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koan-performance

// Streaming, pagination, count strategies, bulk operations

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updated:February 8, 2026
SKILL.mdreadonly
SKILL.md Frontmatter
namekoan-performance
descriptionStreaming, pagination, count strategies, bulk operations

Koan Performance

Core Principle

Optimize for scale from day one. Use streaming for large datasets, batch operations for bulk changes, fast counts for UI, and pagination for web APIs.

Performance Patterns

Streaming (Large Datasets)

// ❌ WRONG: Load everything into memory
var allTodos = await Todo.All(); // 1 million records!

// ✅ CORRECT: Stream in batches
await foreach (var todo in Todo.AllStream(batchSize: 1000))
{
    await ProcessTodo(todo);
}

Count Strategies

// Fast count (metadata estimate - 1000x+ faster)
var fast = await Todo.Count.Fast(ct); // ~5ms for 10M rows

// Exact count (guaranteed accuracy)
var exact = await Todo.Count.Exact(ct); // ~25s for 10M rows

// Optimized (framework chooses)
var optimized = await Todo.Count; // Uses Fast if available

Use Fast for: Pagination UI, dashboards, estimates Use Exact for: Critical business logic, reports, inventory

Bulk Operations

// Bulk create
var todos = Enumerable.Range(1, 1000)
    .Select(i => new Todo { Title = $"Task {i}" })
    .ToList();
await todos.Save(); // Single operation

// Bulk removal
await Todo.RemoveAll(RemoveStrategy.Fast); // TRUNCATE/DROP (225x faster)

Batch Retrieval

// ❌ WRONG: N queries
foreach (var id in ids)
{
    var todo = await Todo.Get(id);
}

// ✅ CORRECT: 1 query
var todos = await Todo.Get(ids);

Pagination

public async Task<IActionResult> GetTodos(
    int page = 1,
    int pageSize = 20,
    CancellationToken ct = default)
{
    var result = await Todo.QueryWithCount(
        t => !t.Completed,
        new DataQueryOptions { OrderBy = nameof(Todo.Created), Descending = true },
        ct);

    Response.Headers["X-Total-Count"] = result.TotalCount.ToString();
    return Ok(result.Items);
}

Performance Benchmarks

OperationInefficientEfficientSpeedup
Bulk Remove (1M)DELETE loop ~45sTRUNCATE ~200ms225x
Count (10M)Full scan ~25sMetadata ~5ms5000x
Batch Get (100)100 queries1 query100x
Stream (1M)Load all (OOM)Stream batchesMemory safe

When This Skill Applies

  • ✅ Performance tuning
  • ✅ Large datasets
  • ✅ Optimization
  • ✅ Production readiness
  • ✅ Memory issues
  • ✅ Query optimization

Reference Documentation

  • Example Code: .claude/skills/entity-first/examples/batch-operations.cs
  • Guide: docs/guides/performance.md
  • Sample: samples/S14.AdapterBench/ (Performance benchmarks)