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.