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[volume-5] 상품 목록 조회 성능, 좋아요 수 정렬 구조 개선 및 인덱스,캐시 적용 #200
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bd44f98
chore: H2 인메모리 DB 및 정적 리소스 설정 추가
plan11plan 7df0527
feat: 유저 도메인 기능 확장 (회원가입, 포인트 충전, 전체 조회)
plan11plan 3e0f000
feat: Admin 유저 관리 API 구현 (목록 조회, 포인트 지급)
plan11plan d84da98
feat: Admin 데이터 생성기 API 구현 (유저/좋아요/주문/쿠폰 대량 생성)
plan11plan ddfa615
feat: 관리자/쇼핑몰 프론트엔드 페이지 구현
plan11plan a070fd4
feat: ApplicationRunner 대용량 데이터 생성기 구현
plan11plan 2f69bc3
docs: Round 5 테스트 데이터 설계 문서 추가
plan11plan 45745f7
refactor: 대용량 데이터 생성 로직을 Service로 분리
plan11plan 19fbf2e
feat: 대용량 데이터 초기화 API 및 대시보드 버튼 추가
plan11plan 3c9205f
docs: 데이터 생성 API 실행 방법 추가
plan11plan 49e5d70
feat: 패션 이커머스 특성 반영 데이터 초기화 개선
plan11plan f29986b
feat: 상품 이미지 모델 및 좋아요 비정규화 구현
plan11plan a40cfce
test: 상품 이미지/좋아요 테스트 코드 추가
plan11plan 0ffb9a9
feat: 데이터 초기화에 상품 이미지 생성 추가
plan11plan 04bd023
feat: 상품 목록/상세 페이지 이미지 UI 추가
plan11plan 7725cdf
chore: static 리소스 디렉토리 gitignore 추가
plan11plan 893a0b6
refactor: 상품 인덱스 전략을 soft delete 대응 복합 인덱스로 변경
plan11plan b20ca33
feat: 데이터 초기화 soft delete 비율 설정 외부화
plan11plan 161ca4a
fix: 상품 목록 가격 정렬 버그 수정
plan11plan 25eec25
feat: 상품 목록 브랜드 사이드바 및 정렬 칩 UI 개선
plan11plan 3a6b812
feat: 상품 조회 유즈케이스별 복합 인덱스 추가
plan11plan ffd203d
feat: 브랜드 목록 Redis 캐시 적용
plan11plan e377bd9
refactor: 브랜드 캐시를 @Cacheable 기반으로 리팩토링
plan11plan 5b96c96
feat: 상품 목록 Redis 캐시 적용
plan11plan 5d17004
refactor: CacheConfig @Qualifier 불일치 수정 및 미사용 import 제거
plan11plan 5bbfc98
refactor: 컨벤션 리뷰 반영 (인라인 변수, 반복 참조 추출)
plan11plan 9a0dab8
test: 상품 목록 E2E 테스트 캐시 오염 방지
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6 changes: 6 additions & 0 deletions
6
apps/commerce-api/src/main/java/com/loopers/domain/product/ImageType.java
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,6 @@ | ||
| package com.loopers.domain.product; | ||
|
|
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| public enum ImageType { | ||
| MAIN, | ||
| DETAIL | ||
| } |
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캐시 키에 Pageable 정보가 포함되지 않아 잘못된 데이터가 반환된다.
key = "'all'"로 고정되어 있어, 서로 다른 page/size 요청이 동일한 캐시 데이터를 반환한다. 예를 들어page=0, size=10요청 후 캐시된 결과가page=1, size=20요청에도 반환되어 운영 환경에서 데이터 불일치가 발생한다.🐛 수정 제안
또는 페이지네이션이 필요 없는 전체 목록 조회라면, Pageable 파라미터를 제거하고 전체 데이터를 캐시해야 한다.
📝 Committable suggestion
🤖 Prompt for AI Agents