[QUZ-125][REFACTOR] 랜덤 매칭 로직에 RediSearch 적용

[QUZ-125][REFACTOR] 랜덤 매칭 로직에 RediSearch 적용

Author: s0o0bn

infrastructure/docker-compose/redis/redis.yml

@@ -1,8 +1,9 @@
 services:
   redis:
     container_name: redis
-    image: redis:latest
+    image: redis/redis-stack:latest
     ports:
       - "6379:6379"
     networks:
       - ${GLOBAL_NETWORK:-app-tier}
+    command: ["redis-stack-server"]

matching-service/matching-domain/src/main/kotlin/com/grepp/quizy/matching/domain/match/MatchingPoolManager.kt

@@ -13,9 +13,9 @@ class MatchingPoolManager(
 ) {
 
     fun save(userId: UserId) {
-        val vector = userVectorizer.vectorizeUser(userId)
-        poolRepository.saveVector(userId, vector)
-        queueRepository.enqueue(UserStatus(userId, vector))
+        val status = UserStatus(userId, userVectorizer.vectorizeUser(userId))
+        poolRepository.saveVector(status)
+        queueRepository.enqueue(status)
         queueRepository.saveSet(userId)
     }
 

matching-service/matching-domain/src/main/kotlin/com/grepp/quizy/matching/domain/match/MatchingPoolRepository.kt

@@ -4,7 +4,7 @@ import com.grepp.quizy.matching.domain.user.UserId
 import com.grepp.quizy.matching.domain.user.UserVector
 
 interface MatchingPoolRepository {
-    fun saveVector(userId: UserId, userVector: UserVector)
+    fun saveVector(userStatus: UserStatus)
 
     fun findNearestUser(userStatus: UserStatus): List<UserStatus>
 

matching-service/matching-infra/build.gradle.kts

@@ -24,9 +24,8 @@ dependencies {
     implementation("org.springframework.boot:spring-boot-starter-data-jpa")
     implementation("mysql:mysql-connector-java:8.0.28")
 
-    implementation("com.fasterxml.jackson.core:jackson-databind")
-    implementation("com.fasterxml.jackson.module:jackson-module-kotlin")
     implementation("org.springframework.boot:spring-boot-starter-data-redis")
+    implementation("redis.clients:jedis:5.2.0")
 
     // Feign
     implementation("org.springframework.cloud:spring-cloud-starter-openfeign:4.1.3")

matching-service/matching-infra/src/main/kotlin/com/grepp/quizy/matching/infra/match/converter/VectorArrayConverter.kt

@@ -1,70 +1,82 @@
 package com.grepp.quizy.matching.infra.match.repository
 
-import com.grepp.quizy.matching.domain.match.MATCHING_K
 import com.grepp.quizy.matching.domain.match.MatchingPoolRepository
 import com.grepp.quizy.matching.domain.match.UserStatus
-import com.grepp.quizy.matching.infra.match.converter.toByteArray
-import com.grepp.quizy.matching.infra.match.converter.toFloatArray
 import com.grepp.quizy.matching.domain.user.UserId
 import com.grepp.quizy.matching.domain.user.UserVector
-import org.springframework.data.redis.core.RedisTemplate
+import com.grepp.quizy.matching.infra.redis.util.toByteArray
+import com.grepp.quizy.matching.infra.redis.util.toFloatArray
+import io.github.oshai.kotlinlogging.KotlinLogging
+import jakarta.annotation.PostConstruct
 import org.springframework.stereotype.Repository
-import kotlin.math.sqrt
+import redis.clients.jedis.JedisPooled
+import redis.clients.jedis.search.IndexDefinition
+import redis.clients.jedis.search.IndexOptions
+import redis.clients.jedis.search.Query
+import redis.clients.jedis.search.Schema
 
-private const val MATCHING_THRESHOLD = 0.5
-private const val MATCHING_POOL_KEY = "MATCHING_POOL"
+private const val MATCHING_INDEX_PREFIX = "MATCHING_VECTOR_POOL:"
+private const val MATCHING_INDEX = "MATCHING_INDEX"
+private const val MATCHING_K = 5
+
+private const val ID_FIELD = "id"
+private const val VECTOR_FIELD = "vector"
 
 @Repository
 class MatchingPoolRepositoryAdapter(
-    private val redisTemplate: RedisTemplate<String, Any>,
+    private val jedis: JedisPooled
 ) : MatchingPoolRepository {
+    private val log = KotlinLogging.logger {}
 
-    override fun saveVector(userId: UserId, userVector: UserVector) {
-        val key = createMatchingPoolKey(userId)
-        redisTemplate.opsForHash<String, Any>().putAll(
-            key, mapOf(
-                "id" to userId.value,
-                "vector" to userVector.value.toByteArray()
-            )
-        )
+    @PostConstruct
+    fun initialize() {
+        log.info { "Initializing RediSearchRepository" }
+        createIndex()
     }
 
-    override fun findNearestUser(userStatus: UserStatus): List<UserStatus> {
-        val keyPattern = "$MATCHING_POOL_KEY:*"
-        val keys = redisTemplate.keys(keyPattern) ?: return emptyList()
+    private fun createIndex() {
+        val definition = IndexDefinition().setPrefixes(MATCHING_INDEX_PREFIX)
+        val vectorAttr = mapOf(
+            Pair("TYPE", "FLOAT32"),
+            Pair("DIM", 15),
+            Pair("DISTANCE_METRIC", "COSINE"),
+        )
+        val schema = Schema()
+            .addNumericField(ID_FIELD)
+            .addHNSWVectorField(VECTOR_FIELD, vectorAttr)
 
-        val results = keys.mapNotNull { key ->
-            val vectorBytes = redisTemplate.opsForHash<String, Any>().get(key, "vector") as ByteArray?
-            val id = redisTemplate.opsForHash<String, Any>().get(key, "id") as Long?
-            if (vectorBytes != null && id != null) {
-                val vector = vectorBytes.toFloatArray()
-                val score = cosineSimilarity(userStatus.vector.value, vector)
-                Triple(id, vector, score) // score도 포함
-            } else null
+        try {
+            jedis.ftCreate(MATCHING_INDEX, IndexOptions.defaultOptions().setDefinition(definition), schema)
+        } catch (e: Exception) {
+            log.error { "Could not create index: ${e.message}" }
         }
-
-        return results
-            .filter { it.third >= MATCHING_THRESHOLD }
-            .sortedByDescending { it.third } // score를 기준으로 정렬
-            .take(MATCHING_K) // 상위 K개 선택
-            .map { (id, vector, _) ->
-                UserStatus(
-                    userId = UserId(id),
-                    vector = UserVector(vector)
-                )
-            }
     }
 
-    override fun remove(userId: UserId) {
-        redisTemplate.delete(createMatchingPoolKey(userId))
+    override fun saveVector(userStatus: UserStatus) {
+        val key = "$MATCHING_INDEX_PREFIX${userStatus.userId.value}"
+        jedis.hset(key, ID_FIELD, userStatus.userId.value.toString())
+        jedis.hset(key.toByteArray(), VECTOR_FIELD.toByteArray(), userStatus.vector.value.toByteArray())
     }
 
-    private fun createMatchingPoolKey(userId: UserId) = "$MATCHING_POOL_KEY:${userId.value}"
+    override fun findNearestUser(pivot: UserStatus): List<UserStatus> {
+        val query = Query("*=>[KNN ${'$'}K @$VECTOR_FIELD ${'$'}query_vector]")
+            .returnFields(ID_FIELD)
+            .addParam("K", MATCHING_K)
+            .addParam("query_vector", pivot.vector.value.toByteArray())
+            .dialect(2)
+        val docs = jedis.ftSearch(MATCHING_INDEX, query).documents
 
-    private fun cosineSimilarity(vec1: FloatArray, vec2: FloatArray): Double {
-        val dotProduct = vec1.indices.fold(0.0) { acc, i -> acc + vec1[i] * vec2[i] }
-        val magnitude1 = sqrt(vec1.fold(0.0) { acc, v -> acc + v * v })
-        val magnitude2 = sqrt(vec2.fold(0.0) { acc, v -> acc + v * v })
-        return dotProduct / (magnitude1 * magnitude2)
+        return docs.map { doc ->
+            val id = doc.get(ID_FIELD) as String
+            val vector = jedis.hget(doc.id.toByteArray(), VECTOR_FIELD.toByteArray())
+            UserStatus(
+                userId = UserId(id.toLong()),
+                vector = UserVector(vector.toFloatArray())
+            )
+        }
+    }
+
+    override fun remove(userId: UserId) {
+        jedis.del("$MATCHING_INDEX_PREFIX${userId.value}")
     }
 }

matching-service/matching-infra/src/main/kotlin/com/grepp/quizy/matching/infra/match/repository/MatchingPoolRepositoryAdapter.kt

@@ -0,0 +1,20 @@
+package com.grepp.quizy.matching.infra.redis.config
+
+import org.springframework.beans.factory.annotation.Autowired
+import org.springframework.context.annotation.Bean
+import org.springframework.context.annotation.Configuration
+import org.springframework.core.env.Environment
+import redis.clients.jedis.JedisPooled
+
+@Configuration
+class JedisConfig @Autowired constructor(private val env: Environment) {
+
+    private val host: String
+        get() = env.getProperty("redis.host") ?: "localhost"
+
+    private val port: Int
+        get() = env.getProperty("redis.port")?.toInt() ?: 6379
+
+    @Bean
+    fun jedis() = JedisPooled(host, port)
+}

matching-service/matching-infra/src/main/kotlin/com/grepp/quizy/matching/infra/redis/config/JedisConfig.kt

@@ -1,4 +1,4 @@
-package com.grepp.quizy.matching.infra.redis
+package com.grepp.quizy.matching.infra.redis.config
 
 import org.springframework.beans.factory.annotation.Autowired
 import org.springframework.context.annotation.Bean

matching-service/matching-infra/src/main/kotlin/com/grepp/quizy/matching/infra/redis/RedisConfig.kt renamed to matching-service/matching-infra/src/main/kotlin/com/grepp/quizy/matching/infra/redis/config/RedisConfig.kt

@@ -0,0 +1,21 @@
+package com.grepp.quizy.matching.infra.redis.util
+
+import java.nio.ByteBuffer
+import java.nio.ByteOrder
+
+fun FloatArray.toByteArray(): ByteArray {
+    val buffer = ByteBuffer.allocate(this.size * 4)
+    this.forEach { buffer.putFloat(it) }
+    return buffer.array()
+}
+
+fun ByteArray.toFloatArray(): FloatArray {
+    require(this.size % 4 == 0) { "ByteArray size must be a multiple of 4" }
+
+    val floatArray = FloatArray(this.size / 4)
+    val buffer = ByteBuffer.wrap(this)
+    for (i in floatArray.indices) {
+        floatArray[i] = buffer.float
+    }
+    return floatArray
+}