jpa-patterns
affaan-m/everything-claude-code
Spring Boot 中用于实体设计、关系、查询优化、事务、审计、索引、分页和连接池的 JPA/Hibernate 设计模式。
...展开全部关于jpa-patterns
jpa-patterns 这是一个专注于特定工作流的可复用AI技能。描述:Spring Boot中用于实体设计、关系、查询优化、事务、审计、索引、分页和连接池的JPA/Hibernate模式。
该技能整合了操作指南、规范以及针对具体任务的指导,以便代理能够更一致地执行工作。适用于 Spring Boot 中的数据建模、存储库和性能调优。- 设计 JPA 实体和表映射 - 定义关系 (@OneToMany、@ManyToOne、@ManyToMany)
实际上,该技能最适合需要可重复执行、且希望减少配置步骤和消除模糊性的用户。 - 优化查询(防止 N+1 问题、获取策略、投影) - 配置事务、审计或软删除 - 设置分页、排序或自定义存储库方法 - 调整连接池(HikariCP)或二级缓存
常见问题
jpa-patterns能提供哪些帮助?
jpa-patterns 可帮助操作人员遵循源文档中描述的聚焦工作流,减少模糊性,并确保执行过程与预期任务保持一致。
何时应使用此技能?
当任务与技能文档中描述的工作流、领域或操作规则相符时,请使用该技能,尤其是在需要保持执行一致性时。
主要限制有哪些?
该技能受其源指令的质量和范围的限制。如果基础文档不完整,客服人员可能仍需要额外的上下文信息或手动验证。
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@EnableJpaAuditingclass 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
@Transactionalpublic 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=20spring.datasource.hikari.minimum-idle=5spring.datasource.hikari.connection-timeout=30000spring.datasource.hikari.validation-timeout=5000For PostgreSQL LOB handling, add:
spring.jpa.properties.hibernate.jdbc.lob.non_contextual_creation=trueCaching
- 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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