Chapter05 Data Base Chapter05 Data Base .pdf

CHAPTER 5
The Relational Data Model and
Relational Database Constraints
Slide 1- 2

Copyright © 2016 Ramez Elmasri and Shamkant B. Navathe Slide 5- 3
Chapter Outline
 Relational Model Concepts
 Relational Model Constraints and Relational
Database Schemas
 Update Operations and Dealing with Constraint
Violations

Relational Model Concepts
 The relational Model of Data is based on the concept of a
Relation
 The strength of the relational approach to data management
comes from the formal foundation provided by the theory of
relations
 We review the essentials of the formal relational model in
this chapter
 In practice, there is a standard model based on SQL –
this is described in Chapters 6 and 7 as a language
 Note: There are several important differences between
the formal model and the practical model, as we shall see

Relational Model Concepts
 A Relation is a mathematical concept based on
the ideas of sets
 The model was first proposed by Dr. E.F. Codd of
IBM Research in 1970 in the following paper:
 "A Relational Model for Large Shared Data
Banks," Communications of the ACM, June 1970
 The above paper caused a major revolution in the
field of database management and earned Dr.
Codd the coveted ACM Turing Award

Informal Definitions
 Informally, a relation looks like a table of values.
 A relation typically contains a set of rows.
 The data elements in each row represent certain facts
that correspond to a real-world entity or relationship
 In the formal model, rows are called tuples
 Each column has a column header that gives an indication
of the meaning of the data items in that column
 In the formal model, the column header is called an
attribute name (or just attribute)

Example of a Relation

Informal Definitions
 Key of a Relation:
 Each row has a value of a data item (or set of items)
that uniquely identifies that row in the table
 Called the key
 In the STUDENT table, SSN is the key
 Sometimes row-ids or sequential numbers are
assigned as keys to identify the rows in a table
 Called artificial key or surrogate key

Formal Definitions - Schema
 The Schema (or description) of a Relation:
 Denoted by R(A1, A2, .....An)
 R is the name of the relation
 The attributes of the relation are A1, A2, ..., An
 Example:
CUSTOMER (Cust-id, Cust-name, Address, Phone#)
 CUSTOMER is the relation name
 Defined over the four attributes: Cust-id, Cust-name,
Address, Phone#
 Each attribute has a domain or a set of valid values.
 For example, the domain of Cust-id is 6 digit numbers.

Formal Definitions - Tuple
 A tuple is an ordered set of values (enclosed in angled
brackets ‘< … >’)
 Each value is derived from an appropriate domain.
 A row in the CUSTOMER relation is a 4-tuple and would
consist of four values, for example:
 <632895, "John Smith", "101 Main St. Atlanta, GA 30332",
"(404) 894-2000">
 This is called a 4-tuple as it has 4 values
 A tuple (row) in the CUSTOMER relation.
 A relation is a set of such tuples (rows)

Formal Definitions - Domain
 A domain has a logical definition:
 Example: “USA_phone_numbers” are the set of 10 digit phone
numbers valid in the U.S.
 A domain also has a data-type or a format defined for it.
 The USA_phone_numbers may have a format: (ddd)ddd-dddd where
each d is a decimal digit.
 Dates have various formats such as year, month, date formatted
as yyyy-mm-dd, or as dd mm,yyyy etc.
 The attribute name designates the role played by a domain in a
relation:
 Used to interpret the meaning of the data elements corresponding
to that attribute
 Example: The domain Date may be used to define two attributes
named “Invoice-date” and “Payment-date” with different meanings

Formal Definitions - State
 The relation state is a subset of the Cartesian
product of the domains of its attributes
 each domain contains the set of all possible values
the attribute can take.
 Example: attribute Cust-name is defined over the
domain of character strings of maximum length
25
 dom(Cust-name) is varchar(25)
 The role these strings play in the CUSTOMER
relation is that of the name of a customer.

Formal Definitions - Summary
 Formally,
 Given R(A1, A2, .........., An)
 r(R)  dom (A1) X dom (A2) X ....X dom(An)
 R(A1, A2, …, An) is the schema of the relation
 R is the name of the relation
 A1, A2, …, An are the attributes of the relation
 r(R): a specific state (or "value" or “population”) of
relation R – this is a set of tuples (rows)
 r(R) = {t1, t2, …, tn} where each ti is an n-tuple
 ti = <v1, v2, …, vn> where each vj element-of dom(Aj)

Formal Definitions - Example
 Let R(A1, A2) be a relation schema:
 Let dom(A1) = {0,1}
 Let dom(A2) = {a,b,c}
 Then: dom(A1) X dom(A2) is all possible combinations:
{<0,a> , <0,b> , <0,c>, <1,a>, <1,b>, <1,c> }
 The relation state r(R)  dom(A1) X dom(A2)
 For example: r(R) could be {<0,a> , <0,b> , <1,c> }
 this is one possible state (or “population” or “extension”) r of
the relation R, defined over A1 and A2.
 It has three 2-tuples: <0,a> , <0,b> , <1,c>

Definition Summary
Informal Terms Formal Terms
Table Relation
Column Header Attribute
All possible Column
Values
Domain
Row Tuple
Table Definition Schema of a Relation
Populated Table State of the Relation

Example – A relation STUDENT

Characteristics Of Relations
 Ordering of tuples in a relation r(R):
 The tuples are not considered to be ordered, even
though they appear to be in the tabular form.
 Ordering of attributes in a relation schema R (and of
values within each tuple):
 We will consider the attributes in R(A1, A2, ..., An) and
the values in t=<v1, v2, ..., vn> to be ordered .
 (However, a more general alternative definition of relation
does not require this ordering. It includes both the name and
the value for each of the attributes ).
 Example: t= { <name, “John” >, <SSN, 123456789> }
 This representation may be called as “self-describing”.

Same state as previous Figure (but
with different order of tuples)

 Values in a tuple:
 All values are considered atomic (indivisible).
 Each value in a tuple must be from the domain of
the attribute for that column
 If tuple t = <v1, v2, …, vn> is a tuple (row) in the
relation state r of R(A1, A2, …, An)
 Then each vi must be a value from dom(Ai)
 A special null value is used to represent values
that are unknown or not available or inapplicable in
certain tuples.

 Notation:
 We refer to component values of a tuple t by:
 t[Ai] or t.Ai
 This is the value vi of attribute Ai for tuple t
 Similarly, t[Au, Av, ..., Aw] refers to the subtuple of
t containing the values of attributes Au, Av, ..., Aw,
respectively in t

CONSTRAINTS
Constraints determine which values are permissible and
which are not in the database.
They are of three main types:
1. Inherent or Implicit Constraints: These are based on
the data model itself. (E.g., relational model does not allow a
list as a value for any attribute)
2. Schema-based or Explicit Constraints: They are
expressed in the schema by using the facilities provided by
the model. (E.g., max. cardinality ratio constraint in the ER
model)
3. Application based or semantic constraints: These are
beyond the expressive power of the model and must be
specified and enforced by the application programs. Slide 5- 21

Relational Integrity Constraints
 Constraints are conditions that must hold on all valid
relation states.
 There are three main types of (explicit schema-based)
constraints that can be expressed in the relational model:
 Key constraints
 Entity integrity constraints
 Referential integrity constraints
 Another schema-based constraint is the domain
constraint
 Every value in a tuple must be from the domain of its
attribute (or it could be null, if allowed for that attribute)

Key Constraints
 Superkey of R:
 Is a set of attributes SK of R with the following condition:
 No two tuples in any valid relation state r(R) will have the
same value for SK
 That is, for any distinct tuples t1 and t2 in r(R), t1[SK]  t2[SK]
 This condition must hold in any valid state r(R)
 Key of R:
 A "minimal" superkey
 That is, a key is a superkey K such that removal of any
attribute from K results in a set of attributes that is not a
superkey (does not possess the superkey uniqueness
property)
 A Key is a Superkey but not vice versa

Key Constraints (continued)
 Example: Consider the CAR relation schema:
 CAR(State, Reg#, SerialNo, Make, Model, Year)
 CAR has two keys:
 Key1 = {State, Reg#}
 Key2 = {SerialNo}
 Both are also superkeys of CAR
 {SerialNo, Make} is a superkey but not a key.
 In general:
 Any key is a superkey (but not vice versa)
 Any set of attributes that includes a key is a superkey
 A minimal superkey is also a key

Key Constraints (continued)
 If a relation has several candidate keys, one is chosen
arbitrarily to be the primary key.
 The primary key attributes are underlined.
 Example: Consider the CAR relation schema:
 CAR(State, Reg#, SerialNo, Make, Model, Year)
 We chose SerialNo as the primary key
 The primary key value is used to uniquely identify each
tuple in a relation
 Provides the tuple identity
 Also used to reference the tuple from another tuple
 General rule: Choose as primary key the smallest of the
candidate keys (in terms of size)
 Not always applicable – choice is sometimes subjective

CAR table with two candidate keys –
LicenseNumber chosen as Primary Key

Relational Database Schema
 Relational Database Schema:
 A set S of relation schemas that belong to the
same database.
 S is the name of the whole database schema
 S = {R1, R2, ..., Rn} and a set IC of integrity
constraints.
 R1, R2, …, Rn are the names of the individual
relation schemas within the database S
 Following slide shows a COMPANY database
schema with 6 relation schemas

COMPANY Database Schema

Relational Database State
 A relational database state DB of S is a set of
relation states DB = {r1, r2, ..., rm} such that each ri is
a state of Ri and such that the ri relation states satisfy
the integrity constraints specified in IC.
 A relational database state is sometimes called a
relational database snapshot or instance.
 We will not use the term instance since it also applies
to single tuples.
 A database state that does not meet the constraints
is an invalid state
Slide 5- 29

Populated database state
 Each relation will have many tuples in its current relation
state
 The relational database state is a union of all the
individual relation states
 Whenever the database is changed, a new state arises
 Basic operations for changing the database:
 INSERT a new tuple in a relation
 DELETE an existing tuple from a relation
 MODIFY an attribute of an existing tuple
 Next slide (Fig. 5.6) shows an example state for the
COMPANY database schema shown in Fig. 5.5.

Populated database state for COMPANY

Entity Integrity
 Entity Integrity:
 The primary key attributes PK of each relation schema
R in S cannot have null values in any tuple of r(R).
 This is because primary key values are used to identify the
individual tuples.
 t[PK]  null for any tuple t in r(R)
 If PK has several attributes, null is not allowed in any of these
attributes
 Note: Other attributes of R may be constrained to
disallow null values, even though they are not
members of the primary key.

Referential Integrity
 A constraint involving two relations
 The previous constraints involve a single relation.
 Used to specify a relationship among tuples in
two relations:
 The referencing relation and the referenced
relation.

Referential Integrity
 Tuples in the referencing relation R1 have
attributes FK (called foreign key attributes) that
reference the primary key attributes PK of the
referenced relation R2.
 A tuple t1 in R1 is said to reference a tuple t2 in
R2 if t1[FK] = t2[PK].
 A referential integrity constraint can be displayed
in a relational database schema as a directed arc
from R1.FK to R2.

Referential Integrity (or foreign key)
Constraint
 Statement of the constraint
 The value in the foreign key column (or columns)
FK of the the referencing relation R1 can be
either:
 (1) a value of an existing primary key value of a
corresponding primary key PK in the referenced
relation R2, or
 (2) a null.
 In case (2), the FK in R1 should not be a part of
its own primary key.

Displaying a relational database
schema and its constraints
 Each relation schema can be displayed as a row of
attribute names
 The name of the relation is written above the attribute
names
 The primary key attribute (or attributes) will be underlined
 A foreign key (referential integrity) constraints is displayed
as a directed arc (arrow) from the foreign key attributes to
the referenced table
 Can also point the the primary key of the referenced relation
for clarity
 Next slide shows the COMPANY relational schema
diagram with referential integrity constraints

Referential Integrity Constraints for COMPANY database

Other Types of Constraints
 Semantic Integrity Constraints:
 based on application semantics and cannot be
expressed by the model per se
 Example: “the max. no. of hours per employee for all
projects he or she works on is 56 hrs per week”
 A constraint specification language may have to be
used to express these
 SQL-99 allows CREATE TRIGGER and CREATE
ASSERTION to express some of these semantic
constraints
 Keys, Permissibility of Null values, Candidate Keys
(Unique in SQL), Foreign Keys, Referential Integrity etc.
are expressed by the CREATE TABLE statement in SQL.

Update Operations on Relations
 INSERT a tuple.
 DELETE a tuple.
 MODIFY a tuple.
 Integrity constraints should not be violated by the
update operations.
 Several update operations may have to be
grouped together.
 Updates may propagate to cause other updates
automatically. This may be necessary to maintain
integrity constraints.

Update Operations on Relations
 In case of integrity violation, several actions can
be taken:
 Cancel the operation that causes the violation
(RESTRICT or REJECT option)
 Perform the operation but inform the user of the
violation
 Trigger additional updates so the violation is
corrected (CASCADE option, SET NULL option)
 Execute a user-specified error-correction routine

Possible violations for each operation
 INSERT may violate any of the constraints:
 Domain constraint:
 if one of the attribute values provided for the new tuple is not
of the specified attribute domain
 Key constraint:
 if the value of a key attribute in the new tuple already exists in
another tuple in the relation
 Referential integrity:
 if a foreign key value in the new tuple references a primary key
value that does not exist in the referenced relation
 Entity integrity:
 if the primary key value is null in the new tuple

 DELETE may violate only referential integrity:
 If the primary key value of the tuple being deleted is
referenced from other tuples in the database
 Can be remedied by several actions: RESTRICT, CASCADE,
SET NULL (see Chapter 6 for more details)
 RESTRICT option: reject the deletion
 CASCADE option: propagate the new primary key value into the
foreign keys of the referencing tuples
 SET NULL option: set the foreign keys of the referencing tuples
to NULL
 One of the above options must be specified during
database design for each foreign key constraint

 UPDATE may violate domain constraint and NOT NULL
constraint on an attribute being modified
 Any of the other constraints may also be violated,
depending on the attribute being updated:
 Updating the primary key (PK):
 Similar to a DELETE followed by an INSERT
 Need to specify similar options to DELETE
 Updating a foreign key (FK):
 May violate referential integrity
 Updating an ordinary attribute (neither PK nor FK):
 Can only violate domain constraints

Summary
 Presented Relational Model Concepts
 Definitions
 Characteristics of relations
 Discussed Relational Model Constraints and Relational
Database Schemas
 Domain constraints
 Key constraints
 Entity integrity
 Referential integrity
 Described the Relational Update Operations and Dealing
with Constraint Violations

In-Class Exercise
(Taken from Exercise 5.15)
Consider the following relations for a database that keeps track of student
enrollment in courses and the books adopted for each course:
STUDENT(SSN, Name, Major, Bdate)
COURSE(Course#, Cname, Dept)
ENROLL(SSN, Course#, Quarter, Grade)
BOOK_ADOPTION(Course#, Quarter, Book_ISBN)
TEXT(Book_ISBN, Book_Title, Publisher, Author)
Draw a relational schema diagram specifying the foreign keys for this
schema.

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