Functional dependency is a relationship that exists when one attribute uniquely determines another attribute.
If R is a relation with attributes X and Y, a functional dependency between the attributes is represented as X → Y, which specifies Y is functionally dependent on X. Hear X is a determinant set and Y is dependent attribute. Each value of X is associated precisely with one Y value.
There are two type of functional dependencies :
Partial Dependency - A partial dependency exists when there is a functional dependency in which the determinant is only part of the primary key (remember we are assuming there is only one candidate key).
For example - if (A,B) → (C,D), B → C, and (A,B) is the primary key, then the functional dependency B → C is a partial dependency because only part of the primary key (B) is needed to determine the value of C. Partial dependencies tend to be rather straight forward and easy to identify.
Student_Project(Student_id,Project_id, Project_name, Student_name)
(Student_id, Project_id) → (Project_Name, Student_name)
Project_id → Project_name
Student_id → Student_name
After Normalization the Student_Project table is divided into the following two tables :
Student(Student_id, Student_name, Project_id)
Transitive Dependency - A transitive dependency exists when there are functional dependencies such that X → Y, Y → Z and X is the primary key, in that case, the dependency X → Z is a transitive dependency because X determines the value of Z via Y. Unlike partial dependencies, transitive dependencies are more difficult to identify among a set of data. Fortunately, there is an easier way to identify transitive dependencies - A transitive dependency will occure only when a functional dependence exists among non-primary key attributes.
Book_Details(Book_name, Author_name, Author_address)
Book_name → (Author_name, Author_address)
Author → Author_address
After Normalization the Book_Details table is divided into the following two tables :
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