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With relations created for all entities in the data model, it is time to provide for the relationships in the data model. For each 1:1 relationship, choose one relation to be the parent and the other to be the child. To implement the relationship, create a foreign key column in the child relation that will be used to associate each tuple in the child relation with the appropriate tuple in the parent. If the minimum cardinality on both sides of the 1:1 relationship is 1, it does not matter which relation is chosen as the parent. However, if the minimum cardinality on one side is 0, then make the other relation the parent. For instance, if there were a 1:1 relationship between Room and Projector , but not all rooms had projectors, you would make the Room relation the parent, and put a foreign key column in the Projector relation. This will be more space-efficient, since you will have a foreign key field only when there is a Projector tuple to associate with a Room tuple. For 1:N relationships, the relation on the 1 side will be the parent, and the relation on the N side will be the child. All one must do is add a foreign key column to the child relation so that the many children can be related to the one parent entity. For instance, to implement the advisor/advisee relationship, simply add a foreign key column to the Student relation, name the foreign key column FacultyAdvisor , and prepare to populate the column with values of the primary key of the Faculty relation. Many-to-many relationships are more complex. To implement an N:M relationship, one must create a new table, a new relation. Such a relation is sometimes called an intersection table or a relationship relation. The intersection table includes foreign key columns for both entities in the relationship. Each tuple in the intersection table will include values of primary keys from both relations. For each association between an instance of one entity type and an instance of the other, there will be a row in the intersection table making the connection. For instance, to create the M:N relationship between the Student and Course tables, one would create the StudentCourseIntersection relation. StudentCourseIntersection would have foreign key columns for Student (perhaps called StudentSSN) and for Course (perhaps called CourseNumber). Each row in StudentCourseIntersection will record the fact that a particular student took a particular course. Any particular student may take many courses, and many students may take any particular course. The primary key of an intersection table usually is the composite of the two foreign key values. Since the foreign key values must be unique among tuples in their respective relations, the combination of the two keys must be unique among the tuples in the intersection table. This rule would only change in special circumstances. For instance, if one were to decide to record multiple attempts by a student to take a particular course, the primary key of the intersection table would have to be expanded to include another attribute that would allow one to distinguish different attempts by the same student to take the same course. Recursive relationships sound difficult to create, but they are not. Suppose some students are student advisors. The relationship is 1:N. One can create this recursive relationship by adding a column to the Student relation named StudentAdvisor . The StudentAdvisor column is essentially a foreign key column that contains values of the primary key from the same relation. Creating a 1:N recursive relationship is just like creating a standard 1:N relationship, except that the parent foreign key links to the same table that contains the child entity. A 1:1 recursive relationship is handled similarly. An M:N recursive relationship requires creating an intersection table, just as for standard M:N relationships. In this case, however, the foreign key columns will both contain primary key values from the same relation. Imagine the recursive roommates relationship. Each row in the intersection table will associate one student with a roommate, another student. NORMALIZATION Some models are better than others. In particular, poor decisions regarding entity definitions can increase data redundancy and lead to update anomalies. Update anomalies include behavior such as requiring information about a second entity (e.g., a dorm) when inserting information about a first entity (e.g., a student), or losing information about a second entity (e.g., a dorm) when an entity of a different type is deleted (e.g., the last student in the dorm). Normalization is the process of subjecting relations to tests. Passing the tests will insure that the relation will show desirable properties. The goal of normalization is to insure that each relation represents a single theme. For instance, a relation should have information about students, and a relation should have information about dorms, but a relation that has information about both students and dorms will lead to trouble.
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