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The Relational Model
Class 2
Book Chapter 3
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Relational Data Model
Relational Query Language (DDL + DML)
Integrity Constraints (IC)
(From ER to Relational)
 Relational Data Model
 Relational Query Language
 Integrity Constraints
 ER to Relational
Why Study the Relational Model?

Most widely used model in Commercial DBMSs:


“Legacy systems” in older models


Vendors: IBM, Informix, Microsoft, Oracle, Sybase…
E.G., IBM’s IMS
Competitors

Object-oriented model
e.g., O2, but also Oracle, DB2

XML Model
e.g. Natix, but also IBM, Oracle

Key-Value Stores/NonSQL
e.g. BigTable, MongoDB, etc.
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 Relational Data Model
 Relational Query Language
 Integrity Constraints
 ER to Relational
Relational Database: Definitions


Relational database: a set of relations
Relation: made up of 2 parts:

Instance : a table, with rows (tuples) and columns (attributes).
#Rows = cardinality,
#attributes = degree / arity.

Schema : specifies name of relation, plus name and type of each
column.
• E.G.
• Students(sid: string, name: string, login: string,age: integer, gpa: real).

Think of a relation as a set of rows or tuples
i.e., all rows are distinct (not required by commercial database)
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 Relational Data Model
 Relational Query Language
 Integrity Constraints
 ER to Relational
Example Instance of Students Relation
sid
53666
53688
53650
name
login
Jones jones@cs
Smith smith@eecs
Smith smith@math
age
18
18
19
gpa
3.4
3.2
3.8
Cardinality = ?, degree = ?
 Cardinality = 3, degree = 5.
 All rows are distinct
 Do all columns in a relation instance have to
be distinct?

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Attribute Types / Domain
 Relational Data Model
 Relational Query Language
 Integrity Constraints
 ER to Relational

Each column of a relation has a name

Set of allowed values for each column is called domain of column

Domain specifies that values of the column must be drawn from the
domain associated with the column – domain constraint

Column values are (normally) required to be atomic, i.e., indivisible

The special value null is a member of every domain (ignore for now)
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Relations are Unordered
 Relational Data Model
 Relational Query Language
 Integrity Constraints
 ER to Relational
 Order of tuples is irrelevant (tuples may be stored in an arbitrary order)
 E.g., Account relation with unordered tuples
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Database


 Relational Data Model
 Relational Query Language
 Integrity Constraints
 ER to Relational
A database consists of multiple relations
Information about an enterprise is broken up into parts, with
each relation storing one part of the information
E.g.: account : stores information about accounts
depositor : stores information about which customer
owns which account
customer : stores information about customers

Storing all information as a single relation such as
bank(account-number, balance, customer-name, ..)
results in:
 repetition of information (e.g., two customers own an account)
 need for null values (e.g., represent a customer without an account)

Normalization theory (Chapter 7) deals with how to efficiently
design relational schemas.
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 Relational Data Model
 Relational Query Language
 Integrity Constraints
 ER to Relational
Relational Query Languages (SQL)
Developed by IBM (system R) in the 1970s
 Need for a standard since it is used by many
vendors
 Standards:






SQL-86
SQL-89 (minor revision)
SQL-92 (major revision)
SQL-99 (major extensions, current standard)
...
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 Relational Data Model
 Relational Query Language
 Integrity Constraints
 ER to Relational
Relational Query Languages (SQL)

A major strength of the relational model:
supports simple, powerful querying of data.

Queries can be written intuitively, and the
DBMS is responsible for efficient evaluation.



The key: precise semantics for relational queries.
Enables: optimizer re-orders operations, yet
ensures that the answer does not change.
SQL = DDL + DML + …… (Chap 5)
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 Relational Data Model
 Relational Query Language
 Integrity Constraints
 ER to Relational
DDL ---- Creating Relations

Creates Students relation.
Observe that type (domain)
of each field is specified, and
enforced by DBMS whenever
tuples are added or modified.

As another example,
Enrolled table holds
information about courses
that students take.
CREATE TABLE Students
(sid: CHAR(20),
name: CHAR(20),
login: CHAR(10),
age: INTEGER,
gpa: REAL)
CREATE TABLE Enrolled
(sid: CHAR(20),
cid: CHAR(20),
grade: CHAR(2))
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 Relational Data Model
 Relational Query Language
 Integrity Constraints
 ER to Relational
DDL --- Destroying and Altering
Relations
DROP TABLE Students

Destroys the relation Students. The schema
information and the tuples are deleted.
ALTER TABLE Students
ADD COLUMN firstYear: integer

The schema of Students is altered by adding a
new field; every tuple in the current instance
is extended with a null value in the new field.
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DML --- Query single relation

 Relational Data Model
 Relational Query Language
 Integrity Constraints
 ER to Relational
To find all 18 year old students, we can write:
SELECT *
FROM Students S
WHERE S.age=18
sid
name
53666 Jones
login
jones@cs
age gpa
18
3.4
53688 Smith smith@ee 18
3.2
•To find just names and logins, replace the first line:
SELECT S.name, S.login
FROM Students S
WHERE S.age=18
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 Relational Data Model
 Relational Query Language
 Integrity Constraints
 ER to Relational
DML --- Querying Multiple Relations

What does the
following query
compute?
SELECT S.name, E.cid
FROM Students S, Enrolled E
WHERE S.sid=E.sid AND E.grade=“A”
Given the following instances
of Enrolled and Students:
sid
53666
53688
53650
name
login
age gpa
Jones jones@cs
18 3.4
Smith smith@eecs 18 3.2
Smith smith@math 19 3.8
sid
53831
53831
53650
53666
cid
grade
Carnatic101
C
Reggae203
B
Topology112
A
History105
B
we get:
S.name E.cid
Smith
Topology112
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 Relational Data Model
 Relational Query Language
 Integrity Constraints
 ER to Relational
DML --- Adding and Deleting Tuples

Can insert a single tuple using:
INSERT INTO Students (sid, name, login, age, gpa)
VALUES (53688, ‘Smith’, ‘smith@ee’, 18, 3.2)

Can delete all tuples satisfying some
condition (e.g., name = Smith):
DELETE
FROM Students S
WHERE S.name = ‘Smith’
* Powerful variants of these commands are available; more later!
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 Relational Data Model
 Relational Query Language
 Integrity Constraints
 ER to Relational
Integrity Constraints (ICs)

IC: condition that must be true for any instance
of the database
• ICs are specified when schema is defined.
• ICs are checked when relations are modified.

A legal instance of a relation is one that satisfies
all specified ICs.
•
DBMS should not allow illegal instances.
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 Relational Data Model
 Relational Query Language
 Integrity Constraints
 ER to Relational
Integrity Constraints (ICs)
 IC
include:
• Fundamental constraints :
• Key
• Foreign Key,
• Domain Constraints
• General constraints:
• table constraints (single table)
• assertions (several tables)
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Key Constraint

 Relational Data Model
 Relational Query Language
 Integrity Constraints
 ER to Relational
Two rules for Key constraints:
 Two distinct tuples in a legal instance cannot have
identical values in all columns of keys (unique)
 No subset of the set of fields in a key is a unique
identifier for a tuple (maximal)
 Example:
• “No two students can have the same student Id “
• “No two students can have the same student Id and name”
CORE IDEA : Minimal subset of columns of the
relation that uniquely identify the tuple.
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 Relational Data Model
 Relational Query Language
 Integrity Constraints
 ER to Relational
Keys


Let K  R
K is a superkey of R if values for K are sufficient to identify a
unique tuple of relation r(R)
 Example: {customer-name, customer-street} and
{customer-name}
are both superkeys of relation Customer.
NO two customers can possibly have the same name.
 Set of all fields is a super key

K is a candidate key if K is minimal
 Example: {customer-name} is a candidate key for Customer.
- if superkey, and
- no subset of it is a superkey.
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 Relational Data Model
 Relational Query Language
 Integrity Constraints
 ER to Relational
Primary and Candidate Keys in SQL

Possibly many candidate keys (specified using
UNIQUE), one of which is chosen as the primary key.
CREATE TABLE Enrolled
(sid CHAR(20)
cid CHAR(20),
grade CHAR(2),
PRIMARY KEY (sid,cid) )
CREATE TABLE Enrolled
(sid CHAR(20)
cid CHAR(20),
grade CHAR(2),
PRIMARY KEY (sid),
UNIQUE (cid, grade) )
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 Relational Data Model
 Relational Query Language
 Integrity Constraints
 ER to Relational
Primary and Candidate Keys in SQL
“For a given student and course, there
is a single grade.”
vs.
“Students can take only one course,
and receive a single grade for that
course; further, no two students in
a course receive the same grade.”
CREATE TABLE Enrolled
(sid CHAR(20)
cid CHAR(20),
grade CHAR(2),
PRIMARY KEY (sid,cid) )
CREATE TABLE Enrolled
(sid CHAR(20)
cid CHAR(20),
grade CHAR(2),
PRIMARY KEY (sid),
UNIQUE (cid, grade) )
Used carelessly, an IC can prevent the storage
of database instances that arise in practice!
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 Relational Data Model
 Relational Query Language
 Integrity Constraints
 ER to Relational
Foreign Keys, Referential Integrity


Foreign key : Set of fields in one relation that is used to
"refer" to a tuple in another relation. (Like a `logical pointer’.)
Foreign key :
 FK in referencing relation must match PK of referenced relation.
 Match = same number of columns, compatible data types
(column names can be different).
Enrolled (referencing relation)
sid
53666
53666
53650
53666
cid
grade
Carnatic101
C
Reggae203
B
Topology112
A
History105
B
Foreign Key
Students (referenced relation)
sid
53666
53688
53650
name
login
Jones jones@cs
Smith smith@eecs
Smith smith@math
age
18
18
19
gpa
3.4
3.2
3.8
Primary Key
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 Relational Data Model
 Relational Query Language
 Integrity Constraints
 ER to Relational
Foreign Keys in SQL

Only students listed in Students relation
should be allowed to enroll for courses.
CREATE TABLE Enrolled
(sid CHAR(20), cid CHAR(20), grade CHAR(2),
PRIMARY KEY (sid,cid),
FOREIGN KEY (sid) REFERENCES Students )
If all foreign key constraints are enforced, referential integrity is
achieved, i.e., no dangling references.

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 Relational Data Model
 Relational Query Language
 Integrity Constraints
 ER to Relational
Enforcing Referential Integrity

sid in Enrolled is a foreign key that references Students.
Enrolled (referencing relation)
sid
53666
53666
53650
53666
cid
grade
Carnatic101
C
Reggae203
B
Topology112
A
History105
B
Foreign Key


Students (referenced relation)
sid
53666
53688
53650
name
login
Jones jones@cs
Smith smith@eecs
Smith smith@math
age
18
18
19
gpa
3.4
3.2
3.8
Primary Key
Insertion: What if a new Student tuple is inserted?
Insertion: What should be done if an Enrolled tuple with a
non-existent student id is inserted?
 Reject it
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Enforcing Referential Integrity
Enrolled (referencing relation)
sid
53666
53666
53650
53666
cid
grade
Carnatic101
C
Reggae203
B
Topology112
A
History105
B
Foreign Key
 Relational Data Model
 Relational Query Language
 Integrity Constraints
 ER to Relational
Students (referenced relation)
sid
53666
53688
53650
name
login
Jones jones@cs
Smith smith@eecs
Smith smith@math
age
18
18
19
gpa
3.4
3.2
3.8
Primary Key
Deletion: What if an Enrolled tuple is deleted?
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Enforcing Referential Integrity
Enrolled (referencing relation)
sid
53666
53666
53650
53666
cid
grade
Carnatic101
C
Reggae203
B
Topology112
A
History105
B
Foreign Key
 Relational Data Model
 Relational Query Language
 Integrity Constraints
 ER to Relational
Students (referenced relation)
sid
53666
53688
53650
name
login
Jones jones@cs
Smith smith@eecs
Smith smith@math
age
18
18
19
gpa
3.4
3.2
3.8
Primary Key
Deletion: What if a Students tuple is deleted?





Cascading -- Also delete all Enrolled tuples that refer to it.
No Action -- Disallow deletion of a Students tuple that is referred to.
Set Default -- Set sid in Enrolled tuples that refer to it to a default sid.
Set Null -- Set sid in Enrolled tuples that refer to it to a special value
null, denoting `unknown’ or `inapplicable’. (Not always applicable)
Similar if primary key of Students tuple is updated.
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 Relational Data Model
 Relational Query Language
 Integrity Constraints
 ER to Relational
Referential Integrity in SQL

SQL/99 supports 4
options on deletes
and updates:



Default is NO ACTION
(delete/update is rejected)
CASCADE (also delete
all tuples that refer to
deleted tuple)
SET NULL / SET
DEFAULT (sets
foreign key value of
referencing tuple)
CREATE TABLE Enrolled
(sid CHAR(20),
cid CHAR(20),
grade CHAR(2),
PRIMARY KEY (sid,cid),
FOREIGN KEY (sid)
REFERENCES Students (sid)
ON DELETE CASCADE
ON UPDATE SET DEFAULT )
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 Relational Data Model
 Relational Query Language
 Integrity Constraints
 ER to Relational
Where do ICs Come From?

ICs are based upon semantics of real-world
enterprise being described in database relations.

Can we check a database instance to see if an IC is
violated ?
Can we infer that an IC is true by looking at a
database instance ?




An IC is a statement about all possible instances!
From example, we know name is not a key, but the assertion
that sid is a key is given to us by domain knowledge !
Key and foreign key ICs are the most common;
but more general ICs supported in some systems.
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 Relational Data Model
 Relational Query Language
 Integrity Constraints
 ER to Relational
Views – Useful For Design

A view is just a relation, but we store a
definition, rather than a set of tuples.
CREATE VIEW YoungActiveStudents (name, sid, course)
AS
SELECT S.name, S.sid, E.cid
FROM Students S, Enrolled E
WHERE S.sid = E.sid

Views can be dropped using DROP VIEW command.

How to handle DROP TABLE if there’s a view on the table?
•
DROP TABLE { RESTRICT | CASCADE }
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 Relational Data Model
 Relational Query Language
 Integrity Constraints
 ER to Relational
Views and Security

Views can be used to present necessary
information (or provide a summary), while
hiding details in underlying relation(s).

For example: Given YoungStudents view only (not
Students or Enrolled table), the user can find
students who have enrolled, but not the grades of
the courses they got.
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 Relational Data Model
 Relational Query Language
 Integrity Constraints
 ER to Relational
Relational Model Terminology
Schema / Data Model
 Relation /Relation Schema
 Instance / Database
 Schema Definition Language

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 Relational Data Model
 Relational Query Language
 Integrity Constraints
 ER to Relational
Relational Model: Summary
Tabular representation of data.
 Simple and intuitive, yet widely used.
 Integrity constraints can be specified by the
DBA, based on application semantics.
 DBMS checks for violations.




Two important ICs: primary and foreign keys
In addition, we always have domain constraints.
Powerful, ‘natural’ query language exist.
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