Chapter_8_SQL.pdf

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Course Name: Database Management System
Course Code: CT – 2212
Chapter Eight
SQL (Structured query language)
Denekew Tadele (Maj.)
Tel: +251913793506
Email: denekew.tad@gmail.com

Contents
 The SQL Query Language
 Data Definition
 Basic Query Structure
 Additional Basic Operations
 Set Operations
 Aggregate Functions
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• Structured Query Language (SQL) is the
standard language for accessing information a
database.
• Terminology:
• Syntax notes:
 Some interfaces require each statement
to end with a semicolon.
 SQL is not case-sensitive
Structured Query Language
Relational Model SQL
relation table
tuple row
attribute column

SQL Environment
• Data Definition Language (DDL)
- Commands that define a database, including creating,
altering, and dropping tables and establishing constraints
- CREATE / DROP / ALTER, …
• Data Manipulation Language (DML)
- Commands that maintain and query a database
- INSERT, UPDATE, DELETE, SELECT, …
• Data Control Language (DCL)
- Commands that control a database, including administering
privileges and committing data
- GRANT, ADD, REVOKE
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SQL Data Definition
• Data Definition Language (DDL)
• Major CREATE statements:
- CREATE TABLE–defines a new table and its columns
- CREATE VIEW–defines a logical table from one or more tables or views
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Steps in table creation:
1. Identify data types for attributes
2. Identify columns that can and
cannot be null
3. Identify columns that must be
unique (candidate keys)
4. Identify primary key
5. Determine default values
6. Identify constraints on columns
(domain specifications)
7. Identify foreign keys
General syntax for CREATE
TABLE
used in data definition language
CREATE TABLE table_name (
field type constraints,
field2 type2,
CONSTRAINT name ...,
...
);
CREATE TABLE Book (
ISBN CHAR(9) NOT NULL,
Title VARCHAR(20) UNIQUE,
Pages INTEGER,
CONSTRAINT ISBN PRIMARY KEY
);

SQL Data Types
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TABLE 1 Sample SQL Data Types

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Basic Data Types
 Numeric data types
• Integer numbers: INT, INTEGER, SMALLINT, BIGINT
• Floating-point (real) numbers: REAL, DOUBLE , FLOAT
• Fixed-point numbers: DECIMAL(n,m), DEC(n,m),
NUMERIC(n,m), NUM(n,m)
• Character-string data types
• Fixed length: CHAR(n), CHARACTER(n)
• Varying length: VARCHAR(n), CHAR VARYING(n), CHARACTER
VARYING(n), LONG VARCHAR
 Large object data types
• Characters: CLOB, CHAR LARGE OBJECT , CHARACTER LARGE
OBJECT
• Bits: BLOB, BINARY LARGE OBJECT
 Boolean data type
• Values of TRUE or FALSE or NULL
 DATE data type
• T
en positions
• Components are YEAR, MONTH, and DAY in the form YYYY-MM-DD

More DataTypes
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 Additional data types
• TIMESTAMPdata type
• Includes the DATE and TIMEfields
• Plus a minimum of six positions for decimal fractions of seconds
• Optional WITH TIME ZONEqualifier
• INTERVAL data type
• Specifies a relative value that can be used to increment or decrement an
absolute value of a date, time, or timestamp
 Columns can be declared to be NOT NULL
 Columns can be declared to have a default value
• Assigned to column in any tuple for which a value is not specified
 Example
CREATE TABLE EMPLOYEE (
…
NICKNAME VARCHAR(20) DEFAULT NULL,
…
Province CHAR(2) NOT NULL DEFAULT 'ON',
…
);

More DataTypes
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 Additional data types
• TIMESTAMPdata type
• Includes the DATE and TIME fields
• Plus a minimum of six positions for decimal fractions of seconds
• Optional WITH TIME ZONEqualifier
• INTERVAL data type
• Specifies a relative value that can be used to increment or decrement
an absolute value of a date, time, or timestamp
 Columns can be declared to be NOT NULL
 Columns can be declared to have a default value
• Assigned to column in any tuple for which a value is not specified
 Example
CREATE TABLE EMPLOYEE (
…
NICKNAME VARCHAR(20) DEFAULT NULL,
…
Province CHAR(2) NOT NULL DEFAULT 'ON',
…
);

Specifying Key Constraints
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 PRIMARY KEY clause
• Specifies one or more attributes that make up the primary key of a
relation
Dnumber INT NOT NULL PRIMARY KEY,
• Primary key attributes must be declared NOT NULL
 UNIQUE clause
• Specifies alternate (candidate) keys
Dname VARCHAR(15) UNIQUE;
• May or may not allow null values, depending on declaration
 If no key constraints, two or more tuples may be identical
in all
columns.
• SQL deviates from pure relational model!
• Multiset (bag) behaviour

Referential Constraints
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 FOREIGNKEYclause
FOREIGN KEY (Dept) REFERENCES DEPARTMENT
(Dnum),
• Default operation: reject update on violation
• Attach referential triggered action clause in case referenced
tuple is deleted
• Options include SET NULL, CASCADE, and SET
DEFAULT
 Foreign key declaration must refer to a table already created

Specifying Tuple Constraints
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 Some constraints involve several columns
 CHECK clause at the end of a CREATE
TABLEstatement
•Apply to each tuple individually
 Example
•CHECK (Dept_create_date <= Mgr_start_date)

Example
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 Recall Employee example:
Figure 2
Referential integrity constraints
displayed on the COMPANY
database schema

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Figure 3
Example illustrating how
default attribute values
and referential integrity
triggered actions are
specified in SQL

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Figure 1
SQL CREATE TABLE data
definition statements
defining the COMPANY
schema from Figure 2

Basic Sql RetrievalQueries
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 All retrievals use SELECTstatement:
SELECT
FROM
[ WHERE
where
<return list>
<table list>
<condition> ] ;
<return list>is a list of expressions or column names whose values are
to be retrieved by the query
<table list> is a list of relation names required to process the
query
<condition> is a Boolean expression that identifies the tuples to
be retrieved by the query
 Example
SELECT title, year, genre FROM
Film
WHERE director = 'Steven Spielberg' AND year > 1990;
 Omitting WHERE clause implies all tuples selected.

Semantics For 1 Relation
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1. Start with the relation named in the FROM clause
2. Consider each tuple one after the other, eliminating those that do
not satisfy the WHERE clause.
• Boolean condition that must be true for any retrieved tuple
• Logical comparison operators
=, <, <=, >, >=, and <>
3. For each remaining tuple, create a return tuple with columns for
each expression (column name) in the SELECT clause.
• Use SELECT * to select all columns.
Film
title genre year director minutes budget gross
The Company Men drama 2010 John Wells 104 15,000,000 4,439,063
Lincoln biography 2012 Steven Spielberg 150 65,000,000 181,408,467
War Horse drama 2011 Steven Spielberg 146 66,000,000 79,883,359
Argo drama 2012 Ben Affleck 120 44,500,000 135,178,251

Select-from-where Semantics
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 What if there are several relations in the FROM clause?
1. Start with cross-product of all relation(s) listed in the FROM clause.
• Every tuple in R1 paired up with every tuple in R2 paired up with…
2. Consider each tuple one after the other, eliminating those that do
not satisfy the WHERE clause.
3. For each remaining tuple, create a return tuple with columns for
each expression (column name) in the SELECT clause.
Steps 2 and 3 are just the same as before.
SELECT actor, birth, movie
FROM Role, Person
WHERE actor = name and birth > 1940;
Role
actor movie persona
BenAffleck Argo Tony Mendez
AlanArkin Argo Lester Siegel
BenAffleck The Company Men Bobby Walker
Tommy Lee Jones The Company Men Gene McClary
Person
name birth city
BenAffleck 1972 Berkeley
AlanArkin 1934 New York
Tommy Lee Jones 1946 San Saba

Ambiguous ColumnNames
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 Same name may be used for two (or more) columns (in
different relations)
• Must qualify the column name with the relation name to
prevent ambiguity
SELECT name, date, product,
quantity FROM Customer, Sale,
LineItem
WHERE price > 100 AND Customer.custid =
Sale.custid AND
Sale.saleid = LineItem.saleid;
 Note
• If SELECT clause includes custid, it must specify whether
to use Customer.custid or Sale.custid even though the
values are guaranteed to be identical.
Customer
custid name address phone
Sale
saleid date custid
LineItem
saleid product quantity price

2-relation Select-from-where
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Honours.movie award category winner actor Role.movie persona
Lincoln Critic's Choice actor Daniel Day-Lewis Ben Affleck Argo Tony Mendez 
Lincoln Critic's Choice actor Daniel Day-Lewis Tommy Lee Jones Lincoln Thaddeus Stevens 
Lincoln Critic's Choice actor Daniel Day-Lewis Daniel Day-Lewis The Boxer Danny Flynn 
Lincoln Critic's Choice actor Daniel Day-Lewis Daniel Day-Lewis Lincoln Abraham Lincoln 
Argo Critic's Choice director Ben Affleck Ben Affleck Argo Tony Mendez 
Argo Critic's Choice director Ben Affleck Tommy Lee Jones Lincoln Thaddeus Stevens 
Argo Critic's Choice director Ben Affleck Daniel Day-Lewis The Boxer Danny Flynn 
Argo Critic's Choice director Ben Affleck Daniel Day-Lewis Lincoln Abraham Lincoln 
Lincoln SAG supporting actor Tommy Lee Jones Ben Affleck Argo Tony Mendez 
Lincoln SAG supporting actor Tommy Lee Jones Tommy Lee Jones Lincoln Thaddeus Stevens 
Lincoln SAG supporting actor Tommy Lee Jones Daniel Day-Lewis The Boxer Danny Flynn 
…
Role
actor movie persona
Ben Affleck Argo Tony Mendez
Tommy Lee Jones Lincoln Thaddeus Stevens
Daniel Day-Lewis The Boxer Danny Flynn
Daniel Day-Lewis Lincoln Abraham Lincoln
SELECT award, actor, persona, Role.movie
FROM Honours, Role
WHERE category = 'actor' AND winner = actor
AND Honours.movie = Role.movie
Honours
movie award category winner
Lincoln Critic's Choice actor Daniel Day-Lewis
Argo Critic's Choice director Ben Affleck
Lincoln SAG supporting actor Tommy Lee Jones
Lincoln Critic's Choice screenplay Tony Kushner
War Horse BMI Flim music John Williams

Recall SampleTables
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Figure 4
One possible database state for the COMPANY relational schema

Set-Difference Example (2)
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Figure 4
One possible database state for the COMPANY relational schema

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Figure 5
In Figure 4 (a) Q0. (b) Q1. (c) Q2. (d) Q8. e Q9. (f) Q10. (g) Q1C.

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In Figure 4 (a) Q0. (b) Q1. (c) Q2. (d) Q8. e Q9. (f) Q10. (g) Q1C.
Figure 5

TablesAs Sets InSql
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 Duplicate tuples may appear in query results
•From duplicates in base tables
•From projecting out distinguishing columns
 Keyword DISTINCT in the SELECT clause
eliminates duplicates

Set Operations
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 Result treated as a set (no duplicates)
• UNION, EXCEPT (difference), INTERSECT
 Corresponding multiset(bag) operations:
• UNION ALL, EXCEPT ALL, INTERSECT ALL
 Arguments must be union-compatible
• Same number of columns
• Corresponding columns of same type

OtherOperators
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 Standard arithmetic operators:
• Addition (+), subtraction (–), multiplication (*), and division (/)
 [NOT] LIKE comparison operator
• Used for string pattern matching
• Percent sign (%) matches zero or more characters
• Underscore (_) matches a single character
e.g., to also match Tommy Lee Jones as supporting actor:
SELECT award, actor, persona,
Role.movie FROM Honours, Role
WHERE category LIKE '%actor' AND winner =
actor AND Honours.movie =
Role.movie;
 [NOT] BETWEEN comparison operator
WHERE year BETWEEN 1990 AND 2010
equivalent to WHERE year >= 1990 AND YEAR <= 2010

Aggregate Functions
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•These functions operate on the multiset of
values of a column of a relation, and return a
value
avg: average value
min: minimum value
max: maximum value
sum: sum of values
count: number of values

Aggregate Functions (Cont.)
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•Find the average salary of instructors in the Computer
Science department
•select avg (salary)
from instructor
where dept_name= ’Comp. Sci.’;
•Find the total number of instructors who teach a course
in the Spring 2010 semester
•select count (distinct ID)
from teaches
where semester = ’Spring’ and year = 2010;
•Find the number of tuples in the course relation
•select count (*)
from course;

Aggregate Functions – Group By
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• Find the average salary of instructors in each department
• select dept_name, avg (salary) as avg_salary
from instructor
group by dept_name;

Aggregate Functions (Cont.)
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•Attributes in select clause outside of aggregate
functions must appear in group by list
•/* erroneous query */
select dept_name, ID, avg (salary)
from instructor
group by dept_name;

Aggregate Functions – Having Clause
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• Find the names and average salaries of all departments
whose average salary is greater than 42000
Note: predicates in the having clause are applied after the
formation of groups whereas predicates in the
where
clause are applied before forming groups
select dept_name, avg (salary)
from instructor
group by dept_name
having avg (salary) > 42000;

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