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Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke1 The Entity-Relationship Model Chapter 2.

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Presentation on theme: "Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke1 The Entity-Relationship Model Chapter 2."— Presentation transcript:

1 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke1 The Entity-Relationship Model Chapter 2

2 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke2 Overview of Database Design Conceptual design: (ER Model is used at this stage.)  What are the entities and relationships in the enterprise?  Students sign up for classes  What information about these entities and relationships should we store in the database?  Student number and phone number of each student  What are the integrity constraints or business rules that hold?  No student takes more than seven courses per semester  A database `schema’ in the ER Model can be represented pictorially (ER diagrams).  Can map an ER diagram into a relational schema. Entity Relationship

3 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke3 Entity & Entity Set  Entity: Real-world object distinguishable from other objects, e.g., a particular employee. An entity is described (in database) using a set of attributes.  Entity Set: A collection of similar entities, e.g., all employees.  All entities in an entity set have the same set of attributes (until we consider ISA hierarchies, anyway!) Employees ssn name lot Entity set Attribute Key  Each attribute has a domain.  Each entity set has a key – uniquely identifies an entity in the set

4 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke4 Relationship Relationship: Association among two or more entities, e.g., “Jessica works in Pharmacy department.” lot dname budget did since name Works_In Departments Employees ssn A relationship

5 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke5 Relationship Set Relationship Set: Collection of similar relationships.  An n-ary relationship set R relates n entity sets E 1... E n ; each relationship in R involves entities e 1 in E 1,..., e n in E n lot dname budget did since name Works_In Departments Employees ssn         EMPLOYEES WORKS_IN DEPARTMENTS Relationship set

6 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke6 A Ternary Relationship Example  Each department has offices in several locations  We want to record the locations at which each employee works budget dname Departments Works_In name Employees ssn lot Locations address capacity did since EmployeesWorks_Ins Departments         Locations Works at two locations

7 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke7 Relationship Participation Same entity set could participate in different relationship sets, or in different “roles” in the same set. Reports_To lot name Employees subor- dinate super- visor ssn “Employees” participates in two different roles

8 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke8 Mapping to Tables lot dname budget did since name Works_In DepartmentsEmployees ssn namelot 1234JennyA456 diddnamebudget 8DB1,000,000 EmployeesDepartments Works_In ssndidsince

9 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke9 Key Constraints: 1-to-Many  Consider Works_In: An employee can work in many departments; a dept can have many employees (many-to- mamy relationship).  In contrast, each dept has at most one manager, according to the key constraint on Manages (1-to- many relationship). dname budgetdid since lot name ssn Manages EmployeesDepartments dname budgetdid from lot name ssn Works_In Employees Departments to many-to- many 1-to- many

10 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke10 Key Constraints dname budgetdid since lot name ssn Manages Employees Departments 1-to Many         EMPLOYEESMANAGESDEPARTMENTS Given a Departments entity, we can uniquely determine the Manages relationship in which it appears

11 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke11 Different Kinds of Relationships 1-to-1 1-to Many Many-to-1 Many-to-Many

12 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke12 Partial participation Total participation (a participation constraint) Total participation (a participation constraint) Participation Constraints 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).  Every did value in Departments table must appear in a row of the Manages table (with a non-null ssn value! - more details later in this course) lot name dname budgetdid since name dname budgetdid since Manages since Departments Employees ssn Works_In

13 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke13 Total vs. Partial Participation Does every department have a manager ? Partial Participation         EmployeesManagesDepartments Total Participation         EmployeesManagesDepartments Manages EmployeesDepartments Manages EmployeesDepartments Has no manager Everyone has a manager

14 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke14 Weak Entities A weak entity can be identified uniquely only by considering the primary key of another (owner) entity. lot name age dpname Dependents Employees ssn Policy cost A weak entity set The owner entity set Partial key Draw both with dark lines to indicate that Policy is the identifying relationship Need both ssn and dpname to identify a “Dependents” entity Need both ssn and dpname to identify a “Dependents” entity

15 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke15 Weak Entities A weak entity can be identified uniquely only by considering the primary key of another (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. lot name age dpname Dependents Employees ssn Policy cost A weak entity set The owner entity set Partial key 1-to-many relationship Total participation 1-to-many relationship Total participation

16 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke16 ISA (`is a’) Hierarchies Contract_Emps name ssn Employees lot hourly_wages ISA Hourly_Emps contractid hours_worked  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.  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)

17 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke17 ISA (‘is a’) Hierarchies Contract_Emps name ssn Employees lot hourly_wages ISA Hourly_Emps contractid hours_worked Reasons for using ISA  To identify entities that participate in a relationship  Example: Only contract employees can be managers (i.e., participating in the Manages relationship)  To add descriptive attributes specific to a subclass  Example: We only need to track hours worked for hourly employees Manages

18 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke18 Aggregation  Used when we have to model a relationship involving (entity sets and) a relationship set.  Aggregation vs. ternary relationship:  Monitors is a distinct relationship, with a descriptive attribute.  Also, can say that each sponsorship is monitored by at most one employee. budget did pid started_on pbudget dname until Departments Projects Sponsors Employees Monitors lot name ssn since Aggregation allows us to treat a relationship set as an entity set for purpose of participation in (other) relationships

19 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke19 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, e.g., functional dependencies (discussed later in this course)

20 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke20 Entity vs. Attribute (1) Should address be an attribute of Employees or an entity (connected to Employees by a relationship)? name Employees ssn lot live_at City StateStreet Address name Employees ssn lot address Option 1 Option 2

21 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke21 Entity vs. Attribute (2)  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). name Employees ssn lot live_at City StateStreet Address name Employees ssn lot address Employees can have multiple addresses Can retrieve employees in a given city

22 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke22 Entity vs. Attribute (Contd.) name Employees ssn lot Works_In4 fromto dname budget did Departments This relationship is mapped to a relation ssndidfromto Same key value → same instance Not allowed Works_In4 does not allow an employee to work in a department for two or more periods

23 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke23 Entity vs. Attribute (Contd.)  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: dname budget did name Departments ssn lot Employees Works_In5 Duration from to  We want to record several values of the descriptive attributes for each instance of this relationship.  Accomplished by introducing new entity set, Duration. ssndidfromto Works_In5

24 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke24 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 that covers all managed depts?  Redundancy: dbudget stored for each dept managed by manager.  Misleading: Suggests dbudget associated with department-mgr combination. Manages2 name dname budget did Employees Departments ssn lot dbudget since Managers dname budget did Departments Manages2 Employees name ssn lot since dbudget ISA This fixes the problem !

25 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke25 EmployeesCovers Policy         Binary vs. Ternary Relationships (1) If each policy is owned by just one employee, and each dependent is tied to the covering policy, we need some constraints age pname Dependents Covers name Employees ssn lot Policies policyid cost Dependents 1.An employee can own several policies 2.Each policy can be owned by several employee 3.Each dependent can be covered by several policies 1.An employee can own several policies 2.Each policy can be owned by several employee 3.Each dependent can be covered by several policies Joint policy Covered by 2 policies Owns 2 policies

26 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke26 Binary vs. Ternary Relationships (2) Constraints: Each policy is owned by just one employee, and each dependent is tied to the covering policy. Beneficiary age pname Dependents policyid cost Policies Purchaser name Employees ssn lot Key constraint – A policy cannot be owned jointly by two or more employees Total participation – Every policy must be owned by some employee Key constraint – A policy cannot be owned jointly by two or more employees Total participation – Every policy must be owned by some employee Weak entity set – Each dependent is uniquely identified by a policy (i.e., policyid and pname)

27 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke27 When to use N-ary Relationships ? No combination of binary relationships is an adequate substitute for the above ternary relationship:  The binary relationships S “can-supply” P, D “needs” P, and D “deals-with” S do not imply that D has agreed to buy P from S.  How do we record qty in the binary relationships ? D “buys” 20 units from S; but what are these units ? Departments Contracts Suppliers Parts qty

28 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke28 Example: University Database We have four entity sets: Professor, Project, Graduate, Department Professo r rank Specialty age ssn Dept dname dno office Project pid end_date sponsor start-date budget Graduate name deg_progage ssn

29 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke29 Example: University Database  Each project is managed by one professor (principal investigator)  Professors can manage multiple projects Professo r Dept Graduate Project rank Specialty age ssn dname pid dno office end_date sponsor start-date budget name deg_progage ssn Manages grad

30 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke30 Example: University Database  Each project is worked on by one or more professors (co-investigators)  Professors can work on multiple projects Professo r Dept Graduate Project Manages rank Specialty age ssn dname pid dno office end_date sponsor start-date budget name deg_progage ssn Work_in

31 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke31 Example: University Database  Each project is worked on by one or more graduate students (research assistants)  Graduate students can work on multiple projects Professo r Dept Graduate Project Manages Work_in rank Specialty age ssn dname pid dno office end_date sponsor start-date budget name deg_progage ssn Work_proj hours

32 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke32 Example: University Database  When graduate students work on multiple projects, they must have a supervisor (professor) for each one. Professo r Dept Graduate Project Manages Work_inWork_proj rank Specialty age ssn dname pid dno office end_date sponsor start-date budget hours name deg_progage ssn Supervises

33 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke33 Example: University Database Departments have a professor who runs the department Professo r Dept Graduate Project Supervises Manages Work_inWork_proj rank Specialty age ssn dname pid dno office end_date sponsor start-date budget hours name deg_progage ssn Runs

34 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke34 Example: University Database  Professors work in one or more departments  For each department a professor works in, a time percentage is associated with their job Professo r Dept Graduate Project Supervises Manages Work_inWork_proj Runs rank Specialty age ssn dname pid dno office end_date sponsor start-date budget hours name deg_progage ssn pc_time Work_dept

35 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke35 Example: University Database Graduate students have one major department in which they are working on their degree Professo r Dept Graduate Project Supervises Manages Work_inWork_proj Runs Work_dept rank Specialty age ssn dname pid dno pc_time office end_date sponsor start-date budget hours name deg_progage ssn Major

36 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke36 Example: University Database Each graduate student has another, more senior graduate student who advises him or her on what courses to take Professo r Dept Graduate Project Supervises Manages MajorWork_inWork_proj Runs Work_dept rank Specialty age ssn dname pid dno pc_time office end_date sponsor start-date budget hours name deg_progage ssn Advisor senior grad

37 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke37 Example: University Database Professo r Dept Graduate Project Supervises Manages MajorWork_inWork_proj Advisor Runs Work_dept rank Specialty age ssn dname pid dno pc_time office end_date sponsor start-date budget hours name deg_progage ssn senior grad

38 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke38 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.

39 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke39 Summary of ER (Contd.)  Several kinds of integrity constraints can be expressed in the ER model:  key constraints,  participation constraints, and  overlap/covering constraints for ISA hierarchies.  Some foreign key constraints are also implicit in the definition of a relationship set (more later in the course).  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 (more later in the course).

40 Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke40 Summary of ER (Contd.)  There are often many ways to model a given scenario! Analyzing alternative ER designs can be tricky. 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.  Functional dependency information and normalization techniques are especially useful (discussed later).


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