Question

I’m using following sql code to find out ‘ALL’ poi closest to the set coordinates, but I would want to find out specific poi instead of all of them. When I try to use the where clause I get an error and it doesn’t work and this is where I’m currently stuck, since I only use one table for all the coordinates off all poi’s.

SET @orig_lat=55.4058;  
SET @orig_lon=13.7907; 
SET @dist=10;
SELECT 
    *, 
    3956 * 2 * ASIN(SQRT(POWER(SIN((@orig_lat -abs(latitude)) * pi()/180 / 2), 2) 
    + COS(@orig_lat * pi()/180 ) * COS(abs(latitude) * pi()/180) 
    * POWER(SIN((@orig_lon - longitude) * pi()/180 / 2), 2) )) as distance 
FROM geo_kulplex.sweden_bobo
HAVING distance < @dist 
ORDER BY distance limit 10;

Answer 1

The problem is that you can not reference an aliased column (distancein this case) in a select or where clause. For example, you can’t do this:

select a, b, a + b as NewCol, NewCol + 1 as AnotherCol from table
where NewCol = 2

This will fail in both: the select statement when trying to process NewCol + 1 and also in the where statement when trying to process NewCol = 2.

There are two ways to solve this:

1) Replace the reference by the calculated value itself. Example:

select a, b, a + b as NewCol, a + b + 1 as AnotherCol from table
where  a + b = 2

2) Use an outer select statement:

select a, b, NewCol, NewCol + 1 as AnotherCol from (
    select a, b, a + b as NewCol from table
) as S
where NewCol = 2

Now, given your HUGE and not very human-friendly calculated column 🙂 I think you should go for the last option to improve readibility:

SET @orig_lat=55.4058;  
SET @orig_lon=13.7907; 
SET @dist=10;

SELECT * FROM (
  SELECT 
    *, 
    3956 * 2 * ASIN(SQRT(POWER(SIN((@orig_lat -abs(latitude)) * pi()/180 / 2), 2) 
    + COS(@orig_lat * pi()/180 ) * COS(abs(latitude) * pi()/180) 
    * POWER(SIN((@orig_lon - longitude) * pi()/180 / 2), 2) )) as distance 
  FROM geo_kulplex.sweden_bobo
) AS S
WHERE distance < @dist
ORDER BY distance limit 10;

Edit: As @Kaii mentioned below this will result in a full table scan. Depending on the amount of data you will be processing you might want to avoid that and go for the first option, which should perform faster.