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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
Prerequisites
  • Spring Boot project with spring-boot-starter-data-jpa
  • Database driver (PostgreSQL, MySQL, etc.)
  • Flyway or Liquibase for migrations (recommended for production)
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How to use jpa-patterns

  1. 1.Define entities with @Entity, @Table, and @Index annotations for your domain model
  2. 2.Enable JPA auditing with @EnableJpaAuditing and @CreatedDate/@LastModifiedDate on fields
  3. 3.Create repository interfaces extending JpaRepository with custom @Query methods
  4. 4.Use lazy loading by default and add JOIN FETCH queries only where needed to prevent N+1
  5. 5.Configure HikariCP pool size, timeouts, and validation in application.properties
  6. 6.Add @Transactional to service methods and use readOnly=true for query-only operations
  7. 7.Implement pagination with PageRequest and Pageable in repository methods
  8. 8.Test data access with @DataJpaTest and enable Hibernate SQL logging to verify query efficiency

Use cases

Good for
  • 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
Who it's for
  • Spring Boot backend developers
  • Database architects designing entity models
  • Performance engineers optimizing data access
  • Teams migrating to JPA from raw SQL

jpa-patterns FAQ

How do I prevent N+1 query problems?

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.

Should I use EAGER loading on collections?

No. EAGER loading on @OneToMany or @ManyToMany collections causes performance issues. Use lazy loading and fetch explicitly with JOIN FETCH or projections.

What HikariCP settings should I use?

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.

How do I add audit fields like createdAt and updatedAt?

Annotate fields with @CreatedDate and @LastModifiedDate, add @EntityListeners(AuditingEntityListener.class) to the entity, and enable @EnableJpaAuditing in a @Configuration class.

When should I use projections instead of full entities?

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 FETCH in queries when needed
  • Avoid EAGER on 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 saveAll and hibernate.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 @DataJpaTest with Testcontainers to mirror production
  • Assert SQL efficiency using logs: set logging.level.org.hibernate.SQL=DEBUG and logging.level.org.hibernate.orm.jdbc.bind=TRACE for 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.