How to Effectively Use async/await for Optimistic Concurrency in ASP.NET Core

This guide explains how to properly implement `async/await` for handling optimistic concurrency in ASP.NET Core applications, ensuring data integrity when multiple users are updating records.
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Optimizing Data Updates with async/await in ASP.NET Core

When working with data in modern applications, especially in ASP.NET Core, maintaining data integrity during updates is vital. A specific challenge developers often face is handling optimistic concurrency effectively. This guide will explore how to implement async/await for your database operations, with a focus on preventing concurrency issues when multiple users attempt to update the same record.

Understanding the Problem

Optimistic concurrency allows developers to manage data updates without locking out other users. However, it can lead to data integrity issues if not managed correctly. Here's a brief scenario to illustrate this problem:

User A and User B both retrieve the same record for editing.

User A changes a field (e.g., a name) and saves it.

User B changes a different field (e.g., a description) and saves it afterward, without realizing User A's changes have already been saved.

In this situation, if there’s no concurrency check, User B's changes could overwrite those made by User A, leading to data loss. This is where implementing a row version as a concurrency check becomes crucial.

The Solution: Async Handling of Updates

To ensure that concurrent updates are handled gracefully, we’ll modify the existing code to check for concurrency while allowing for asynchronous operations. Below is a revised version of the code snippet you provided. We will focus on the key differences to handle optimistic concurrency properly.

Step 1: Fetching the Job Entity

First, we need to fetch the job entity from the database asynchronously to ensure we are working with the most recent data.

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This line retrieves the job entity from the database, ensuring that we have the current state before any updates are applied.

Step 2: Validating Row Version for Concurrency

Next, we’ll implement a check for the row version:

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This check makes sure the data hasn’t changed since it was fetched. If the row version from the database doesn't match the one from the view model, it indicates that another user has done an update in the meantime. You can handle this scenario in various ways, such as notifying the user or logging the conflict.

Step 3: Mapping Updates

Using AutoMapper, you can easily handle data mapping with a single line of code. This simplifies updating the fields you want to change without needing to manually specify which fields should be updated:

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This allows your changes to be reflected only in the necessary columns based on what's been altered.

Step 4: Saving Changes Asynchronously

Finally, save the changes back to the database asynchronously to complete the operation:

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By using async/await, you ensure your application remains responsive and can handle multiple concurrent requests efficiently.

Conclusion

Using async/await in ASP.NET Core applications can provide not only performance benefits but also help enforce data integrity when multiple users are editing records. By managing optimistic concurrency with row version checks, you can avoid silent data overwrites and provide a better user experience.

Feel free to implement these strategies in your own projects to improve data handling and ensure robustness in your applications.

For further reading on this topic, consider looking into additional resources on Entity Framework Core and concurrency handling.