1. Lecture4: Informal guidelines for good relational design Mapping ERD to Relation Prepared by L. Nouf Almujally Ref. Chapter3 Lecture4 1

2. Outlines Guideline 1: Semantics of the Relation Attributes Guideline 2: insertion, deletion and update anomalies Guideline 3: Null Values in Tuples Guideline 4: primary key Guideline 5: Avoid Data redundancy Mapping ERD to Relations

3. The Process of Database Design Lecture4 Real World Domain Conceptual model (ERD) Relational Data Model Create schema (DDL) Load Data (DML) 3

4. Relational Model Terminology A relation is a table with columns and rows. Attribute is a named column of a relation. Tuple is a row of a relation. Alternative Terminology for Relational Model: 4

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6. GUIDELINE 1: Semantics of the Relation Attributes and tuples Design a schema that can be explained easily relation by relation. Each cell of the relation should contains exactly single value Each Attribute has a distinct name Only foreign keys should be used to refer to other entities Each tuple is distinct. There are no duplicate tuples The order of attributes and tuples have no significance. Lecture4 6

7. GUIDELINE 2: insertion, deletion and update anomalies Design a schema that does not suffer from the insertion, deletion and update anomalies. Attributes of different entities (EMPLOYEEs, DEPARTMENTs, PROJECTs) should not be mixed in the same relation Example Consider the relation: EMP_PROJ ( Emp#, Proj#, Ename, Pname, No_hours) 1.Update Anomaly: Changing the name of project number P1 from “Billing” to “Customer-Accounting” may cause this update to be made for all 100 employees working on project P1. Lecture4 7

8. 2. Insert Anomaly: Cannot insert a project unless an employee is assigned to. Inversely - Cannot insert an employee unless an he/she is assigned to a project. 3. Delete Anomaly: When a project is deleted, it will result in deleting all the employees who work on that project. Alternately, if an employee is the sole employee on a project, deleting that employee would result in deleting the corresponding project. Example of an anomaly Lecture4 8

9. EXAMPLE OF AN UPDATE ANOMALY Tbl_Staff_Branch Tbl_StaffTbl_Branch

10. 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) NULL values: Unknown value: a particular person has a date of birth but it is unknown, so it is represented by NULL in the database. Unavailable value: a person has a home phone but does not want it to be listed, so it is represented as NULL in the database. Not applicable attribute: an attribute College Degree would be NULL for a person who has no college degrees. GUIDELINE 3: Null Values in Tuples Lecture4 10

11. 1.The candidate key must be unique within its domain. 2.The candidate key cannot hold NULL values (NULL is not zero. Zero is a number. NULL is 'nonexistent value'). 3.The candidate key can never change. It must hold the same value for a given occurrence of an entity for the lifetime of that entity. GUIDELINE 4: Candidate key Lecture4 11

12. Data redundancy is a term used about databases and means simply that some data fields appear more than once in the database. Disadvantages : 1.weak maintaining of the database 2.waste memory GUIDELINE 5: Avoid Data redundancy Lecture4 12

13. Lecture4 13

14. Derive relations for logical data model To implement the database in relational DBMS, ERD must be translated to tables 1.Specify the name of the relation. 2.A list of the relation’s simple attributes enclosed in brackets. 3.Identify the primary key and foreign key(s) of the relation. 4.Specify the identification of a foreign key, the relation containing the referenced For example: Staff (staffNo, fName, lName, position, sex, DOB) Client (clientNo, fName, lName, telNo, prefType, maxRent, staffNo) Foreign Key staffNo references Staff(staffNo) 14

15. 1- Mapping strong entity types A (strong) entity set reduces to a table with the same attributes and PK. If composite attributes exist, only their component simple attributes are needed. Derived attributes are usually omitted. Lecture4 15 Name FName MName LName Employee EmpNo Employee ( EmpNo, Fname, Mname, Lname )

16. A multivalued attribute M of an entity E is represented by a separate table EM 1.Includes the multivalued attribute M in EM 2.Includes the PK of E as FK in EM 3.The PK of EM is the combination of the PK of E and the multivalued attribute M. EM ( M, EPK) FKs : EPK references E (EPK) 2- mapping Multi_valued Attributes Lecture4 16

17. Example of Multi-valued Attributes Branch( brachNo, street, city, postCode) BrachTel (telNo, brachNo) FK: brachNo references Branch(branchNo) Branch BranchNo street city postCo de telNo

18. A weak entity set becomes a table that includes its key and the primary key of the owner entity as FK. The combination of the two keys form the PK of the weak entity. Example: Employee has Dependents Employee ( EmpNo, Lname) Dependents(empNo, depName, DepAge) FK : empNo referneces Employee (EmpNo) 3- Mapping Weak Entities Lecture4 18 1M empNoDepName Lname DepAge

19. 4- mapping Binary Relationships 1. Many-to-many binary relationship set create a new relation with columns for the PKs of the two participating entity sets, and attributes of the relationship. The PK of the new relatoin consists of the PKs of the two entities. The PKs of the two entities also serve as foreign keys referencing the entities. Lecture4 19 Student (stNo, stName) Subject (scode, sName) Enroll (stNo, scode, date) FKs: stNO reference Student(stNo) scode reference Subject(sCode) SUBJECTSTUDENTenroll MN date sName sCode stNo stName

20. 4- mapping Binary Relationships 2. One-to-many binary relationship sets Instead of using a separate table for the relationship, just modify the tables for the two entities: add the PK of the one side to the many side. It also serves as a FK of the many side. Add the attributes of the relationship to the many-side. Lecture4 20 staff Department Has 1N year sName sCode DeptNo DeptName Department (DeptNo, DeptName) Staff (scode, sName, DeptNo, year) FKs: DeptNO references Department(DeptNo)

21. Lecture4 4- mapping Binary Relationships 3.One-to-one relationship sets mandatory participation on both sides add the PK attributes of one side, and attributes of the relationship, to the other side. mandatory on one side add the PK attributes of the optional side, and attributes of the relationship, to the mandatory side. Optional on both sides choose one side and add its PK, and attributes of the relationship, to the other side. 21

22. 1:1 relationship -Mandatory on both sides Employee( emp_name, emp_id ) Office (officeNo, office_Loc, emp_id, year) FKs: emp_id references employee (Emp_id) employee office 11 has Emp_name officeNo Emp_id Office_Loc year

23. 1:1 relationship - Mandatory on one sides Employee( emp_name, emp_id ) Spouse(spouse_id, spouse_name, emp_id, year) FKs: emp_id references employee (Emp_id) employee spouse 11 has Emp_name Spouse_id Emp_id Spoude_name year

24. 1:1 relationship - Optional on both sides Employee( emp_name, emp_id ) Car (Car_No, Car_name, emp_id, year) FKs: emp_id reference employee (Emp_id) employee Car 11 use Emp_name Car_No Emp_id Car_name year

25. Follow rules for 1:1 binary relationship. single relation with two copies of the primary key (one needs to be renamed), plus attributes of the relationship. 5 – Mapping Unary Relationships Lecture4 25 staff supervise N 1 staffNo staffname Staff ( staffNo, staffname, supervisorstaffNo)

26. Create a relation R to represent the relationship Include the PK of the participating entities E1,E2.. En as FKs in R. The combination of all FKs form the PK of R. Add the relationship attributes to R 6 – Mapping n-ary Relationships Lecture4 26 Supplier (Sname)Project (projname)Part (PartNo) Supply (Sname, PartNo, ProjName, Quantity) fKs : Sname references Supplier(Sname) PartNo references Part (PartNo) ProjName references Project (ProjName)

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28. References “Database Systems: A Practical Approach to Design, Implementation and Management.” Thomas Connolly, Carolyn Begg. 5 th Edition, Addison-Wesley, 2009. Lecture4 28