Skip to content
advanced Phase · Database Integration

Query Optimization

Optimize database queries for better backend performance.

45m
0 problems
Topic Progress 0%

Query Optimization

EXPLAIN ANALYZE

EXPLAIN ANALYZE
SELECT * FROM products WHERE price > 100 ORDER BY name LIMIT 20;
-- Shows: Seq Scan, cost, execution time

Strategies

Strategy Description
Avoid SELECT * Load only needed columns
Add indexes On WHERE, JOIN, ORDER BY
Use LIMIT Don't return unbounded results
Batch operations Bulk inserts/updates

Key Points

  • Understanding Query Optimization is essential for production systems
  • Always consider scalability and maintainability
  • Test thoroughly before deploying to production
  • Monitor performance and set up alerting

Common Patterns

  1. Validation: Always validate input at the boundary
  2. Error Handling: Use structured error responses
  3. Logging: Log key events for debugging
  4. Testing: Unit, integration, and load tests
  5. Documentation: Keep docs updated with code changes

Best Practices

Key Principles

  1. Follow SOLID principles
  2. Write clean, readable code
  3. Test thoroughly
  4. Document decisions
  5. Monitor in production

Implementation

  • Start simple, refactor as needed
  • Use established patterns
  • Consider trade-offs
  • Review with peers

Continuous Improvement

  • Learn from incidents
  • Update documentation
  • Share knowledge
  • Mentor others

Key Points

  • Understanding Query Optimization is essential for production systems
  • Always consider scalability and maintainability
  • Test thoroughly before deploying to production
  • Monitor performance and set up alerting

Common Patterns

  1. Validation: Always validate input at the boundary
  2. Error Handling: Use structured error responses
  3. Logging: Log key events for debugging
  4. Testing: Unit, integration, and load tests
  5. Documentation: Keep docs updated with code changes

Practice Problems

0 / 3 solved
Implement Query Optimization

Design and implement a solution for Query Optimization in a backend system. Consider scalability, error handling, and production readiness.

Solution 
// Query Optimization implementation
// Key aspects: validation, error handling, logging, testing

public class QueryOptimization {
    // Production-ready implementation
}
Query Optimization Edge Cases

Identify and handle edge cases for Query Optimization. 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, idempotency
Query Optimization Testing Strategy

Write a testing strategy for Query Optimization. Include unit tests, integration tests, and performance tests.

Solution 
// Test plan:
// - Unit: 80% coverage target
// - Integration: API contracts
// - Performance: latency, throughput
// - Chaos: failure injection

Quiz

1. EXPLAIN ANALYZE shows?

Question 1 options

2. Avoid SELECT * by?

Question 2 options

3. What is a common mistake when implementing Query Optimization?

Question 3 options

Flashcards

Question

EXPLAIN purpose?

Click to reveal answer

Answer

Show query execution plan

Question

Avoid SELECT *?

Click to reveal answer

Answer

Load only needed columns

Question

Query Optimization best practices

Click to reveal answer

Answer

Follow SOLID principles, write clean code, test thoroughly, document decisions, and monitor in production.

Revision Notes

Key Takeaways

  • 1. EXPLAIN ANALYZE shows execution plans
  • 2. Avoid SELECT *
  • 3. Add indexes on WHERE/JOIN/ORDER BY

Interview Tips

  • • Optimize slow queries
  • • Use EXPLAIN

Cheat Sheet

Query Optimization

  • EXPLAIN ANALYZE: execution plan
  • Avoid SELECT *
  • Add indexes
  • Use LIMIT