186 lines
7.3 KiB
Markdown
186 lines
7.3 KiB
Markdown
---
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name: kotlin-backend-jpa-entity-mapping
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description: >
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Model Kotlin persistence code correctly for Spring Data JPA and Hibernate.
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Covers entity design, identity and equality, uniqueness constraints,
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relationships, fetch plans, and common ORM (Object-Relational Mapping) traps
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specific to Kotlin. Use when creating or reviewing JPA (Java Persistence API)
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entities, diagnosing N+1 or LazyInitializationException, placing indexes and
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uniqueness rules, or preventing Kotlin-specific bugs such as data class
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entities and broken equals/hashCode.
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license: Apache-2.0
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metadata:
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author: JetBrains
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version: "1.0.0"
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---
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# JPA Entity Mapping for Kotlin
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Kotlin's `data class` is natural for DTOs but dangerous for JPA entities. Hibernate relies on
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identity semantics that `data class` breaks: `equals`/`hashCode` over all fields corrupts
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`Set`/`Map` membership after state changes, and auto-generated `copy()` creates detached
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duplicates of managed entities.
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This skill teaches correct entity design, identity strategies, and uniqueness constraints
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for Kotlin + Spring Data JPA projects.
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## Entity Design Rules
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- **Never use `data class` for JPA entities.** Use a regular `class`. Keep `data class` for DTOs.
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- Keep transport DTOs and persistence entities separate unless the project clearly uses a shared model.
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- Model required columns as non-null only when object construction and persistence lifecycle make it safe.
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- Use `lateinit` only when the project already accepts that tradeoff and the lifecycle is safe.
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- Verify `kotlin("plugin.jpa")` or equivalent no-arg support when JPA entities exist.
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- Verify classes and members are compatible with proxying where needed.
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## Identity and Equality
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- Never accept all-field `equals`/`hashCode` generated by `data class` on an entity.
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- Follow project conventions when they already define an identity strategy.
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- If no convention exists, use ID-based equality with a stable `hashCode`.
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- For DB-generated IDs, model the unsaved state with nullable `var id: Long? = null`
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and a `protected set`; do not use `0L` as a sentinel value.
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- Be explicit about mutable fields and lazy associations when discussing equality.
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### Broken: `data class` Entity
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```kotlin
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// WRONG: data class generates equals/hashCode from ALL fields,
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// and the generated ID uses a 0 sentinel instead of null
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data class Order(
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@Id @GeneratedValue val id: Long = 0,
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var status: String,
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var total: BigDecimal
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)
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// BUG: order.status = "SHIPPED"; set.contains(order) → false (hash changed)
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// BUG: Hibernate proxy.equals(entity) → false (proxy has lazy fields uninitialized)
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```
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### Correct: Regular Class with ID-Based Identity
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```kotlin
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@Entity
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@Table(name = "orders")
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class Order(
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@Column(nullable = false)
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var status: String,
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@Column(nullable = false)
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var total: BigDecimal
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) {
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@Id
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@GeneratedValue(strategy = GenerationType.IDENTITY)
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var id: Long? = null
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protected set
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override fun equals(other: Any?): Boolean {
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if (this === other) return true
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if (other !is Order) return false
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return id != null && id == other.id
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}
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override fun hashCode(): Int = javaClass.hashCode()
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// toString must NOT reference lazy collections
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override fun toString(): String = "Order(id=$id, status=$status)"
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}
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```
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**Key rules:**
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- `equals` compares by ID only — stable under dirty tracking and proxy unwrapping
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- `hashCode` returns class-based constant — avoids `Set`/`Map` corruption after persist
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- `toString` excludes lazy-loaded relations — prevents `LazyInitializationException`
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- Constructor params are mutable entity fields; DB-generated `id` is nullable with a protected setter
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## Uniqueness Constraints
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When an API must be idempotent (e.g., "reserve stock for order X"), enforce uniqueness
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at both layers: database constraint for correctness, application check for clean errors.
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### Broken: No Duplicate Guard
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```kotlin
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@Service
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class ReservationService(private val repo: ReservationRepository) {
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@Transactional
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fun createReservation(variantId: Long, orderId: String, qty: Int): Reservation {
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// BUG: no check — duplicates silently accumulate
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return repo.save(Reservation(variantId = variantId, orderId = orderId, quantity = qty))
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}
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}
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```
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### Correct: Database Constraint + Application Guard
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```kotlin
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@Entity
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@Table(
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name = "reservations",
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uniqueConstraints = [
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UniqueConstraint(columnNames = ["variant_id", "order_id"])
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]
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)
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class Reservation(
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@Column(name = "variant_id", nullable = false)
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val variantId: Long,
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@Column(name = "order_id", nullable = false)
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val orderId: String,
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@Column(nullable = false)
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var quantity: Int
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) {
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@Id @GeneratedValue(strategy = GenerationType.IDENTITY)
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var id: Long? = null
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protected set
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}
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interface ReservationRepository : JpaRepository<Reservation, Long> {
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fun findByVariantIdAndOrderId(variantId: Long, orderId: String): Reservation?
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}
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@Service
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class ReservationService(private val repo: ReservationRepository) {
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@Transactional
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fun createReservation(variantId: Long, orderId: String, qty: Int): Reservation {
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repo.findByVariantIdAndOrderId(variantId, orderId)?.let {
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throw IllegalStateException(
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"Reservation already exists for variant=$variantId, order=$orderId"
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)
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}
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return repo.save(Reservation(variantId = variantId, orderId = orderId, quantity = qty))
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}
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}
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```
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**Key rules:**
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- Database constraint is mandatory — application checks alone have race conditions
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- Application check provides clean error messages — without it, users get raw `DataIntegrityViolationException`
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- Both layers together: application catches the common case, database catches the race
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- Spring Data derives `findByXAndY` queries automatically
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## Query and Fetch Rules
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- Diagnose N+1 by looking at actual query count or SQL logs, not by guessing from annotations.
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- Prefer targeted fetch solutions: `@EntityGraph`, `JOIN FETCH`, batch fetching, or DTO projection.
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- Be careful with collection fetch joins plus pagination — call out the tradeoff.
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- Use indexes and uniqueness constraints to support real query patterns.
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## Common ORM Traps
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- **Bidirectional associations:** maintain both sides in domain methods. Half-updated graphs cause subtle bugs.
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- **`orphanRemoval` vs cascade remove:** not interchangeable. Explain lifecycle semantics before choosing.
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- **Lazy load triggers:** `toString`, debug logging, JSON serialization, and IDE inspection can all trigger lazy loads.
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- **Bulk updates/deletes:** bypass persistence context and lifecycle callbacks. Subsequent reads may be stale.
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- **Multiple bag fetches:** can cause Cartesian explosion. Verify the ORM can execute collection-heavy fetch plans safely.
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- **`Set` + mutable equality:** collection membership can break after entity state changes.
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- **`@Version`:** the clearest optimistic concurrency mechanism when concurrent updates matter.
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- **`open-in-view` disabled:** DTO mapping touching lazy fields must happen inside a transaction boundary.
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## Guardrails
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- Do not use `data class` for JPA entities.
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- Do not recommend `FetchType.EAGER` everywhere to silence lazy loading symptoms.
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- Do not expose entities directly through API responses by default.
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- Do not claim an N+1 fix without explaining how the fetch plan changes query behavior.
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