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jpa-patterns

Helps your agent use JPA/Hibernate patterns efficiently. Improves entity design, queries, and transaction management in Spring Boot applications.

What it does

This guide teaches how to organize and optimize data access in Java applications using JPA and Hibernate. It shows how to create efficient data models, improve query speed, and manage transactions and database connections.

When to use it

  • ✓When creating database tables and their relationships.
  • ✓When database queries are slow or encountering errors.
  • ✓When configuring how the application connects to and manages database connections.

Example of what to ask your AI

“How can I optimize my JPA queries to avoid the N+1 problem?”

Want more? Open the sections below.

How to use

The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.

Skill link

https://github.com/affaan-m/ECC/blob/main/pi/core/skills/jpa-patterns/SKILL.md

Ready-to-paste message

Use this skill to help me: https://github.com/affaan-m/ECC/blob/main/pi/core/skills/jpa-patterns/SKILL.md Read the SKILL.md file at that link and follow its instructions for my task.
How it works

It provides code examples and explanations on using JPA/Hibernate annotations to define tables, relationships, and optimize performance. It also covers configurations for transactions, pagination, and database connections.

Installation

Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.

In the terminal (Claude Code, Codex, Cursor), in your project folder:

npx skills add affaan-m/ECC --skill jpa-patterns

Or download just the file:

curl -L https://raw.githubusercontent.com/affaan-m/ECC/main/pi/core/skills/jpa-patterns/SKILL.md -o SKILL.md
Technical content (original SKILL.md)

Original text by the author, straight from GitHub.

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.

FAQ

What is the N+1 problem?

It's a performance issue where the application makes an initial query to fetch a list of items, and then makes a separate query for each item in the list, resulting in many unnecessary queries.

What are 'projections'?

They are a way to ask the database for only the data you actually need, instead of all data from a table, making queries faster.

What is 'auditing'?

It's the automatic recording of when data was created or modified, useful for tracking changes.

Details

Original description by the author

JPA/Hibernate patterns for entity design, relationships, query optimization, transactions, auditing, indexing, pagination, and pooling in Spring Boot. Use when designing JPA entities or relationships, or when a Hibernate query, transaction, or N+1 problem needs fixing.

repo: affaan-m/ECC

Popularity

GitHub stars
280k
Ranking position
#67
License
MIT
Updated
10/15/2026

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