1 / 6

Functional Dependencies

Functional Dependencies. Alternative Data Modeling Approach Based on Formal Logic ER Diagrams can be mapped into FDs (sans some cardinality information) Algorithms to automatically generate 3 rd Normal form.

colby
Download Presentation

Functional Dependencies

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Functional Dependencies • Alternative Data Modeling Approach • Based on Formal Logic • ER Diagrams can be mapped into FDs • (sans some cardinality information) • Algorithms to automatically generate 3rd Normal form. • FDs (alone with MVDs and JDs) are used to formally define the various relational normal forms (e.g., 3rd normal form).

  2. Functional Dependencies Attribute(s) B are said to be functionally dependent on attribute(s) A iff (if and only if) for all valid instance(s) of A, those values of A uniquely determine the value(s) for B. P#  Color P#,S#  Qty P# > PN

  3. Employee(EmpID,Name,Dept,Salary,Course,Date Completed) • FDs: • EMPID  Name,Dept,Salary • Course  date completed • Note: A key is a set of non-redundant attributes that functionally determines all the attributes in the relation schema. • empid,course  name,dept,salary,date completed

  4. Functional Dependency Rules • Augmentation: if x Y, then ZX Y • Student#  StudentName thenStudent # course #  student name • Transitivity:if X  Y & Y  Z then X Z • Student #  major and major  advisor then student#  advisor • Pseudo Transitivity: if X Y & YZ  W then XZ  W Thus if student #  major and major, class  advisor then student #,Class  advisor

  5. If X,Y,Z, and W are attributes: • X  X (reflexive) • If X  y then XZ  Y (augmentation) • If X  Y & X  Z then X  YZ (union) • If X  Y then X  Z where Z subset of Y (Decomposition) • IF X  Y & Y  Z then X  Z (transitivity) • IF X  Y & YZ  W, then XZ  W (pseudotransitivity)

  6. Suppose relation (A B C D) with A  BC, B  D, and DB  A • Are These Valid Derivations? • A  B A  D A  BD • A  A A  C B  A • Is this a “Minimal” equivalent Set? • B  A • A  CD

More Related