Can I normalize my experimental data table further?

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Question :

I am attempting to get a MySQL database to 3NF, but I’m unsure as to how to get there. I’m new to database design, so please correct me if my understanding is incorrect.

I have 6 columns: date(yyyy-mm-dd), compound_type, location, method, value, unit

The database represents values of samples taken on a particular day at a particular location. There are 21 locations that happen for every date event that samples are taken, and 10 different types of compounds that are tested at each location. There are three different methods to run on each compound. So there is a value (and associated unit column) for each method for each compound type at each location on each day.

I got a pseudo-1NF by setting up a table like so:

id(PK), date,       compound_type,  location,   method, value,  unit   
1,      2011-07-03, 1,              1,          1,      foo,    g
2,      2011-07-03, 2,              1,          1,      bar,    g
3,      2011-07-03, 1,              2,          1,      789,    g
4,      2011-07-03, 2,              2,          1,      123,    g
5,      2011-07-03, 3,              2,          1,      345,    g

And et cetera for all other compounds and locations and methods. Obviously, there are a lot of repeats of dates for every compound, location and method combination. To me, it seems fairly redundant to have that much repetition.

My question is: is it possible to further normalize this database, or is using an id(PK) column like I have above the best way to go with all of the repeating dates? Am I better off using indexes or unique keys? Would it be better to have a table for every date which breaks down into the compound/location/method categories?

I’m a newbie, so any resources you can point me to would be excellent.


Eventually, I’m going to be writing a front-end to this database for reporting and graphing, so I’m looking for a database design that will allow me to use brief SQL statements for returning data.

Answer :

Second normal form

If I understand you correctly, the combination of {date, compound_type, location, method} uniquely identifies {value, units}, and all four are needed in order to identify a unique sample ({date, location, method} isn’t enough by itself, for example).

I’m going to write this as if I hadn’t received an answer on my question about functional dependencies, since other people might be interested in an explanation of both possibilities.

If there are no partial dependencies

1) Assuming none of the non-prime attributes {value, unit} depend on part of the candidate keys {id} or {date, compound_type, location, method}, your table is in 2NF since, as Wikipedia puts it, “every non-prime attribute of the table is either dependent on the whole of a candidate key, or on another non-prime attribute.”

If there are partial dependencies

2) One or both of the non-prime attributes {value, unit} depend on only parts of the candidate key {date, compound_type, location, method}. You’ve confirmed this is the case with {compund}->{unit}, so your table is not in 2NF.

In order to fix the violation of 2NF, I would suggest moving {unit} to the compound table, which I’m guessing would end up looking something like this: {id, name, unit}. Here, the candidate keys are {id} and {name}. Since there are no composite candidate keys, the table is automatically 2NF. It’s also 3NF since there are no transitive dependencies, I.E. there’s no attribute that’s dependent on unit.

Third normal form

OK, that leaves us with the samples table looking like this: {id, date, compund_type, location, method, value}. The two candidate keys are {id} and {date, compund_type, location, method}, which leaves {value} as the single non-prime attribute. Assuming that there are no more 2NF violations (you can’t use a subset of {date, compund_type, location, method} to uniquely determine value), we can check the table for violations against 3NF.

3NF states that every non-prime attribute (attributes that don’t belong to a candidate key) must be directly dependent on every superkey. Since we only have one non-prime attribute, {value}, it’s impossible for the table to violate 3NF, since there’s no non-prime attribute for {value} to be dependent on, and no non-prime attribute that can depend on {value}.

I’m going to leave discussions about BCNF out of this for simplicity.

Surrogate key vs. natural key

As for your other questions: “is using an id(PK) column like I have above the best way to go with all of the repeating dates?”
I think so. Semantically, the surrogate key id isn’t necessary, but it does help keep things simple. I’m not sure how MySQL works underneath the hood, but in other DBMSs composite primary keys with non-integer data types can lead to unnecessary overhead for example when indexing. Another problem with composite keys is that it gets annoying to query them.

Imagine that you need to add information about which labs each sample was sent to. A sample can be sent to several labs and each lab can receive several samples, so you create a table to connect the two tables. Would you rather write this

SELECT *
FROM samples s
JOIN labs_samples ls ON 
    s.date = sl.date,
    s.compund_type = sl.compund_type,
    s.location = sl.location,
    s.method = sl.method

or this

SELECT *
FROM samples s
JOIN labs_samples ls ON s.id = ls.id

?

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