaming of data.
Implement the Streaming Logic
Finally, we’ll implement the streaming logic using the await foreach construct, which allows us to iterate asynchronously over the items in the IAsyncEnumerable. Inside the loop, we can process each item as it becomes available, improving the responsiveness of our API.
Conclusion
By utilizing IAsyncEnumerable with Dapper in your ASP.NET Core API, you can significantly enhance the streaming capabilities of your endpoints. This improvement allows you to handle large datasets and slow database operations more efficiently, resulting in a more responsive and performant API.
Remember, adopting new features and optimizing your codebase is an ongoing process. Stay up to date with the latest developments in C# and regularly review your code to identify areas where you can leverage new language features and libraries to improve your application’s performance.
We hope you found this blog post helpful. If you have any questions or insights to share, please leave a comment below.
