在我的Rails应用程序中，我具有允许查找与当前登录用户最接近的用户的功能。我为此使用了Geocoder gem。在用户模型中，我具有如下范围：

   scope :close_to, -> (user:, distance:) {
    where.not(id: user.id)
    .near([user.latitude, user.longitude], distance)
  }

这非常有效，但是对于大量用户而言却很慢。当我调用此作用域时，它将生成以下sql查询：

SELECT users.*, 6371.0 * 2 * ASIN(SQRT(POWER(SIN((48.471645 - users.latitude) * PI() / 180 / 2), 2) + COS(48.471645 * PI() / 180) * COS(users.latitude * PI() / 180) * POWER(SIN((-83.102801 - users.longitude) * PI() / 180 / 2), 2))) AS distance, MOD(CAST((ATAN2( ((users.longitude - -83.102801) / 57.2957795), ((users.latitude - 48.471645) / 57.2957795)) * 57.2957795) + 360 AS decimal), 360) AS bearing FROM "users" WHERE ("users"."id" != 43362) AND (users.latitude BETWEEN 39.4784289408127 AND 57.46486105918731 AND users.longitude BETWEEN -96.6674214298497 AND -69.5381805701503 AND (6371.0 * 2 * ASIN(SQRT(POWER(SIN((48.471645 - users.latitude) * PI() / 180 / 2), 2) + COS(48.471645 * PI() / 180) * COS(users.latitude * PI() / 180) * POWER(SIN((-83.102801 - users.longitude) * PI() / 180 / 2), 2)))) BETWEEN 0.0 AND 1000) ORDER BY distance ASC;

我正在尝试为此创建索引，但它们不起作用。我正在尝试以下组合：

1.
    add_index :users, [:id, :latitude]
    add_index :users, [:id, :longitude]

2.  add_index :users, [:id, :latitude, :longitude]

3.  add_index :users, [:latitude]
    add_index :users, [:longitude]

4. add_index :users, [:id, :latitude]

我应该如何添加索引以加快此查询的速度？

编辑：我忘记添加我的纬度和经度列是小数。

此查询的ANALYZE返回类似以下内容：

 Sort  (cost=7141.66..7142.14 rows=191 width=327) (actual time=575.995..585.543 rows=36598 loops=1)
   Sort Key: ((12742::double precision * asin(sqrt((power(sin((((((48.471645 - latitude))::double precision * 3.14159265358979::double precision) / 180::double precision) / 2::double precision)), 2::double precision) + ((0.662990616338754::double precision * cos((((latitude)::double precision * 3.14159265358979::double precision) / 180::double precision))) * power(sin(((((((-83.102801) - longitude))::double precision * 3.14159265358979::double precision) / 180::double precision) / 2::double precision)), 2::double precision)))))))
   Sort Method: external merge  Disk: 4672kB
   ->  Seq Scan on users  (cost=0.00..7134.43 rows=191 width=327) (actual time=0.381..517.615 rows=36598 loops=1)
         Filter: ((id <> 43362) AND (latitude >= 39.4784289408127) AND (latitude <= 57.46486105918731) AND (longitude >= (-96.6674214298497)) AND (longitude <= (-69.5381805701503)) AND ((12742::double precision * asin(sqrt((power(sin((((((48.471645 - latitude))::double precision * 3.14159265358979::double precision) / 180::double precision) / 2::double precision)), 2::double precision) + ((0.662990616338754::double precision * cos((((latitude)::double precision * 3.14159265358979::double precision) / 180::double precision))) * power(sin(((((((-83.102801) - longitude))::double precision * 3.14159265358979::double precision) / 180::double precision) / 2::double precision)), 2::double precision)))))) >= 0::double precision) AND ((12742::double precision * asin(sqrt((power(sin((((((48.471645 - latitude))::double precision * 3.14159265358979::double precision) / 180::double precision) / 2::double precision)), 2::double precision) + ((0.662990616338754::double precision * cos((((latitude)::double precision * 3.14159265358979::double precision) / 180::double precision))) * power(sin(((((((-83.102801) - longitude))::double precision * 3.14159265358979::double precision) / 180::double precision) / 2::double precision)), 2::double precision)))))) <= 1000::double precision))
         Rows Removed by Filter: 6756
 Planning time: 1.041 ms
 Execution time: 587.695 ms
(8 rows)

编辑2：

我注意到postgresql使用了我的

add_index :users, [:latitude, :longitude]

仅当我键入小距离ex时。用户在10公里左右。