11.1 GEO数据结构的基本用法

11.2 导入店铺数据到GEO

Key Value Score
shop:geo:美食 海底捞 40691512240174598
吉野家 40691519846517915
shop:geo:KTV KTV 01 40691165486458787
KTV 02 40691514154651657 
@Test
public void loadShopData(){
    //1. 查询所有店铺信息
    List<Shop> shopList = shopService.list();
    //2. 按照typeId，将店铺进行分组
    Map<Long, List<Shop>> map = shopList.stream().collect(Collectors.groupingBy(Shop::getTypeId));
    //3. 逐个写入Redis
    for (Map.Entry<Long, List<Shop>> entry : map.entrySet()) {
        //3.1 获取类型id
        Long typeId = entry.getKey();
        //3.2 获取同类型店铺的集合
        List<Shop> shops = entry.getValue();
        String key = SHOP_GEO_KEY + typeId;
        for (Shop shop : shops) {
            //3.3 写入redis GEOADD key 经度 纬度 member
            stringRedisTemplate.opsForGeo().add(key,new Point(shop.getX(),shop.getY()),shop.getId().toString());
        }
    }
}

是上面的代码不够优雅，是一条一条写入的，效率较低，那我们现在来改进一下，这样只需要写入等同于type_id数量的次数

@Test
public void loadShopData() {
    List<Shop> shopList = shopService.list();
    Map<Long, List<Shop>> map = shopList.stream().collect(Collectors.groupingBy(Shop::getTypeId));
    for (Map.Entry<Long, List<Shop>> entry : map.entrySet()) {
        Long typeId = entry.getKey();
        List<Shop> shops = entry.getValue();
        String key = SHOP_GEO_KEY + typeId;
        List<RedisGeoCommands.GeoLocation<String>> locations = new ArrayList<>(shops.size());
        for (Shop shop : shops) {
            //将当前type的商铺都添加到locations集合中
            locations.add(new RedisGeoCommands.GeoLocation<>(shop.getId().toString(), new Point(shop.getX(), shop.getY())));
        }
        //批量写入
        stringRedisTemplate.opsForGeo().add(key, locations);
    }
}

• 代码编写完毕，我们启动测试方法，然后去Redis图形化界面中查看是否有对应的数据

11.3 实现附近商户功能

<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-data-redis</artifactId>
    <exclusions>
        <exclusion>
            <artifactId>spring-data-redis</artifactId>
            <groupId>org.springframework.data</groupId>
        </exclusion>
        <exclusion>
            <artifactId>lettuce-core</artifactId>
            <groupId>io.lettuce</groupId>
        </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>6.1.6.RELEASE</version>
</dependency>

看样子是ShopController中的方法，那我们现在来修改其代码，除了typeId，分页码，我们还需要其坐标

@GetMapping("/of/type")
public Result queryShopByType(
        @RequestParam("typeId") Integer typeId,
        @RequestParam(value = "current", defaultValue = "1") Integer current,
        @RequestParam(value = "x", required = false) Double x,
        @RequestParam(value = "y", required = false) Double y
) {
   return shopService.queryShopByType(typeId,current,x,y);
}

具体业务逻辑依旧是写在ShopServiceImpl中

@Override
public Result queryShopByType(Integer typeId, Integer current, Double x, Double y) {
    //1. 判断是否需要根据距离查询
    if (x == null || y == null) {
        // 根据类型分页查询
        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. 计算分页查询参数
    int from = (current - 1) * SystemConstants.MAX_PAGE_SIZE;
    int end = current * SystemConstants.MAX_PAGE_SIZE;
    String key = SHOP_GEO_KEY + typeId;
    //3. 查询redis、按照距离排序、分页; 结果：shopId、distance
    //GEOSEARCH key FROMLONLAT x y BYRADIUS 5000 m WITHDIST
    GeoResults<RedisGeoCommands.GeoLocation<String>> results = stringRedisTemplate.opsForGeo().search(key,
            GeoReference.fromCoordinate(x, y),
            new Distance(5000),
            RedisGeoCommands.GeoSearchCommandArgs.newGeoSearchArgs().includeDistance().limit(end));
    if (results == null) {
        return Result.ok(Collections.emptyList());
    }
    //4. 解析出id
    List<GeoResult<RedisGeoCommands.GeoLocation<String>>> list = results.getContent();
    if (list.size() < from) {
        //起始查询位置大于数据总量，则说明没数据了，返回空集合
        return Result.ok(Collections.emptyList());
    }
    ArrayList<Long> ids = new ArrayList<>(list.size());
    HashMap<String, Distance> distanceMap = new HashMap<>(list.size());
    list.stream().skip(from).forEach(result -> {
        String shopIdStr = result.getContent().getName();
        ids.add(Long.valueOf(shopIdStr));
        Distance distance = result.getDistance();
        distanceMap.put(shopIdStr, distance);
    });
    //5. 根据id查询shop
    String idsStr = StrUtil.join(",", ids);
    List<Shop> shops = query().in("id", ids).last("ORDER BY FIELD( id," + idsStr + ")").list();
    for (Shop shop : shops) {
        //设置shop的举例属性，从distanceMap中根据shopId查询
        shop.setDistance(distanceMap.get(shop.getId().toString()).getValue());
    }
    //6. 返回
    return Result.ok(shops);
}