This question requires some hypothetical background. Let’s consider an employee table that has columns name, date_of_birth, title, salary, using MySQL as the RDBMS. Since if any given person has the same name and birth date as another person, they are, by definition, the same person (barring amazing coincidences where we have two people named Abraham Lincoln born on February 12, 1809), we’ll put a unique key on name and date_of_birth that means “don’t store the same person twice.” Now consider this data:
id name date_of_birth title salary
1 John Smith 1960-10-02 President 500,000
2 Jane Doe 1982-05-05 Accountant 80,000
3 Jim Johnson NULL Office Manager 40,000
4 Tim Smith 1899-04-11 Janitor 95,000
If I now try to run the following statement, it should and will fail:
INSERT INTO employee (name, date_of_birth, title, salary)
VALUES ('Tim Smith', '1899-04-11', 'Janitor', '95,000')
If I try this one, it will succeed:
INSERT INTO employee (name, title, salary)
VALUES ('Jim Johnson', 'Office Manager', '40,000')
And now my data will look like this:
id name date_of_birth title salary
1 John Smith 1960-10-02 President 500,000
2 Jane Doe 1982-05-05 Accountant 80,000
3 Jim Johnson NULL Office Manager 40,000
4 Tim Smith 1899-04-11 Janitor 95,000
5 Jim Johnson NULL Office Manager 40,000
This is not what I want but I can’t say I entirely disagree with what happened. If we talk in terms of mathematical sets,
{'Tim Smith', '1899-04-11'} = {'Tim Smith', '1899-04-11'} <-- TRUE
{'Tim Smith', '1899-04-11'} = {'Jane Doe', '1982-05-05'} <-- FALSE
{'Tim Smith', '1899-04-11'} = {'Jim Johnson', NULL} <-- UNKNOWN
{'Jim Johnson', NULL} = {'Jim Johnson', NULL} <-- UNKNOWN
My guess is that MySQL says, “Since I don’t know that Jim Johnson with a NULL birth date isn’t already in this table, I’ll add him.”
My question is: How can I prevent duplicates even though date_of_birth is not always known? The best I’ve come up with so far is to move date_of_birth to a different table. The problem with that, however, is that I might end up with, say, two cashiers with the same name, title and salary, different birth dates and no way to store them both without having duplicates.
A fundamental property of a unique key is that
it must be unique. Making part of that key Nullable destroys this property.
There are two possible solutions to your problem:
One way, the wrong way, would be to use some magic date to represent unknown. This just gets you past
the DBMS “problem” but does not solve the problem in a logical sense.
Expect problems with two “John Smith” entries having unknown dates
of birth. Are these guys one and the same or are they unique individuals?
If you know they are different then you are back to the same old problem –
your Unique Key just isn’t unique. Don’t even think about assigning a whole range of magic dates
to represent “unknown” – this is truly the road to hell.
A better way is to create an EmployeeId attribute as a surrogate key. This is just an
arbitrary identifier that you assign to individuals that you know are unique. This
identifier is often just an integer value.
Then create an Employee table to relate the EmployeeId (unique, non-nullable
key) to what you believe are the dependant attributers, in this case
Name and Date of Birth (any of which may be nullable). Use the EmployeeId surrogate key everywhere that you
previously used the Name/Date-of-Birth. This adds a new table to your system but
solves the problem of unknown values in a robust manner.