程序代写代做代考 database ER Functional Dependencies Database Systems, GMU, Dr. Brodsky, Module 2 1

Database Systems, GMU, Dr. Brodsky, Module 2 1

The Entity-Relationship (ER) Model

Module 2

Professor Alex Brodsky
Database Systems

Database Systems, GMU, Dr. Brodsky, Module 2 2

Purposes of DBMS

  Provide support for “easy-to-use” data
–  Data model (data)
–  Transaction model (operation)

  Provide efficient storage and access of the
data in terms of the data model and
transactional model.

Database Systems, GMU, Dr. Brodsky, Module 2 3

Data Models

  Tools to obtain data abstraction.
  Necessary to be general and intuitive.
  Data model: A class of mathematical

structures, with description and operations
  Conceptual data model: Just structural

description

Database Systems, GMU, Dr. Brodsky, Module 2 4

Overview of Database Design

  Conceptual design
–  Use ER Model: E- Entities and R-Relationships
–  Decide the entities and relationships in the enterprise.
–  Decide what information about these entities and

relationships should we store in the database.
–  Decide the integrity constraints or business rules.

  Implementation
–  Map an ER model into a relational schema.

Database Systems, GMU, Dr. Brodsky, Module 2 5

ER Model Basics

  Entity: A real-world object distinguishable from other
objects.

  Distinguishable via its description (data)
  Attribute: a mapping that maps an object to a value

(called the attribute value). E.g.: Age is an attribute of
students objects.

  An entity is described (in DB) using a set of attributes
values.

  Entity Set: A collection of similar entities. E.g., all
employees.

–  Similar: All entities in an entity set have the same set of
attributes.

Database Systems, GMU, Dr. Brodsky, Module 2 6

ER Diagram: Entity Set & Example

Employees

ssn
name

lot

Diagram rule:

Entity set: Box
Attribute: “bubble”
Primary key: underlined

Database Systems, GMU, Dr. Brodsky, Module 2 7

Keys of Entity Sets
  A superkey of an entity set is a (sub)set of the

attributes such that no two entities in the set is
allowed to have the same values on all these (key)
attributes.

  Allowed?
–  Designer’s choice!

  Candidate key =A superkey that does not have a
“redundant” attribute, i.e., if any attribute is
removed, the set is not a superkey anymore.

  Primary key = One of the candidate keys designated to
be so.
–  Designated? By whom?

  Every entity set must have a key.

Database Systems, GMU, Dr. Brodsky, Module 2 8

ER Model Basics (Contd.)
  Relationship: Association among two or more entities.

E.g., Gandalf works in the Pharmacy department.
  Relationship Set: Collection of similar relationships.
  Similarity: is in terms of entity sets where the entities are

from.
  E.g.: A person (from employees entity set) works in a

department (from Departments entity set).
  An n-ary relationship set R relates n entity sets E1 … En;

each relationship in R involves entities e1 in E1,…,en in En
  Same entity set could participate in different

relationship sets, or in different “roles” in same set.

Database Systems, GMU, Dr. Brodsky, Module 2 9

Relationship Set Example

lot
dname

budget did

since
name

Works_In Departments Employees

ssn

Relationship set: Works_In

Database Systems, GMU, Dr. Brodsky, Module 2 10

Descriptive Attributes

  Relationships can have attributes
  These attributes are called “descriptive”

attributes, because they only “describe”
relationships, but do not “distinguish”
relationships.

  A relationship can only be distinguished by
the participating entities.

  Therefore, there can’t be more than one
relationship involving the same entities.

Database Systems, GMU, Dr. Brodsky, Module 2 11

Another Relationship Set

Reports_To

lot

name

Employees

subordinate supervisor

ssn

since

Database Systems, GMU, Dr. Brodsky, Module 2 12

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 constraint on Manages.

dname

budget did

since

lot

name

ssn

Manages Employees Departments

since

Works_In

Database Systems, GMU, Dr. Brodsky, Module 2 13

Types of Binary Relationship Sets

Many-to-Many 1-to-1 1-to Many Many-to-1

Database Systems, GMU, Dr. Brodsky, Module 2 14

Key Constraint

  An entity set may participate in a relationship
set as a “key” participant.

  What it means is that each entity of the “key”
entity set can only participate at most once in
the relationship set.

  More than one relationship set can be key
participant (e.g. one-to-one relationship set).

Database Systems, GMU, Dr. Brodsky, Module 2 15

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!)

lot
name dname

budget did

since
name dname

budget did

since

Manages

since

Departments Employees

ssn

Works_In

Database Systems, GMU, Dr. Brodsky, Module 2 16

Weak Entities

  Consider the following situation:

lot

name

age pname

Dependents Employees

ssn

Policy

Database Systems, GMU, Dr. Brodsky, Module 2 17

Weak Entity Sets
  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 pname

Dependents Employees

ssn

Policy

cost

Database Systems, GMU, Dr. Brodsky, Module 2 18

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)
  Reasons for using ISA:

–  To add descriptive attributes specific to a subclass.
–  To identify entitities that participate in a relationship.

Database Systems, GMU, Dr. Brodsky, Module 2 19

Aggregation
  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.

  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

Database Systems, GMU, Dr. Brodsky, Module 2 20

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.

Database Systems, GMU, Dr. Brodsky, Module 2 21

Entity vs. Attribute

  Should address be 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).

Database Systems, GMU, Dr. Brodsky, Module 2 22

Entity vs. Attribute (Contd.)

  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.

name

Employees

ssn lot

Works_In2

from to
dname

budget did

Departments

dname
budget did

name

Departments

ssn lot

Employees Works_In3

Duration from to

Database Systems, GMU, Dr. Brodsky, Module 2 23

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 of dbudget,
which is stored for each
dept managed by the
manager.

Manages2

name dname
budget did

Employees Departments

ssn lot

dbudget since

Employees

since

name dname
budget did

Departments

ssn lot

Mgr_Appts

Manages3

dbudget
apptnum Misleading: suggests dbudget

tied to managed dept.

Database Systems, GMU, Dr. Brodsky, Module 2 24

Binary vs. Ternary Relationships

  If each policy is
owned by just 1
employee:

–  Key constraint
on Policies
would mean
policy can only
cover 1
dependent!

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

age pname

Dependents Covers

name

Employees

ssn lot

Policies

policyid cost

Beneficiary

age pname

Dependents

policyid cost

Policies

Purchaser

name

Employees

ssn lot

Bad design

Better design

Database Systems, GMU, Dr. Brodsky, Module 2 25

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?

Database Systems, GMU, Dr. Brodsky, Module 2 26

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.

Database Systems, GMU, Dr. Brodsky, Module 2 27

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.
–  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.

Database Systems, GMU, Dr. Brodsky, Module 2 28

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.