jpa-patterns
affaan-m/ecc
JPA/Hibernate patterns for entity design, relationships, query optimization, transactions, and performance tuning in Spring Boot.
What is jpa-patterns?
Provides best practices for designing JPA entities, managing relationships, optimizing queries to prevent N+1 problems, configuring transactions, and tuning connection pooling in Spring Boot applications. Use when building data access layers, defining entity mappings, or improving database performance.
- Design entities with proper indexing, auditing, and column constraints
- Define and optimize relationships (@OneToMany, @ManyToOne, @ManyToMany) with lazy loading and JOIN FETCH strategies
- Prevent N+1 query problems using projections and fetch strategies
- Configure transactions with @Transactional and readOnly optimization
- Implement pagination and sorting with Spring Data Page and Pageable
- Tune HikariCP connection pooling and configure second-level caching
How to install jpa-patterns
npx skills add null --skill jpa-patterns- Spring Boot project with spring-boot-starter-data-jpa
- Database driver (PostgreSQL, MySQL, etc.)
- Flyway or Liquibase for migrations (recommended for production)
How to use jpa-patterns
- 1.Define entities with @Entity, @Table, and @Index annotations for your domain model
- 2.Enable JPA auditing with @EnableJpaAuditing and @CreatedDate/@LastModifiedDate on fields
- 3.Create repository interfaces extending JpaRepository with custom @Query methods
- 4.Use lazy loading by default and add JOIN FETCH queries only where needed to prevent N+1
- 5.Configure HikariCP pool size, timeouts, and validation in application.properties
- 6.Add @Transactional to service methods and use readOnly=true for query-only operations
- 7.Implement pagination with PageRequest and Pageable in repository methods
- 8.Test data access with @DataJpaTest and enable Hibernate SQL logging to verify query efficiency
Use cases
- Building Spring Boot data access layers with JPA repositories
- Optimizing slow queries by adding indexes and using DTO projections
- Preventing N+1 query problems in one-to-many relationships
- Setting up audit fields (createdAt, updatedAt) with @EntityListeners
- Implementing cursor-based or offset pagination for large datasets
- Spring Boot backend developers
- Database architects designing entity models
- Performance engineers optimizing data access
- Teams migrating to JPA from raw SQL
jpa-patterns FAQ
Use lazy loading by default, add JOIN FETCH to queries when you need related entities, or use DTO projections to fetch only required columns. Verify with Hibernate SQL logging.
No. EAGER loading on @OneToMany or @ManyToMany collections causes performance issues. Use lazy loading and fetch explicitly with JOIN FETCH or projections.
Start with maximum-pool-size=20, minimum-idle=5, connection-timeout=30000ms. Adjust based on your workload; monitor connection usage to avoid exhaustion or waste.
Annotate fields with @CreatedDate and @LastModifiedDate, add @EntityListeners(AuditingEntityListener.class) to the entity, and enable @EnableJpaAuditing in a @Configuration class.
Use projections for read-only queries where you only need a few columns. They reduce memory overhead and allow the database to optimize the query.
Full instructions (SKILL.md)
Source of truth, from affaan-m/ecc.
name: jpa-patterns description: JPA/Hibernate patterns for entity design, relationships, query optimization, transactions, auditing, indexing, pagination, and pooling in Spring Boot. metadata: origin: ECC
JPA/Hibernate Patterns
Use for data modeling, repositories, and performance tuning in Spring Boot.
When to Activate
- Designing JPA entities and table mappings
- Defining relationships (@OneToMany, @ManyToOne, @ManyToMany)
- Optimizing queries (N+1 prevention, fetch strategies, projections)
- Configuring transactions, auditing, or soft deletes
- Setting up pagination, sorting, or custom repository methods
- Tuning connection pooling (HikariCP) or second-level caching
Entity Design
@Entity
@Table(name = "markets", indexes = {
@Index(name = "idx_markets_slug", columnList = "slug", unique = true)
})
@EntityListeners(AuditingEntityListener.class)
public class MarketEntity {
@Id @GeneratedValue(strategy = GenerationType.IDENTITY)
private Long id;
@Column(nullable = false, length = 200)
private String name;
@Column(nullable = false, unique = true, length = 120)
private String slug;
@Enumerated(EnumType.STRING)
private MarketStatus status = MarketStatus.ACTIVE;
@CreatedDate private Instant createdAt;
@LastModifiedDate private Instant updatedAt;
}
Enable auditing:
@Configuration
@EnableJpaAuditing
class JpaConfig {}
Relationships and N+1 Prevention
@OneToMany(mappedBy = "market", cascade = CascadeType.ALL, orphanRemoval = true)
private List<PositionEntity> positions = new ArrayList<>();
- Default to lazy loading; use
JOIN FETCHin queries when needed - Avoid
EAGERon collections; use DTO projections for read paths
@Query("select m from MarketEntity m left join fetch m.positions where m.id = :id")
Optional<MarketEntity> findWithPositions(@Param("id") Long id);
Repository Patterns
public interface MarketRepository extends JpaRepository<MarketEntity, Long> {
Optional<MarketEntity> findBySlug(String slug);
@Query("select m from MarketEntity m where m.status = :status")
Page<MarketEntity> findByStatus(@Param("status") MarketStatus status, Pageable pageable);
}
- Use projections for lightweight queries:
public interface MarketSummary {
Long getId();
String getName();
MarketStatus getStatus();
}
Page<MarketSummary> findAllBy(Pageable pageable);
Transactions
- Annotate service methods with
@Transactional - Use
@Transactional(readOnly = true)for read paths to optimize - Choose propagation carefully; avoid long-running transactions
@Transactional
public Market updateStatus(Long id, MarketStatus status) {
MarketEntity entity = repo.findById(id)
.orElseThrow(() -> new EntityNotFoundException("Market"));
entity.setStatus(status);
return Market.from(entity);
}
Pagination
PageRequest page = PageRequest.of(pageNumber, pageSize, Sort.by("createdAt").descending());
Page<MarketEntity> markets = repo.findByStatus(MarketStatus.ACTIVE, page);
For cursor-like pagination, include id > :lastId in JPQL with ordering.
Indexing and Performance
- Add indexes for common filters (
status,slug, foreign keys) - Use composite indexes matching query patterns (
status, created_at) - Avoid
select *; project only needed columns - Batch writes with
saveAllandhibernate.jdbc.batch_size
Connection Pooling (HikariCP)
Recommended properties:
spring.datasource.hikari.maximum-pool-size=20
spring.datasource.hikari.minimum-idle=5
spring.datasource.hikari.connection-timeout=30000
spring.datasource.hikari.validation-timeout=5000
For PostgreSQL LOB handling, add:
spring.jpa.properties.hibernate.jdbc.lob.non_contextual_creation=true
Caching
- 1st-level cache is per EntityManager; avoid keeping entities across transactions
- For read-heavy entities, consider second-level cache cautiously; validate eviction strategy
Migrations
- Use Flyway or Liquibase; never rely on Hibernate auto DDL in production
- Keep migrations idempotent and additive; avoid dropping columns without plan
Testing Data Access
- Prefer
@DataJpaTestwith Testcontainers to mirror production - Assert SQL efficiency using logs: set
logging.level.org.hibernate.SQL=DEBUGandlogging.level.org.hibernate.orm.jdbc.bind=TRACEfor parameter values
Remember: Keep entities lean, queries intentional, and transactions short. Prevent N+1 with fetch strategies and projections, and index for your read/write paths.
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