feat: Implement job title suggestion service with caching and tokenization

ruoyi-bussiness/pom.xml

@@ -102,6 +102,26 @@
             <artifactId>easy-es-boot-starter</artifactId>
             <version>2.0.0</version>
         </dependency>
+        <!-- Java 侧岗位名称预分词；使用 IKSegmenter，不覆盖 Elasticsearch 自带的 Lucene 版本 -->
+        <dependency>
+            <groupId>com.jianggujin</groupId>
+            <artifactId>IKAnalyzer-lucene</artifactId>
+            <version>8.0.0</version>
+            <exclusions>
+                <exclusion>
+                    <groupId>org.apache.lucene</groupId>
+                    <artifactId>lucene-core</artifactId>
+                </exclusion>
+                <exclusion>
+                    <groupId>org.apache.lucene</groupId>
+                    <artifactId>lucene-queryparser</artifactId>
+                </exclusion>
+                <exclusion>
+                    <groupId>org.apache.lucene</groupId>
+                    <artifactId>lucene-analyzers-common</artifactId>
+                </exclusion>
+            </exclusions>
+        </dependency>
         <dependency>
             <groupId>cn.hutool</groupId>
             <artifactId>hutool-all</artifactId>

ruoyi-bussiness/src/main/java/com/ruoyi/cms/controller/app/AppJobController.java

@@ -6,6 +6,7 @@ import com.ruoyi.cms.domain.query.ESJobSearch;
 import com.ruoyi.cms.service.IESJobSearchService;
 import com.ruoyi.cms.service.IJobCollectionService;
 import com.ruoyi.cms.service.IJobService;
+import com.ruoyi.cms.service.IJobTitleSuggestService;
 import com.ruoyi.cms.util.RoleUtils;
 import com.ruoyi.cms.util.sensitiveWord.SensitiveWordChecker;
 import com.ruoyi.common.annotation.BussinessLog;
@@ -22,6 +23,7 @@ import org.springframework.beans.factory.annotation.Autowired;
 import org.springframework.web.bind.annotation.*;
 
 import javax.servlet.http.HttpServletRequest;
+import java.util.Collections;
 import java.util.List;
 
 /**
@@ -42,8 +44,27 @@ public class AppJobController extends BaseController
     @Autowired
     private IESJobSearchService esJobSearchService;
     @Autowired
+    private IJobTitleSuggestService jobTitleSuggestService;
+    @Autowired
     private SensitiveWordChecker sensitiveWordChecker;
 
+    /**
+     * 岗位名称联想
+     *
+     * <p>缓存由定时任务根据有效岗位名称预先构建，接口只查询 Redis，
+     * 不在用户输入时访问岗位数据库。</p>
+     */
+    @ApiOperation("岗位名称联想")
+    @GetMapping("/suggest")
+    public AjaxResult suggest(@RequestParam(required = false) String keyword,
+                              @RequestParam(required = false, defaultValue = "10") Integer limit)
+    {
+        if (keyword == null || keyword.trim().isEmpty()) {
+            return success(Collections.emptyList());
+        }
+        return success(jobTitleSuggestService.suggest(keyword, limit));
+    }
+
     /**
      * 查询岗位列表
      */

ruoyi-bussiness/src/main/java/com/ruoyi/cms/cron/JobCron.java

@@ -5,6 +5,7 @@ import com.ruoyi.cms.service.IBussinessOperLogService;
 import com.ruoyi.cms.service.ICompanyService;
 import com.ruoyi.cms.service.IESJobSearchService;
 import com.ruoyi.cms.service.IJobService;
+import com.ruoyi.cms.service.IJobTitleSuggestService;
 import com.ruoyi.common.utils.spring.SpringUtils;
 import org.springframework.beans.factory.annotation.Autowired;
 import org.springframework.stereotype.Component;
@@ -26,4 +27,12 @@ public class JobCron {
     public void updateJobCountOfCompany(){
         SpringUtils.getBean(ICompanyService.class).updateJobCountOfCompany();
     }
+
+    /**
+     * 重建岗位名称联想缓存。
+     * Quartz 任务调用目标：jobCron.rebuildJobTitleSuggest()
+     */
+    public void rebuildJobTitleSuggest(){
+        SpringUtils.getBean(IJobTitleSuggestService.class).rebuildCache();
+    }
 }

ruoyi-bussiness/src/main/java/com/ruoyi/cms/mapper/JobMapper.java

@@ -43,6 +43,13 @@ public interface JobMapper extends BaseMapper<Job> {
 
     List<Job> selectAllJob(Map<String, Object> params);
 
+    /**
+     * 查询去重后的有效岗位名称，供 IK 分词缓存构建使用。
+     *
+     * @return 有效岗位名称
+     */
+    List<String> selectValidJobTitles();
+
     void insertBatchRowWork(List<RowWork> batchList);
 
     List<RowWork> selectAllInsertRowWork();

ruoyi-bussiness/src/main/java/com/ruoyi/cms/service/IJobTitleSuggestService.java

@@ -0,0 +1,23 @@
+package com.ruoyi.cms.service;
+
+import java.util.List;
+
+/**
+ * 岗位名称联想服务。
+ */
+public interface IJobTitleSuggestService {
+
+    /**
+     * 根据输入前缀查询岗位名称建议。
+     *
+     * @param keyword 输入关键词
+     * @param limit 最大返回数量
+     * @return 岗位名称列表
+     */
+    List<String> suggest(String keyword, Integer limit);
+
+    /**
+     * 重建有效岗位名称的 Redis 联想缓存。
+     */
+    void rebuildCache();
+}

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));
+    }
+}

ruoyi-bussiness/src/main/java/com/ruoyi/cms/util/JobTitleSuggestTokenizer.java

@@ -0,0 +1,66 @@
+package com.ruoyi.cms.util;
+
+import org.wltea.analyzer.core.IKSegmenter;
+import org.wltea.analyzer.core.Lexeme;
+
+import java.io.IOException;
+import java.io.StringReader;
+import java.text.Normalizer;
+import java.util.LinkedHashSet;
+import java.util.Locale;
+import java.util.Set;
+
+/**
+ * 岗位名称联想用的 IK 分词器。
+ *
+ * <p>岗位名称中通常同时包含中文、英文、数字和技术栈符号，例如
+ * {@code Java开发工程师}、{@code C++工程师}。这里只保留 IKSegmenter
+ * smart 模式产生的分词结果，不额外生成完整岗位名称、字符片段或前缀。</p>
+ */
+public final class JobTitleSuggestTokenizer {
+
+    private JobTitleSuggestTokenizer() {
+    }
+
+    /**
+     * 对岗位名称或查询词做统一标准化。
+     */
+    public static String normalize(String text) {
+        if (text == null) {
+            return "";
+        }
+        String normalized = Normalizer.normalize(text, Normalizer.Form.NFKC)
+                .toLowerCase(Locale.ROOT)
+                .replaceAll("\\s+", "")
+                .trim();
+        return normalized;
+    }
+
+    /**
+     * 生成岗位名称的 IK 分词结果。
+     */
+    public static Set<String> tokenize(String title) {
+        String normalizedTitle = normalize(title);
+        Set<String> result = new LinkedHashSet<>();
+        if (normalizedTitle.isEmpty()) {
+            return result;
+        }
+
+        try (StringReader reader = new StringReader(normalizedTitle)) {
+            // true 对应 IK 的 smart 分词模式，和 ES 中的 IK_SMART 保持一致。
+            IKSegmenter segmenter = new IKSegmenter(reader, true);
+            Lexeme lexeme;
+            while ((lexeme = segmenter.next()) != null) {
+                String token = normalize(lexeme.getLexemeText());
+                if (!token.isEmpty()) {
+                    result.add(token);
+                }
+            }
+        } catch (IOException e) {
+            // StringReader 通常不会发生 I/O 异常；异常时不添加非 IK 结果，
+            // 保证 Redis 中始终只保留 IK 分词结果。
+        }
+        return result;
+    }
+
+}

ruoyi-bussiness/src/main/resources/mapper/app/JobMapper.xml

@@ -305,6 +305,15 @@
         LEFT JOIN (SELECT jc1.*, ROW_NUMBER() OVER(PARTITION BY jc1.job_id ORDER BY jc1.id) rn FROM job_contact jc1 WHERE jc1.del_flag='0') jc ON jc.job_id = j.job_id AND jc.rn=1
         WHERE j.del_flag = '0' and job_status='0' limit #{offset},#{batchSize}
     </select>
+
+    <select id="selectValidJobTitles" resultType="java.lang.String">
+        SELECT DISTINCT trim(job_title)
+        FROM job
+        WHERE del_flag = '0'
+          AND job_status = '0'
+          AND job_title IS NOT NULL
+          AND trim(job_title) &lt;&gt; ''
+    </select>
     <select id="selectAllInsertRowWork" resultType="com.ruoyi.cms.domain.RowWork">
         select  Id, TaskId, TaskName, Std_class, SF, ZCMC, Aca112, Acb22a, Aac011, Acb240,
                 Recruit_Num, Acb202, Aab302, Acb241, Salary, SalaryLow, SalaryHight, Aae397,