Slide 8- 1
Chapter 8
SQL: SchemaDefinition,
Constraints, and Queries and Views
History of SQL

SQL: Structured Query Language

In 1974, D. Chamberlin (IBM San Jose
Laboratory) defined language called ‘Structured
English Query Language’ (SEQUEL).

A revised version, SEQUEL/2, was defined in
1976 but name was subsequently changed to
SQL for legal reasons.
Slide 8- 3
History of SQL


Still pronounced ‘see-quel’,
pronunciation is ‘S-Q-L’.
though
official
IBM subsequently produced a prototype DBMS
called System R, based on SEQUEL/2.
Slide 8- 4
History of SQL






In late 70s, ORACLE appeared and was probably
first commercial RDBMS based on SQL.
In 1987, ANSI and ISO published an initial
standard for SQL.
In 1989, ISO published an addendum that defined
an ‘Integrity Enhancement Feature’.
In 1992, first major revision to ISO standard
occurred, referred to as SQL2 or SQL/92.
In 1999, SQL:1999 was released with support for
object-oriented data management.
In late 2003, SQL:2003 was released.
Slide 8- 5
DBMS Languages


Data Definition Language (DDL)
Data Manipulation Language (DML)

High-Level or Non-procedural Languages: These
include the relational language SQL



May be used in a standalone
or may be embedded in a programming language
Low Level or Procedural Languages:

These must be embedded in a programming
language
Slide 2- 6
DBMS Languages

Data Definition Language (DDL):



Used by the DBA and database designers to
specify the conceptual schema of a database.
In many DBMSs, the DDL is also used to define
internal and external schemas (views).
In some DBMSs, separate storage definition
language (SDL) and view definition language
(VDL) are used to define internal and external
schemas.

SDL is typically realized via DBMS commands
provided to the DBA and database designers
Slide 2- 7
DBMS Languages

Data Manipulation Language (DML):


Used to specify database retrievals and updates
DML commands can be embedded in a generalpurpose programming language (host language),
such as C++, or Java.


A library of functions can also be provided to access
the DBMS from a programming language
Alternatively, stand-alone DML commands can be
applied directly (called a query language).
Slide 2- 8
Types of DML

High Level or Non-procedural Language:




For example, the SQL relational language
Are “set”-oriented and specify what data to retrieve
rather than how to retrieve it.
Also called declarative languages.
Low Level or Procedural Language:


Retrieve data one record-at-a-time;
Constructs such as looping are needed to retrieve
multiple records, along with positioning pointers.
Slide 2- 9
Objectives of SQL



Ideally, database language should allow user to:
 create the database and relation structures;
 perform insertion, modification, deletion of data from
relations;
 perform simple and complex queries.
It must be portable.
SQL is relatively easy to learn:
it is non-procedural - you specify what information you
require, rather than how to get it
Can be used by range of users including DBAs,
management, application developers, and other types of
end users.


Slide 8- 10
Objectives of SQL

Consists of standard English words:
1) CREATE TABLE Staff(
staffNo VARCHAR(5),
lName VARCHAR(15),
salary INTEGER);
2) INSERT INTO Staff VALUES (‘SG16’, ‘Brown’,
8300);
3) SELECT staffNo, lName, salary
FROM Staff
WHERE salary > 10000;
Slide 8- 11
Writing SQL Commands

SQL statement consists of reserved words and
user-defined words.

Most components of an SQL statement are case
insensitive, except for literal character data.
Slide 8- 12
Writing SQL Commands
- Upper-case letters represent reserved words.
- Lower-case letters represent user-defined words.
- | indicates a choice among alternatives.
- Curly braces indicate a required element.
- Square brackets indicate an optional element.
- … indicates optional repetition (0 or more).
Slide 8- 13
Literals

Literals are constants used in SQL statements.

All non-numeric literals must be enclosed in
single quotes (e.g. ‘London’).

All numeric literals must not be enclosed in
quotes (e.g. 650.00).
Slide 8- 14
Attribute Data Types in SQL

Basic data types

Numeric data types
•
•

Integer numbers: INTEGER and SMALLINT
Floating-point (real) numbers: FLOAT or REAL, and
DOUBLE PRECISION
Character-string data types
•
•
Fixed length: CHAR(n)
Varying length: VARCHAR(n)
Attribute Data Types in SQL (cont’d.)

Bit-string data types
•
•

Boolean data type
•

Fixed length: BIT(n)
Varying length: BIT VARYING(n)
Values of TRUE or FALSE or NULL
DATE data type
•
•
Ten positions
Components are YEAR, MONTH, and DAY in the
form YYYY-MM-DD
Attribute Data Types in SQL (cont’d.)

Additional data types

TIME:


TIME(i):



Made up of hour:minute:second in the format hh:mm:ss
Made up of hour:minute:second plus i additional digits
specifying fractions of a second
format is hh:mm:ss:ii...i
Timestamp data type (TIMESTAMP)
•
•
•
Includes the DATE and TIME fields
Plus a minimum of six positions for decimal
fractions of seconds
Optional WITH TIME ZONE qualifier
Attribute Data Types in SQL (cont’d.)

Additional data types

INTERVAL data type
•
•
Specifies a relative value that can be used to
increment or decrement an absolute value of a date,
time, or timestamp
Can be DAY/TIME intervals or YEAR/MONTH
intervals
Data Definition, Constraints, and
Schema Changes

Used to CREATE, DROP, and ALTER the
descriptions of the tables (relations) of a
database
Slide 8- 19
CREATE TABLE



Specifies TABLE
CREATE
a new base
command
relation
can
bybe
giving
usedit for
a name,
specifying
and the
primary keyeach
specifying
attributes,
of its attributes
secondary
and
key,
their
and
data
referential
types
integrity constraints
(INTEGER,
FLOAT, (foreign
DECIMAL(i,j),
keys). CHAR(n),
VARCHAR(n))
Key attributes can be specified via the PRIMARY KEY
and
A
constraint
UNIQUENOT
phrases
NULL may be specified on an attribute
CREATE TABLE DEPT (
DNAME
VARCHAR(10)
NOT NULL,
DNUMBER
INTEGER
NOT NULL,
MGRSSN
CHAR(9),
MGRSTARTDATE
CHAR(9),
PRIMARY KEY (DNUMBER),
UNIQUE (DNAME),
FOREIGN KEY (MGRSSN) REFERENCES EMP );
Slide 8- 20
Specifying Constraints in SQL

Basic constraints:



Key and referential integrity constraints
Restrictions on attribute domains and NULLs
Constraints on individual tuples within a relation
Specifying Attribute Constraints and
Attribute Defaults

NOT NULL


Default value


NULL is not permitted for a particular attribute
DEFAULT <value>
CHECK clause

Dnumber INT NOT NULL CHECK (Dnumber >
0 AND Dnumber < 21);
Specifying Key and Referential
Integrity Constraints

PRIMARY KEY clause



Specifies one or more attributes that make up the
primary key of a relation
Dnumber INT PRIMARY KEY;
UNIQUE clause


Specifies alternate (secondary) keys
Dname VARCHAR(15) UNIQUE;
Specifying Key and Referential
Integrity Constraints (cont’d.)

FOREIGN KEY clause


Default operation: reject update on violation
Attach referential triggered action clause
•
•
Options include RESTRICT, SET NULL, CASCADE,
and SET DEFAULT
CASCADE option suitable for “relationship” relations
REFERENTIAL INTEGRITY
OPTIONS
CREATE TABLE DEPT (
DNAME
VARCHAR(10)
NOT NULL,
DNUMBER
INTEGER
NOT NULL,
MGRSSN
CHAR(9) DEFAULT ‘NO’,
MGRSTARTDATE CHAR(9),
PRIMARY KEY (DNUMBER),
UNIQUE (DNAME),
FOREIGN KEY (MGRSSN) REFERENCES EMP
ON DELETE SET DEFAULT ON UPDATE
CASCADE);
Slide 8- 26
REFERENTIAL INTEGRITY
OPTIONS (continued)
CREATE TABLE EMP(
ENAME
VARCHAR(30)
NOT NULL,
ESSN
CHAR(9),
BDATE
DATE,
DNO
INTEGER DEFAULT 1,
SUPERSSN CHAR(9),
PRIMARY KEY (ESSN),
FOREIGN KEY (DNO) REFERENCES DEPT
ON DELETE SET DEFAULT ON UPDATE
CASCADE,
FOREIGN KEY (SUPERSSN) REFERENCES EMP
ON DELETE SET NULL ON UPDATE CASCADE);
Slide 8- 27
Giving Names to Constraints

Keyword CONSTRAINT


Name a constraint
Useful for later altering
Specifying Constraints on Tuples
Using CHECK

CHECK clauses at the end of a CREATE TABLE
statement


Apply to each tuple individually
CHECK (Dept_create_date <=
Mgr_start_date);
The DROP Command

DROP command


Drop behavior options:


Used to remove named schema elements, such as
tables, domains, or constraint
CASCADE and RESTRICT
Examples:
DROP TABLE DEPENDENT;
DROP SCHEMA COMPANY CASCADE;
Slide 8- 30
The ALTER Command

Alter table actions include:

Adding or dropping a column (attribute)





The new attribute will have NULLs in all the tuples of
the relation right after the command is executed
the NOT NULL constraint is not allowed for such an
attribute
Changing a column definition
Adding or dropping table constraints
Examples:


ALTER TABLE COMPANY.EMPLOYEE ADD
COLUMN Job VARCHAR(12);
Or: ALTER TABLE EMPLOYEE ADD JOB
VARCHAR(12);
The ALTER Command (cont’d.)

The database users must still enter a value for
the new attribute JOB for each EMPLOYEE tuple.


To drop a column


This can be done using the UPDATE command.
Choose either CASCADE or RESTRICT
Change constraints specified on a table

Add or drop a named constraint
ALTER TABLE Examples

ALTER TABLE EMPLOYEE ADD JOB
VARCHAR(12);

ALTER TABLE EMPLOYEE DROP ADDRESS
CASCADE;

ALTER TABLE DEPARTMENT ALTER MGRSSN
DROP DEFAULT;

ALTER TABLE DEPARTMENT ALTER MGRSSN
SET DEFAULT "333445555";
Slide 8- 33
Retrieval Queries in SQL

SQL has one basic statement for retrieving information
from a database; the SELECT statement


Important distinction between SQL and the formal
relational model:


This is not the same as the SELECT operation of the
relational algebra
SQL allows a table (relation) to have two or more tuples that
are identical in all their attribute values
SQL relations can be constrained to be sets by specifying
PRIMARY KEY or UNIQUE attributes, or by using the
DISTINCT option in a query
Slide 8- 34
Retrieval Queries in SQL (contd.)

Basic form of the SQL SELECT statement is called a
mapping or a SELECT-FROM-WHERE block
SELECT
FROM
WHERE



<attribute list>
<table list>
<condition>
<attribute list> is a list of attribute names whose values are
to be retrieved by the query
<table list> is a list of the relation names required to process
the query
<condition> is a conditional (Boolean) expression that
identifies the tuples to be retrieved by the query

Logical comparison operators:
=, <, <=, >, >=, and <>
Slide 8- 35
Relational Database Schema--Figure 5.5
Slide 8- 36
Populated Database--Fig.5.6
Slide 8- 37
Simple SQL Queries

Basic SQL queries correspond to using the
following operations of the relational algebra:




SELECT
PROJECT
JOIN
All subsequent examples use the COMPANY
database
Slide 8- 38
Simple SQL Queries (contd.)


Example of a simple query on one relation
Query 0: Retrieve the birthdate and address of
the employee whose name is 'John B. Smith'.
Q0:SELECT
FROM
WHERE


BDATE, ADDRESS
EMPLOYEE
FNAME='John' AND MINIT='B’ AND
LNAME='Smith’
Similar to a SELECT-PROJECT pair of relational
algebra operations:
 The SELECT-clause specifies the projection
attributes and the WHERE-clause specifies the
selection condition
However, the result of the query may contain duplicate
tuples
Slide 8- 40
Simple SQL Queries (contd.)

Query 1: Retrieve the name and address of all employees
who work for the 'Research' department.
Q1:SELECT
FROM
WHERE



FNAME, LNAME, ADDRESS
EMPLOYEE, DEPARTMENT
DNAME='Research' AND DNUMBER=DNO
Similar to a SELECT-PROJECT-JOIN sequence of
relational algebra operations
(DNAME='Research') is a selection condition (corresponds
to a SELECT operation in relational algebra)
(DNUMBER=DNO) is a join condition (corresponds to a
JOIN operation in relational algebra)
Slide 8- 41
Simple SQL Queries (contd.)

Query 2: For every project located in 'Stafford', list the project number,
the controlling department number, and the department manager's last
name, address, and birthdate.
Q2:
SELECT
FROM
WHERE



PNUMBER, DNUM, LNAME, BDATE, ADDRESS
PROJECT, DEPARTMENT, EMPLOYEE
DNUM=DNUMBER AND MGRSSN=SSN AND
PLOCATION='Stafford'
In Q2, there are two join conditions
The join condition DNUM=DNUMBER relates a project to its
controlling department
The join condition MGRSSN=SSN relates the controlling department
to the employee who manages that department
Slide 8- 43
Ambiguous Attribute Names

In SQL, we can use the same name for two (or more)
attributes as long as the attributes are in different relations

A query that refers to two or more attributes with the same
name must qualify the attribute name with the relation
name by prefixing the relation name to the attribute name

Example:
EMPLOYEE.LNAME, DEPARTMENT.DNAME
Slide 8- 44
ALIASES

Declare alternative relation names

Some queries need to refer to the same relation twice
 In this case, aliases are given to the relation name
Query 8: For each employee, retrieve the employee's name, and
the name of his or her immediate supervisor.

Q8: SELECT
FROM
WHERE


E.FNAME, E.LNAME, S.FNAME, S.LNAME
EMPLOYEE E S
E.SUPERSSN=S.SSN
In Q8, the alternate relation names E and S are called aliases
or tuple variables for the EMPLOYEE relation
We can think of E and S as two different copies of
EMPLOYEE; E represents employees in role of supervisees
and S represents employees in role of supervisors
Slide 8- 45
ALIASES (contd.)


Aliasing can also be used in any SQL query for
convenience
Can also use the AS keyword to specify aliases
Q8:
SELECT
FROM
WHERE

E.FNAME, E.LNAME,
S.FNAME, S.LNAME
EMPLOYEE AS E,
EMPLOYEE AS S
E.SUPERSSN=S.SSN
Renaming of Attributes

Rename any attribute that appears in the result of a query
Slide 8- 46
UNSPECIFIED
WHERE-clause

A missing WHERE-clause indicates no condition;



Query 9: Retrieve the SSN values for all employees.


All tuples of the relations in the FROM-clause are selected
This is equivalent to the condition WHERE TRUE
Q9:
SELECT
FROM
SSN
EMPLOYEE
If more than one relation is specified in the FROM-clause
and there is no join condition, then the CARTESIAN
PRODUCT of tuples is selected
Slide 8- 47
UNSPECIFIED
WHERE-clause (contd.)

Example:
Q10:

SELECT
FROM
SSN, DNAME
EMPLOYEE, DEPARTMENT
It is extremely important not to overlook specifying
any selection and join conditions in the WHEREclause; otherwise, incorrect and very large
relations may result
Slide 8- 48
USE OF ASTERISK *

To retrieve all the attribute values of the selected tuples, a
* is used, which stands for all the attributes
Examples:
Q1C:
SELECT
FROM
WHERE
*
EMPLOYEE
DNO=5
Q1D:
SELECT
FROM
WHERE
*
EMPLOYEE, DEPARTMENT
DNAME='Research' AND
DNO=DNUMBER
Slide 8- 49
USE OF DISTINCT



SQL does not treat a relation as a set; duplicate tuples
can appear
To eliminate duplicate tuples in a query result, the
keyword DISTINCT is used
For example, the result of Q11 may have duplicate
SALARY values whereas Q11A does not have any
duplicate values
Q11:
Q11A:
SELECT
FROM
SELECT
FROM
SALARY
EMPLOYEE
DISTINCT SALARY
EMPLOYEE
Slide 8- 50
SET OPERATIONS

SQL has directly incorporated some set operations

There is a union operation (UNION), set difference
(EXCEPT) and intersection (INTERSECT) operations

The resulting relations of these set operations are sets of
tuples; duplicate tuples are eliminated from the result

The set operations apply only to union compatible
relations; the two relations must have

the same attributes and the attributes must appear in the
same order
Slide 8- 51
SET OPERATIONS (contd.)

Query 4: Make a list of all project numbers for projects that involve an
employee whose last name is 'Smith' as a worker or as a manager of
the department that controls the project.

Q4:
(SELECT
FROM
WHERE
UNION
(SELECT
FROM
WHERE
DISTINCT PNUMBER
PROJECT, DEPARTMENT,
EMPLOYEE
DNUM=DNUMBER AND
MGRSSN=SSN AND LNAME='Smith')
DISTINCT PNUMBER
PROJECT, WORKS_ON, EMPLOYEE
PNUMBER=PNO AND
ESSN=SSN AND LNAME='Smith')
Slide 8- 52
NESTING OF QUERIES

A complete SELECT query, called a nested query, can be
specified within the WHERE-clause of another query,
called the outer query


Many of the previous queries can be specified in an
alternative form using nesting
Query 1: Retrieve the name and address of all employees
who work for the 'Research' department.
Q1:SELECT
FROM
WHERE
FROM
WHERE
FNAME, LNAME, ADDRESS
EMPLOYEE
DNO IN (SELECT DNUMBER
DEPARTMENT
DNAME='Research' )
Slide 8- 53
NESTING OF QUERIES (contd.)



The nested query selects the number of the
'Research' department
The outer query select an EMPLOYEE tuple if its
DNO value is in the result of either nested query
The comparison operator IN



compares a value v with a set (or multi-set) of
values V
evaluates to TRUE if v is one of the elements in V
In general, we can have several levels of nested
queries
Slide 8- 54
Nested Queries
Nested Queries (cont’d.)

Use tuples of values in comparisons

Place them within parentheses

Other comparison operators
THE EXISTS FUNCTION AND
CORRELATED NESTED QUERIES

Query 6: Retrieve the names of employees who have no
dependents.
Q6:
SELECT
FROM
WHERE
FNAME, LNAME
EMPLOYEE E
NOT EXISTS (SELECT
*
FROM
DEPENDENT
WHERE
E.SSN=ESSN)

If a condition in the WHERE-clause of a nested query references
an attribute of a relation declared in the outer query, the two
queries are said to be correlated

In Q6, the correlated nested query retrieves all DEPENDENT
tuples related to an EMPLOYEE tuple. If none exist, the
EMPLOYEE tuple is selected
Slide 8- 61
EXPLICIT SETS

It is also possible to use an explicit
(enumerated) set of values in the WHEREclause rather than a nested query

Query 13: Retrieve the social security numbers of
all employees who work on project number 1, 2,
or 3.
Q13:
SELECT
FROM
WHERE
DISTINCT ESSN
WORKS_ON
PNO IN (1, 2, 3)
Slide 8- 62
NULLS IN SQL QUERIES

SQL allows queries that check if a value is NULL
(missing or undefined or not applicable)

SQL uses IS or IS NOT to compare NULLs.

Query 14: Retrieve the names of all employees
who do not have supervisors.
Q14:
SELECT
FROM
WHERE
FNAME, LNAME
EMPLOYEE
SUPERSSN IS NULL
Slide 8- 63
Joined Relations Feature

Can specify a "joined relation" in the FROMclause


Looks like any other relation but is the result of a
join
Allows the user to specify different types of joins
(regular "theta" JOIN, NATURAL JOIN, LEFT
OUTER JOIN, RIGHT OUTER JOIN, etc)
Slide 8- 64
Joined Relations Feature

Examples:
Q1:SELECT FNAME, LNAME, ADDRESS
FROM
EMPLOYEE, DEPARTMENT
WHERE
DNAME='Research' AND
DNUMBER=DNO

could be written as:
Q1:SELECT
FROM
WHERE
FNAME, LNAME, ADDRESS
(EMPLOYEE JOIN DEPARTMENT
ON DNUMBER=DNO)
DNAME='Research’
Slide 8- 65
Joined Relations Feature (contd.)

Another Example: Q2 could be written as follows;
this illustrates multiple joins in the joined tables
Q2:
SELECT
FROM
WHERE
PNUMBER, DNUM, LNAME,
BDATE, ADDRESS
((PROJECT JOIN
DEPARTMENT ON
DNUM=DNUMBER) JOIN
EMPLOYEE ON
MGRSSN=SSN)
PLOCATION='Stafford’
Slide 8- 66
AGGREGATE FUNCTIONS

Include COUNT, SUM, MAX, MIN, and AVG




Used to summarize information from multiple tuples into a singletuple summary
Functions can be used in the SELECT clause or in a HAVING
clause
NULL values are discarded when aggregate functions are applied
to a particular column
Query 15: Find the maximum salary, the minimum salary,
and the average salary among all employees.
Q15:
SELECT
MAX(SALARY),
MIN(SALARY), AVG(SALARY)
FROMEMPLOYEE
Slide 8- 67
AGGREGATE FUNCTIONS (contd.)

Query 16: Find the maximum salary, the
minimum salary, and the average salary among
employees who work for the 'Research'
department.
Q16:
SELECT
FROM
WHERE
MAX(SALARY),
MIN(SALARY), AVG(SALARY)
EMPLOYEE, DEPARTMENT
DNO=DNUMBER AND
DNAME='Research'
Slide 8- 68
AGGREGATE FUNCTIONS (contd.)

Queries 17 and 18: Retrieve the total number of
employees in the company (Q17), and the number of
employees in the 'Research' department (Q18).
Q17:
SELECT
FROM
COUNT (*)
EMPLOYEE
Q18:
SELECT
FROM
WHERE
COUNT (*)
EMPLOYEE, DEPARTMENT
DNO=DNUMBER AND
DNAME='Research’
Slide 8- 69
GROUPING

In many cases, we want to apply the aggregate functions
to subgroups of tuples in a relation

Partition relation into subsets of tuples



Create subgroups of tuples before summarizing
Each subgroup of tuples consists of the set of tuples that have the
same value for the grouping attribute(s)
The function is applied to each subgroup independently

SQL has a GROUP BY-clause for specifying the grouping
attributes, which must also appear in the SELECTclause

If NULLs exist in grouping attribute

Separate group is created for all tuples with a NULL value in
grouping attribute
Slide 8- 70
GROUPING (contd.)

Query 20: For each department, retrieve the department
number, the number of employees in the department, and
their average salary.
Q20:


DNO, COUNT (*), AVG (SALARY)
EMPLOYEE
DNO
In Q20, the EMPLOYEE tuples are divided into groups

SELECT
FROM
GROUP BY
Each group having the same value for the grouping attribute
DNO
The COUNT and AVG functions are applied to each such
group of tuples separately
The SELECT-clause includes only the grouping attribute
and the functions to be applied on each group of tuples
Slide 8- 71
GROUPING (contd.)

Query 21: For each project, retrieve the project number,
project name, and the number of employees who work on
that project.
Q21:

SELECT
FROM
WHERE
GROUP BY
PNUMBER, PNAME, COUNT (*)
PROJECT, WORKS_ON
PNUMBER=PNO
PNUMBER
In this case, the grouping and functions are applied after
the joining of the two relations
Slide 8- 72