Designing a Filterable Product API (Spring Boot System Design)

Designing an API to Filter Products by productType

REST API

GET /api/products?productType=ELECTRONICS

Controller

@GetMapping("/products")
public List<Product> getProductsByType(@RequestParam String productType) {
    return productService.getProductsByType(productType);
}

Making the Filter Optional

To return all products when productType isn’t supplied, make the parameter optional and branch on it:

@GetMapping("/products")
public List<Product> getProducts(
        @RequestParam(required = false) String productType) {

    return productType == null
            ? productService.getAllProducts()
            : productService.findByProductType(productType);
}

This way GET /products and GET /products?productType=ELECTRONICS are both handled by the same endpoint.

Service

public List<Product> getProductsByType(String productType) {
    return productRepository.findByProductType(productType);
}

Repository

public interface ProductRepository extends JpaRepository<Product, Long> {
    List<Product> findByProductType(String productType);
}

Entity

@Entity
public class Product {

    @Id
    @GeneratedValue
    private Long id;

    private String name;

    private String productType;
}

Optimizations

• Pagination

GET /products?productType=ELECTRONICS&page=0&size=20

• Database index

CREATE INDEX idx_product_type ON product(product_type);

• Redis caching

@Cacheable("products")

Interview Checklist

1. Explain the API design.
2. Discuss database indexing.
3. Mention caching.
4. Explain load balancing.
5. Cover asynchronous processing.
6. Mention monitoring and observability.

Key Comparisons

Topic	Recommended Approach	Full Coverage
Product filtering	Repository query + index + pagination	This page
High traffic scaling	Horizontal scaling, caching, async processing	Performance Optimization and Scalability
Distributed transactions	Saga pattern	Saga Pattern and Compensation Failures
Entity tracking	Events or CDC (Debezium)	Spring Boot Auditing
Centralized logging	ELK stack + distributed tracing	Microservices Communication Patterns

Key Takeaways

• A filterable product API is a classic system-design warm-up: derived repository query, pagination, an index on the filtered column, and a caching layer on top.
• Combine @RequestParam filtering with pagination (page/size) so result sets stay bounded as data grows.
• Cache read-heavy, rarely-changing lookups like product listings with @Cacheable, backed by a database index on the filtered column.