恢复误删除的文件

ruoyi-admin/src/main/resources/application-local.yml

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+# 项目相关配置
+ruoyi:
+  # 名称
+  name: RuoYi
+  # 版本
+  version: 3.8.8
+  # 版权年份
+  copyrightYear: 2024
+  # 文件路径 示例（ Windows配置D:/ruoyi/uploadPath，Linux配置 /home/ruoyi/uploadPath）
+  profile: /Users/chenyanchang/logs/ruoyi/uploadPath
+  # 获取ip地址开关
+  addressEnabled: false
+  # 验证码类型 math 数字计算 char 字符验证
+  captchaType: math
+
+# 数据源配置
+spring:
+  datasource:
+    type: com.alibaba.druid.pool.DruidDataSource
+    driverClassName: com.highgo.jdbc.Driver
+    druid:
+      # 主库数据源
+      # master:
+      #   url: jdbc:highgo://124.243.245.42:5866/shz?useUnicode=true&characterEncoding=utf8&currentSchema=shz&stringtype=unspecified
+      #   #username: syssso
+      #   username: sysdba
+      #   password: ZKR2024@comzkr
+      # 正式环境
+      # master:
+      #   url: jdbc:highgo://39.98.44.136:6023/highgo?useUnicode=true&characterEncoding=utf8&currentSchema=shz&stringtype=unspecified
+      #   username: sysdba
+      #   password: Hello@2026
+      # 测试环境
+      master:
+        url: jdbc:highgo://47.111.103.66:5866/highgo?useUnicode=true&characterEncoding=utf8&currentSchema=shz&stringtype=unspecified
+        username: sysdba
+        password: Hello@2026
+      # 从库数据源
+      slave:
+        # 从数据源开关/默认关闭
+        enabled: false
+        url:
+        username:
+        password:
+      # 初始连接数
+      initialSize: 10
+      # 最小连接池数量
+      minIdle: 30
+      # 最大连接池数量
+      maxActive: 50
+      # 配置获取连接等待超时的时间
+      maxWait: 60000
+      # 配置连接超时时间
+      connectTimeout: 30000
+      # 配置网络超时时间
+      socketTimeout: 60000
+      # 配置间隔多久才进行一次检测，检测需要关闭的空闲连接，单位是毫秒
+      timeBetweenEvictionRunsMillis: 60000
+      # 配置一个连接在池中最小生存的时间，单位是毫秒
+      minEvictableIdleTimeMillis: 300000
+      # 配置一个连接在池中最大生存的时间，单位是毫秒
+      maxEvictableIdleTimeMillis: 900000
+      # 配置检测连接是否有效
+      validationQuery: SELECT version()
+      testWhileIdle: true
+      testOnBorrow: false
+      testOnReturn: false
+      webStatFilter:
+        enabled: true
+      statViewServlet:
+        enabled: true
+        # 设置白名单，不填则允许所有访问
+        allow:
+        url-pattern: /druid/*
+        # 控制台管理用户名和密码
+        login-username: ruoyi
+        login-password: 123456
+      filter:
+        stat:
+          enabled: true
+          # 慢SQL记录
+          log-slow-sql: true
+          slow-sql-millis: 1000
+          merge-sql: true
+        wall:
+          config:
+            multi-statement-allow: true
+  redis:
+    # 本地
+    #host: 127.0.0.1
+    #port: 6379
+    host: 124.243.245.42
+    port: 5379
+    # 数据库索引
+    database: 0
+    # 密码（本地通常无密码）
+    password:
+    # 连接超时时间
+    timeout: 100s
+    lettuce:
+      pool:
+        # 连接池中的最小空闲连接
+        min-idle: 0
+        # 连接池中的最大空闲连接
+        max-idle: 8
+        # 连接池的最大数据库连接数
+        max-active: 8
+        # #连接池最大阻塞等待时间（使用负值表示没有限制）
+        max-wait: -1ms
+
+# easy-es
+easy-es:
+    enable: true
+    banner: false
+    address: 124.243.245.42:9200
+    global-config:
+        process-index-mode: manual
+        db-config:
+            refresh-policy: immediate
+    username: elastic
+    password: zkr2024@@.com
+
+#ai
+chat:
+  baseUrl: http://39.98.44.136:8082
+  chatUrl: /v1/chat/completions
+  chatDetailUrl: /core/chat/getPaginationRecords
+  chatHistoryUrl: /core/chat/getHistories
+  updateNameUrl: /core/chat/updateHistory
+  stickChatUrl: /core/chat/updateHistory
+  delChatUrl: /core/chat/delHistory
+  delAllChatUrl: /core/chat/clearHistories
+  guestUrl: /v1/chat/completions
+  praiseUrl: /core/chat/feedback/updateUserFeedback
+  appId: 67cd49095e947ae0ca7fadd8
+  apiKey: fastgpt-qMl63276wPZvKAxEkW77bur0sSJpmuC6Ngg9lzyEjufLhsBAurjT55j
+  model: qd-job-turbo
+
+audioText:
+  asr: http://127.0.0.1:8000/asr/file
+  tts: http://127.0.0.1:19527/synthesize
+
+#浪潮单点登录相关
+#互联网端：
+lc_web_auth:
+  appId: cloud-out-2fb6330e9c0843e1a1424efda5d604c0
+  appSecret: x14lueHbtLQL7Pz2G7gE4wcGCV6TDblO5xfeu9V2wGk=
+  getTokenUrl: http://218.31.252.15:9081/prod-psout-api/auth/token
+  getUserInfoUrl: http://218.31.252.15:9081/prod-psout-api/system/app/authorize/user/info
+  editUserInfoUrl: http://218.31.252.15:9081/prod-psout-api/auth/user/edit
+#监管端：
+lc_cms_auth:
+  appId: cloud-9793ee8a8c3d47b8871007ffc4128502
+  appSecret: Yi+NACK70UPg8rFvsnnfBUq1wcLD4nm6ilC4II/4C4k=
+  getTokenUrl: http://218.31.252.15:9081/prod-api/auth/token
+  getUserInfoUrl: http://218.31.252.15:9081/prod-api/system/app/authorize/user/info
+  resrtPwdUrl: http://218.31.252.15:9081/prod-api/ps/user/resetPwd/zkr
+  changeStatusUrl: http://218.31.252.15:9081/prod-api/ps/user/change/status/zkr

ruoyi-bussiness/src/main/java/com/ruoyi/cms/service/impl/JobTitleSuggestServiceImpl.java

@@ -0,0 +1,187 @@
+package com.ruoyi.cms.service.impl;
+
+import com.ruoyi.cms.mapper.JobMapper;
+import com.ruoyi.cms.service.IJobTitleSuggestService;
+import com.ruoyi.cms.util.JobTitleSuggestTokenizer;
+import com.ruoyi.common.core.redis.RedisCache;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+import org.springframework.beans.factory.annotation.Autowired;
+import org.springframework.stereotype.Service;
+
+import javax.annotation.PostConstruct;
+import java.util.ArrayList;
+import java.util.Collections;
+import java.util.LinkedHashMap;
+import java.util.LinkedHashSet;
+import java.util.List;
+import java.util.Map;
+import java.util.Set;
+import java.util.TreeMap;
+import java.util.TreeSet;
+import java.util.UUID;
+import java.util.concurrent.TimeUnit;
+import java.util.stream.Collectors;
+
+/**
+ * 岗位名称 IK 分词联想服务实现。
+ */
+@Service
+public class JobTitleSuggestServiceImpl implements IJobTitleSuggestService {
+
+    private static final Logger logger = LoggerFactory.getLogger(JobTitleSuggestServiceImpl.class);
+
+    /**
+     * Redis Hash：field 是 IK 分词，value 是包含该分词的完整岗位名称列表。
+     */
+    private static final String CACHE_KEY = "app:job:title:suggest";
+    private static final String BUILDING_CACHE_KEY = CACHE_KEY + ":building";
+    private static final String LOCK_KEY = CACHE_KEY + ":rebuild:lock";
+
+    private static final int DEFAULT_LIMIT = 10;
+    private static final int MAX_LIMIT = 20;
+    private static final int LOCK_EXPIRE_MINUTES = 30;
+
+    @Autowired
+    private JobMapper jobMapper;
+
+    @Autowired
+    private RedisCache redisCache;
+
+    /**
+     * 确保服务启动后 Redis 中已有一份缓存；后续由 Quartz 定时任务周期性重建。
+     */
+    @PostConstruct
+    public void init() {
+        rebuildCache();
+    }
+
+    @Override
+    public List<String> suggest(String keyword, Integer limit) {
+        String normalizedKeyword = JobTitleSuggestTokenizer.normalize(keyword);
+        if (normalizedKeyword.isEmpty()) {
+            return Collections.emptyList();
+        }
+
+        int resultLimit = normalizeLimit(limit);
+        try {
+            Map<String, Object> tokenTitles = redisCache.getCacheMap(CACHE_KEY);
+            if (tokenTitles == null || tokenTitles.isEmpty()) {
+                return Collections.emptyList();
+            }
+
+            // Hash field 只来自 IK 分词；这里仅对已有词项做前缀过滤，不生成新的前缀词。
+            List<Map.Entry<String, Object>> matchedTokens = tokenTitles.entrySet().stream()
+                    .filter(entry -> entry.getKey() != null)
+                    .filter(entry -> entry.getKey().startsWith(normalizedKeyword))
+                    .sorted(Map.Entry.comparingByKey())
+                    .collect(Collectors.toList());
+
+            Set<String> result = new LinkedHashSet<>();
+            for (Map.Entry<String, Object> entry : matchedTokens) {
+                if (result.size() >= resultLimit) {
+                    break;
+                }
+
+                // 先返回匹配到的 IK 分词本身。
+                result.add(entry.getKey());
+
+                // 再返回包含该 IK 分词的完整岗位名称。
+                appendTitles(result, entry.getValue(), resultLimit);
+            }
+            return new ArrayList<>(result).subList(0, Math.min(result.size(), resultLimit));
+        } catch (Exception e) {
+            // 联想属于非核心能力，Redis 异常时返回空列表，不影响岗位主搜索。
+            logger.warn("查询岗位名称 IK 分词缓存失败，keyword={}", keyword, e);
+            return Collections.emptyList();
+        }
+    }
+
+    @Override
+    public void rebuildCache() {
+        String lockValue = UUID.randomUUID().toString();
+        boolean lockAcquired = false;
+        try {
+            lockAcquired = redisCache.setIfAbsent(
+                    LOCK_KEY, lockValue, LOCK_EXPIRE_MINUTES, TimeUnit.MINUTES);
+            if (!lockAcquired) {
+                logger.info("其他节点正在重建岗位名称 IK 分词缓存，本节点跳过");
+                return;
+            }
+
+            List<String> sourceList = jobMapper.selectValidJobTitles();
+            Map<String, List<String>> cacheData = buildTokenTitles(sourceList);
+
+            // 先写临时 Hash，再原子替换正式 Hash，避免接口读到半成品。
+            redisCache.deleteObject(BUILDING_CACHE_KEY);
+            if (cacheData.isEmpty()) {
+                redisCache.deleteObject(CACHE_KEY);
+            } else {
+                redisCache.setCacheMap(BUILDING_CACHE_KEY, cacheData);
+                redisCache.redisTemplate.rename(BUILDING_CACHE_KEY, CACHE_KEY);
+            }
+            logger.info("岗位名称 IK 分词缓存重建完成，有效岗位名称{}个，IK 词{}个",
+                    sourceList == null ? 0 : sourceList.size(), cacheData.size());
+        } catch (Exception e) {
+            logger.error("重建岗位名称 IK 分词缓存失败", e);
+        } finally {
+            if (lockAcquired) {
+                redisCache.deleteObject(LOCK_KEY);
+            }
+        }
+    }
+
+    private Map<String, List<String>> buildTokenTitles(List<String> sourceList) {
+        Map<String, Set<String>> tokenTitles = new TreeMap<>();
+        if (sourceList == null) {
+            return Collections.emptyMap();
+        }
+
+        for (String title : sourceList) {
+            String displayTitle = normalizeDisplayTitle(title);
+            if (displayTitle.isEmpty()) {
+                continue;
+            }
+
+            Set<String> tokens = JobTitleSuggestTokenizer.tokenize(displayTitle);
+            for (String token : tokens) {
+                tokenTitles.computeIfAbsent(token, key -> new TreeSet<>()).add(displayTitle);
+            }
+        }
+
+        Map<String, List<String>> result = new LinkedHashMap<>();
+        for (Map.Entry<String, Set<String>> entry : tokenTitles.entrySet()) {
+            result.put(entry.getKey(), new ArrayList<>(entry.getValue()));
+        }
+        return result;
+    }
+
+    private void appendTitles(Set<String> result, Object cachedTitles, int resultLimit) {
+        if (!(cachedTitles instanceof Iterable)) {
+            return;
+        }
+        for (Object cachedTitle : (Iterable<?>) cachedTitles) {
+            if (cachedTitle == null || result.size() >= resultLimit) {
+                break;
+            }
+            String title = String.valueOf(cachedTitle);
+            if (!title.isEmpty()) {
+                result.add(title);
+            }
+        }
+    }
+
+    private String normalizeDisplayTitle(String title) {
+        if (title == null) {
+            return "";
+        }
+        return title.trim().replaceAll("\\s+", " ");
+    }
+
+    private int normalizeLimit(Integer limit) {
+        if (limit == null) {
+            return DEFAULT_LIMIT;
+        }
+        return Math.max(1, Math.min(limit, MAX_LIMIT));
+    }
+}