Entity Framework (EF) provides various data loading strategies to control how data is retrieved from the database. These strategies allow you to optimize performance and reduce the number of database queries. Here are the main options:

1. Lazy Loading

• Definition: Related data is automatically loaded from the database the first time it is accessed.
• How It Works: EF issues separate queries for related entities only when they are accessed.
• Pros:
  • Reduces initial data load if related data is not always needed.
• Cons:
  • Can lead to the N+1 query problem, where EF makes one query for the main entity and additional queries for each related entity.
• Setup:
  • Configure navigation properties as virtual and use EF proxies.
  csharp

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  public virtual ICollection<Order> Orders { get; set; }

2. Eager Loading

• Definition: Related data is loaded with the main entity in a single query using Include or ThenInclude.
• How It Works: You explicitly specify which related entities should be loaded when querying the main entity.
• Pros:
  • Reduces the number of database queries.
  • Better for scenarios where you know you’ll need related data.
• Cons:
  • Can load unnecessary data if not carefully configured.
  • Larger queries may impact performance.
• Setup:
  csharp

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  var customers = context.Customers .Include(c => c.Orders) .ThenInclude(o => o.OrderDetails) .ToList();

3. Explicit Loading

• Definition: Related data is loaded on demand, but explicitly using the Load method.
• How It Works: You manually load related entities for already retrieved entities.
• Pros:
  • Complete control over what related data is loaded and when.
• Cons:
  • Requires more code to manage.
  • Can also result in the N+1 query problem if not handled carefully.
• Setup:
  csharp

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  var customer = context.Customers.Find(1); context.Entry(customer).Collection(c => c.Orders).Load();

4. Filtered Eager Loading

• Definition: Eagerly loads only specific related data based on a filter.
• How It Works: Apply filters to the Include clause using LINQ.
• Pros:
  • Reduces the amount of related data loaded.
  • Optimized for scenarios where only a subset of related data is needed.
• Cons:
  • Requires careful query design.
• Setup:
  csharp

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  var customers = context.Customers .Include(c => c.Orders.Where(o => o.Status == "Completed")) .ToList();

5. Split Queries (EF Core)

• Definition: Related data is loaded in separate queries but combined in memory.
• How It Works: Introduced in EF Core to handle scenarios where single large queries could cause performance issues.
• Pros:
  • Avoids loading unnecessary data in one large query.
• Cons:
  • Increased complexity in query configuration.
• Setup:
  csharp

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  var customers = context.Customers .Include(c => c.Orders) .AsSplitQuery() .ToList();

Choosing the Right Option

• Lazy Loading: Use when data access patterns are unpredictable or related data is rarely accessed.
• Eager Loading: Use when related data is always or frequently needed.
• Explicit Loading: Use for fine-grained control over related data loading.
• Filtered Eager Loading: Use when only a specific subset of related data is required.
• Split Queries: Use to avoid large single queries that could impact database performance.

Each approach has trade-offs, and the best option depends on your application’s requirements and usage patterns

*AI generated