The entity relationship er model
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The Entity-Relationship (ER) Model. CS541 Computer Science Department Rutgers University. Overview of Database Design. Conceptual design : ( ER Model is used at this stage.) What are the entities and relationships in the enterprise?

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The Entity-Relationship (ER) Model

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The entity relationship er model

The Entity-Relationship (ER) Model

CS541

Computer Science Department

Rutgers University


Overview of database design

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.

  • Schema Refinement: (normalization)

    • Check schema for redundancies and anomalies

  • Physical DB Design and Tuning:

    • Adapt DB to typical use and workoads


Er model basics

name

ssn

lot

Employees

ER Model Basics

  • Entity: Real-world object distinguishable from other objects. An entity is described (in DB) 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!)

    • Each entity set has a key.

    • Each attribute has a domain.


Er model basics contd

name

ssn

lot

Employees

since

name

dname

super-visor

subor-dinate

ssn

budget

lot

did

Reports_To

Works_In

Employees

Departments

ER Model Basics (Contd.)

  • Relationship: Association among two or more entities. E.g., Attishoo works in Pharmacy department.

  • Relationship Set: Collection of similar relationships.

    • An n-ary relationship set R relates n entity sets E1 ... En; each relationship in R involves entities e1 E1, ..., en En

    • Same entity set could participate in different relationship sets, or in different “roles” in same set.


Key constraints

since

name

dname

ssn

lot

Employees

Manages

Key Constraints

  • Consider Works_In: An employee can work in many departments; a dept can have many employees.

  • In contrast, each dept has at most one manager, according to the key constrainton Manages.

did

budget

Departments

1-to-1

1-to Many

Many-to-1

Many-to-Many


Participation constraints

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 Departments entity must appear in an instance of the Manages relationship.

since

since

name

name

dname

dname

ssn

did

did

budget

budget

lot

Departments

Employees

Manages

Works_In

since


Weak entities

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.

name

cost

pname

age

ssn

lot

Policy

Dependents

Employees


Isa is a hierarchies

name

ISA (`is a’) Hierarchies

ssn

lot

Employees

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.

hourly_wages

  • 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)

  • Reasons for using ISA:

    • To add descriptive attributesspecific to a subclass.

    • To identify entitities that participate in a relationship.

ISA

contractid

Contract_Emps

Hourly_Emps


Aggregation

Employees

name

Aggregation

ssn

lot

  • Used when we have to model a relationship involving (entitity sets and) a relationship set.

    • Aggregation allows us to treat a relationship set as an entity set for purposes of participation in (other) relationships.

Monitors

until

since

started_on

dname

pid

pbudget

did

budget

Sponsors

Departments

Projects

  • 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.


Conceptual design using the er model

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.

  • Need for schema refinement


Entity vs attribute

Entity vs. Attribute

  • Should addressbe an attribute of Employees or an entity (connected to Employees by a relationship)?

  • 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).


Entity vs attribute contd

name

dname

ssn

lot

did

Employees

dname

did

budget

Duration

to

from

Entity vs. Attribute (Contd.)

to

from

  • Works_In2 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.

budget

Departments

Works_In2

name

ssn

lot

Works_In3

Departments

Employees


Entity vs relationship

Entity vs. Relationship

since

dbudget

  • 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.

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


Binary vs ternary relationships

name

ssn

lot

Employees

Policies

policyid

cost

name

ssn

lot

Employees

Beneficiary

Policies

policyid

cost

Binary vs. Ternary Relationships

pname

age

  • If each policy is owned by just 1 employee, and each dependent is tied to the covering policy, first diagram is inaccurate.

  • What are the additional constraints in the 2nd diagram?

Dependents

Covers

Bad design

pname

age

Dependents

Purchaser

Better design


Binary vs ternary relationships contd

Binary vs. Ternary Relationships (Contd.)

  • Previous example illustrated a case when two binary relationships were better than one ternary relationship.

  • An example in the other direction: 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:

    • 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?


Summary of conceptual design

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.


Summary of er contd

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.


Summary of er contd1

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 information and normalization techniques are especially useful.

    • Subject of future lectures…


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