Indexing a mysql table for geo lookup using latitude/longitude

I have a legacy innodb table Listing containing a business with latitude/longitude. Given an input latitude/longitude (below 51.2167/4.41667), the query is to return the first active, enabled, not-deleted 30 businesses in order of proximity (kilometers). A join with the accounts table is made to check the validity of the listing.

select 
    listing.*
from
    listing listing ,
    account account 
where
    listing.account_id = account.id 
    and listing.active = 1 
    and listing.approved = 1 
    and listing.deleted = 0 
    and listing.enabled = 1 
    and account.enabled = 1 
    and account.activated_by_user = 1 
group by
    listing.id
having
     111.222569*degrees(acos(sin(radians(listing.latitude))*sin(radians( 51.2167)) +cos(radians(listing.latitude))*cos(radians( 51.2167))*cos(radians(listing.longitude - 4.41667)))) < 250
order by
     111.222569*degrees(acos(sin(radians(listing.latitude))*sin(radians( 51.2167)) +cos(radians(listing.latitude))*cos(radians( 51.2167))*cos(radians(listing.longitude - 4.41667))))
limit 30;

The table Listing and Account each contain over 50,000 rows, but the query still takes on average 24sec to run. Without the order by, it takes 17sec.

I've already tried setting some indexes on active, approved, deleted, enabled. Can I rewrite the query or add certain indexes to efficiently perform this query - without changing the table structure?

+----+-------------+---------+-------------+-------------------------------------------------------------------------------------------------+-----------------------------------------------------------------+---------+------------------------+------+-----开发者_JAVA百科---------------------------------------------------------------------------------------------------------------------------+
| id | select_type | table   | type        | possible_keys                                                                                   | key                                                             | key_len | ref                    | rows | Extra                                                                                                                          |
+----+-------------+---------+-------------+-------------------------------------------------------------------------------------------------+-----------------------------------------------------------------+---------+------------------------+------+--------------------------------------------------------------------------------------------------------------------------------+
|  1 | SIMPLE      | listing | index_merge | FKB4DC521D9306A80C,listing_active,listing_approved,listing_enabled,listing_deleted,index_test_1 | listing_active,listing_approved,listing_enabled,listing_deleted | 1,1,1,1 | NULL                   | 3392 | Using intersect(listing_active,listing_approved,listing_enabled,listing_deleted); Using where; Using temporary; Using filesort |
|  1 | SIMPLE      | account | eq_ref      | PRIMARY,account_enabled,account_activated_by_user,index_test_2                                  | PRIMARY                                                         | 8       | ctm.listing.account_id |    1 | Using where                                                                                                                    |
+----+-------------+---------+-------------+-------------------------------------------------------------------------------------------------+-----------------------------------------------------------------+---------+------------------------+------+--------------------------------------------------------------------------------------------------------------------------------+

Any help is greatly appreciated.

This is taking a long time because your query is computing that great-circle-distance formula with all the transcendental functions once for each row in your 50k row table (twice when you include the sort).

Can you limit the distance range of your search? You've probably noticed that most store-finder web apps have a pulldown menu item giving a choice "within 5 miles," "within 10 miles," and so forth.

If you CAN do this, you should add a WHERE clause to your search, and optimize it by putting an index on your LATITUDE column. Let's say you use the value RANGELIMIT for your search range limit, in miles.

Try this clause

WHERE LISTING.LATITUDE BETWEEN LOCATION.LATITUDE - (RANGELIMIT * 1.1508/60) 
                           AND LOCATION.LATITUDE + (RANGELIMIT * 1.1508/60)

This works because a nautical mile is almost exactly equal to one minute (1/60th) of a degree of latitude. The 1.1508 factor converts nautical miles into statute miles.

The clause I suggested will use a latitude index to narrow down the search, and you'll compute the great circle distance a whole lot less frequently.

You could also include a BETWEEN clause on longitude. But in my experience just doing the latitude BETWEEN search gets you excellent results.

You might want to have a look at this question. Unfortunately you cannot create a SPATIAL index on any columns which are not a GEOMETRY type, so at the very least you will need to add one column to the table.