1. Kingdom of Saudi Arabia Ministry of Higher Education Al-Imam Muhammad Ibn Saud Islamic University College of Computer and Information Sciences Normalization IS 320: Introduction to Database Hatoon AlSagri Introduction to Databases

2. Informal Design Guidelines for Relational Databases Relational database design: The grouping of attributes to form "good" relation schemas Two levels of relation schemas: The logical "user view" level The storage "base relation" level Design is concerned mainly with base relations Introduction to Databases2

3. Informal Design Guidelines for Relational Databases Four informal measures of quality for relation schema design: 1. Semantics of the Relation Attributes 2. Reducing the redundant information in tuples 3. Reducing Null values in tuples 4. Disallowing the possibility of one generating spurious tuples. Introduction to Databases3

4. 1- Semantics of the Relation Attributes Each tuple in a relation should represent one entity or relationship instance Guideline #1: Design a schema that can be explained easily relation by relation. The semantics of attributes should be easy to interpret. Introduction to Databases4

5. 2- Redundant Information in Tuples and Update Anomalies Mixing attributes of multiple entities may cause problems: Information is stored redundantly wasting storage Problems with update anomalies: Insertion anomalies Deletion anomalies Modification anomalies Guideline #2: Design a schema that does not suffer from the insertion, deletion and update anomalies. If there are any present, then note them so that applications can be made to take them into account Introduction to Databases5

6. Base Relations EMP_PROJ with redundant information Introduction to Databases6

7. 3- Null Values in Tuples Reasons for nulls: a. attribute not applicable or invalid b. attribute value unknown (may exist) c. value known to exist, but unavailable Guideline #3: Relations should be designed such that their tuples will have as few NULL values as possible Attributes that are NULL frequently could be placed in separate relations (with the primary key) Introduction to Databases7

8. 4- Spurious Tuples Bad designs for a relational database may result in erroneous results for certain JOIN operations Guideline #4: The relations should be designed to satisfy the lossless join condition. No spurious tuples should be generated by doing join of any relations. Introduction to Databases8

9. Functional Dependencies Functional dependencies (FDs) are used to specify formal measures of the "goodness" of relational designs FDs and keys are used to define normal forms for relations FDs are constraints that are derived from the meaning and interrelationships of the data attributes Introduction to Databases9

10. Examples of FD constraints Social security number determines employee name SSN -> ENAME Project number determines project name and location PNUMBER -> {PNAME, PLOCATION} Employee ssn and project number determines the hours per week that the employee works on the project {SSN, PNUMBER} -> HOURS Introduction to Databases10

11. Functional Dependencies Introduction to Databases11 Describes the relationship between attributes in a relation. If A and B are attributes of relation R, B is functionally dependent on A, denoted by A B, if each value of A is associated with exactly one value of B. B may have several values of A. Determinant Dependent AB B is functionally dependent on A

12. Functional Dependencies Introduction to Databases12 Example StaffNoposition Position is functionally dependent on Staffno positionStaffNo StaffNo is NOT functionally dependent on position SL21 Manager Manager SL21 SG5 1:1 or M:1 relationship between attributes in a relation 1:M relationship between attributes in a relation

13. Trivial Functional Dependencies Introduction to Databases13 A B is trivial if B  A StaffNo, Sname SName StaffNo, SName StaffNo We are not interested in trivial functional dependencies as it provides no genuine integrity constraints on the value held by these attributes.

14. Question Find FDs of the relation shown below that lists dentist/patient appointment data; known that: A patient is given an appointment at a specific time and date with a dentist located at a particular surgery. On each day of patient appointments, a dentist is allocated to a specific surgery for that day. Dentist-patient (staffNo, aDate, aTime, dentistName, patNo, patName, surgeryNo) Introduction to Databases14

15. Question Dentist-patient (staffNo, aDate, aTime, dentistName, patNo, patName, surgeryNo) FDs list FD1: staffNo, aDate, aTime  patNo, patName FD2: staffNo  dentistName FD3: patNo  patName, surgeryNo FD4: staffNo, aDate  surgeryNo FD5: aDate, aTime, patNo  dentistName, staffNo Introduction to Databases15

16. Introduction to Normalization Normalization: Process of decomposing unsatisfactory "bad" relations by breaking up their attributes into smaller relations Normal form: Condition using keys and FDs of a relation to certify whether a relation schema is in a particular normal form Introduction to Databases16

17. Normalization into 1NF Introduction to Databases17

18. Examples First Normal Form EMP_PROJ (Ssn, Ename, {Phone#}) { } Mulitvalue attribute EMP_PROJ1 (Ssn, Ename) EMP_PROJ2 (Ssn, Phone#) EMP_PROJ (Ssn, Ename (Fname, Lname)) ( ) composite attribute EMP_PROJ (Ssn, Fname,Lname) EMP_PROJ (Ssn, Ename, {PROJS (Pnamber, Hours)}) EMP_PROJ1 (Ssn, Ename) EMP_PROJ2 (Ssn, Pnamber, Hours) Introduction to Databases18

19. Second Normal Form Uses the concepts of FDs, primary key Definitions: Prime attribute - attribute that is member of the primary key K Full functional dependency - a FD Y  Z where removal of any attribute from Y means the FD does not hold any more Introduction to Databases19

20. Full Functional Dependency Introduction to Databases20 If A and B are attributes of a relation. B is fully functionally dependent on A if B is functionally dependent on A, but not on any proper subset of A. B is partial functional dependent on A if some attributes can be removed from A & the dependency still holds. StaffNo, Sname BranchNo Partial dependency ClientNo, PropertyNo RentDate Full dependency

21. 1NF 2NF Introduction to Databases21 1. Start with 1NF relation. 2. Find the FDs of a relation. 3. Test the FDs whose determinant attribute is part of the PK.

22. Examples Second Normal Form {SSN, PNUMBER}  HOURS is a full FD since neither SSN  HOURS nor PNUMBER  HOURS hold {SSN, PNUMBER}  ENAME is not a full FD (it is called a partial dependency ) since SSN  ENAME also holds A relation schema R is in second normal form (2NF) if every non- prime attribute A in R is fully functionally dependent on the primary key R can be decomposed into 2NF relations via the process of 2NF normalization Introduction to Databases22

23. Examples Second Normal Form Introduction to Databases 23

24. Second Normal Form Note: The test for 2NF involves testing for functional dependencies whose left-hand side attributes are part of the primary key. If the primary key contains a single attribute, the test need not be applied at all. Introduction to Databases24

25. Third Normal Form Definition Transitive functional dependency – a FD X  Y in R is a transitive dependency if there is a set of attributes Z that are neither a primary or candidate key and both X  Z and Z  Y holds. Examples: SSN  DMGRSSN is a transitive FD since SSN  DNUMBER and DNUMBER  DMGRSSN hold SSN  ENAME is non-transitive since there is no set of attributes X where SSN  X and X  ENAME Introduction to Databases25

26. 3 rd Normal Form A relation schema R is in third normal form (3NF) if it is in 2NF and no non-prime attribute A in R is transitively dependent on the primary key Introduction to Databases26

27. Examples Third Normal Form Introduction to Databases 27

28. SUMMARY OF NORMAL FORMS based on Primary Keys Introduction to Databases28

29. BCNF (Boyce-Codd Normal Form) A relation schema R is in Boyce-Codd Normal Form (BCNF) if whenever an FD X  A holds in R, then X is a superkey of R Each normal form is strictly stronger than the previous one: Every 2NF relation is in 1NF Every 3NF relation is in 2NF Every BCNF relation is in 3NF There exist relations that are in 3NF but not in BCNF The goal is to have each relation in BCNF (or 3NF) Introduction to Databases29

30. BCNF R1(A,C) R2(C,B) Introduction to Databases 30

31. Introduction to Databases 31

32. BCNF FDs: {Student,course}  Instructor Instructor  Course It is in 3NF not in BCNF Decomposing into 2 schemas {Student, Instructor} {Instructor, Course} Introduction to Databases32

33. Examples BCNF R ( Client#, Problem, Consultant _name) R1 (Client#, Consultant _name) R2 (Consultant _name, Problem) ■R (Stud#, Class#, Instructor, Grade) R1 (Stud#, Instructor, Grade) R2 (Instructor, Class#) Introduction to Databases 33

34. Example Consider the following relation for published books: BOOK (Book_title, Author_name, Book_type, Listprice, Author_affil, Publisher) - Author_affil referes to the affiliation of the author. Suppose thefollowing dependencies exist: Book_title -> Publisher, Book_type Book_type -> Listprice Author_name -> Author-affil (a) What normal form is the relation in? Explain your answer. (b) Apply normalization until you cannot decompose the relations further. State the reasons behind each decomposition. Introduction to Databases34

35. Answer BOOK (Book_title, Authorname, Book_type, Listprice, Author_affil, Publisher) (a) The key for this relation is (Book_title, Authorname). This relation is in 1NF and not in 2NF as no attributes are Full FD on the key. It is also not in 3NF. (b) 2NF decomposition: Book0(Book_title, Authorname) Book1(Book_title, Publisher, Book_type, Listprice) Book2(Authorname, Author_affil) This decomposition eliminates the partial dependencies. 3NF decomposition: Book0(Book_title, Authorname) Book1-1(Book_title, Publisher, Book_type) Book1-2(Book_type, Listprice) Book2(Authorname, Author_affil) This decomposition eliminates the transitive dependency of Listprice Introduction to Databases35

36. Example Given the relation schema Car_Sale (Car#, Salesman#, Date_sold, Commission%, Discount_amt) with the functional dependencies Date_sold -> Discount_amt Salesman# -> Commission% Car# -> Date_sold This relation satisfies 1NF but not 2NF (Car# -> Date_sold and Salesman# -> Commission%) so these two attributes are not Full FD on the primary key and not 3NF Introduction to Databases36

37. To normalize, 2NF: Car_Sale1 (Car#, Salesman#) Car_Sale2 (Car#, Date_sold, Discount_amt) Car_Sale3 (Salesman#,Commission%) 3NF: Car_Sale1(Car#, Salesman#) Car_Sale2-1(Car#, Date_sold) Car_Sale2-2(Date_sold, Discount_amt) Car_Sale3(Salesman#,Commission%) Introduction to Databases37 Answer

38. Question Given the following Dentist-patient database schema: Dentist-patient (staffNo, aDate, aTime, dentistName, patNo, patName, surgeryNo) Normalize the above relation, showing appropriate dependency diagrams to justify decomposition. Introduction to Databases38 FDs List: FD1: staffNo, aDate, aTime  patNo, patName FD2: staffNo  dentistName FD3: patNo  patName, surgeryNo FD4: staffNo, aDate  surgeryNo FD5: aDate, aTime, patNo  dentistName, staffNo

39. Answer 1NF Dentist-patient (staffNo, aDate, aTime, dentistName, patNo, patName, surgeryNo) 2NF (fd2 and fd4 violates 2NF) Dentist-patient (staffNo, aDate, aTime, patNo, patName) Surgery (staffNo, aDate, surgeryNo) Dentist (staffNo, dentistName) 3NF (Fd3’ violates 3NF) Dentist-patient (staffNo, aDate, aTime, patNo) Surgery (staffNo, aDate, surgeryNo) Dentist (staffNo, dentistName) Patient (patNo, patName) Introduction to Databases39

40. Answer BCNF (No violation) Dentist-patient (staffNo, aDate, aTime, patNo) Surgery (staffNo, aDate, surgeryNo) Dentist (staffNo, dentistName) Patient (patNo, patName) Introduction to Databases40