jpa-patterns
JPA/Hibernate patterns for entity design, relationships, query optimization, transactions, auditing, indexing, pagination, and pooling in Spring Boot.
Best use case
jpa-patterns is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
JPA/Hibernate patterns for entity design, relationships, query optimization, transactions, auditing, indexing, pagination, and pooling in Spring Boot.
Teams using jpa-patterns should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/jpa-patterns/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How jpa-patterns Compares
| Feature / Agent | jpa-patterns | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
JPA/Hibernate patterns for entity design, relationships, query optimization, transactions, auditing, indexing, pagination, and pooling in Spring Boot.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# JPA/Hibernate Patterns
Use for data modeling, repositories, and performance tuning in Spring Boot.
## Entity Design
```java
@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:
```java
@Configuration
@EnableJpaAuditing
class JpaConfig {}
```
## Relationships and N+1 Prevention
```java
@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
```java
@Query("select m from MarketEntity m left join fetch m.positions where m.id = :id")
Optional<MarketEntity> findWithPositions(@Param("id") Long id);
```
## Repository Patterns
```java
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:
```java
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
```java
@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
```java
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.Related Skills
swiftui-patterns
SwiftUI architecture patterns, state management with @Observable, view composition, navigation, performance optimization, and modern iOS/macOS UI best practices.
springboot-patterns
Spring Boot architecture patterns, REST API design, layered services, data access, caching, async processing, and logging. Use for Java Spring Boot backend work.
rust-patterns
Idiomatic Rust patterns, ownership, error handling, traits, concurrency, and best practices for building safe, performant applications.
pytorch-patterns
PyTorch deep learning patterns and best practices for building robust, efficient, and reproducible training pipelines, model architectures, and data loading.
python-patterns
Pythonic idioms, PEP 8 standards, type hints, and best practices for building robust, efficient, and maintainable Python applications.
postgres-patterns
PostgreSQL database patterns for query optimization, schema design, indexing, and security. Based on Supabase best practices.
perl-patterns
Modern Perl 5.36+ idioms, best practices, and conventions for building robust, maintainable Perl applications.
nuxt4-patterns
Nuxt 4 app patterns for hydration safety, performance, route rules, lazy loading, and SSR-safe data fetching with useFetch and useAsyncData.
nestjs-patterns
NestJS architecture patterns for modules, controllers, providers, DTO validation, guards, interceptors, config, and production-grade TypeScript backends.
mcp-server-patterns
Build MCP servers with Node/TypeScript SDK — tools, resources, prompts, Zod validation, stdio vs Streamable HTTP. Use Context7 or official MCP docs for latest API.
laravel-patterns
Laravel architecture patterns, routing/controllers, Eloquent ORM, service layers, queues, events, caching, and API resources for production apps.
kotlin-patterns
Idiomatic Kotlin patterns, best practices, and conventions for building robust, efficient, and maintainable Kotlin applications with coroutines, null safety, and DSL builders.