Pagination Performance
Offset vs Cursor Performance
-- Offset (slow at high pages)
SELECT * FROM products ORDER BY id LIMIT 20 OFFSET 100000;
-- Scans 100,000 rows!
-- Cursor (constant)
SELECT * FROM products WHERE id > 50000 ORDER BY id LIMIT 20;
-- Uses index
Spring Data
// Cursor-based
ScrollPosition position = ScrollPosition.keyset();
Slice<Product> slice = repository.findByOrderById(position, Limit.of(20));
Key Points
- Understanding Pagination Performance is essential for production systems
- Always consider scalability and maintainability
- Test thoroughly before deploying to production
- Monitor performance and set up alerting
Common Patterns
- Validation: Always validate input at the boundary
- Error Handling: Use structured error responses
- Logging: Log key events for debugging
- Testing: Unit, integration, and load tests
- Documentation: Keep docs updated with code changes
Pagination Best Practices
Types
- Offset: Simple, but slow for large offsets
- Cursor: Consistent, better performance
- Keyset: Composite key ordering
Response Format
{
"data": [...],
"pagination": {
"page": 1,
"pageSize": 20,
"total": 100,
"hasMore": true
}
}
Best Practices
- Default page size: 20-50
- Maximum page size: 100
- Use cursor for large datasets
Key Points
- Understanding Pagination Performance is essential for production systems
- Always consider scalability and maintainability
- Test thoroughly before deploying to production
- Monitor performance and set up alerting
Common Patterns
- Validation: Always validate input at the boundary
- Error Handling: Use structured error responses
- Logging: Log key events for debugging
- Testing: Unit, integration, and load tests
- Documentation: Keep docs updated with code changes
Practice Problems
Design and implement a solution for Pagination Performance in a backend system. Consider scalability, error handling, and production readiness.
Solution
// Pagination Performance implementation
// Key aspects: validation, error handling, logging, testing
public class PaginationPerformance {
// Production-ready implementation
}Identify and handle edge cases for Pagination Performance. What happens under high load, with invalid input, or during failures?
Solution
// Edge case handling:
// 1. Null/empty input -> validation
// 2. High load -> rate limiting, queuing
// 3. Failures -> retries, circuit breaker
// 4. Concurrent access -> locks, idempotencyWrite a testing strategy for Pagination Performance. Include unit tests, integration tests, and performance tests.
Solution
// Test plan:
// - Unit: 80% coverage target
// - Integration: API contracts
// - Performance: latency, throughput
// - Chaos: failure injectionQuiz
1. Deep offset pagination degrades because?
2. Best for large datasets?
3. What is the primary purpose of Pagination Performance?
4. What is a common mistake when implementing Pagination Performance?
Flashcards
Question
Deep offset degrades?
Click to reveal answer
Answer
Must scan all skipped rows
Question
Best for large data?
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Answer
Cursor-based (index-based)
Question
What is Pagination Performance?
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Answer
Pagination Performance is a key concept in backend development.
Question
When to use Pagination Performance?
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Answer
Use Pagination Performance when building production systems that require reliability, scalability, and maintainability.
Question
Pagination Performance best practices
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Answer
Follow SOLID principles, write clean code, test thoroughly, document decisions, and monitor in production.
Revision Notes
Key Takeaways
- 1.Offset pagination degrades at high offsets
- 2.Cursor-based: constant performance
- 3.Use indexed column for cursor
- 4.Spring: ScrollPosition.keyset()
Interview Tips
- •Optimize pagination
- •Know cursor vs offset
Cheat Sheet
Pagination Performance
- Offset: degrades at high pages (scans skipped)
- Cursor: constant (uses index)
- Use: indexed column for cursor