Beginning SQL

surprisingly, the MemberDetails table holds member details, the second results set. Now it’s necessary to
combine the two sets to get the result you want: a list of all members whose city is not listed in the
Location table. More than one city may have the same name, so assume that such cities in the same state
are the same. Therefore, you joined the MemberDetails table to the Location table using an INNER JOIN
based on the City and State columns:
FROM MemberDetails INNER JOIN Location
ON (MemberDetails.City Location.City AND MemberDetails.State = Location.State)
OR (MemberDetails.City = Location.City AND MemberDetails.State Location.State)
ORDER BY MemberDetails.LastName;
The ON clause is the key to this query, so you need results where the cities don’t match but the states do
(same state but different city name). You also want to include records where the city name is the same
but the state name is different (same city name but in a different state). It seems obvious when written
down, but oftentimes looking at the two results sets and making the comparison in your mind first is
helpful. The key fields in both tables are City and State, so you need to make your comparison with
those fields. Figure 3-5 shows the set diagram.
Figure 3-5
SELECT City, State FROM Location
City
Big Apple City
Windy Village
Big City
State
New State
Golden State
Mega State
SELECT City, State FROM MemberDetails
City
Townsville
Townsville
Windy Village
New Town
Orange Town
Orange Town
Big City
Big City
Windy Village
Big Apple City
Windy Village
Big City
Dover
Extracting Information
State
Mega State
Mega State
Golden State
New State
New State
New State
Mega State
Mega State
Golden State
New State
Golden State
Mega State
Golden State
Check if the Townsville record at the top of the MemberDetails table appears in the City field in any of
the records in the Location set. Townsville doesn’t appear, so you know that Townsville is not a valid
meeting location, and therefore it should form part of the results. You also need to take into account data
that isn’t there but should be. For example, say that a city called Big City in Sunny State appears in the
Location table. In this case, simply comparing the City columns in each table means that Big City, Sunny
State, would not be included in the results even though clearly Big City, Mega State, and Big City, Sunny
State, are totally different cities.
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