Performance Patterns

by hculap

codeapidata

Use when user asks about N+1 queries, performance optimization, query optimization, reduce API calls, improve render performance, fix slow code, optimize database, or reduce bundle size. Provides guidance on identifying and fixing performance anti-patterns across database, backend, frontend, and API layers.

Skill Details

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name: performance-patterns description: Use when user asks about N+1 queries, performance optimization, query optimization, reduce API calls, improve render performance, fix slow code, optimize database, or reduce bundle size. Provides guidance on identifying and fixing performance anti-patterns across database, backend, frontend, and API layers. allowed-tools: Read, Grep, Glob

Performance Anti-Patterns Reference

N+1 Query Problem

The N+1 problem occurs when code executes N additional queries to fetch related data for N items from an initial query.

Identification:

  • Queries inside loops
  • Lazy loading of associations during iteration
  • GraphQL resolvers fetching per-item

Fix Strategies:

  1. Eager Loading: Load related data in initial query
  2. Batching: Collect IDs, fetch all at once
  3. DataLoader: For GraphQL, batch and cache per-request
  4. Denormalization: Store computed/related data together

Severity: HIGH - Scales linearly with data size, causes exponential slowdown

Over-Fetching

Retrieving more data than needed from API or database.

Identification:

  • SELECT * queries
  • API endpoints returning full objects
  • No field selection support
  • Loading nested relations by default

Fix Strategies:

  1. Field Selection: Only query needed columns
  2. Sparse Fieldsets: Support ?fields=id,name parameter
  3. GraphQL: Let clients specify exact fields
  4. DTOs: Map to response-specific objects

Severity: MEDIUM - Increases bandwidth, memory, serialization time

Under-Fetching

Requiring multiple requests to get needed data.

Identification:

  • Waterfall requests (request depends on previous)
  • Multiple endpoints for related data
  • No include/expand support

Fix Strategies:

  1. Compound Endpoints: /users?include=orders
  2. GraphQL: Single query for nested data
  3. BFF Pattern: Backend aggregates for frontend
  4. Parallel Requests: When dependencies allow

Severity: MEDIUM - Increases latency, connection overhead

Missing Pagination

Returning unbounded result sets.

Identification:

  • List endpoints without limit
  • findAll() without pagination
  • No cursor for large datasets

Fix Strategies:

  1. Offset Pagination: ?page=1&limit=20
  2. Cursor Pagination: ?cursor=abc&limit=20 (better for large sets)
  3. Default Limits: Always apply max limit server-side
  4. Streaming: For very large exports

Severity: HIGH - Can crash server/client with large data

Inefficient Algorithms

O(n²) or worse complexity where better solutions exist.

Identification:

  • Nested loops on collections
  • Repeated array.find/includes in loops
  • String concatenation in loops
  • Sort inside loops

Fix Strategies:

  1. Use Maps/Sets: O(1) lookup instead of O(n)
  2. Single Pass: Combine operations
  3. Pre-compute: Calculate once, reuse
  4. Better Algorithms: Binary search for sorted data

Severity: HIGH - Becomes unusable with large data

Unnecessary Re-renders (Frontend)

Components re-rendering when their output hasn't changed.

Identification:

  • Inline objects/arrays in JSX
  • Inline function handlers
  • Missing React.memo/useMemo/useCallback
  • Context changes affecting all consumers

Fix Strategies:

  1. Memoization: React.memo for components
  2. Stable References: useMemo for objects, useCallback for functions
  3. Context Splitting: Separate frequently-changing state
  4. Selectors: Only subscribe to needed state slices

Severity: MEDIUM-HIGH - Causes janky UI, especially on lists

Sequential Async Operations

Running async operations one-by-one when parallel is possible.

Identification:

  • Sequential await statements
  • Waterfall promises
  • Loop with await inside

Fix Strategies:

  1. Promise.all: Run independent operations in parallel
  2. Promise.allSettled: When some can fail
  3. Batching: Group operations efficiently
  4. Pipelining: Stream processing

Severity: MEDIUM - Multiplies latency

Quick Reference by Layer

Database

Issue Detect Fix
N+1 queries Query in loop Eager load / batch
Missing index Slow WHERE/JOIN Add index
SELECT * No column list Specify columns
No LIMIT Unbounded query Add pagination

Backend

Issue Detect Fix
O(n²) loop Nested iteration Use Set/Map
Sequential await await in sequence Promise.all
Sync I/O fs.readFileSync Use async version
No caching Repeated computation Memoize

Frontend

Issue Detect Fix
Re-renders Inline objects/functions Memoize
Bundle size Large imports Tree-shake/split
Memory leak No cleanup useEffect cleanup
Layout thrash Read+write DOM Batch DOM ops

API

Issue Detect Fix
Over-fetching All fields returned Field selection
Under-fetching Multiple requests Include/expand
No pagination Unbounded lists Add limit/cursor
N+1 calls Fetch in loop Batch endpoint

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Skill Information

Category:Technical
Allowed Tools:Read, Grep, Glob
Last Updated:12/16/2025