dbms er model

Agenda
 Entity Set
 Attribute Types
 Relationship Sets
 Mapping Constraints
 E-R Diagram
 Keys
 Design Issues
 EXTENDED E-R FEATURES

Types of Attribute
 Attribute: A characteristic of an entity.
 Domain: A set of possible values for an
attribute.
 Attribute types:
 Simple and composite attributes.
 Single-valued and multi-valued attributes
 Derived attributes

 Simple : cannot further divided.
Eg: Age, Customer_no .
 Composite : divided eg: Name ,
address,
 Single-value: salary, id, roll no.
 Multivalue : phone number.
 Derived : Age from Birth year.

Relationship Sets
 A relationship is an association among several
entities
 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

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. Like Ternary relationship.
 Or N-Ary

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

Mapping Cardinalities
One to one One to many
Note: Some elements in A and B may not be mapped to any
elements in the other set

Many to one Many to many
Note: Some elements in A and B may not be mapped to any
elements in the other set

E-R Diagrams
 Rectangles represent entity sets.
 Diamonds represent relationship sets.
 Lines link attributes to entity sets and entity sets to
relationship sets.
 Ellipses represent attributes
 Double ellipses represent multivalued attributes.
 Dashed ellipses denote derived attributes.
 Underline indicates primary key attributes

E-R Diagram With Composite,
Multivalued, and Derived Attributes

Relationship Sets with
Attributes

Roles
 Entity sets of a relationship need not be distinct
 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

Cardinality Constraints
 We express cardinality constraints by drawing either a
directed line (), signifying “one,” or an undirected line
(—), signifying “many,” between the relationship set and
the entity set.
 E.g.: One-to-one relationship:
 A customer is associated with at most one loan via the
relationship borrower
 A loan is associated with at most one customer via
borrower

One-To-Many Relationship
 In the one-to-many relationship a loan is
associated with at most one customer via
borrower, a customer is associated with several
(including 0) loans via borrower

Many-To-One Relationships
 In a many-to-one relationship a loan is
associated with several (including 0) customers
via borrower, a customer is associated with at
most one loan via borrower

Many-To-Many Relationship
 A customer is associated with several (possibly 0)
loans via borrower
 A loan is associated with several (possibly 0)
customers via borrower

Participation of an Entity Set
in a Relationship Set
 Total participation (indicated by double line):
every entity in the entity set participates in at
least one relationship in the relationship set
 E.g. participation of loan in borrower is
total
 every loan must have a customer
associated to it via borrower
 Partial participation: some entities may not
participate in any relationship in the
relationship set
 E.g. participation of customer in borrower is
partial

Alternative Notation for
Cardinality Limits
 Cardinality limits can also express
participation constraints

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
 Customer-id 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

Keys for Relationship Sets
 The combination of primary keys of the
participating entity sets forms a super key of a
relationship set.
 (customer-id, account-number) is the super key
of depositor
 Must consider the mapping cardinality of the
relationship set when deciding the what are the
candidate keys
 Need to consider semantics of relationship set
in selecting the primary key in case of more
than one candidate key

E-R Diagram with a Ternary
Relationship

Binary Vs. Non-Binary
Relationships
 Some relationships that appear to be non-binary
may be better represented using binary
relationships
 E.g. A ternary relationship parents, relating
a child to his/her father and mother, is best
replaced by two binary relationships, father
and mother
 Using two binary relationships allows
partial information (e.g. only mother
being know)
 But there are some relationships that are
naturally non-binary
 E.g. works-on

Converting Non-Binary
Relationships to Binary Form
 In general, any non-binary relationship can be represented
using binary relationships by creating an artificial entity set.
 Replace R between entity sets A, B and C by an entity
set E, and three relationship sets:
1. RA, relating E and A
2.RB, relating E and B
3. RC, relating E and C
 Create a special identifying attribute for E
 Add any attributes of R to E
 For each relationship (ai , bi , ci) in R, create
1. a new entity ei in the entity set E
2. add (ei , ai ) to RA
3. add (ei , bi ) to RB
4. add (ei , ci ) to RC

 Also need to translate constraints
 Translating all constraints may not be possible
 There may be instances in the translated schema that
cannot correspond to any instance of R
 Exercise: add constraints to the relationships RA, RB
and RC to ensure that a newly created entity
corresponds to exactly one entity in each of entity sets
A, B and C
 We can avoid creating an identifying attribute by making E
a weak entity set (described shortly) identified by the three
relationship sets

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 identifying entity set
 it must relate to the identifying entity set via a
total, one-to-many relationship set from the
identifying to the weak entity set
 Identifying relationship depicted using a double
diamond
 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.

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)

Weak Entity Sets (Cont.)
 Note: the primary key of the strong entity set is
not explicitly stored with the weak entity set,
since it is implicit in the identifying
relationship.
 If loan-number were explicitly stored, payment
could be made a strong entity, but then the
relationship between payment and loan would
be duplicated by an implicit relationship
defined by the attribute loan-number common
to payment and loan

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 any 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.
 Placement of relationship attributes

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 (E.g. customer “is a”
person).

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.
 The terms specialization and
generalization are used interchangeably.

Specialization and
Generalization (Contd.)
 Can have multiple specializations of an entity
set based on different features.
 E.g. permanent-employee vs. temporary-
employee, in addition to officer vs. secretary vs.
teller
 Each particular employee would be
 a member of one of permanent-employee or
temporary-employee,
 and also a member of one of officer,
secretary, or teller
 The ISA relationship also referred to as
superclass - subclass relationship

 Union of subtype members is
always equal to the set
supertype. (Generalization)
 Eg: vehicals : air, surface, water.
 Union of subtype members is
not always equal to the set
supertype. (Specialization)
 Eg: employee : manager and
clerk.

Design Constraints on a
Specialization/Generalization
 Attribute inheritance:
 It is a crucial property of the higher and lower
level entities created by specialization and
generalization
 It is a lower-level entity set inherits all the
attributes and relationship participation of the
higher-level entity set to which it is linked.
 A higher level entity set with attributes and
relationships that apply to all of its lower-level
entity sets
 Lower level entity sets with distinctive features
that apply only within a particular lower-level
entity set

 Constraint on which entities can be members
of a given lower-level entity set.
 condition-defined
 E.g. all customers over 65 years are
members of senior-citizen entity set;
senior-citizen ISA person.
 user-defined
 It is not constrained by a given condition,
The database user assigns entities to a
given entity set.

 Constraint on whether or not entities may
belong to more than one lower-level entity set
within a single generalization
 Disjoint
 an entity can belong to only one lower-
level entity set
 Noted in E-R diagram by writing disjoint
next to the ISA triangle.
 Example : An account entity can satisfy
only one condition for the account-type
attribute; an entity can be either a savings
account or a checking account, but
cannot be both
 Overlapping
 an entity can belong to more than one
lower-level entity set

Example of overlapping
 Assume that certain managers
participate in more than one
work team.
 suppose generalization applied
to entity sets customer and
employee leads to a higher-level
entity set person. The
generalization is overlapping if
an employee can also be a
customer.

 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 : an entity must belong to one of the
lower-level entity sets
 partial: an entity need not belong to one of
the lower-level entity sets

Aggregation
 Consider the ternary relationship works-on,
which we saw earlier
 Suppose we want to record managers for tasks
performed by an employee at a branch

Aggregation (Cont.)
 Relationship sets works-on and manages
represent overlapping information
 Every manages relationship corresponds to a
works-on relationship
 However, some works-on relationships may
not correspond to any manages relationships
 So we can’t discard the works-on
relationship
 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:
 An employee works on a particular job at a particular
branch
 An employee, branch, job combination may have an
associated manager

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 specialization/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.

Summary of Symbols Used in
E-R Notation

 Construct an E-R diagram for a
car-insurance company, that
has a set of customer. Each
customer own one or more cars.
Each car has associated with it
zero to any number of recorded
accidents.

 Construct an ER diagram for the
Company that handles the
projects from various clients.
The Company has different
business units headed by the
unit heads. Each Business unit
have employees to work on
client's projects. Identify all the
Entities and relationships and
design a logical schema also.

 Construct an E-R diagram for a
hospital with a set of patients
and a set of medical doctors.
Associate with each patient a
log of the various tests and
examinations conducted.

 A university registrar’s ofﬁce maintains
data about the following entities: (a)
courses, including number, title, credits,
syllabus, and prerequisites; (b) course
offerings, including course number, year,
semester, section number,
instructor(s),timings, and classroom; (c)
students, including student-id, name, and
program; and (d) instructors, including
identiﬁcation number, name, department,
and title. Further, the enrollment of
students in courses and grades awarded to
students in each course they are enrolled
for must be appropriately modeled.

Reduction of an E-R Schema to Tables

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.

Conversion of Strong Entities
 For each strong entity in E-R
diagram, create a separate table
with the same name. Include all
simple attributes of the strong
entity with the same name.
 Create a key for the table

Conversion of Weak Entities
 A weak entity set becomes a
table that includes a column for
the primary key of the identifying
strong entity set, along with its
own attributes

Conversion of Strong
Entity(Customer)

Conversion of Weak
Entity(payment)

Conversion of one-one
Relationship
 For each one-one relationship,(betn
A and B),modify one of the table
(A or B),to include the P.Key of
other relation as F.Key
 If relationship has attributes,it must
be transferred to the modified
relation
 If any relation has a total
participation, only that table must
be modifed

Conversion of one-many
Relationship
 For each one-Many relationship,
modify N-side relation to hold the
primary key of other as a foreign
key

Conversion of many-many
Relationship
 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.

Advantages Of E-R model
1. Conceptual Simplicity
2. Maps well to the relational model
3. Simple and easy to understand
4. It is acting as a effective
communication tool between user
and developer

Disadvantages Of E-R model
1. Limited Constraint representation
2. Limited Relationship
representation
3. Loss of Information content
4. Suitable only for big projects

dbms er model

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