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[REFACTOR] Redisearch로 매칭 알고리즘 리팩토링 #374

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Merged
Yoonchulchung merged 4 commits into from
Feb 11, 2026
Merged

[REFACTOR] Redisearch로 매칭 알고리즘 리팩토링 #374

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d5da136
refactor(#372): Redisearch로 매칭 알고리즘 변화
Yoonchulchung Feb 11, 2026
7fa72b1
fix: 체크스타일 반영
Yoonchulchung Feb 11, 2026
70ae0c9
fix(#372): 매칭 알고리즘 수정
Yoonchulchung Feb 11, 2026
67297ca
Merge branch 'dev' into refactor/372-match-type
Yoonchulchung Feb 11, 2026
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37 changes: 21 additions & 16 deletions data/generators/redis_matching_generator.py
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Original file line number Diff line number Diff line change
Expand Up @@ -104,6 +104,11 @@ def _get_random_tag_ids_by_type(self, tag_type, min_count=1, max_count=3):
count = random.randint(min_count, min(max_count, len(available_ids)))
return random.sample(available_ids, count)

@staticmethod
def _to_str_list(int_list):
"""RediSearch TAG 필드는 문자열만 허용하므로 정수 리스트를 문자열 리스트로 변환"""
return [str(v) for v in int_list] if int_list else []

def generate_brand_documents(self):
print("\n[브랜드] Redis 브랜드 태그 문서 생성 중...")

Expand Down Expand Up @@ -165,19 +170,19 @@ def generate_brand_documents(self):
'brandId': brand_id,
'brandName': brand['brand_name'],
'categories': categories,
'preferredFashionTags': fashion_tags,
'preferredBeautyTags': beauty_tags,
'preferredContentTags': content_tags,
'preferredFashionTags': self._to_str_list(fashion_tags),
'preferredBeautyTags': self._to_str_list(beauty_tags),
'preferredContentTags': self._to_str_list(content_tags),
'minCreatorHeight': random.choice([None, 150, 155, 160]),
'maxCreatorHeight': random.choice([None, 175, 180, 185]),
'preferredBodyTypeTags': body_type_tags,
'preferredTopSizeTags': [s for s in random.sample(range(44, 110, 2), 3)],
'preferredBottomSizeTags': [s for s in random.sample(range(24, 36), 3)],
'preferredBodyTypeTags': self._to_str_list(body_type_tags),
'preferredTopSizeTags': self._to_str_list(random.sample(range(44, 110, 2), 3)),
'preferredBottomSizeTags': self._to_str_list(random.sample(range(24, 36), 3)),
'minContentsAverageViews': random.choice([None, 10000, 50000, 100000]),
'maxContentsAverageViews': random.choice([None, 500000, 1000000]),
'preferredContentsAgeTags': audience_age_tags,
'preferredContentsGenderTags': audience_gender_tags,
'preferredContentsLengthTags': video_length_tags,
'preferredContentsAgeTags': self._to_str_list(audience_age_tags),
'preferredContentsGenderTags': self._to_str_list(audience_gender_tags),
'preferredContentsLengthTags': self._to_str_list(video_length_tags),
}

key = f"com.example.RealMatch.match.infrastructure.redis.document.BrandTagDocument:brand:{brand_id}"
Expand Down Expand Up @@ -225,21 +230,21 @@ def generate_campaign_documents(self):
'rewardAmount': float(campaign['reward_amount']) if campaign['reward_amount'] else None,
'recruitEndDate': campaign['recruit_end_date'].isoformat() if campaign['recruit_end_date'] else None,
'categories': categories,
'preferredFashionTags': fashion_tags,
'preferredBeautyTags': beauty_tags,
'preferredContentTags': content_tags,
'preferredFashionTags': self._to_str_list(fashion_tags),
'preferredBeautyTags': self._to_str_list(beauty_tags),
'preferredContentTags': self._to_str_list(content_tags),
'minCreatorHeight': random.choice([None, 150, 155, 160]),
'maxCreatorHeight': random.choice([None, 175, 180, 185]),
'preferredBodyTypeTags': body_type_tags,
'preferredBodyTypeTags': self._to_str_list(body_type_tags),
'minCreatorTopSizes': random.choice([None, 44, 50, 55]),
'maxCreatorTopSizes': random.choice([None, 100, 105, 110]),
'minCreatorBottomSizes': random.choice([None, 24, 26, 28]),
'maxCreatorBottomSizes': random.choice([None, 32, 34, 36]),
'minContentsAverageViews': random.choice([None, 10000, 50000, 100000]),
'maxContentsAverageViews': random.choice([None, 500000, 1000000]),
'preferredContentsAgeTags': audience_age_tags,
'preferredContentsGenderTags': audience_gender_tags,
'preferredContentsLengthTags': video_length_tags,
'preferredContentsAgeTags': self._to_str_list(audience_age_tags),
'preferredContentsGenderTags': self._to_str_list(audience_gender_tags),
'preferredContentsLengthTags': self._to_str_list(video_length_tags),
'startDate': campaign['start_date'].isoformat() if campaign['start_date'] else None,
'endDate': campaign['end_date'].isoformat() if campaign['end_date'] else None,
'quota': campaign['quota'],
Expand Down
39 changes: 37 additions & 2 deletions src/main/java/com/example/RealMatch/match/infrastructure/redis/RedisDocumentHelper.java
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Original file line number Diff line number Diff line change
Expand Up @@ -32,14 +32,15 @@ public class RedisDocumentHelper {
private static final String CAMPAIGN_INDEX = "com.example.RealMatch.match.infrastructure.redis.document.CampaignTagDocumentIdx";

private static final int SEARCH_LIMIT = 200;
private static final int TOP_MATCH_COUNT = 10;

public List<BrandTagDocument> findCandidateBrands(UserTagDocument userDoc) {
String query = buildTagOverlapQuery(
userDoc.getFashionTags(), "preferredFashionTags",
userDoc.getBeautyTags(), "preferredBeautyTags",
userDoc.getContentTags(), "preferredContentTags"
);
return executeSearch(BRAND_INDEX, query, BrandTagDocument.class);
return searchWithFallback(BRAND_INDEX, query, BrandTagDocument.class);
}

public List<CampaignTagDocument> findCandidateCampaigns(UserTagDocument userDoc) {
Expand All @@ -48,7 +49,41 @@ public List<CampaignTagDocument> findCandidateCampaigns(UserTagDocument userDoc)
userDoc.getBeautyTags(), "preferredBeautyTags",
userDoc.getContentTags(), "preferredContentTags"
);
return executeSearch(CAMPAIGN_INDEX, query, CampaignTagDocument.class);
return searchWithFallback(CAMPAIGN_INDEX, query, CampaignTagDocument.class);
}

private <T> List<T> searchWithFallback(String indexName, String query, Class<T> clazz) {
List<T> results = executeSearch(indexName, query, clazz);

if (results.size() < TOP_MATCH_COUNT && !"*".equals(query)) {
log.info("Tag-based search returned only {} results, falling back to full search. index={}",
results.size(), indexName);
List<T> allResults = executeSearch(indexName, "*", clazz);

// 태그 매칭된 결과의 key를 기억해서 중복 방지
Set<Object> existingIds = new java.util.HashSet<>(results.stream()
.map(this::extractDocId)
.toList());

for (T doc : allResults) {
Object docId = extractDocId(doc);
if (!existingIds.contains(docId)) {
results.add(doc);
}
}
}

return results;
}

private Object extractDocId(Object doc) {
if (doc instanceof BrandTagDocument brandDoc) {
return brandDoc.getBrandId();
}
if (doc instanceof CampaignTagDocument campaignDoc) {
return campaignDoc.getCampaignId();
}
return doc;
}

@Deprecated
Expand Down
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