Chapter 2: EntityEntity-Relationship Model
Whats the use of the E-R model? Entity Sets Relationship Sets Design Issues Mapping Constraints Keys E-R Diagram Extended E-R Features Design of an E-R Database Schema Reduction of an E-R Schema to Tables
Database System Concepts
2.1
Silberschatz, Korth and Sudarshan
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 (will study later)
Database System Concepts 2.2 Silberschatz, Korth and Sudarshan
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-id, customer-name, customer-street, customer-city) loan = (loan-number, amount) Domain the set of permitted values for each attribute Attribute types: Simple and composite attributes. Single-valued and multi-valued attributes
E.g.
multivalued attribute: phone-numbers be computed from other attributes age, given date of birth
Derived attributes
Can E.g.
Database System Concepts
2.3
Silberschatz, Korth and Sudarshan
Entity Sets
A database can be modeled as:
a collection of entities, relationship among entities.
An entity is an object that exists and is distinguishable from other
objects. Example: specific person, company, event, plant
Entities have attributes
Example: people have names and addresses
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 System Concepts
2.4
Silberschatz, Korth and Sudarshan
Relationship Sets with Attributes
Database System Concepts
2.5
Silberschatz, Korth and Sudarshan
E-R Diagram With Composite, Multivalued, and Derived Attributes Attributestry to avoid them
Database System Concepts
2.6
Silberschatz, Korth and Sudarshan
Composite Attributes
Database System Concepts
2.7
Silberschatz, Korth and Sudarshan
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
Database System Concepts
2.8
Silberschatz, Korth and Sudarshan
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
Database System Concepts
2.9
Silberschatz, Korth and Sudarshan
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
Database System Concepts 2.10 Silberschatz, Korth and Sudarshan
Mapping Cardinalities
Many to one
Many to many
Note: Some elements in A and B may not be mapped to any elements in the other set
Database System Concepts 2.11 Silberschatz, Korth and Sudarshan
OneOne-ToTo-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
Database System Concepts
2.12
Silberschatz, Korth and Sudarshan
ManyMany-ToTo-One Relationships
Example of many-to-one relationships: a loan is associated with
several (including 0) customers via borrower, a customer is associated with at most one loan via borrower
Database System Concepts
2.13
Silberschatz, Korth and Sudarshan
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.
Example of 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
Database System Concepts
2.14
Silberschatz, Korth and Sudarshan
ManyMany-ToTo-Many Relationship
Example of Many to Many Relationships:
A customer is associated with several (possibly 0) loans via
borrower
A loan is associated with several (possibly 0) customers via
borrower
Database System Concepts
2.15
Silberschatz, Korth and Sudarshan
Alternative Notation for Cardinality Limits
Cardinality limits can also express participation constraints
Database System Concepts
2.16
Silberschatz, Korth and Sudarshan
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.
Database System Concepts
2.17
Silberschatz, Korth and Sudarshan
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.
E.g. Suppose employees of a bank may have jobs (responsibilities)
at multiple branches, with different jobs at different branches. Then there is a ternary relationship set between entity sets employee, job and branch Relationships between more than two entity sets are not as
common as binary ones.
Database System Concepts
2.18
Silberschatz, Korth and Sudarshan
E-R Diagram with a Ternary Relationship
Database System Concepts
2.19
Silberschatz, Korth and Sudarshan
Cardinality Constraints on Ternary Relationship
We allow at most one arrow out of a ternary (or greater degree)
relationship to indicate a cardinality constraint
E.g. an arrow from works-on to job indicates each employee works
on at most one job at any branch.
If there is more than one arrow, there are two ways of defining the
meaning. E.g a ternary relationship R between A, B and C with arrows to B and C
could mean
1. each A entity is associated with a unique entity from B and C or 2. each pair of entities from (A, B) is associated with a unique C entity,
and each pair (A, C) is associated with a unique B
Each alternative has been used in different formalisms To avoid confusion we outlaw more than one arrow
Database System Concepts
2.20
Silberschatz, Korth and Sudarshan
10
Binary Vs. NonNon-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) works-on
But there are some relationships that are naturally non-binary
E.g.
Database System Concepts
2.21
Silberschatz, Korth and Sudarshan
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 sets discriminator.
Database System Concepts
2.22
Silberschatz, Korth and Sudarshan
11
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)
Database System Concepts
2.23
Silberschatz, Korth and Sudarshan
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
Database System Concepts
2.24
Silberschatz, Korth and Sudarshan
12
More Weak Entity Set Examples
In a university, a course is a strong entity and a course-offering
can be modeled as a weak entity
The discriminator of course-offering would be semester (including
year) and section-number (if there is more than one section)
If we model course-offering as a strong entity we would model
course-number as an attribute. Then the relationship with course would be implicit in the coursenumber attribute
Database System Concepts
2.25
Silberschatz, Korth and Sudarshan
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).
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 System Concepts
2.26
Silberschatz, Korth and Sudarshan
13
Specialization Example
Database System Concepts
2.27
Silberschatz, Korth and Sudarshan
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.
Database System Concepts
2.28
Silberschatz, Korth and Sudarshan
14
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
Database System Concepts
2.29
Silberschatz, Korth and Sudarshan
Design Constraints on a Specialization/Generalization
Constraint on which entities can be members of a given
lower-level entity set. condition-defined
all customers over 65 years are members of seniorcitizen entity set; senior-citizen ISA person. user-defined Constraint on whether or not entities may belong to more than
E.g.
one lower-level entity set within a single generalization. Disjoint
an Noted
entity can belong to only one lower-level entity set in E-R diagram by writing disjoint next to the ISA triangle entity can belong to more than one lower-level entity set
Overlapping
an
Database System Concepts
2.30
Silberschatz, Korth and Sudarshan
15
Design Constraints on aSpecialization/Generalization aSpecialization/Generalization (Contd.)
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
Database System Concepts
2.31
Silberschatz, Korth and Sudarshan
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
Database System Concepts
2.32
Silberschatz, Korth and Sudarshan
16
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 cant 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
Database System Concepts
2.33
Silberschatz, Korth and Sudarshan
E-R Diagram With Aggregation
Database System Concepts
2.34
Silberschatz, Korth and Sudarshan
17
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.
Database System Concepts
2.35
Silberschatz, Korth and Sudarshan
E-R Diagram for a Banking Enterprise
Database System Concepts
2.36
Silberschatz, Korth and Sudarshan
18
Summary of Symbols Used in EE-R Notation
Database System Concepts
2.37
Silberschatz, Korth and Sudarshan
Summary of Symbols (Cont.)
Database System Concepts
2.38
Silberschatz, Korth and Sudarshan
19
Alternative EE-R Notations
Database System Concepts
2.39
Silberschatz, Korth and Sudarshan
Reduction of an EE-R Schema to Tables
1. A database which conforms to an E-R diagram can be
represented by a collection of tables
2. For each (strong) entity set there is a table having as
candidate key the key of the entity set
3. For relationship set there is a table having as columns
the keys of the participating entities. The candidate key for the table is determined by the cardinality constraints among participating entities.
4. A weak entity set becomes a table that includes a column
for the primary key of the identifying strong entity set
5. Inheritance to be discussed later
Database System Concepts
2.40
Silberschatz, Korth and Sudarshan
20
ManyMany-ToTo-One Relationships
Example of many-to-one relationships: a loan is associated with
several (including 0) customers via borrower, a customer is associated with at most one loan via borrower
Database System Concepts
2.41
Silberschatz, Korth and Sudarshan
Representing Entity Sets as Tables
A strong entity set reduces to a table with the same attributes.
Database System Concepts
2.42
Silberschatz, Korth and Sudarshan
21
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.
E.g.: table for relationship set borrower
Database System Concepts
2.43
Silberschatz, Korth and Sudarshan
Redundancy of Tables
Table with equivalent keys can be merged together---as
in the 3NF design algorithm E.g.: Merge the tables account-branch with account
Database System Concepts
2.44
Silberschatz, Korth and Sudarshan
22
Redundancy of Tables (Cont.)
For one-to-one relationship sets, either side can be chosen
to act as the many side
That is, extra attribute can be added to either of the tables corresponding to the two entity sets
If participation is partial on the many side null values
might be needed
Database System Concepts
2.45
Silberschatz, Korth and Sudarshan
Composite and Multivalued Attributes
Previous rules hold for simple attributes Composite attributes are flattened out by creating a separate attribute
for each component attribute E.g. given entity set customer with composite attribute name with
component attributes first-name and last-name the table corresponding to the entity set has two attributes name.first-name and name.last-name
Database System Concepts
2.46
Silberschatz, Korth and Sudarshan
23
Representing Weak Entity Sets
A weak entity set becomes a table that includes a column for
the primary key of the identifying strong entity set:
Database System Concepts
2.47
Silberschatz, Korth and Sudarshan
Representing Specialization as Tables
Method 1: Form a table for the higher level entity Form a table for each lower level entity set, include primary key of
higher level entity set and local attributes table person customer employee table attributes name, street, city name, credit-rating name, salary
Drawback: getting information about, e.g., employee requires accessing two tables
Database System Concepts
2.48
Silberschatz, Korth and Sudarshan
24
Representing Specialization as Tables (Cont.)
Method 2: Form a table for each entity set with all local and inherited
attributes table person customer employee table attributes name, street, city name, street, city, credit-rating name, street, city, salary
If specialization is total, no need to create table for generalized entity (person)
Drawback: street and city may be stored redundantly for persons who are both customers and employees
Database System Concepts
2.49
Silberschatz, Korth and Sudarshan
Relations Corresponding to Aggregation
To represent aggregation, create a table containing primary key of the aggregated relationship, the primary key of the associated entity set Any descriptive attributes
Database System Concepts
2.50
Silberschatz, Korth and Sudarshan
25
Relations Corresponding to Aggregation (Cont.)
E.g. to represent aggregation manages between relationship
works-on and entity set manager, create a table manages(employee-id, branch-name, title, manager-name)
Table works-on is redundant provided we are willing to store
null values for attribute manager-name in table manages
Database System Concepts
2.51
Silberschatz, Korth and Sudarshan
End of Chapter 2
26
