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@@ -2,6 +2,10 @@ package com.zhentao.service;
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import com.fasterxml.jackson.databind.ObjectMapper;
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import com.zhentao.entity.MatchData;
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+import com.zhentao.entity.User;
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+import com.zhentao.entity.UserProfile;
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+import com.zhentao.mapper.UserMapper;
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+import com.zhentao.mapper.UserProfileMapper;
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import com.zhentao.redis.RedisMatchPool;
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import com.zhentao.redis.RedisMatchQueue;
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import com.zhentao.util.MatchingAlgorithmUtils;
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@@ -11,6 +15,9 @@ import org.springframework.data.redis.core.script.DefaultRedisScript;
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import org.springframework.stereotype.Service;
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import java.util.*;
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+import java.time.LocalDate;
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+import java.time.Period;
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+import java.time.ZoneId;
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import java.util.concurrent.TimeUnit;
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@Slf4j
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@@ -26,15 +33,21 @@ public class MatchService {
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private final ObjectMapper objectMapper;
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private final RedisMatchQueue matchQueue;
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private final RedisTemplate<String, Object> redisTemplate;
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+ private final UserMapper userMapper;
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+ private final UserProfileMapper userProfileMapper;
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private final java.util.concurrent.ConcurrentHashMap<String, Long> localLocks = new java.util.concurrent.ConcurrentHashMap<>();
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public MatchService(RedisMatchPool redisMatchPool,
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ObjectMapper objectMapper, RedisMatchQueue matchQueue,
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- RedisTemplate<String, Object> redisTemplate) {
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+ RedisTemplate<String, Object> redisTemplate,
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+ UserMapper userMapper,
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+ UserProfileMapper userProfileMapper) {
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this.redisMatchPool = redisMatchPool;
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this.objectMapper = objectMapper;
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this.matchQueue = matchQueue;
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this.redisTemplate = redisTemplate;
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+ this.userMapper = userMapper;
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+ this.userProfileMapper = userProfileMapper;
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}
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public Map<String, Object> handleMatchRequest(MatchData data) {
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@@ -79,6 +92,20 @@ public class MatchService {
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}
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double threshold = getMatchThreshold(matchMode);
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+ // 先尝试从匹配池中匹配
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+ MatchResult poolResult = tryMatchFromPool(userId, userData, matchMode, threshold);
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+ if (poolResult.isMatched()) {
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+ return poolResult;
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+ }
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+
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+ // 如果匹配池中没有合适的，从数据库中的所有用户中匹配
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+ return tryMatchFromDatabase(userId, userData, matchMode, threshold);
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+ }
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+
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+ /**
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+ * 从匹配池中尝试匹配
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+ */
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+ private MatchResult tryMatchFromPool(String userId, MatchData userData, String matchMode, double threshold) {
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List<String> online = redisMatchPool.getAllUsersInPool();
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Set<String> unmatched = redisMatchPool.getUserUnmatchedSet(userId);
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Map<String, Double> scores = new HashMap<>();
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@@ -124,6 +151,136 @@ public class MatchService {
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return new MatchResult(false, null, 0);
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}
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+ /**
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+ * 从数据库中的所有已注册用户中匹配
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+ */
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+ private MatchResult tryMatchFromDatabase(String userId, MatchData userData, String matchMode, double threshold) {
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+ try {
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+ // 获取异性用户（只匹配异性）
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+ Integer targetGender = userData.getGender() == 1 ? 2 : 1;
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+ List<User> allUsers = userMapper.getUsersByGender(targetGender);
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+
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+ if (allUsers == null || allUsers.isEmpty()) {
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+ log.info("数据库中没有找到异性用户");
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+ return new MatchResult(false, null, 0);
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+ }
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+
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+ Set<String> unmatched = redisMatchPool.getUserUnmatchedSet(userId);
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+ Map<String, Double> scores = new HashMap<>();
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+
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+ for (User user : allUsers) {
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+ String otherUserId = String.valueOf(user.getUserId());
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+
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+ // 排除自己
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+ if (userId.equals(otherUserId)) continue;
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+
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+ // 排除已经不匹配的用户
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+ if (unmatched.contains(otherUserId)) continue;
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+
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+ // 构建MatchData
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+ MatchData otherData = buildMatchDataFromUser(user);
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+ if (otherData == null) continue;
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+
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+ // 根据匹配模式进行额外筛选
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+ if (!shouldMatchByMode(userData, otherData, matchMode)) {
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+ continue;
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+ }
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+
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+ // 计算匹配分数
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+ double score = MatchingAlgorithmUtils.calculateMatchScore(userData, otherData);
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+ scores.put(otherUserId, score);
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+
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+ // 如果分数达到阈值，立即返回匹配成功
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+ if (score >= threshold) {
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+ log.info("从数据库匹配成功: userId={}, matchedUserId={}, score={}", userId, otherUserId, score);
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+ return new MatchResult(true, otherUserId, score);
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+ }
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+ }
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+
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+ // 如果没有达到阈值的，返回分数最高的
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+ if (!scores.isEmpty()) {
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+ Map.Entry<String, Double> best = scores.entrySet().stream()
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+ .max(Map.Entry.comparingByValue())
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+ .get();
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+
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+ // 降低阈值要求，只要分数大于30就可以匹配
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+ if (best.getValue() >= 30.0) {
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+ log.info("从数据库匹配成功（降低阈值）: userId={}, matchedUserId={}, score={}",
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+ userId, best.getKey(), best.getValue());
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+ return new MatchResult(true, best.getKey(), best.getValue());
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+ }
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+
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+ // 记录最佳但未匹配的用户
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+ redisMatchPool.recordUnmatch(userId, best.getKey());
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+ }
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+
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+ log.info("数据库中未找到合适的匹配对象: userId={}", userId);
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+ return new MatchResult(false, null, 0);
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+
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+ } catch (Exception e) {
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+ log.error("从数据库匹配时发生错误", e);
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+ return new MatchResult(false, null, 0);
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+ }
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+ }
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+
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+ /**
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+ * 从User和UserProfile构建MatchData
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+ */
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+ private MatchData buildMatchDataFromUser(User user) {
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+ try {
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+ MatchData data = new MatchData();
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+ data.setUserId(String.valueOf(user.getUserId()));
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+ data.setNickname(user.getNickname());
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+ data.setGender(user.getGender());
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+ data.setAvatarUrl(user.getAvatarUrl());
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+
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+ // 计算年龄
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+ if (user.getBirthDate() != null) {
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+ LocalDate birthDate = user.getBirthDate().toInstant()
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+ .atZone(ZoneId.systemDefault()).toLocalDate();
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+ int age = Period.between(birthDate, LocalDate.now()).getYears();
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+ data.setAge(age);
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+ }
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+
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+ // 获取用户资料
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+ UserProfile profile = userProfileMapper.getByUserId(user.getUserId());
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+ if (profile != null) {
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+ // 设置兴趣爱好
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+ if (profile.getHobby() != null) {
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+ try {
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+ if (profile.getHobby() instanceof String) {
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+ String hobbyStr = (String) profile.getHobby();
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+ List<String> interests = objectMapper.readValue(hobbyStr, List.class);
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+ data.setInterests(interests);
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+ } else if (profile.getHobby() instanceof List) {
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+ data.setInterests((List<String>) profile.getHobby());
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+ }
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+ } catch (Exception e) {
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+ log.warn("解析兴趣爱好失败: userId={}", user.getUserId());
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+ data.setInterests(new ArrayList<>());
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+ }
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+ } else {
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+ data.setInterests(new ArrayList<>());
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+ }
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+
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+ // 设置城市信息（使用cityId）
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+ if (profile.getCityId() != null) {
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+ data.setCity("城市" + profile.getCityId());
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+ }
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+ } else {
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+ data.setInterests(new ArrayList<>());
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+ }
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+
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+ // 设置默认简介
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+ data.setIntroduction("来自数据库的用户");
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+
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+ return data;
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+ } catch (Exception e) {
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+ log.error("构建MatchData失败: userId={}", user.getUserId(), e);
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+ return null;
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+ }
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+ }
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+
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/**
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* 根据匹配模式获取阈值
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*/
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@@ -259,8 +416,10 @@ public class MatchService {
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}
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private Map<String, Object> buildUserInfo(String userId) {
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+ // 先尝试从匹配池获取
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MatchData data = redisMatchPool.getUserMatchData(userId);
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Map<String,Object> m = new HashMap<>();
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+
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if (data != null) {
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m.put("userId", data.getUserId());
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m.put("nickname", data.getNickname());
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@@ -270,6 +429,27 @@ public class MatchService {
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m.put("interests", data.getInterests());
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m.put("city", data.getCity());
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m.put("introduction", data.getIntroduction());
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+ } else {
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+ // 如果匹配池中没有，从数据库获取
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+ try {
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+ Integer userIdInt = Integer.parseInt(userId);
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+ User user = userMapper.selectById(userIdInt);
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+ if (user != null) {
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+ MatchData dbData = buildMatchDataFromUser(user);
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+ if (dbData != null) {
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+ m.put("userId", dbData.getUserId());
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+ m.put("nickname", dbData.getNickname());
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+ m.put("gender", dbData.getGender());
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+ m.put("age", dbData.getAge());
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+ m.put("avatarUrl", dbData.getAvatarUrl());
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+ m.put("interests", dbData.getInterests());
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+ m.put("city", dbData.getCity());
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+ m.put("introduction", dbData.getIntroduction());
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+ }
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+ }
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+ } catch (Exception e) {
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+ log.error("从数据库获取用户信息失败: userId={}", userId, e);
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+ }
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}
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return m;
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}
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