I have a MedService class in my ASP.NET Core application which uses Entity Framework Core to interact with my database. This service class is responsible for CRUD operations on the Med entities. Here's a simplified version of the service class:
public class MedService:IMedService {
private MedAppContext _context;
public MedService(MedAppContext context)
{
_context = context;
}
public async Task<List<Med>> GetAllMedsAsync()
{
return await _context.Meds.ToListAsync();
}
public async Task<Med?> GetMedAsync(int Id)
{
return await _context.Meds.FirstOrDefaultAsync(p => p.Id == Id);
}
public async Task DeleteMedync(int Id)
{
var med = await GetMedAsync(Id);
if (med == null) return;
_context.Meds.Remove(med);
await _context.SaveChangesAsync();
}
public async Task UpdateMedAsync(Med med)
{
_context.ChangeTracker.Clear();
_context.Meds.Update(med);
await _context.SaveChangesAsync();
}
public async Task AddMedAsync(Med med)
{
if (med == null) return;
await _context.Meds.AddAsync(new Med()
{
Name = med.Name,
Count = med.Count,
IngredientId = med.IngredientId,
MedFormId = med.MedFormId,
SideEffectsId=med.SideEffectsId,
SideEffectRarityId=med.SideEffectRarityId,
});
await _context.SaveChangesAsync();
}
}
In my Program.cs:
builder.Services.AddScoped<IUserService, UserService>();
Now, my concern is about handling concurrency issues, especially when updating entities using the UpdateMedAsync method. How can I ensure that I'm handling concurrency conflicts properly in this scenario? Should I be implementing any specific patterns or techniques within this service class or elsewhere in my ASP.NET Core application? Any guidance or examples would be greatly appreciated. Thank you!
From the official documentation: https://learn.microsoft.com/en-us/ef/core/saving/concurrency?tabs=data-annotations
Optimistic Concurrency and Conflict Resolution Techniques
In database management, concurrent modifications by multiple application instances can lead to inconsistencies. Optimistic concurrency, as implemented in EF Core, addresses this by assuming rare conflicts and avoiding upfront locks. Instead, conflicts are detected during the save operation, notifying the application to handle them accordingly.
Concurrency tokens, such as the Version property in EF Core, play a crucial role in detecting changes. These tokens are loaded and tracked during entity queries, and their values are compared during updates to ensure consistency. For example, a [Timestamp] attribute can be used to map a property to a SQL Server rowversion column, automatically updating it on each change.
When conflicts arise, techniques for resolution vary. Applications may inform users of conflicting changes, retry operations after re-querying data, or implement more sophisticated merging strategies. For instance, in EF Core, DbUpdateConcurrencyException is caught, and original values are refreshed to bypass subsequent checks.
Considerations for Isolation Levels
Another aspect of concurrency management involves isolation levels, particularly in ensuring data consistency. The repeatable reads transaction isolation level guarantees that a transaction sees data as it was when the transaction started, regardless of subsequent concurrent activity.
Implementation details of isolation levels vary across databases. For example, SQL Server's "repeatable read" level utilizes shared locks to prevent interference, while PostgreSQL's approach includes serialization errors to handle conflicts.
However, higher isolation levels may impact performance and require transactions to span all operations. It's crucial to weigh the benefits of data consistency against these drawbacks, especially considering the potential impact on concurrent performance.
This summarized article provides insights into managing concurrency in databases, covering optimistic concurrency, concurrency token implementation, conflict resolution techniques, and considerations for isolation levels.