Transcript Document

Conceptual Design Using the
Entity-Relationship (ER) Model
Database Management Systems,
1
Database Design Process

Requirements analysis
– What data, what applications, what most frequent
operations,…

Conceptual database design
– High level description of the data and the
constraint
– This step can use ER or similar high level models

Logical database design
– Convert database design into a database schema,
e.g. relational db schema
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Database Design Process (cont.)

Schema refinement
– Analyze the the collection of the data for potential
problems and refine it

Physical database design
– Ensure that the design meets the performance
requirements, based on used indexation, etc.

Security design
– Identify different user groups with different roles,
so that data protection is enforced accordingly.
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ER Model Basics


ssn
Entity: Real-world object
distinguishable from
other objects.
– An entity is described (in DB)
using a set of attributes.
Entity Set: A collection of similar
entities. E.g., all employees.
name
lot
Employees
ssn
name
lot
123-22-3666 Attishoo
48
231-31-5368 Smiley
22
131-24-3650 Smethurst 35
– All entities in an entity set have the
same set of attributes.
CREATE TABLE Employees
– Each entity set has a key, uniquely
(ssn CHAR(11),
identifies it.
name CHAR(20),
– Each attribute has a domain.
lot INTEGER,
– Can map entity set to a relation easily.
PRIMARY KEY (ssn)) 4
Database Management Systems,
ER Model Basics (Contd.)
name
ssn
lot
since
name
ssn
dname
lot
did
Employees
budget
supervisor
Employees
Works_In
Departments
subordinate
Reports_To
Relationship: Association among 2 or more entities.
E.g., Zeynep works in Sales department.
 Relationship Set: Collection of similar relationships.

 Same
entity set could participate in different
relationship sets, or in different “roles” in the
same set.
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ER Model Basics (Contd.)
CREATE TABLE Works_In(
 Relationship sets can also have
ssn CHAR(11),
descriptive attributes (e.g., the
did INTEGER,
since attribute of Works_In).
since DATE,
 In translating a relationship set
PRIMARY KEY (ssn, did),
to a relation, attributes of the
FOREIGN KEY (ssn)
relation must include:
REFERENCES Employees,
FOREIGN KEY (did)
– Keys for each participating
REFERENCES Departments)
entity set (as foreign keys).
This set of attributes
forms superkey for the
relation.
– All descriptive attributes.

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ssn
123-22-3666
123-22-3666
231-31-5368
did
51
56
51
since
1/1/91
3/3/93
2/2/92
6
Key Constraints

Consider Works_In: An employee can work in many
departments; a dept can have many employees, manyto-many, as in the previous figure

In contrast, each dept has at most one manager,
according to the key constraint on Manages, one-tomany…
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Key Constraints
since
name
ssn
dname
lot
Employees
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did
Manages
budget
Departments
8
Types of relationship sets
1-to-1
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1-to Many
Many-to-1
Many-to-Many
9
Translating ER Diagrams with Key Constraints-1

Map relationship to a table: Example: manages relationship
– Note that did is the key now!
– Separate tables for Employees and Departments.
CREATE TABLE Manages(
ssn CHAR(11),
did INTEGER,
since DATE,
PRIMARY KEY (did),
FOREIGN KEY (ssn) REFERENCES Employees,
FOREIGN KEY (did) REFERENCES Departments)
THIS MAPPING CAN NOT INCLUDE TOTAL PARTICIPATION!
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Translating ER Diagrams with Key Constraints-2


Since each department has a unique manager, we could instead
combine Manages and Departments, create relationship Dept_Mgr.
Every dept. may not have a manager, null values allowed for ssn.
CREATE TABLE Dept_Mgr(
did INTEGER,
dname CHAR(20),
budget REAL,
ssn CHAR(11),
since DATE,
PRIMARY KEY (did),
FOREIGN KEY (ssn) REFERENCES Employees)
This shows key constraint but not total participation because of absence of NOT NULL on ssn
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Participation Constraints:Total vs. Partial

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).
 For total participation, every did value in Departments
table must appear in a row of the Manages table, with a
non-null ssn value, indicating that every department has
a manager.
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Participation constraints (cont.)
since
name
ssn
dname
did
lot
Employees
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Manages
budget
Departments
13
Participation Constraints(Cont.)
In the corresponding SQL mapping, the Null value
for the ssn in Dept_Mgr is not allowed…
 ON DELETE NO ACTION specification is actually
the default case:

– It ensures that an Employee tuple cannot be deleted while
it is pointed to by a Dept_Mgr
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Participation Constraints in SQL

Capture of participation constraints using one entity
set, in a binary relationship.
CREATE TABLE Dept_Mgr(
did INTEGER,
dname CHAR(20),
budget REAL,
ssn CHAR(11) NOT NULL,
since DATE,
PRIMARY KEY (did),
FOREIGN KEY (ssn) REFERENCES Employees,
ON DELETE NO ACTION)
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Participation Constraints (cont.)


Many participations cannot be captured by SQL easily
For example, take the two relationship set as in the
following Manages and Works_In ER diagram.
since
name
ssn
dname
did
lot
Employees
Manages
budget
Departments
Works_In
since
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Participation Constraints (cont.)


How to ensure total participation in SQL relation
corresponding to Works_In relationship? Note that
ssn and did alone cannot be keys for ths
relationship….
We have to guarantee that every did value in
Departments appears in a tuple of Works_In
– This tuple must also have NOT NULL values in the foreign
key fields
– This cannot be achieved similar to Manages relationship,
because did cannot be taken as the key for Works_In
relationship
– This situation needs assertions in SQL, which exist in the
current SQL releases…
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Participation Constraints (cont.)

Another constraint that cannot be express in
SQL easily is the requirement that each
employee must manage at least one
department.
– Again, in SQL this is achieved using Assertions,
which are constraints that associated to multiple
relations or tables.
– Assertions are imposed by the CHECK clause in
SQL, although its implementation is
cumbersome… this is left out of scope of this lecture
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Weak Entities
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.
 A weak entity always has a partial key, it can only be
uniquely defined if we take its key together with the
key of the owner entity.

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Weak Entities (cont.)

Employee is owner entity, Dependent is weak
entity, Policy is the relationship set:
name
ssn
lot
Employees
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cost
Policy
pname
age
Dependents
20
Translating Weak Entity Sets

Weak entity set and identifying relationship
set are translated into a single table. ssn
cannot be null.
– When the owner entity is deleted, all owned weak
entities must also be deleted.
CREATE TABLE Dep_Policy (
pname CHAR(20),
age INTEGER,
cost REAL,
ssn CHAR(11) NOT NULL,
PRIMARY KEY (pname, ssn),
FOREIGN KEY (ssn) REFERENCES Employees,
ON DELETE CASCADE)
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ISA (`is a’) Hierarchies
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.
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name
ISA (`is a’) Hierarchies-2
ssn
lot
Employees
Subclasses are
defined first!
hourly_wages
hours_worked
ISA
contractid
Hourly_Emps


Contract_Emps
Overlap constraints: Can Zeynep be an Hourly_Emps as well
as a Contract_Emps entity? (posibility:Allowed using
OVERLAP)
Covering constraints: Does every Employees entity also have to
be an Hourly_Emps or a Contract_Emps entity? (allowed using
COVER)
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ISA (`is a’) Hierarchies-3

Reasons for using ISA:
– To add descriptive attributes specific to a subclass.
– To identify the set of entities that participate in a
particular relationship, e.g. only Senior Employees can
be allowed to be Managers of Departments.
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Translating ISA Hierarchies to Relations

General approach:
– 3 relations: Employees, Hourly_Emps and Contract_Emps.
 Hourly_Emps: Every employee is recorded in Employees. For
hourly emps, extra info recorded in Hourly_Emps (hourly_wages,
hours_worked, ssn); must delete Hourly_Emps tuple if referenced
Employees tuple is deleted).
 Queries involving all employees are easy, those involving just
Hourly_Emps require a join to get some attributes.

Alternative: two subentities exist: Hourly_Emps and
Contract_Emps:
– Each employee must be in one of these two subclasses.
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Translating ISA Hierarchies to
Relations(cont.)
The second alternative is not applicable if
there are employees who are neither of the
subclasses.
 Also, with the second method there may be
more redundant fields, repeated in the subs.
 Overlap and covering constraints can only be
expressed using assertions.

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name
ssn
Aggregation-1
Suppose:
 entity set Projects
 each Projects is sponsored by
at least one Departments
 each Departments that
sponsors a Projects might
assign employees to monitor
sponsorship
Intuitively…
Monitors should be a
relationship set that
associates a Sponsors
relation (versus a Projects
or Departments) with an
Employees entity.
Database Management Systems,
lot
Employees
since
started_on
pid
pbudget
Projects
did
Sponsors
dname
budget
Departments
27
name
ssn
Aggregation-2


Used when we have to
model a relationship
involving (entity sets and)
a relationship set.
Aggregation allows us to
treat a relationship set as
an entity set for purposes
of participation in (other)
relationships.
Database Management Systems,
lot
Employees
Monitors
since
started_on
pid
pbudget
Projects
until
did
Sponsors
dname
budget
Departments
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Aggregation vs.
Ternary relation
name
ssn
lot
Employees
Each relationship in an aggregation
may have a different descriptive
attribute like since and until.
Suppose:

No need to record until
attribute of Monitors
one can use
ternary relationship
Sponsors2
Then…
since
started_on
pid
pbudget
Projects
did
Sponsors2
dname
budget
Departments
But suppose we have constraint that:
Each sponsorship (of a project by a department) be monitored
by at most one employee?
Then… one can’t do it with Sponsors2  Need aggregated relationship Sponsors
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Aggregation vs.
Ternary relation
(Contd.)
name
ssn
lot
Employees
Monitors
Monitors is a
distinct relationship,
with a descriptive
attribute (until).
until

since
started_on
pid
pbudget
Projects
did
Sponsors
dname
budget
Departments
Also, can say that
each sponsorship
is monitored by at
most one employee.

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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.

Need for further refinement of the schema:
– Relational schema obtained from ER diagram is a good first
step. But ER design is subjective & can’t express certain
constraints; so this relational schema may need refinement.
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Entity vs. Attribute
Should address be an attribute of Employees or an
entity (connected to Employees by a relationship)?
 Depending upon the purpose 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).

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Entity vs. Attribute (Contd.)

Works_In2 does not allow an employee to work in a
department for two or more periods.
from
name
ssn
dname
lot
Employees

to
did
Works_In2
budget
Departments
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.
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Entity vs. Attribute (Contd.)

Use Duration entity to allow more than one duration per
relationship…
name
dname
ssn
lot
Employees
from
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did
Works_In3
Duration
budget
Departments
to
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Entity vs. Relationship

Following ER diagram OK if a manager gets a
separate discretionary budget for each dept.
since
dbudget
name
ssn
dname
lot
Employees
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did
Manages2
budget
Departments
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Entity vs. Relationship

What if a manager gets a discretionary budget is sum that covers
by that employee? Then the previous ER diagram will cause
–
–

all depts managed
Redundancy of dbudget, where the same value is stored for each dept managed by the same
manager.
Misleading as it suggests dbudget tied to managed dept rather than emloyee.
Instead a separate entity Mgr_Appts can be used with apptnum as key. This way the
redundancy is eliminated!
name
ssn
dname
lot
Employees
did
Manages3
budget
Departments
since
apptnum
Mgr_Appts
dbudget
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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!


Every policy must be owned by some employee
Dependents is a weak entity set
name
ssn
pname
lot
Employees
Bad design: with
or without dark
arrow
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age
Dependents
Covers
Policies
policyid
cost
37
Binary vs. Ternary Relationships


What are the additional constraints in the 2nd diagram? A policy cannot be owned
by more than one employee, every policy must be owned by some employee an
cover at least one dependent, dependent is a weak entity set.
Beneficiary is an identifying relationship for the weak entity Dependents, ie. Each
dependent will have one policy only…
name
ssn
pname
lot
Dependents
Employees
Purchaser
Better design
policyid
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age
Beneficiary
Policies
With two binary relationships
cost
38
Binary vs. Ternary Relationships (Contd.)
CREATE TABLE Policies (
 The key
policyid INTEGER,
constraints allow cost REAL,
us to combine
ssn CHAR(11) NOT NULL,
Purchaser with
PRIMARY KEY (policyid).
Policies and
FOREIGN KEY (ssn) REFERENCES Employees,
Beneficiary with
ON DELETE CASCADE)
Dependents.
CREATE TABLE Dependents (
pname CHAR(20),
 Participation
constraints lead to age INTEGER,
policyid INTEGER,
NOT NULL
constraints.
PRIMARY KEY (pname, policyid).
FOREIGN KEY (policyid) REFERENCES Policies,
ON DELETE CASCADE)
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Binary vs. Ternary Relationships (Contd.)
Previous example illustrated a case when 2 binary
relationships were better than a ternary relationship.
 An example in the other direction: a ternary relation
Contracts with descriptive attribute qty relates entity
sets Parts, Departments and Suppliers.
 No combination of binary relationships is an
adequate substitute for ternary relationship:

– 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?
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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.

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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 of these constraints can be expressed in SQL only if
we use general CHECK constraints or assertions.
– 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.
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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.
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Views


Views are computed as needed using view definition
Example
CREATE VIEW B-Students(name, sid, course)
AS SELECT S.name, S.sid, E.cid
FROM Students S, Enrolled E
WHERE S.sid=E.sid AND E.grade=‘B’



Whenever B-Students is used in a query, the view
definition is first evaluated, before using B-Students in
any other query operation.
View concept provides logical data independence, as
it can be used to mask the changes in the conceptual
schema.
Views can be defined taken security aspect into
consideration, e.g., dbadmin, user, group, etc..
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Updates on Views





The updateable views are the one defined on single
base tables, without aggregate operations.
Update on an updateable table implies update of the
corresponding base table as well.
A view can be dropped by DROP VIEW command.
Deleting base tables is more restrictive, as they have
to have RESTRICT or CASCADE options, concerning
integrity…
With RESTRICT, drop of a base is possible if no
reference to it exist; with CASCADE, drop of base
causes drop of all references recursively…
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Example
name
addr
Bookshops
name
Books
Sells
license
Note:
license =
Books, yes,
no
Attend
name
Database Management Systems,
Likes
Reader
manf
Bookshops sell som
Books.
readers like to read
some Books.
Readers attend
some Bookshops.
addr
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Relationship Set

The current “value” of an entity set is the set
of entities that belong to it.
 Example: the set of all Bakkals in our database.

The “value” of a relationship is a set of lists of
currently related entities, one from each of the
related entity sets.
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Examples
A University database contains information about
professors (identified by social security number,
or SSN) and courses (identified by courseid).
Professors teach courses.
 Each of the following situations concerns the
Teaches relationship set. For each situation, draw
an ER diagram that describes it (assuming that no
further constraints hold).

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Examples (cont’)
Professors can teach the same course in several
semesters, and each offering must be recorded.
2)
Professors can teach the same course in several
semesters, and only the most recent such offering needs
to be recorded. (Assume this condition applies to all
subsequent questions.)
3)
Every professor must teach some course
4) Every professor teaches exactly one course (no more, no
less).
5)
Every professor teaches exactly one course (no more no
less), and every course must be taught by some professor.
6)
Now assume that certain courses can be taught by a team
of professors jointly, but it is possible that no one
professor in a team can teach the course. Model this
situation introducing additional entity sets and
relationship sets if necessary.
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1)
Example (cont’)
1)
Professors can teach the same course in several
semesters, and each offering must be recorded.
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Example (cont’)
2)
Professors can teach the same course in several
semesters, and only the most recent such offering
needs to be recorded. (Assume this condition
applies to all subsequent questions.)
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Example (cont’)
3)
Every professor must teach some course
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Example (cont’)
4)
Every professor teaches exactly one course (no
more, no less).
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Example (cont’)
5)
Every professor teaches exactly one course (no
more no less), and every course must be taught
by some professor.
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Example (cont’)
6)
Now assume that certain courses can be taught
by a team of professors jointly, but it is possible
that no one professor in a team can teach the
course. Model this situation introducing
additional entity sets and relationship sets if
necessary.
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Example

A company database needs to store information
about employees (identified by ssn, with salary
and phone as attributes); departments (identified
by dno, with dname and budget as attributes); and
children of employees (with name and age as
attributes). Employees work in departments; each
department is managed by an employee; a child
must be identified uniquely by name when the
parent (who is an employee; assume that only one
parent works for the company) is known. We are
not interested in information about a child once
the parent leaves the company.
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