Pessimistic Concurrency Control

Managing Concurrency in Entity Framework: A Comprehensive Guide to Pessimistic Concurrency Control

Entity Framework is a powerful object-relational mapping (ORM) library that provides developers with an easy way to access and manage data in their applications. One of the key challenges when working with data is managing concurrency, and Entity Framework provides several options for tackling this issue.

In this guide, we’ll explore pessimistic concurrency control and how it can be used to ensure data integrity in an Entity Framework application. We’ll also look at some examples of how it can be implemented and provide some tips that can help you get the most out of this approach.

What Is Pessimistic Concurrency Control?

Pessimistic concurrency control is a type of concurrency control strategy that assumes that data conflicts are common and should be prevented. It works by locking a record in the database while it is being accessed by a user, preventing other users from modifying the same record until the first user is done.

This approach can help ensure that data is not lost or corrupted due to concurrent access by multiple users. It also ensures that data remains consistent across all users, as any changes made by one user will be reflected in the records of other users.

How to Implement Pessimistic Concurrency Control in Entity Framework

Implementing pessimistic concurrency control in Entity Framework is relatively straightforward. The first step is to configure the database to enable row-level locking. This can be done by setting the ROWLOCK hint when querying the database.

Next, you’ll need to add a timestamp column to each table that you want to protect. This column will be used to track when the record was last updated, and it will be used to ensure that any changes made to the record are valid.

Finally, you’ll need to add a Where clause to your queries that checks the timestamp column to see if the record has been updated since it was last accessed. If the timestamp has changed, then the query will fail and the user will be notified that the data has been modified by another user.

Example of Implementing Pessimistic Concurrency Control in Entity Framework

Let’s look at an example of how to implement pessimistic concurrency control in Entity Framework. We’ll be using a simple table that stores customer information.

First, we’ll add a timestamp column to the table and configure the database to enable row-level locking. Then, we’ll create an Entity Framework query that checks the timestamp column to see if the record has been modified since it was last accessed.

using (var context = new MyContext())
{
    // Get customer record with ID = 1
    var customer = await context.Customers
        .Where(c => c.Id == 1)
        .WithHint("ROWLOCK")
        .FirstOrDefaultAsync();
    
    // Check if the record has been modified since it was last accessed
    if (customer.Timestamp != customer.OriginalTimestamp)
    {
        // Record has been modified, throw exception
        throw new ConcurrencyException("Record has been modified by another user");
    }
    
    // Update the customer record
    customer.Name = "John Doe";
    
    // Update the timestamp field
    customer.Timestamp = DateTime.Now;
    
    // Save the changes to the database
    await context.SaveChangesAsync();
}

In this example, we’re using the WithHint method to enable row-level locking on the query. We’re also checking the timestamp field to see if the record has been modified since it was last accessed. If it has been modified, then we throw a ConcurrencyException and prevent the transaction from completing.

Tips for Working with Pessimistic Concurrency Control

When working with pessimistic concurrency control in Entity Framework, there are a few tips that can help you get the most out of this approach.

• Make sure to take advantage of the ROWLOCK hint when querying the database. This will ensure that row-level locking is enabled and prevent data conflicts.
• Make sure to check the timestamp column when querying the database. This will ensure that any changes made by other users are detected.
• Use a try-catch block when updating records. This will ensure that any concurrency exceptions are caught and handled appropriately.

Conclusion

Pessimistic concurrency control is a powerful approach for managing concurrency in Entity Framework applications. It works by locking records in the database and checking for changes before allowing a transaction to complete. By following the steps outlined in this guide, you’ll be able to implement this approach in your own applications and ensure that data integrity is maintained.