The Entity-Relationship Model (Chapter 2)

1. The Entity-Relationship Model (Chapter 2) 1

2. Main Phases of Database Design 2

3. Overview of Database Design • Conceptual design: (ER Model is used at this stage.) • What are the entities and relationships in the enterprise? • What information about these entities and relationships should we store in the database? • What are the integrity constraints or business rules that hold? • A database `schema’ in the ER Model can be represented pictorially (ER diagrams). • Can map an ER diagram into a relational schema.

4. ER Model Basics name ssn lot Employees • Entity-Relationship (ER) data model • A database can be modeled as a collection of entities and relationship among entities • Widely used to develop an initial database design • Entity: Real-world object distinguishable from other objects. • An entity is described (in DB) using a set of attributes.

5. ER Model Basics (Contd.) name ssn lot Employees • Entity Set: A collection of similar entities. E.g., all employees. • All entities in an entity set have the same set of attributes. • Each entity set has a key. • Key: a minimal set of attributes whose values uniquely identify an entity in the set • Each attribute has a domain. • A domain defines the possible values of each attributes • E.g., attribute name might be the set of 20-character string 5

6. 6

7. ER Model Basics (Contd.) since name dname ssn lot budget did Works_In Employees Departments • Relationship: Association among two or more entities. • E.g., James works in Pharmacy department. • Descriptive attribute, since • Record the information about the relationship, rather than about one of the participating entities

8. ER Model Basics (Contd.) since since name name dname dname ssn did did budget budget lot Departments Employees Manages Works_In since • Relationship Set: Collection of similar relationships. • Same entity set could participate in different relationship sets 8

9. ER Model Basics (Contd.) name ssn lot Employees super-visor subor-dinate Reports_To • Relationship Set: Collection of similar relationships. • A relationship might involve two entities in the same entity set • Two entities with different “roles” in same set. 9

10. Key Constraints 1-to-1 1-to Many Many-to-1 Many-to-Many since name dname ssn lot budget did Works_In Employees Departments • Consider Works_In: An employee can work in many departments; a dept can have many employees.

11. Key Constraints since name dname ssn lot did budget Employees Manages Departments 1-to-1 1-to Many Many-to-1 Many-to-Many • In contrast, each dept has at most one manager, according to the key constrainton Manages. • The constraint that each department has at most one manager is an example of a key constraint, and it implies that each Departments entity appear in at most one Manages relationship. • Arrow states that given a Department entity, we can uniquely determine the manages relationship in which it appears.

12. Key Constraints 1-to-1 1-to Many Many-to-1 Many-to-Many since name dname ssn lot did budget Employees Manages Departments • Each department has only one manager • And each employee can manage only one department. 12

13. Participation Constraints since since name name dname dname ssn did did budget budget lot Departments Employees Manages Works_In since • Does every department have a manager? • If so, this is a participation constraint: the participation of Departments in Manages is said to be total (vs. partial). • If the participation of an entity set in a relationship set is total, the two are connected by a thick line • Every Departments entity must appear in an instance of the Manages relationship.

14. exercise 14

15. 15

16. 16

17. 17

18. 18

19. Homework • Page 53, exercise 2.4 • Submit your homework (softcopy, PDF or DOC format) at usm.csc411@gmail.com or hardcopy at class) • Due date: Next Thursday (Sept, 5th) 19

20. Weak Entities name cost pname age ssn lot Policy Dependents Employees • Employees can purchase insurance to cover their dependents. • Only dependents’ SSN is not needed • If an employee quits, any policy owned by the employee is terminated and all relevant policy and dependent info will be deleted from the database. ssn 20

21. Weak Entities name cost pname age ssn lot Policy Dependents Employees • A weak entity can be identified uniquely only by considering the primary key of another (owner) entity. • (One of two or more candidate keys is designated as the primary key) • (Partial key: the set of attributes of a weak entity set that uniquely identify a weak entity for a given owner entity) • Owner entity set and weak entity set must participate in a one-to-many relationship set (one owner, many weak entities). • Weak entity set must have total participation in this identifying relationship set.

22. ISA (`is a’) Hierarchies name ssn lot Employees hours_worked hourly_wages ISA contractid Contract_Emps Hourly_Emps • As in C++, or other PLs, attributes are inherited. • If we declare A ISA B, every A entity is also considered to be a B entity. • Employees is specialized into subclasses • Hourly-Emp and Contract_EMps are generalized by Employees 22

23. ISA (`is a’) Hierarchies (Contd.) • Overlap constraints: Can Joe be an Hourly_Emps as well as a Contract_Emps entity? (Allowed/disallowed) • Covering constraints: • Does every Employees entity also have to be an Hourly_Emps or a Contract_Emps entity? (Yes/no). Intuitively, No. • Reasons for using ISA: • To add descriptive attributesspecific to a subclass. • To identify entities that participate in a relationship.

24. Aggregation name ssn lot Employees Monitors until since started_on dname pid pbudget did budget Sponsors Departments Projects • Used to model a relationship between a collection of entities and relationships. • Aggregation allows us to treat a relationship set as an entity set for purposes of participation in (other) relationships.

25. Aggregation (Contd.) name ssn lot Employees Monitors until since started_on dname pid pbudget did budget Sponsors Departments Projects • Aggregation vs. ternary relationship: why not make Sponsors a ternary relationship? • There are really two distinct relationships (monitors and sponsors), each with attribute of its own. • Monitors is a distinct relationship, with a descriptive attribute. • Also, can say that each sponsorship is monitored by at most one employee. • How to set key constraint in aggregation and ternary relationship? 25

26. Conceptual Design Using the ER Model • Design choices: • Should a concept be modeled as an entity or an attribute? • Should a concept be modeled as an entity or a relationship? • Identifying relationships: Binary or ternary? Aggregation? • Constraints in the ER Model: • A lot of data semantics can (and should) be captured. • But some constraints cannot be captured in ER diagrams.

27. Entity vs. Attribute name ssn address Employees • Should addressbe an attribute of Employees or an entity (connected to Employees by a relationship)?

28. Entity vs. Attribute name ssn address Employees • Depends upon the use we want to make of address information, and the semantics of the data: • If we have several addresses per employee, address must be an entity (since attributes cannot be set-valued). • If the structure (city, street, etc.) is important, e.g., we want to retrieve employees in a given city, address must be modeled as an entity (since attribute values are atomic).

29. Entity vs. Attribute name street ssn a# city Employees Lives_in addresses • If we have several addresses per employee, address must be an entity (since attributes cannot be set-valued). • If the structure (city, street, etc.) is important, e.g., we want to retrieve employees in a given city, address must be modeled as an entity (since attribute values are atomic).

30. Entity vs. Attribute (Contd.) since name dname ssn lot budget did Works_In Employees Departments to from name dname ssn lot did budget Departments Works_In4 Employees

31. Entity vs. Attribute (Contd.) to from name dname ssn lot did budget Departments Works_In4 Employees dname did budget Duration to from • Works_In4 does not allow an employee to work in a department for two or more periods. • Similar to the problem of wanting to record several addresses for an employee: • We want to record several values of the descriptive attributes for each instance of this relationship. • Accomplished by introducing new entity set, Duration. name ssn lot Works_In4 Departments Employees

32. Entity vs. Relationship • First ER diagram OK if a manager gets a separate discretionary budget for each dept. • What if a manager gets a discretionary budget (sum) that covers all managed depts? • Redundancy: dbudget stored for each dept managed by manager. • Misleading: Suggests that dbudget associated with department-mgr combination. since dbudget name dname ssn lot did budget Departments Employees Manages2 name ssn lot dname since did Employees budget Departments Manages2 ISA This fixes the problem! Managers dbudget

33. Binary vs. Ternary Relationships (1) name cost pname age ssn lot Policy Dependents Employees name ssn pname lot age Dependents Employees Covers Policies policyid cost • The ER diagram shows • An employee can own several policies (dental, health) • Each policy can be owned by several employees • Each dependent can be covered by several policies

34. Binary vs. Ternary Relationships (1) name ssn pname lot age Dependents Employees Covers Policies policyid cost • If each policy is owned by just 1 employee, and each dependent is tied to the covering policy, this ER diagram is inaccurate. Why? • Key constraint on Policies with respect to Covers implies that a policy can cover only one dependent.

35. Binary vs. Ternary Relationships (2) name pname age ssn lot Dependents Employees Purchaser Beneficiary Policies policyid cost • Additional constraints in the following ER diagram • A policy cannot be owned jointly by two or more employees (key constraint) • Every policy must be owned by some employees (total participation constraint) • Dependents is a week entity set • (uniquely identified by pname and policyid) Better design

36. Binary vs. Ternary Relationships (3) • Previous example illustrated a case when two binary relationships were better than one ternary relationship. • An example of ternary relationship • a ternary relation Contracts relates entity sets Parts, Departments and Suppliers, and has descriptive attribute qty. • No combination of binary relationships is an adequate substitute (without aggregation) • S “can-supply” P, D “needs” P, and D “deals-with” S does not imply that D has agreed to buy P from S. • How do we record qty?

37. Summary of Conceptual Design • Conceptual design follows requirements analysis, • Yields a high-level description of data to be stored • ER model popular for conceptual design • Constructs are expressive, close to the way people think about their applications. • Basic constructs • entities, relationships, and attributes (of entities and relationships). • Some additional constructs • weak entities, ISA hierarchies, and aggregation. • Note: There are many variations on ER model.

38. Summary of ER (Contd.) • Several kinds of integrity constraints can be expressed in the ER model • key constraints, participationconstraints, and overlap/covering constraints for ISA hierarchies. • Some foreign key constraints are also implicit in the definition of a relationship set. • Some constraints (notably, functional dependencies) cannot be expressed in the ER model. • Constraints play an important role in determining the best database design for an enterprise.

39. Summary of ER (Contd.) • ER design is subjective. • There are often many ways to model a given scenario! Analyzing alternatives can be tricky, especially for a large enterprise. • Common choices include: • Entity vs. attribute, entity vs. relationship, binary or n-ary relationship, whether or not to use ISA hierarchies, and whether or not to use aggregation. • Ensuring good database design • resulting relational schema should be analyzed and refined further. • FD (functional dependency) information and normalization techniques are especially useful.

42. 42

43. Questions? 43