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Chapter 2: Entity-Relationship Model
· Entity Sets
· Relationship Sets
· Design Issues
· Mapping Constraints
· Keys
· E­R Diagram
· Extended E-R Features
· Design of an E-R Database Schema
· Reduction of an E-R Schema to Tables
Database Systems Concepts 2.1 Silberschatz, Korth and Sudarshan c 1997
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Entity Sets
· A database can be modeled as:
­ a collection of entities,
­ relationships among entities.
· An entity is an object that exists and is distinguishable from
other objects.
Example: specific person, company, event, plant
· An entity set is a set of entities of the same type that share the
same properties.
Example: set of all persons, companies, trees, holidays
Database Systems Concepts 2.2 Silberschatz, Korth and Sudarshan c 1997
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Attributes
· An entity is represented by a set of attributes, that is,
descriptive properties possessed by all members of an entity
set.
Example:
customer = (customer-name, social-security,
customer-street, customer-city)
account = (account-number, balance)
· Domain ­ the set of permitted values for each attribute
· Attribute types:
­ Simple and composite attributes.
­ Single-valued and multi-valued attributes.
­ Null attributes.
­ Derived attributes.
Database Systems Concepts 2.3 Silberschatz, Korth and Sudarshan c 1997
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Relationship Sets
· A relationship is an association among several entities
Example:
Hayes depositor A-102
customer entity relationship set account entity
· A relationship set is a mathematical relation among n  2
entities, each taken from entity sets
{(e1, e2, ..., en) | e1  E1, e2  E2, ..., en  En}
where (e1, e2, ..., en) is a relationship
­ Example:
(Hayes, A-102)  depositor
Database Systems Concepts 2.4 Silberschatz, Korth and Sudarshan c 1997
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Relationship Sets (Cont.)
· An attribute can also be a property of a relationship set.
For instance, the depositor relationship set between entity sets
customer and account may have the attribute access-date
social-security customer-street
customer-name customer-city
customer
balance
accountdepositor
access-date
account-number
Database Systems Concepts 2.5 Silberschatz, Korth and Sudarshan c 1997
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Degree of a Relationship Set
· Refers to number of entity sets that participate in a relationship
set.
· Relationship sets that involve two entity sets are binary (or
degree two). Generally, most relationship sets in a database
system are binary.
· Relationship sets may involve more than two entity sets.
The entity sets customer, loan, and branch may be linked by
the ternary (degree three) relationship set CLB.
Database Systems Concepts 2.6 Silberschatz, Korth and Sudarshan c 1997
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Roles
Entity sets of a relationship need not be distinct
e-social-security
employee-name
telephone-number
employee works-for
manager
worker
· The labels "manager" and "worker" are called roles; they
specify how employee entities interact via the works-for
relationship set.
· Roles are indicated in E-R diagrams by labeling the lines that
connect diamonds to rectangles.
· Role labels are optional, and are used to clarify semantics of
the relationship
Database Systems Concepts 2.7 Silberschatz, Korth and Sudarshan c 1997
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Design Issues
· Use of entity sets vs. attributes
Choice mainly depends on the structure of the enterprise being
modeled, and on the semantics associated with the attribute in
question.
· Use of entity sets vs. relationship sets
Possible guideline is to designate a relationship set to describe
an action that occurs between entities
· Binary versus n-ary relationship sets
Although it is possible to replace a nonbinary (n-ary, for n > 2)
relationship set by a number of distinct binary relationship sets,
a n-ary relationship set shows more clearly that several entities
participate in a single relationship.
Database Systems Concepts 2.8 Silberschatz, Korth and Sudarshan c 1997
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Mapping Cardinalities
· Express the number of entities to which another entity can be
associated via a relationship set.
· Most useful in describing binary relationship sets.
· For a binary relationship set the mapping cardinality must be
one of the following types:
­ One to one
­ One to many
­ Many to one
­ Many to many
· We distinguish among these types by drawing either a directed
line (), signifying "one," or an undirected line (--), signifying
"many," between the relationship set and the entity set.
Database Systems Concepts 2.9 Silberschatz, Korth and Sudarshan c 1997
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One-To-One Relationship
social-security customer-street
customer-name customer-city
customer
loan-number amount
loanborrower
· A customer is associated with at most one loan via the
relationship borrower
· A loan is associated with at most one customer via borrower
Database Systems Concepts 2.10 Silberschatz, Korth and Sudarshan c 1997
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One-To-Many and Many-to-One Relationships
social-security customer-street
customer-name customer-city
customer
loan-number amount
loanborrower
(a)
social-security customer-street
customer-name customer-city
customer
loan-number amount
loanborrower
(b)
Database Systems Concepts 2.11 Silberschatz, Korth and Sudarshan c 1997
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One-To-Many and Many-to-One (Cont.)
· In the one-to-many relationship (a), a loan is associated with at
most one customer via borrower; a customer is associated with
several (including 0) loans via borrower
· In the many-to-one relationship (b), a loan is associated with
several (including 0) customers via borrower; a customer is
associated with at most one loan via borrower
Database Systems Concepts 2.12 Silberschatz, Korth and Sudarshan c 1997
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Many-To-Many Relationship
social-security customer-street
customer-name customer-city
customer
loan-number amount
loanborrower
· A customer is associated with several (possibly 0) loans via
borrower
· A loan is associated with several (possibly 0) customers via
borrower
Database Systems Concepts 2.13 Silberschatz, Korth and Sudarshan c 1997
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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.
­ y is a dominant entity (in example below, loan)
­ x is a subordinate entity (in example below, payment)
paymentloan-paymentloan
· If a loan entity is deleted, then all its associated payment
entities must be deleted also.
Database Systems Concepts 2.14 Silberschatz, Korth and Sudarshan c 1997
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Keys
· A super key of an entity set is a set of one or more attributes
whose values uniquely determine each entity
· A candidate key of an entity set is a minimal super key
­ social-security is candidate key of customer
­ account-number is candidate key of account
· Although several candidate keys may exist, one of the
candidate keys is selected to be the primary key.
· The combination of primary keys of the participating entity sets
forms a candidate key of a relationship set.
­ must consider the mapping cardinality and the semantics of
the relationship set when selecting the primary key.
­ (social-security, account-number) is the primary key of
depositor
Database Systems Concepts 2.15 Silberschatz, Korth and Sudarshan c 1997
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E-R Diagram Components
· Rectangles represent entity sets.
· Ellipses represent attributes.
· Diamonds represent relationship sets.
· Lines link attributes to entity sets and entity sets to relationship
sets.
· Double ellipses represent multivalued attributes.
· Dashed ellipses denote derived attributes.
· Primary key attributes are underlined.
Database Systems Concepts 2.16 Silberschatz, Korth and Sudarshan c 1997
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Weak Entity Sets
· An entity set that does not have a primary key is referred to as
a weak entity set.
· The existence of a weak entity set depends on the existence of
a strong entity set; it must relate to the strong set via a
one-to-many relationship set.
· The discriminator (or partial key) of a weak entity set is the set
of attributes that distinguishes among all the entities of a weak
entity set.
· The primary key of a weak entity set is formed by the primary
key of the strong entity set on which the weak entity set is
existence dependent, plus the weak entity set's discriminator.
Database Systems Concepts 2.17 Silberschatz, Korth and Sudarshan c 1997
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Weak Entity Sets (Cont.)
· We depict a weak entity set by double rectangles.
· We underline the discriminator of a weak entity set with a
dashed line.
· payment-number ­ discriminator of the payment entity set
· Primary key for payment ­ (loan-number, payment-number)
loan-number amount
loan
payment-number payment-amount
paymentloan-payment
payment-date
Database Systems Concepts 2.18 Silberschatz, Korth and Sudarshan c 1997
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Specialization
· Top-down design process; we designate subgroupings within
an entity set that are distinctive from other entities in the set.
· These subgroupings become lower-level entity sets that have
attributes or participate in relationships that do not apply to the
higher-level entity set.
· Depicted by a triangle component labeled ISA (i.e.,
savings-account "is an" account)
Database Systems Concepts 2.19 Silberschatz, Korth and Sudarshan c 1997
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Specialization Example
checking-account
gold
interest-rate
seniorstandard
savings-account
overdraft-amount
account
account-number balance
num-checks interest-payment min-balance date-of-birth
ISA
ISA
Database Systems Concepts 2.20 Silberschatz, Korth and Sudarshan c 1997
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Generalization
· A bottom-up design process ­ combine a number of entity sets
that share the same features into a higher-level entity set
· Specialization and generalization are simple inversions of each
other; they are represented in an E-R diagram in the same way.
· Attribute Inheritance ­ a lower-level entity set inherits all the
attributes and relationship participation of the higher-level
entity set to which it is linked.
Database Systems Concepts 2.21 Silberschatz, Korth and Sudarshan c 1997
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Design Constraints on a Generalization
· Constraint on which entities can be members of a given
lower-level entity set.
­ condition-defined
­ user-defined
· Constraint on whether or not entities may belong to more than
one lower-level entity set within a single generalization.
­ disjoint
­ overlapping
· Completeness constraint ­ specifies whether or not an entity in
the higher-level entity set must belong to at least one of the
lower-level entity sets within a generalization.
­ total
­ partial
Database Systems Concepts 2.22 Silberschatz, Korth and Sudarshan c 1997
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Aggregation
· Loan customers may be advised by a loan-officer.
customer-name
customer
social-security customer-street
customer-city
loan-number amount
loanborrower
loan-officer
employee
employee-name
e-social-security telephone-number
Database Systems Concepts 2.23 Silberschatz, Korth and Sudarshan c 1997
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Aggregation (Cont.)
· Relationship sets borrower and loan-officer represent the same
information
· Eliminate this redundancy via aggregation
­ Treat relationship as an abstract entity
­ Allows relationships between relationships
­ Abstraction of relationship into new entity
· Without introducing redundancy, the following diagram
represents that:
­ A customer takes out a loan
­ An employee may be a loan officer for a customer-loan pair
Database Systems Concepts 2.24 Silberschatz, Korth and Sudarshan c 1997
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Aggregation Example
customer-name
customer
social-security customer-street
customer-city
loan-number amount
loanborrower
loan-officer
employee
employee-name
e-social-security telephone-number
Database Systems Concepts 2.25 Silberschatz, Korth and Sudarshan c 1997
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E-R Design Decisions
· The use of an attribute or entity set to represent an object.
· Whether a real-world concept is best expressed by an entity
set or a relationship set.
· The use of a ternary relationship versus a pair of binary
relationships.
· The use of a strong or weak entity set.
· The use of generalization ­ contributes to modularity in the
design.
· The use of aggregation ­ can treat the aggregate entity set as
a single unit without concern for the details of its internal
structure.
Database Systems Concepts 2.26 Silberschatz, Korth and Sudarshan c 1997
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E-R Diagram for Banking Enterprise
checking-account
interest-rate
savings-account
overdraft-amount
account
account-number balance
ISA
social-security
customer-street
customer-name
customer-city
customer
branch-city
branch-name assets
branch
loan-number
amount
loan
payment-number payment-amount
paymentloan-payment
payment-date
type
employee
dependent-name
e-social-security
employment-length
access-date
borrower
loan-branch
cust-banker
depositor
works-for
manager
worker
employee-name
telephone-number
start-date
Database Systems Concepts 2.27 Silberschatz, Korth and Sudarshan c 1997
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Reduction of an E-R Schema to Tables
· Primary keys allow entity sets and relationship sets to be
expressed uniformly as tables which represent the contents of
the database.
· A database which conforms to an E-R diagram can be
represented by a collection of tables.
· For each entity set and relationship set there is a unique table
which is assigned the name of the corresponding entity set or
relationship set.
· Each table has a number of columns (generally corresponding
to attributes), which have unique names.
· Converting an E-R diagram to a table format is the basis for
deriving a relational database design from an E-R diagram.
Database Systems Concepts 2.28 Silberschatz, Korth and Sudarshan c 1997
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Representing Entity Sets as Tables
· A strong entity set reduces to a table with the same attributes.
customer-name social-security c-street c-city
Jones 321-12-3123 Main Harrison
Smith 019-28-3746 North Rye
Hayes 677-89-9011 Main Harrison
The customer table
· A weak entity set becomes a table that includes a column for
the primary key of the identifying strong entity set.
loan-number payment-number payment-date payment-amount
L-17 5 10 May 1996 50
L-23 11 17 May 1996 75
L-15 22 23 May 1996 300
The payment table
Database Systems Concepts 2.29 Silberschatz, Korth and Sudarshan c 1997
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Representing Relationship Sets as Tables
· A many-to-many relationship set is represented as a table with
columns for the primary keys of the two participating entity
sets, and any descriptive attributes of the relationship set.
social-security account-number access-date
... ... ...
The depositor table
· The table corresponding to a relationship set linking a weak
entity set to its identifying strong entity set is redundant.
The payment table already contains the information that would
appear in the loan-payment table (i.e., the columns
loan-number and payment-number).
Database Systems Concepts 2.30 Silberschatz, Korth and Sudarshan c 1997
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Representing Generalization as Tables
· Method 1: Form a table for the generalized entity account
Form a table for each entity set that is generalized (include
primary key of generalized entity set)
table table attributes
account account-number, balance, account-type
savings-account account-number, interest-rate
checking-account account-number, overdraft-amount
· Method 2: Form a table for each entity set that is generalized
table table attributes
savings-account account-number, balance, interest-rate
checking-account account-number, balance, overdraft-amount
Method 2 has no table for generalized entity account
Database Systems Concepts 2.31 Silberschatz, Korth and Sudarshan c 1997
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Relations Corresponding to Aggregation
customer
customer-name cust-social-security customer-street customer-city
loan
loan-number amount
borrower
cust-social-security loan-number
employee
emp-social-security employee-name phone-number
loan-officer
emp-social-security cust-social-security loan-number
Database Systems Concepts 2.32 Silberschatz, Korth and Sudarshan c 1997