Question

I’m working on an application that is location specific — think of it as a store locator where store owners enter their address information and other users can only see nearby stores within a certain range. However, it’s a little different in the sense that an exact location is not required, only the city/state is required (weird, I know). I have thought about the schema for storing locations, and have decided on this one.

Locations

id                      -- int
formatted_address       -- varchar(200)
is_point_of_interest    -- bool
name                    -- varchar(100) -- NULL
street_number           -- varchar(10)  -- NULL
street                  -- varchar(40)  -- NULL
city                    -- varchar(40)
state                   -- varchar(40)
state_code              -- varchar(3)
postal_code             -- varchar(10)
country                 -- varchar(40)
country_code            -- varchar(3)
latitude                -- float(10,6)
longitude               -- float(10,6)
last_updated_at         -- timestamp

Here are some notes about the application:

• I want to keep the door open for international locations
• I plan to use a geocoding service to search for and validate the locations specified by the store owner
• I truly only need the lat/lon, but the other data is necessary for displaying store information
• The formatted_address field will contain the fully formatted address — e.g., Giants Stadium, 50 NJ-120, East Rutherford, NJ 07073, USA — to allow for easier searching of stored locations
• There will possibly be a lot of duplicate fields, because each row may have a different level of granularity — for instance, 123 Main Street, City, State 12345 is different from Main Street, City, State 12345 because one has a specified street number and the other doesn’t

I understand that the schema is not very normalized, but I also do not see the need to normalize it any more because locations are very complex, which is why I’m relying on a stable geocode service (google). Also, I plan to allow freeform text input/search, so theres no need for any dropdown lists.

Does anybody see anything wrong or have any improvements, taking into consideration what I’ve mentioned? I can see this table growing rather large.

Answer 1

I do not think so. Here is my two-minute synopsis:

This very badly normalized. At least city->country should be moved out to a different table (and normalized from there). I believe postal codes can cross city boundaries though (or I am very badly misremembering); I am not aware of such a city that crosses a state boundary.

formatted_address is an “optimization” and should likely be a computed field: that is, all the data to re-create it should exist elsewhere. (This means that it doesn’t need to worried about now.)

Happy designing.

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The simple “more-normalized” form just doing the above proposed:

LOCATIONS
location_id             -- int
is_point_of_interest    -- bool
name                    -- varchar(100) -- NULL
street_number           -- varchar(10)  -- NULL
street                  -- varchar(40)  -- NULL
city_id                 -- int
postal_code             -- varchar(10)
latitude                -- float(10,6)
longitude               -- float(10,6)
last_updated_at         -- timestamp

CITIES
city_id                 
name                    -- varchar
-- similarly, the following should be normalized to STATES and COUNTRIES
state                   -- varchar(40)
state_code              -- varchar(3)
country                 -- varchar(40)
country_code            -- varchar(3)

Of course, CITIES can be further normalized, and so could a POSTALS table: I don’t know enough about postal codes, or the application domain though. postal_code acts as part of an implicit compound-surrogate-FK so it’s not super terrible as it is there. However, moving it into a separate table could easily allow verification and integrity constraints.

Edit: Normalizing a POSTALs table would be best, as only a very samll number of postal codes are valid for a given city: I am not sure the relation between a postal code and a city, though, so I can’t recommend how to do this. Perhaps look at existing schemas used?