Member-only story
Top 10 Spring Data JPA Mistakes and How to Avoid Them (With Examples)
Spring Data JPA simplifies database interactions, but many developers make common mistakes that lead to performance issues, data inconsistency, and unexpected behavior. Understanding these pitfalls is crucial for building efficient and scalable applications.
In this article, we will explore the Top 10 Spring Data JPA mistakes and how to avoid them, with real-world examples.
1️⃣ Using EAGER Fetch Type Everywhere ⚠️
❌ Mistake: Fetching All Related Entities by Default
By default, @ManyToOne and @OneToOne relationships use EAGER fetching, which can result in N+1 query issues.
@Entity
public class Order {
@Id
@GeneratedValue(strategy = GenerationType.IDENTITY)
private Long id;
@ManyToOne(fetch = FetchType.EAGER) // ❌ Avoid EAGER fetching unless necessary
private Customer customer;
}✔ Issue: Every time you fetch an Order, it automatically fetches the associated Customer, even when it's not needed.
✅ Solution: Use LAZY Fetching
@ManyToOne(fetch = FetchType.LAZY) // ✅ Fetch only when needed
private Customer customer;✔ Best Practice: Use JPQL or JOIN FETCH queries when eager loading is required.
2️⃣ Ignoring Transactions (@Transactional) 🔄
❌ Mistake: Performing Multiple Database Calls Without a Transaction
public void updateUser(Long id, String email) {
User user = userRepository.findById(id).orElseThrow();
user.setEmail(email);
userRepository.save(user); // ❌ No transaction control
}✔ Issue: If an error occurs after fetching the user, the update may never happen, leading to inconsistent data.
✅ Solution: Use @Transactional to Ensure Atomicity
@Transactional
public void updateUser(Long id, String email) {
User user = userRepository.findById(id).orElseThrow();
user.setEmail(email);
userRepository.save(user);
}✔ Best Practice: Let JPA automatically commit changes within a transaction.
