optimizing-ef-core-queries

description	Optimize Entity Framework Core queries by fixing N+1 problems, choosing correct tracking modes, using compiled queries, and avoiding common performance traps. Use when EF Core queries are slow, generating excessive SQL, or causing high database load.
metadata	{"github-path":"plugins/dotnet-data/skills/optimizing-ef-core-queries","github-ref":"refs/tags/v1.0.0","github-repo":"https://github.com/dotnet/skills","github-tree-sha":"d92ec598e2f129285ed6cbd1998531ee40ba6155"}
name	optimizing-ef-core-queries

Optimizing EF Core Queries

When to Use

• EF Core queries are slow or generating too many SQL statements
• Database CPU/IO is high due to ORM inefficiency
• N+1 query patterns are detected in logs
• Large result sets cause memory pressure

When Not to Use

• The user is using Dapper or raw ADO.NET (not EF Core)
• The performance issue is database-side (missing indexes, bad schema)
• The user is building a new data access layer from scratch

Inputs

Input	Required	Description
Slow EF Core queries	Yes	The LINQ queries or DbContext usage to optimize
SQL output or logs	No	EF Core generated SQL or query execution logs

Workflow

Step 1: Enable query logging to see the actual SQL

// In Program.cs or DbContext configuration:
optionsBuilder
    .UseSqlServer(connectionString)
    .LogTo(Console.WriteLine, LogLevel.Information)
    .EnableSensitiveDataLogging()  // shows parameter values (dev only!)
    .EnableDetailedErrors();

Or use the Microsoft.EntityFrameworkCore log category:

{
  "Logging": {
    "LogLevel": {
      "Microsoft.EntityFrameworkCore.Database.Command": "Information"
    }
  }
}

Step 2: Fix N+1 query patterns

The #1 EF Core performance killer. Happens when loading related entities in a loop.

Before (N+1 — 1 query for orders + N queries for items):

var orders = await db.Orders.ToListAsync();
foreach (var order in orders)
{
    // Each access triggers a lazy-load query!
    var items = order.Items.Count;
}

After (eager loading — 1 or 2 queries total):

// Option 1: Include (JOIN)
var orders = await db.Orders
    .Include(o => o.Items)
    .ToListAsync();

// Option 2: Split query (separate SQL, avoids cartesian explosion)
var orders = await db.Orders
    .Include(o => o.Items)
    .AsSplitQuery()
    .ToListAsync();

// Option 3: Explicit projection (best - only fetches needed columns)
var orderSummaries = await db.Orders
    .Select(o => new OrderSummary
    {
        OrderId = o.Id,
        Total = o.Items.Sum(i => i.Price),
        ItemCount = o.Items.Count
    })
    .ToListAsync();

When to use Split vs Single query:

Scenario	Use
1 level of Include	Single query (default)
Multiple Includes (Cartesian risk)	AsSplitQuery()
Include with large child collections	AsSplitQuery()
Need transaction consistency	Single query

Step 3: Use NoTracking for read-only queries

Change tracking overhead is significant. Disable it when you don't need to update entities:

// Per-query
var products = await db.Products
    .AsNoTracking()
    .Where(p => p.IsActive)
    .ToListAsync();

// Global default for read-heavy apps
services.AddDbContext<AppDbContext>(options =>
    options.UseSqlServer(connectionString)
           .UseQueryTrackingBehavior(QueryTrackingBehavior.NoTracking));

Use AsNoTrackingWithIdentityResolution() when the query returns duplicate entities to avoid duplicated objects in memory.

Step 4: Use compiled queries for hot paths

// Define once as static
private static readonly Func<AppDbContext, int, Task<Order?>> GetOrderById =
    EF.CompileAsyncQuery((AppDbContext db, int id) =>
        db.Orders
            .Include(o => o.Items)
            .FirstOrDefault(o => o.Id == id));

// Use repeatedly — skips query compilation overhead
var order = await GetOrderById(db, orderId);

Step 5: Avoid common query traps

Trap	Problem	Fix
ToList() before Where()	Loads entire table into memory	Filter first: .Where().ToList()
Count() to check existence	Scans all rows	Use .Any() instead
.Select() after .Include()	Include is ignored with projection	Remove Include, use Select only
string.Contains() in Where	May not translate, falls to client eval	Use EF.Functions.Like() for SQL LIKE
Calling .ToList() inside Select()	Causes nested queries	Use projection with Select all the way

Step 6: Use raw SQL or FromSql for complex queries

When LINQ can't express it efficiently:

var results = await db.Orders
    .FromSqlInterpolated($@"
        SELECT o.* FROM Orders o
        INNER JOIN (
            SELECT OrderId, SUM(Price) as Total
            FROM OrderItems
            GROUP BY OrderId
            HAVING SUM(Price) > {minTotal}
        ) t ON o.Id = t.OrderId")
    .AsNoTracking()
    .ToListAsync();

Validation

• SQL logging shows expected number of queries (no N+1)
• Read-only queries use AsNoTracking()
• Hot-path queries use compiled queries
• No client-side evaluation warnings in logs
• Include/split strategy matches data shape

Common Pitfalls

Pitfall	Solution
Lazy loading silently creating N+1	Remove Microsoft.EntityFrameworkCore.Proxies or disable lazy loading
Global query filters forgotten in perf analysis	Check HasQueryFilter in model config; use IgnoreQueryFilters() if needed
DbContext kept alive too long	DbContext should be scoped (per-request); don't cache it
Batch updates fetching then saving	EF Core 7+: use ExecuteUpdateAsync / ExecuteDeleteAsync for bulk operations
String interpolation in FromSqlRaw	SQL injection risk — use FromSqlInterpolated (parameterized)