Validation in Spring

Common Annotations

public class CreateProductRequest {

    @NotBlank(message = "Name is required")
    @Size(min = 2, max = 100)
    private String name;

    @NotNull(message = "Price is required")
    @Positive(message = "Price must be positive")
    private BigDecimal price;

    @Email(message = "Invalid email")
    private String sellerEmail;

    @Pattern(regexp = "^[A-Z]{2}-[0-9]{8}$")
    private String productCode;

    @PastOrPresent
    private LocalDate manufacturingDate;

    @NotEmpty
    private List<String> categories;
}

Annotation Reference

Annotation	Validation
@NotNull	Not null
@NotBlank	Not null, not empty, not whitespace
@NotEmpty	Not null, not empty (collections)
@Size	String/collection size bounds
@Min/@Max	Numeric bounds
@Positive/@Negative	Positive/negative numbers
@Email	Email format
@Pattern	Regex match
@Past/@Future	Date in past/future

Custom Validator

@Constraint(validatedBy = UniqueEmailValidator.class)
@Target({FIELD})
@Retention(RUNTIME)
public @interface UniqueEmail {
    String message() default "Email already exists";
    Class<?>[] groups() default {};
    Class<? extends Payload>[] payload() default {};
}

public class UniqueEmailValidator
        implements ConstraintValidator<UniqueEmail, String> {

    @Autowired
    private UserRepository userRepository;

    @Override
    public boolean isValid(String email, ConstraintValidatorContext context) {
        return email != null && !userRepository.existsByEmail(email);
    }
}

Validation Layers

1. Client-side: Immediate feedback
2. API Gateway: Basic validation
3. Service: Business rules
4. Database: Constraints

Types

• Type checking
• Format validation (email, phone)
• Range checking
• Length limits
• Business rules

Best Practices

• Validate on server (never trust client)
• Return specific error messages
• Use whitelist approach
• Log validation failures

Key Points

• Understanding Spring Validation 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