1. Chapter 2 Entity-Relationship Model 2.1 IntroductionIntroduction 2.2 Basic conceptsBasic concepts 2.3 mapping constrainsmapping constrains 2.4 keyskeys 2.5 Entity Relationship DiagramEntity Relationship Diagram 2.6 Weak Entity SetsWeak Entity Sets 2.7 Extended E-R FeaturesExtended E-R Features 2.8 Reduction of an E-R Schema to TableReduction of an E-R Schema to Table

2. 2.1 Introduction We can characterize the overall approach to the semantic modeling problem in terms of the following four steps: First, identify a set of semantic concepts. ① we might agree that the world is made up of entities. ② we might go further and agree that entities can usefully be classified into entity types. ③ we might go still further and agree that every entity has a special property that severs to identify that entity. ④ we might go further again and agree that any entity can be related to other entities by means of relationships.

3. 2.1 Introduction Next we try to devise a set of corresponding symbolic objects that can be used to represent the foregoing semantic concepts. We also devise a set of formal, general integrity rules to go along with those formal objects. Finally, we also develop a set of formals operators for manipulating those formal objects.

4. 2.2 Basic Concepts There are three basic notions that the E-R data model employs: entity sets, relationship sets, and attributes. 1.Entity Sets An entity is a “thing ” or “object” in the real world that is distinguishable from all other objects. An entity has a set of properties, and the values for some set of properties may uniquely identify an entity, an entity may be concrete or it may be abstract. An entity set is a set of entities of the same type that share the same properties, or attributes. Entity set do not need to be disjoint. An entity is represented by a set of attributes. For each attribute, there is a set of permitted values, called the domain, or value set, of that attribute.

5. 2.2 Basic Concepts An attribute, as used in the E-R model, can be characterized by the following attribute types: 1)simple and composite attributes the simple attributes are not divided into subparts composite attributes can be divided into subparts customer-name first-namemiddle-initiallast-name customer-address streetstatecitypostal-code street-numberstreet-nameapartment-number Example: Figure 2.2 composite attributes customer-name and customer-address

6. 2.2 Basic Concepts 2)single-valued and multivalued attributes the attributes that have a single value for a particular entity is called single-valued attributes. an attribute that has a set of values for a specific entity is called multivalued attributes. Example: phone-number, dependent-name 3)null attributes A null value is used when an entity does not have a value for an attribute. an attribute value is unknown : missing (name) or not known(apartment-number) 4)derived attribute the value for this type of attribute can be derived from the values of other related attributes or entities. age=date – date-of-birth

7. 2.2 Basic Concepts 2.Relationship Sets A relationship is an association among several entities. A relationship set is a set of relationships of the same type. A relationship set is a mathematical relation on n≥2 entity sets. If E1,E2,……En are entity sets, then a relationship set R is a subset of {(e1,e2,……en) ︱ e1 ∈ E1, e2 ∈ E2…… en ∈ En} The entities involved in a given relationship are said to be participants in that relationship. The number of participants in a given relationship is called the degree of that relationship.

8. 335-57-7991 Adams Spring Pittsfield 321-12-3123 Jones Main Harrison 019-28-3746 Smith North Rye 677-89-9001 Hayes Main Harrison 555-55-5555 Jackson Dupont Woodside 244-66-8800 Curry North Rye 963-96-3969 Williams Nassau Princeton L-23 1000 L-17 1000 L-15 1500 L-14 1500 L-19 500 L-11 900 L-16 1300 customer loan Figure 2.3 Relationship set borrower

9. 2.3 Mapping constrains An E-R enterprise schema may define certain constraints to which the contents of a database must conform. 1.Mapping cardinalities mapping cardinalities, of cardinality ratios, express the number of entities to which another entity can be associated via a relationship set. For a binary relationship set R between entity sets A and B, the mapping cardinality must be one of the following: 1)one to one : an entity in A is associated with at most one entity in B, and entity in B is associated with at most one entity in A. 2)one to many: an entity in A is associated with any number of entities in B. An entity in B, however, can be associated with at most one entity in A.

10. 2.3 Mapping constrains 3)many to one: An entity in A is associated with at most one entity in B. An entity in B, however, can be associated with any number of entities in A. 4)many to many: An entity in A is associated with any number of entities in B, and an entity in B is associated with any number of entities in A. a2 a3 a4 a1 b2 b3 b4 b1 A B One to one b2 b3 b4 b5 b1 a2 a3 a1 A B One to many b2 b3 b1 a2 a3 a4 a5 a1 AB Many to one a2 a3 a4 a1 b2 b3 b4 b1 AB Many to many

11. 2. Existence Dependencies If the existence of entity x depends on the existence of entity y, then x is said to be existence dependent on y. Operationally, if y is deleted, so is x. Entity y is said to be a dominant entity, and x is said to be a subordinate entity. The participation of an entity set E in a relationship set R is said to be total if every entity in E participates in at least one relationship in R. If only some entities in E participate in relationship in R, the participation of entity set E in relationship R is said to be partial. 2.3 Mapping constrains

12. 2.4 key A key allows us to identify a set of attributes that suffice to distinguish entities from each other. (relationships) 1. Entity Sets superkey : superkey is a set of one or more attributes, that, taken collectively, allows us to identify uniquely an entity in the entity set. candidate keys: minimal superkeys primary key: a candidate key that is chosen by the database designer as the principal means of identifying entities within an entity set. superkey candidate keys primary key

13. 2.4 key 2. Relationship Sets Let R be a relationship set involving entity sets E 1,E 2,……E n. Let primary-key(E i ) denote the set of attributes that forms the primary key for entity set E i. The composition of the primary key for a relationship set depends on the structure of the attributes associated with the relationship set R. If the relationship set R has no attributes associated with it, then the set of attributes primary-key(E 1 ) ∪ primary-key(E 2 ) ∪ …… ∪ primary-key(E n ) describes an individual relationship in set R.

14. 2.4 key If the relationship set R has attributes a1,a2, …… an associated with if, then the set of attributes. primary-key(E 1 ) ∪ primary-key(E 2 ) ∪ …… ∪ primary-key(E n ) ∪ {a1,a2, …… an } describes an individual relationship in set R. In both of the above cases, the set of attributes. primary-key(E 1 ) ∪ primary-key(E 2 ) ∪ …… ∪ primary-key(E n ) from a superkey for the relationship set. The structure of the primary key for the relationship set depends on the mapping cardinality of the relationship set.

15. 2.5 Entity Relationship Diagram A E-R diagram consists of the following major components: 1. Rectangles, which represent entity sets 2. Ellipses, which represent attributes 3. Diamonds, which represent relationship sets 4. Lines, which link attributes to entity sets and entity sets to relationship sets 5. Double ellipses, which represent multivalued attributes 6. Dashed ellipses, which denote derived attributes 7. Double links, which indicate total participation of an entity in a relationship set

16. 2.5 Entity Relationship Diagram many to many borrower loan customer 1M borrower loan customer M 1 borrower loan customer M M borrower loan amount customer-city loan-number customer customer-name customer-id customer-street one to many many to one one to one

17. depositor account balance customer-city account-number customer customer-name customer-id customer-street 2.5 Entity Relationship Diagram access-date We have the access-date descriptive attribute attached to the relationship set depositor to specify the most recent date on which a customer accessed that account. Figure 2.10 E-R diagram with an attribute attached to a relationship set

18. 2.5 Entity Relationship Diagram name date-of-birth street-name customer first-name customer-id street last-name middle-initial address city state zip-code phone-number street-numberapartment-number age multivalued attributes derived attributes composit e attributes Example:

19. 2.5 Entity Relationship Diagram works-for telephone-number employee employee-name employee-id manager worker Figure2.12 E-R diagram with role indicators role

20. 2.5 Entity Relationship Diagram works-on branch branch-city city branch-name employee employee-name employee-id street assets job leveltitle Figure2.13 E-R diagram with a ternary relationship

21. 2.5 Entity Relationship Diagram borrower loan amount customer-city loan-number customer customer-name customer-id customer-street total participation Figure2.14 Total participation of an entity set in a relationship set

22. borrower loan amount customer-city loan-number customer customer-name customer-id customer-street 2.5 Entity Relationship Diagram 0..*1..1 Figure2.15 Cardinality limits on relationship sets l..h: l minimum cardinality h maximum cardinality A minimum value of 1 : total participation A maximum value of 1 : the entity participates in at most one relationship A maximum value * : no limit 1..* =total participation

23. 2.6 Weak Entity Sets An entity set may not have sufficient attributes to form a primary key. Such an entity set is termed a weak entity set. primary key of payment = loan-number + payment-number primary key of loandiscriminator payment-number payment loan-payment loan loan-number amount M 1 payment-datepayment-amount discriminato r doubly outlined diamond doubly outlined box weak entity set strong entity set total participation

24. Example:(E-R) partly A manufacturing company will wish to record information about :the projects it has on hand;the parts used in those projects;the suppliers who supply those parts;the employees who work on those projects;the departments which employees belong to; the employee ’ s dependent. The employee comprise those information: the number of the employee, employee ’ s name, (include first name... ) and the salary. The supplier comprise those information: the number of the supplier, the supplier ’ s name, supplier ’ s address(include status and city) A employee(manager,worker) must belong to a department and may take part in more than one projects A manager is responsible for more than one projects but a project should assign to one manger A supplier provide a certain quantity parts to projects.

25. M M PROJ- WORK QTY PROJ- MANAGER PROJECT SUPP PART_PROJ SUPP_ PART PART_ STRUCTURE QTY SUPPLIER CITY STATUSSNAMES# M M M M M M MM M 1 DEPENDENT EMP_DEP DEPT-EMP EMPLOYEE DEPART MENT SALARY EMP# ENAME FIRSTMILAST M 1 1 total participation many to many one to many weak entity set composit e attributes

26. 2.7 Extended E-R Features 1. Specialization An entity set may include subgroupings of entities that are distinct in some way from other entities in the set. The process of designating subgroupings within an entity set is specialization. Specialization emphasizes differences among entities within the set 2. Generalization This commonality can be expressed by generalization, which is a containment relationship that exists between a higher-level entity set and one or more lower -level entity sets. generalization emphasizes commonalties among entity sets ISA

27. employee is a person hours-worked officer hours-worked customer citystreetname employee person credit-rating salary office-number station-number ISA tellersecretary specialization generalization officer is a employee Figure2.17 Specialization and generalization

28. 2.7 Extended E-R Features Total(double line) partial(line) disjoint (d) overlapping(o) employee ISA customer person savings- account ISA checking- account disjoint overlapping partial participation total participation

29. 2.7 Extended E-R Features 3. Attribute Inheritance A crucial property of the higher-and lower-level entities created by specialization and generalization is attribute inheritance. The attributes of the higher-level entity sets are said to be inherited by the lower-level entity sets. If an entity set is a lower-level entity set in more than one ISA relationship, the resulting structure is said to be a lattice. A higher-level entity set with attributes and relationships that apply to all of its lower-level entity sets. Lower-level entity sets with distinctive features that apply only within a particular lower-level entity set.

30. 2.7 Extended E-R Features 4. Aggregation One limitation of the E-R modal is that it is not possible to express relationships among relationships. works-on branch employee job manages manager redundant relationships Figure2.18 E-R diagram with redundant relationships

31. works-on branch employee job manages manager 2.7 Extended E-R Features Aggregation is an abstraction through which relationship are treated as higher-level entities. aggregation higher-level entities Figure2.19 E-R diagram with aggregation

32. 2.8 Reduction of an E-R Schema to Tables A database that conforms to an E-R database schema can be represented by a collection of tables. 1. Tabular Representation of Strong Entity Sets In general, if we have a table of n columns. We denote the Cartesian product of D1,D2 …… Dn by D1×D2 × …… ×Dn-1 ×Dn. 1. Tabular Representation of Strong Entity Sets telephone-number employee employee-name employee-id employee -name employee -id telephone -number employee

33. 2.8 Reduction of an E-R Schema to Tables 2. Tabular Representation of Weak Entity Sets Let A be a weak entity set with attributes a 1,a 2 ……a n. Let B be the strong entity set on which A is dependent. Let the primary key of B consist of attributes b 1,b 2 ……b n. {a 1,a 2 ……a m } ∪ {b 1,b 2 ……b n } payment-number payment loan-payment loan loan-number amount M 1 payment-datepayment-amount loan-numberpayment- number payment- date payment- amount payment

34. 3. Tabular Representation of Relationship Sets 2.8 Reduction of an E-R Schema to Tables depositor account balance customer-city account-number customer customer-name customer-id customer-street access-date customer-idaccount-numberaccess-date depositor

35. 2.8 Reduction of an E-R Schema to Tables ⑴ Redundancy of Tables In general, the table for the relationship set linking a weak entity set to its corresponding strong entity set is redundant and does not need to be present in a tabular representation of an E-R diagram. payment-number payment loan-payment loan loan-number amount M 1 payment-datepayment-amount loan- number payment -number payment -date payment -amount loan- number payment- number redundancy loan- payment payment

36. ⑵ Combination of Tables (1 to many) 2.8 Reduction of an E-R Schema to Tables account- branch assetsbranch-name account account-number branch-city balance account-numberbalance account-numberbranch-name account-numberbalancebranch-name account account- branch combination

37. 2.8 Reduction of an E-R Schema to Tables 4. Composite Attributes customer-street customer customer-city customer-id customer-address customer-name customer-idcustomer-namecustomer-streetcustomer-city customer

38. 2.8 Reduction of an E-R Schema to Tables 5. Multivalued Attributes New tables should be created for multivalued attributes. For a multivalued attributes M, we create a table T with a column C that corresponds to M and columns corresponding to the primary key of the entity set or relationship set of which M is an attribute. employee-id employee … dependent-name … employee-idd-name dependent-name

39. 2.8 Reduction of an E-R Schema to Tables 6. Tabular Representation of Generalization account-number savings-account overdraft-amount account interest-rate balance ISA checking-account

40. 2.8 Reduction of an E-R Schema to Tables 6. Tabular Representation of Generalization 1 、 Create a table for the higher-level entity set. For each lower- level entity set, create a table that includes a column for each of the attributes of that entity set plus a column for each attribute of the primary key of the higher-level entity set. account-numberbalance account account-numberinterest-rate savings-account checking-account account-numberoverdraft-amount

41. 2.8 Reduction of an E-R Schema to Tables 2 、 If the generalization is disjoint and complete then we should not create a table for the higher-level entity set. Instead, for each lower-level entity set, create a table that includes a column for each of the attributes of that entity set plus a column for each attribute of the higher-level entity set. account-numberbalanceinterest-rate savings-account account-numberbalanceoverdraft -amount checking-account

42. 2.8 Reduction of an E-R Schema to Tables 7. Tabular Representation of Aggregation borrower loan customer loan-number customer-name loan-officer employee employee-number customer- name loan- number employee- number loan-officer

43. Exercises: P 72 : 2.1 2.3 2.5 2.6 2.9 2.12