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黑马点评9——附近商户-GEO数据结构

news 2025/7/7 17:22:33

文章目录

GEO数据结构的基本用法
导入店铺数据结构到GEO
实现附件商户功能

GEO数据结构的基本用法

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导入店铺数据结构到GEO

数据库里没法实现按照地理坐标排序等复杂的搜索功能，我们把数据存到redis中，只需要保存id和对应的x以及y的坐标，就可以在查询的时候，从redis中根据坐标查询出id，然后根据id去数据库中查询要的数据。

    @Testpublic void loadShopData(){// 1. 查询店铺信息List<Shop> list = shopService.list();// 2. 把店铺信息分组， 按照typeId分组， id一致的放到一个集合Map<Long, List<Shop>> map = list.stream().collect(Collectors.groupingBy(Shop::getTypeId));// 3. 分批完成写入redisfor (Map.Entry<Long, List<Shop>> entry : map.entrySet()) {// 3.1 获取类型idLong typeId = entry.getKey();String key = RedisConstants.SHOP_GEO_KEY + typeId;// 3.2 获取同类型的店铺的集合List<Shop> value = entry.getValue();List<RedisGeoCommands.GeoLocation<String>> locations = new ArrayList<>(value.size());// 3.3 写入redis GEOADD key经度， 维度 memberfor (Shop shop : value) {
//                stringRedisTemplate.opsForGeo().add(key, new Point(shop.getX(), shop.getY()), shop.getId().toString());  // 效率低locations.add(new RedisGeoCommands.GeoLocation<>(shop.getId().toString(),new Point(shop.getX(), shop.getY())));}stringRedisTemplate.opsForGeo().add(key, locations);  // 批量存入}}

实现附件商户功能

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<dependency><groupId>org.springframework.boot</groupId><artifactId>spring-boot-starter-data-redis</artifactId><exclusions><exclusion><groupId>org.springframework.data</groupId><artifactId>spring-data-redis</artifactId></exclusion><exclusion><groupId>io.lettuce</groupId><artifactId>lettuce-core</artifactId></exclusion></exclusions></dependency><dependency><groupId>org.springframework.data</groupId><artifactId>spring-data-redis</artifactId><version>2.6.2</version></dependency><dependency><groupId>io.lettuce</groupId><artifactId>lettuce-core</artifactId><version>6.1.8.RELEASE</version></dependency>

@Overridepublic Result queryShopByType(Integer typeId, Integer current, Double x, Double y) {// 1. 是否需要根据坐标查询if(x == null || y == null){// 不需要坐标查询、按数据库查询Page<Shop> page = query().eq("type_id", typeId).page(new Page<>(current, SystemConstants.DEFAULT_PAGE_SIZE));// 返回数据return Result.ok(page.getRecords());}// 2. 计算分页参数int from = (current - 1) * SystemConstants.DEFAULT_PAGE_SIZE;int end = current * SystemConstants.DEFAULT_PAGE_SIZE;// 3. 查询redis、按照距离排序、分页. 结果：shopId， distanceString key = RedisConstants.SHOP_GEO_KEY + typeId;GeoResults<RedisGeoCommands.GeoLocation<String>> results = stringRedisTemplate.opsForGeo().search(key,GeoReference.fromCoordinate(x, y),new Distance(5000),RedisGeoCommands.GeoSearchCommandArgs.newGeoSearchArgs().includeDistance().limit(end));  // 这里只能传入end， 返回的是0 - end， 我们接收后在手动分页// 4. 解析出idif(results == null){return Result.ok(Collections.emptyList());}List<GeoResult<RedisGeoCommands.GeoLocation<String>>> content = results.getContent();if(content.size() <= from){// 没有下一页return Result.ok(Collections.emptyList());}// 4.1 截取从from到end部分List<Long> ids = new ArrayList<>(content.size());Map<String, Distance> distanceMap = new HashMap<>(content.size());content.stream().skip(from).forEach(result -> {// 4.2 获取店铺idString shopId = result.getContent().getName();ids.add(Long.valueOf(shopId));// 4.3 获取距离Distance distance = result.getDistance();distanceMap.put(shopId, distance);});// 5. 根据id查询shopString idStr = StrUtil.join(",", ids);List<Shop> shops = query().in("id", ids).last("ORDER BY FIELD(id," + idStr + ")").list();for (Shop shop : shops) {shop.setDistance(distanceMap.get(shop.getId().toString()).getValue());}// 6. 返回return Result.ok(shops);}