jpa-patterns
affaan-m/everything-claude-code
Spring Boot 中用於實體設計、關聯、查詢優化、交易處理、稽核、索引、分頁及連接池的 JPA/Hibernate 設計模式。
...展開全部關於 jpa-patterns
jpa-patterns 這是一項專注於特定工作流程的可重複使用 AI 技能。描述:適用於 Spring Boot 環境中,針對實體設計、關聯、查詢優化、交易處理、稽核、索引建立、分頁及連接池等情境的 JPA/Hibernate 設計模式。
此技能整合了操作說明、規範及針對特定任務的指引,使執行者能更一致地執行工作。適用於 Spring Boot 中的資料建模、儲存庫及效能調校。- 設計 JPA 實體與資料表對應 - 定義關聯 (@OneToMany、@ManyToOne、@ManyToMany)
實際上,此技能最適合需要可重複執行、且設定步驟較少、模糊性較低的使用者。 - 優化查詢(防止 N+1 問題、擷取策略、投影) - 配置交易、稽核或軟刪除 - 設定分頁、排序或自訂儲存庫方法 - 調校連線池(HikariCP)或第二層快取
常見問題
jpa-patterns 能提供哪些協助?
jpa-patterns 協助執行者遵循原始文件中所述的聚焦工作流程,減少模糊性,並確保執行過程與預期任務保持一致。
何時應使用此技能?
當任務符合技能文件中所述的工作流程、領域或操作規則時,請使用此技能,特別是在需要一致執行時。
主要限制有哪些?
此技能受限於其原始指示的品質與範圍。若基礎文件不完整,客服人員可能仍需額外的背景資訊或進行手動驗證。
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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