# 基于Redis+ES的高效LBS ## 实现思路 ```aiignore 用户 → Redis GEO 筛选附近用户 → ES 排序（标签+距离+活跃时间） → 返回结果 ``` 标签相同个数按照从多到少排序，距离按照从近到远排序，活跃时间和当前时间的差从小到大排序，主要目标对象还是附近的人所以先用Redis筛选附近的人 ## 引入依赖 :warning: ES版本是8.18.2 ```xml org.springframework.boot spring-boot-starter-web org.springframework.boot spring-boot-starter-data-redis org.projectlombok lombok true co.elastic.clients elasticsearch-java 8.18.2 org.elasticsearch.client elasticsearch-rest-client 8.18.2 com.fasterxml.jackson.core jackson-databind org.springframework.boot spring-boot-starter-test test ``` ## 简单Web逻辑代码实体类 ```java @Data public class Location { private Double lat; private Double lon; } ``` ```java @Data public class User { private Long id; private String name; private List tags; @JsonFormat(pattern = "yyyy-MM-dd HH:mm:ss", timezone = "Asia/Shanghai") private Date lastLogin; private Location location; } ``` ```java @Data public class UserVO { private Long id; private String name; private List tags; @JsonFormat(pattern = "yyyy-MM-dd HH:mm:ss", timezone = "Asia/Shanghai") private Date lastLogin; private Double distance; } ``` ES配置类 ```java @Configuration public class ElasticsearchConfig { @Value("${elasticsearch.host:localhost}") private String host; @Value("${elasticsearch.port:9200}") private Integer port; @Value("${elasticsearch.username:}") private String username; @Value("${elasticsearch.password:}") private String password; @Bean public RestClient restClient() { RestClientBuilder builder = RestClient.builder( new HttpHost(host, port, "http") ); // 如果配置了用户名和密码,则使用认证 if (username != null && !username.isEmpty()) { CredentialsProvider credentialsProvider = new BasicCredentialsProvider(); credentialsProvider.setCredentials( AuthScope.ANY, new UsernamePasswordCredentials(username, password) ); builder.setHttpClientConfigCallback(httpClientBuilder -> httpClientBuilder.setDefaultCredentialsProvider(credentialsProvider) ); } return builder.build(); } @Bean public ElasticsearchTransport elasticsearchTransport(RestClient restClient) { // ObjectMapper with JavaTimeModule ObjectMapper mapper = new ObjectMapper(); mapper.registerModule(new JavaTimeModule()); mapper.disable(SerializationFeature.WRITE_DATES_AS_TIMESTAMPS); // JacksonJsonpMapper 使用自定义的 ObjectMapper JacksonJsonpMapper jsonpMapper = new JacksonJsonpMapper(mapper); return new RestClientTransport(restClient, jsonpMapper); } @Bean public ElasticsearchClient elasticsearchClient(ElasticsearchTransport transport) { return new ElasticsearchClient(transport); } } ``` Redis配置类 ```java @Configuration public class RedisConfig { /** * RedisTemplate 配置 */ @Bean public RedisTemplate redisTemplate(RedisConnectionFactory redisConnectionFactory) { RedisTemplate template = new RedisTemplate<>(); template.setConnectionFactory(redisConnectionFactory); // key 序列化 StringRedisSerializer stringSerializer = new StringRedisSerializer(); // value 序列化（JSON） GenericJackson2JsonRedisSerializer jsonSerializer = new GenericJackson2JsonRedisSerializer(); // key & hash key template.setKeySerializer(stringSerializer); template.setHashKeySerializer(stringSerializer); // value & hash value template.setValueSerializer(jsonSerializer); template.setHashValueSerializer(jsonSerializer); template.afterPropertiesSet(); return template; } } ``` controller类 ```java @RestController @RequestMapping("/user") public class UserController { @Resource private ElasticsearchClient elasticsearchClient; @Resource private UserService userService; @GetMapping("/createIndex") public String createIndex() throws IOException { if (elasticsearchClient.indices().exists(e -> e.index("user")).value()) { return "索引 user 已存在"; } TypeMapping mapping = new TypeMapping.Builder() .properties("id", new Property.Builder() .long_(l -> l) .build()) .properties("name", new Property.Builder() .keyword(k -> k) .build()) .properties("tags", new Property.Builder() .keyword(k -> k) .build()) .properties("lastLogin", new Property.Builder() .date(d -> d.format("yyyy-MM-dd HH:mm:ss||strict_date_optional_time")) .build()) .properties("location", new Property.Builder() .geoPoint(g -> g) .build()) .build(); CreateIndexRequest createIndexRequest = new CreateIndexRequest.Builder() .index("user") .mappings(mapping) .build(); CreateIndexResponse createIndexResponse = elasticsearchClient.indices().create(createIndexRequest); return "user 索引创建成功"; } /** * 初始化 50 条假数据（写入 Redis + ES） */ @GetMapping("/init") public String init() throws IOException { userService.generateUsers(); return "初始化数据成功"; } @PostMapping("/search") public List query(@RequestBody User user){ if(user==null){ throw new RuntimeException("未登录"); } if(user.getLocation()==null){ throw new RuntimeException("未开启位置定位，无法使用"); } return userService.searchUsers(user); } } ``` service接口 ```java public interface UserService { public void generateUsers() throws IOException; List searchUsers(User user); } ``` service实现类(ES实现使用的是低级客户端，高级客户端lambda一堆报错) ```java @Service public class UserServiceImpl implements UserService { @Resource private RedisTemplate redisTemplate; @Resource private ElasticsearchClient elasticsearchClient; @Resource private RestClient restClient; private static final String GEO_KEY = "user:geo"; private static final List TAG_POOL = Arrays.asList( "唱歌", "跳舞", "Java", "LOL", "绘画", "健身", "旅游", "摄影", "美食", "篮球","C++","Rust","Go","C" ); private static final double R = 6371.0; @Override public void generateUsers() throws IOException { double baseLon = 116.403; double baseLat = 39.923; for (int i = 1; i <= 50; i++) { User user = new User(); user.setId((long) i); user.setName("用户" + i); user.setLastLogin(new Date(System.currentTimeMillis() - new Random().nextInt(600) * 60 * 1000L)); // 随机兴趣标签 Collections.shuffle(TAG_POOL); user.setTags(TAG_POOL.subList(0, 3)); // 随机坐标 double lon = baseLon + (Math.random() - 0.5) * 0.04; double lat = baseLat + (Math.random() - 0.5) * 0.04; // 使用 Location 类来设置坐标（关键修改点） Location location = new Location(); location.setLat(lat); location.setLon(lon); user.setLocation(location); // Redis GEO 使用 lon + lat redisTemplate.opsForGeo().add( GEO_KEY, new Point(lon, lat), user.getId().toString() ); // 写入 ES（自动序列化为 { "lat": xx, "lon": xx }） elasticsearchClient.index(k -> k .index("user") .id(user.getId().toString()) .document(user) ); } } @Override public List searchUsers(User requestUser) { double lat = requestUser.getLocation().getLat(); double lon = requestUser.getLocation().getLon(); List tags = requestUser.getTags(); if (tags == null || tags.isEmpty()) { throw new RuntimeException("请至少传入一个兴趣标签"); } try { //1. Redis 查询附近用户（半径 5km） GeoResults> nearby = redisTemplate.opsForGeo().radius( GEO_KEY, new Circle(new Point(lon, lat), new Distance(5, Metrics.KILOMETERS)), RedisGeoCommands.GeoRadiusCommandArgs.newGeoRadiusArgs().sortAscending() ); List nearIds = nearby.getContent() .stream() .map(r -> r.getContent().getName().toString()) // ← 必须 toString .collect(Collectors.toList()); // 删除当前用户自身 nearIds.remove(requestUser.getId().toString()); // 附近没人直接返回空 if (nearIds.isEmpty()) { return Collections.emptyList(); } // 构造 terms id 过滤字段 String filterIds = nearIds.stream() .map(id -> "\"" + id + "\"") .collect(Collectors.joining(",")); // ========== 2. 构造 should (tags) ========== String shouldTags = tags.stream() .map(t -> "{\"term\":{\"tags\":\"" + t + "\"}}") .collect(Collectors.joining(",")); // ========== 3. painless 参数 ========== String paramsTags = tags.stream() .map(t -> "\"" + t + "\"") .collect(Collectors.joining(",")); // ========== 4. 当前时间（用于 lastLogin decay） ========== String nowStr = new SimpleDateFormat("yyyy-MM-dd HH:mm:ss").format(new Date()); // ========== 5. ES 查询 JSON ========== String jsonQuery = "{\n" + " \"size\": 5,\n" + " \"query\": {\n" + " \"bool\": {\n" + " \"filter\": {\n" + " \"terms\": { \"id\": [" + filterIds + "] }\n" + " },\n" + " \"must\": {\n" + " \"function_score\": {\n" + " \"query\": {\"bool\": {\"should\": [" + shouldTags + "], \"minimum_should_match\": 1}},\n" + " \"functions\": [\n" + " {\n" + " \"script_score\": {\n" + " \"script\": {\n" + " \"source\": \"int s=0; for(tag in params.tags){ if(doc['tags'].contains(tag)){s++;}} return s;\",\n" + " \"params\": {\"tags\": [" + paramsTags + "]}\n" + " }\n" + " },\n" + " \"weight\": 3\n" + " },\n" + " {\n" + " \"gauss\": {\"lastLogin\": {\"origin\": \"" + nowStr + "\", \"scale\": \"2h\", \"decay\": 0.5}},\n" + " \"weight\": 2\n" + " },\n" + " {\n" + " \"gauss\": {\"location\": {\"origin\": \"" + lat + "," + lon + "\", \"scale\": \"3km\", \"decay\": 0.5}},\n" + " \"weight\": 3\n" + " }\n" + " ],\n" + " \"score_mode\": \"sum\",\n" + " \"boost_mode\": \"sum\"\n" + " }\n" + " }\n" + " }\n" + " }\n" + "}"; // ========== 6. 调 ES ========== Request req = new Request("GET", "/user/_search"); req.setJsonEntity(jsonQuery); Response response = restClient.performRequest(req); String json = EntityUtils.toString(response.getEntity(), "UTF-8"); // ========== 7. 解析结果 ========== ObjectMapper mapper = new ObjectMapper(); mapper.registerModule(new JavaTimeModule()); mapper.disable(SerializationFeature.WRITE_DATES_AS_TIMESTAMPS); JsonNode hits = mapper.readTree(json).path("hits").path("hits"); List result = new ArrayList<>(); for (JsonNode hit : hits) { User u = mapper.treeToValue(hit.path("_source"), User.class); UserVO vo = new UserVO(); BeanUtils.copyProperties(u, vo); // 计算真实距离（2位小数） double dist = calculateDistance(lat, lon, u.getLocation().getLat(), u.getLocation().getLon()); vo.setDistance(dist); result.add(vo); } return result; } catch (Exception e) { throw new RuntimeException("搜索失败：" + e.getMessage(), e); } } private double calculateDistance(double lat1, double lon1, double lat2, double lon2) { // 地球半径 km double dLat = Math.toRadians(lat2 - lat1); double dLon = Math.toRadians(lon2 - lon1); lat1 = Math.toRadians(lat1); lat2 = Math.toRadians(lat2); double a = Math.sin(dLat / 2) * Math.sin(dLat / 2) + Math.cos(lat1) * Math.cos(lat2) * Math.sin(dLon / 2) * Math.sin(dLon / 2); double c = 2 * Math.atan2(Math.sqrt(a), Math.sqrt(1 - a)); double distance = R * c; return new BigDecimal(distance) .setScale(2, RoundingMode.HALF_UP) .doubleValue(); } } ``` yml配置(ES未开始HTTPS) ```yml server: port: 8080 servlet: context-path: /api spring: redis: host: localhost port: 6379 elasticsearch: host: localhost port: 9200 ``` ## Postman测试 GET ```GET http://localhost:8080/api/user/createIndex ``` GET ``` http://localhost:8080/api/user/init ``` POST ``` http://localhost:8080/api/user/search ``` POST方法的body ```json { "id": 1, "name": "张三", "tags": ["Java", "摄影", "美食","跳舞"], "lastLogin": "2024-01-23 10:30:00", "location": { "lat": 39.89, "lon": 116.40 } } ``` 测试结果结果： ![LBS1.png](https://pic.code-nav.cn/post_picture/1849772491394826242/CTG9dyhYs5pij6kT.webp)

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