忽略本地配置文件
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francis-fh
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package com.ruoyi.cms.service.impl;
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import com.ruoyi.cms.mapper.JobMapper;
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import com.ruoyi.cms.service.IJobTitleSuggestService;
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import com.ruoyi.cms.util.JobTitleSuggestTokenizer;
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import com.ruoyi.common.core.redis.RedisCache;
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import org.slf4j.Logger;
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import org.slf4j.LoggerFactory;
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import org.springframework.beans.factory.annotation.Autowired;
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import org.springframework.stereotype.Service;
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import javax.annotation.PostConstruct;
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import java.util.ArrayList;
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import java.util.Collections;
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import java.util.LinkedHashMap;
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import java.util.LinkedHashSet;
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import java.util.List;
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import java.util.Map;
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import java.util.Set;
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import java.util.TreeMap;
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import java.util.TreeSet;
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import java.util.UUID;
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import java.util.concurrent.TimeUnit;
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import java.util.stream.Collectors;
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/**
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* 岗位名称 IK 分词联想服务实现。
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*/
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@Service
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public class JobTitleSuggestServiceImpl implements IJobTitleSuggestService {
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private static final Logger logger = LoggerFactory.getLogger(JobTitleSuggestServiceImpl.class);
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/**
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* Redis Hash：field 是 IK 分词，value 是包含该分词的完整岗位名称列表。
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*/
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private static final String CACHE_KEY = "app:job:title:suggest";
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private static final String BUILDING_CACHE_KEY = CACHE_KEY + ":building";
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private static final String LOCK_KEY = CACHE_KEY + ":rebuild:lock";
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private static final int DEFAULT_LIMIT = 10;
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private static final int MAX_LIMIT = 20;
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private static final int LOCK_EXPIRE_MINUTES = 30;
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@Autowired
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private JobMapper jobMapper;
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@Autowired
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private RedisCache redisCache;
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/**
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* 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。
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*/
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@PostConstruct
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public void init() {
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rebuildCache();
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}
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@Override
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public List<String> suggest(String keyword, Integer limit) {
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String normalizedKeyword = JobTitleSuggestTokenizer.normalize(keyword);
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if (normalizedKeyword.isEmpty()) {
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return Collections.emptyList();
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}
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int resultLimit = normalizeLimit(limit);
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try {
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Map<String, Object> tokenTitles = redisCache.getCacheMap(CACHE_KEY);
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if (tokenTitles == null || tokenTitles.isEmpty()) {
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return Collections.emptyList();
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}
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// 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。
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List<Map.Entry<String, Object>> matchedTokens = tokenTitles.entrySet().stream()
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.filter(entry -> entry.getKey() != null)
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.filter(entry -> entry.getKey().startsWith(normalizedKeyword))
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.sorted(Map.Entry.comparingByKey())
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.collect(Collectors.toList());
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Set<String> result = new LinkedHashSet<>();
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for (Map.Entry<String, Object> entry : matchedTokens) {
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if (result.size() >= resultLimit) {
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break;
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}
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// 先返回匹配到的 IK 分词本身。
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result.add(entry.getKey());
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// 再返回包含该 IK 分词的完整岗位名称。
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appendTitles(result, entry.getValue(), resultLimit);
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}
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return new ArrayList<>(result).subList(0, Math.min(result.size(), resultLimit));
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} catch (Exception e) {
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// 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。
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logger.warn("查询岗位名称 IK 分词缓存失败，keyword={}", keyword, e);
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return Collections.emptyList();
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}
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}
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@Override
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public void rebuildCache() {
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String lockValue = UUID.randomUUID().toString();
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boolean lockAcquired = false;
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try {
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lockAcquired = redisCache.setIfAbsent(
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LOCK_KEY, lockValue, LOCK_EXPIRE_MINUTES, TimeUnit.MINUTES);
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if (!lockAcquired) {
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logger.info("其他节点正在重建岗位名称 IK 分词缓存，本节点跳过");
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return;
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}
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List<String> sourceList = jobMapper.selectValidJobTitles();
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Map<String, List<String>> cacheData = buildTokenTitles(sourceList);
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// 先写临时 Hash，再原子替换正式 Hash，避免接口读到半成品。
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redisCache.deleteObject(BUILDING_CACHE_KEY);
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if (cacheData.isEmpty()) {
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redisCache.deleteObject(CACHE_KEY);
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} else {
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redisCache.setCacheMap(BUILDING_CACHE_KEY, cacheData);
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redisCache.redisTemplate.rename(BUILDING_CACHE_KEY, CACHE_KEY);
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}
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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",
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sourceList == null ? 0 : sourceList.size(), cacheData.size());
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} catch (Exception e) {
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logger.error("重建岗位名称 IK 分词缓存失败", e);
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} finally {
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if (lockAcquired) {
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redisCache.deleteObject(LOCK_KEY);
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}
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}
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}
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private Map<String, List<String>> buildTokenTitles(List<String> sourceList) {
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Map<String, Set<String>> tokenTitles = new TreeMap<>();
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if (sourceList == null) {
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return Collections.emptyMap();
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}
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for (String title : sourceList) {
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String displayTitle = normalizeDisplayTitle(title);
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if (displayTitle.isEmpty()) {
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continue;
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}
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Set<String> tokens = JobTitleSuggestTokenizer.tokenize(displayTitle);
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for (String token : tokens) {
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tokenTitles.computeIfAbsent(token, key -> new TreeSet<>()).add(displayTitle);
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}
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}
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Map<String, List<String>> result = new LinkedHashMap<>();
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for (Map.Entry<String, Set<String>> entry : tokenTitles.entrySet()) {
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result.put(entry.getKey(), new ArrayList<>(entry.getValue()));
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}
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return result;
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}
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private void appendTitles(Set<String> result, Object cachedTitles, int resultLimit) {
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if (!(cachedTitles instanceof Iterable)) {
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return;
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}
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for (Object cachedTitle : (Iterable<?>) cachedTitles) {
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if (cachedTitle == null || result.size() >= resultLimit) {
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break;
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}
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String title = String.valueOf(cachedTitle);
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if (!title.isEmpty()) {
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result.add(title);
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}
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}
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}
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private String normalizeDisplayTitle(String title) {
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if (title == null) {
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return "";
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}
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return title.trim().replaceAll("\\s+", " ");
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}
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private int normalizeLimit(Integer limit) {
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if (limit == null) {
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return DEFAULT_LIMIT;
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}
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return Math.max(1, Math.min(limit, MAX_LIMIT));
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}
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}
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