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COIS20026 Database
Development & Management
Week 5 – SQL (Part – I)
Prepared by: Angelika Schlotzer
Updated by: Satish Balmuri
Updated by: Tony Dobele
This week: SQL

Objectives:
explain the role of SQL in relational
DBMS
 identify & explain the distinction
between DDL, DML & DCL
 use the SQL commands: CREATE
TABLE, DROP TABLE, ALTER TABLE,
CREATE INDEX
 be able to use the SQL commands:
INSERT, UPDATE, DELETE

Objectives (cont’d)
Be able to discuss the role of indexes
and use the CREATE INDEX/DROP
INDEX commands (including being able
to create a primary key).
 construct correct single table SQL
queries with the SELECT command
using, as appropriate, its various
clauses & options

Note : Unless otherwise mentioned all the references of this lecture material are from
the prescribed course text book or images from publishers.
3
What is SQL?

SQL - Structured Query Language



high level declarative language used for
creating & querying relational
databases
declarative language that focuses on
the ‘what’ not the ‘how’
included as a subset in many fourthgeneration languages
4
What is SQL (cont’d)


has basically become the de-facto
standard for relational database
querying
first ANSI SQL standards published in
1986 and updated in 1989, 1992 (SQL92) and 1999 (SQL-99)
5
RDBMS


The Relational Database
Management System implements the
relational model
In a SQL enabled RDBMS, users or
applications deal with the RDBMS
through SQL statements; ie the SQL
acts as an agent between the two

users can create tables, retrieve data,
etc
6
Figure 7-1:
A simplified schematic of a typical SQL environment, as
described by the SQL-92 standard
Note that the catalogue is itself stored as a table
7

Catalog


Commands that define a database, including creating,
altering, and dropping tables and establishing constraints
Data Manipulation Language (DML)


The structure that contains descriptions of objects created
by a user (base tables, views, constraints)
Data Definition Language (DDL):


a set of schemas that constitute the description of a
database
Schema


SQL Environment
Commands that maintain and query a database
Data Control Language (DCL)

Commands that control a database, including administering
privileges and committing data
8
Data Definition Language (DDL)


The DDL component of SQL allows us
to create, alter and drop tables and
indexes, and implement data
integrity and domain constraints
DDL commands currently available
(see p 295 of the text)
Create Table Drop Table Alter Table
 Create Index Drop Index Create View
 Drop View
Create Schema, Drop Schema

9
Data Manipulation Language
(DML)

The DML component of SQL allows
users & applications to query,
update, delete existing records in
tables and insert new records

eg Select, Update, Insert, Delete
10
Data Control Language (DCL)

The DCL component is used to
implement controls on a database,
including administering user
privileges and ensuring that
transactions are completed before
committing changes to the database
11
Creating a Table



The CREATE TABLE command allows us
to create a new table in an existing
database
The general format for this command is
shown in figure 7-5 on page 299 of the
text
You will need to do some preparation
before creating a table; eg identify
which columns can contain NULL
values, etc (see steps in text on pp 299-301)
12
Table Creation
Figure 7-5: General syntax for CREATE TABLE
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 keyforeign key mates
5.
Determine default values
6.
Identify constraints on
columns (domain
specifications)
7.
Create the table and
associated indexes
13
Create Table Command

Assume that you have the following
normalised relation for which you wish
to create a table -
EMPLOYEE(EmpID, Name, DateOfBirth,
Department)


We know that EmpID is the primary
key
We will assume the following domains
for the columns
14
Create Table Command
EmpID - consists of an alphabetic
character followed by 3 digits (eg
D912)
 Name - consists of a maximum of 40
alphabetic characters (eg Alan
Jones)
 DateOfBirth - would be a valid date
(eg 27/02/1965)
 Department - consists of maximum of
25 alphabetic characters (eg
Production, Sales, Advertising)

15
Create Table Command

We would use the following command
to create this table CREATE TABLE EMPLOYEE_T
(EMP_ID VARCHAR(4) NOT NULL,
NAME
VARCHAR(40) NOT NULL,
DATE_OF_BIRTH DATE,
DEPARTMENT VARCHAR(25),
CONSTRAINT EMPLOYEE_PK PRIMARY KEY
(EMP_ID));
(figure 7-6 of the text has additional example table creation
declarations)
16
Create Table Command (again)

Note how the text (fig 7-6) uses
CONSTRAINT and REFERENCES to
identify foreign keys in a table



REFERENCES ensures that a value entered
for a foreign key in one table must exist as
a primary key value in the referenced table
does not stop the primary key value from
being altered
the ON UPDATE option (p 302) allows us to
determine what should happen when a
primary key value (that appears as a
foreign key in another table) is changed
17
Figure 7-3: Sample Pine Valley Furniture data
customers
orders
order lines
products
18
Figure 7-6: SQL database definition commands for Pine Valley Furniture
19
Figure 7-6: SQL database definition commands for Pine Valley Furniture
Defining
attributes and
their data types
20
Figure 7-6: SQL database definition commands for Pine Valley Furniture
Non-nullable
specifications
Note: primary
keys should not
be null
21
Figure 7-6: SQL database definition commands for Pine Valley Furniture
Identifying
primary keys
This is a composite
primary key
22
Figure 7-6: SQL database definition commands for Pine Valley Furniture
Identifying
foreign keys and
establishing
relationships
23
Figure 7-6: SQL database definition commands for Pine Valley Furniture
Default values
and domain
constraints
24
Figure 7-6: SQL database definition commands for Pine Valley Furniture
Overall table
definitions
25
Microsoft Access Tables

Creating tables in Microsoft Access is
somewhat different 

a table definition window is opened up
for you in which you can give the same
information, but in a slightly more userfriendly way
data integrity controls can be identified
when the relationships between the
tables are established
26
Alter Table Command

Allows us to make changes to an
existing table 
add and drop columns
change column names, data type,
constraint, etc

eg.

ALTER TABLE EMPLOYEE_T
ADD (COMMENCE_DATE DATE);
27
Drop Table Command

If a table is dropped (deleted) all
indexes, views, privileges, etc defined
for the table will also be dropped 

use carefully as command cannot be
undone
The command to drop the Employee
table would be:
DROP TABLE EMPLOYEE_T ;
28
Create Index Command



Indexes are created to improve query
performance
For instance, we might create an index
for our Employee table so that queries
on names are handled more quickly:
CREATE INDEX NAME_IDX ON
EMPLOYEE_T (NAME);
The command to drop this index would
be:
DROP INDEX NAME_IDX ;
29
Create Index Command

You should consider carefully before
creating numerous indexes for your
tables 


each index requires extra storage space
the applicable index must be updated
when data values for the indexed
columns change
in the end performance may actually be
reduced
30
DML-Inserting Data into a Table


Data can be inserted interactively or
in batch mode - we will focus on the
interactive mode
If you will be inserting values for
every column in the table then an
example command for the Employee
table might be:
INSERT INTO EMPLOYEE_T VALUES
(‘D325’, ‘Alison Hart’, 19/04/2000,
‘Sales’) ;
31
Inserting Data into a Table

If some attributes (column values) will
not be inserted, then the following
format of the command would be used:
INSERT INTO EMPLOYEE_T (EMP_ID,
NAME)
VALUES (‘F123’,’Henry Chang’);
32
Inserting Data into a Table

You can also add rows to a table by
using a subset of another table using
both the INSERT and SELECT
commands; eg
INSERT INTO YEAR2NET_T
SELECT ID, Name, Class
FROM ENROLLED
WHERE YEAR_LEVEL = 2;
33
Insert Statement – More examples

Inserting into a table


Inserting a record that has some null attributes requires
identifying the fields that actually get data


INSERT INTO CUSTOMER_T
VALUES (001, ‘CONTEMPORARY Casuals’, 1355 S. Himes Blvd.’,
‘Gainesville’, ‘FL’, 32601);
INSERT INTO PRODUCT_T
(PRODUCT_ID, PRODUCT_DESCRIPTION,PRODUCT_FINISH, STANDARD_PRICE,
PRODUCT_ON_HAND)
VALUES (1, ‘End Table’, ‘Cherry’, 175, 8);
Inserting from another table

INSERT INTO CA_CUSTOMER_T
SELECT * FROM CUSTOMER_T WHERE STATE = ‘CA’;
34
DML-Deleting Data from a Table


You can delete all of the rows in a table
by using the DELETE command without
specifying any criteria; eg
DELETE FROM EMPLOYEE_T;
When criteria are added only those
rows that meet these are removed; eg
DELETE FROM EMPLOYEE_T
WHERE EMP_ID = ‘C434’;
35
DML-Updating Data in a Table


Existing data can be updated through the UPDATE
command; eg assume that all employees are to receive a
5% pay increase
the command for this might be:
UPDATE PRODUCT_T
SET UNIT_PRICE = 775
WHERE PRODUCT_ID = 7;
OR
UPDATE SALARY_T
SET SALARY_AMOUNT =
SALARY_AMOUNT * 1.05;
36
DML-Select Statement

The SELECT statement is the one
most commonly used by users 

allows us to retrieve information from 1
or more tables in the way in which we
need to see that information
The 3 most common clauses are:



SELECT - columns, etc to be displayed
FROM - identifies table(s)/views to use
WHERE - conditions to apply
37
Select



This is the most common statement
The SELECT and FROM statements
are always required
WHERE is only needed if conditions
are to be applied to the result
38
The SELECT Statement


Used for queries on single or multiple tables
Clauses of the SELECT statement:

SELECT


FROM


Indicate categorization of results
HAVING


Indicate the conditions under which a row will be included in the
result
GROUP BY


Indicate the table(s) or view(s) from which data will be obtained
WHERE


List the columns (and expressions) that should be returned from
the query
Indicate the conditions under which a category (group) will be
included
ORDER BY

Sorts the result according to specified criteria
39
SQL statement
processing order
(adapted from
van der Lans,
p.100)
40
Select Examples
SELECT *
FROM EMPLOYEE_T
 The above will display all the data in
the employee table 
column order will be same as for table
41
Select Examples
SELECT NAME, DEPARTMENT
FROM EMPLOYEE_T;
Only the name and department values
from the employee table will be
displayed
42
SELECT Example

Find products with standard price less than
$275
SELECT PRODUCT_NAME, STANDARD_PRICE
FROM PRODUCT_V
WHERE STANDARD_PRICE < 275
Table 7-3: Comparison Operators in SQL
43
Select Examples
Display those employees who were
employed on or after 1 January, 1985
SELECT EMP_ID, NAME, DEPARTMENT
FROM EMPLOYEE_T
WHERE COMMENCE_DATE >=
#01/01/85#
44
Select with Expressions
Display the number of items on hand &
the selling price of all inventory items
(assumes a 25% mark up for all items)
SELECT ITEM_NO, DESCRIPTION,
ON_HAND, COST * 1.25 AS SELL PRICE
FROM INVENTORY
45
SELECT Example with ALIAS

Alias is an alternative column or table name
SELECT CUST.CUSTOMER AS NAME,
CUST.CUSTOMER_ADDRESS
FROM CUSTOMER_V AS CUST
WHERE NAME = ‘Home Furnishings’;
46
Select with Functions
How many employees do we currently
employ?
SELECT COUNT (*)
FROM EMPLOYEE_T;
47
Select with Functions
How many different types of inventory
items do we currently stock?
SELECT COUNT (ITEM_NO)
FROM INVENTORY;
Note: with aggregate functions you can’t have single-valued
columns included in the SELECT clause
48
Wildcards



Wildcards can be used when an exact
match is not possible. For example, you
may know that a person’s name begins
with ‘C’, but cannot remember the rest.
The ‘LIKE’ qualifier is often used with
wildcards (except for the asterisk)
The asterisk (*) matches up anything
49
Wildcards (cont’d)



% - used for any number of characters;
eg LIKE “C%”
_ - underscore takes the place of
exactly one character; eg LIKE
“SMITH_”;
Note: MS Access uses the ‘*’ instead of
‘%’ as wildcard
50
Boolean Operators




AND - joins two or more conditions
and will only return results if all
conditions are true
OR - joins two or more conditions
and will return results if any of the
conditions is true
NOT - negates any expression
Precedence: NOT, AND, OR
51
Boolean Operator Example
SELECT ITEM_NO, ON_HAND
FROM INVENTORY
WHERE ON_HAND > 10
AND DESCRIPTION LIKE “%bolts”
OR COST < 1.00;
Note: with multiple conditions separated by OR/AND, it is
recommended to use braces ()
52
Distinct Qualifier


Used to eliminate duplication of column
values in returned results
Example:
SELECT DISTINCT ITEM_NO
FROM ITEM_SALES_T;
Note: In MS ACCESS Query Designer DISTINCT
is not available with COUNT, e.g., COUNT
(DISTINCT Item No) is not available in MS
Access query designer.
53
IN and NOT IN



IN and NOT IN are used to match (or
negate matches) from a list of value
List of values can be obtained using a
SELECT statement
Example:
SELECT S_ID, SUPPLIER_NAME, PHONE
FROM SUPPLIER_T
WHERE CITY IN (“Sydney”, “Melb”,
“Canberra”);
54
BETWEEN
SELECT ITEM_NO, ON_HAND
FROM INVENTORY
WHERE ITEM_COST
BETWEEN 10 AND 25;
55
Order By
ORDER BY clause used to sort one
or more columns values in
resultant set into ascending (ASC)
or descending (DESC) order;
 Example:
SELECT FIRST_NAME, LAST_NAME,
CUST_ID, ADDRESS
FROM CUSTOMER_T
ORDER BY LAST_NAME ASC;

56
Group By and Having


GROUP BY - Groups rows in an
intermediate results table where the
values in those rows are the same for
one or more columns
HAVING - can only be used with the
GROUP BY clause and is used as a
secondary WHERE clause to specify
additional conditions
57
GROUP BY Example
 List states & their individual count of
Suppliers
SELECT STATE, COUNT (STATE)
FROM SUPPLIER
GROUP BY STATE;
58
Select with Group By & Functions
Which inventory item currently has the
lowest quantity in stock?
SELECT ITEM_NO, MIN(ON_HAND)
FROM INVENTORY
GROUP BY ITEM_NO;
59
Select with Group By & Functions
Which item has the greatest quantity of
stock on hand?
SELECT ITEM_NO, MAX(ON_HAND)
FROM INVENTORY
GROUP BY ITEM_NO;
60
GROUP BY with HAVING
Example
Identify states that have few than
100 customers
SELECT STATE, COUNT (STATE)
FROM CUSTOMER
GROUP BY STATE
HAVING COUNT (STATE) < 100;
61
Activity
Given the following relations:
CUSTOMER(ID, F_NAME, L_NAME,
ADDRESS1, CITY, STATE, POSTCODE,
TELEPHONE)
ITEM(NO, DESCRIPTION, ON_HAND,
COST)
ORDER(ORDER_ID, DATE, CUST_ID)
ORDER_ITEM(ORDER_ID, ITEM_NO,
QUANTITY)

62
Create Table Activity

Create tables with appropriate data
types and constraints for each of the
relations shown on the previous slide
 consider:
 are
there any foreign keys in the
relations?
 Do we need to consider referential
integrity? Why or why not?
 How will you ensure data integrity?
 Are any indexes required?
63
Select Activity





List all of our customers.
Which items do we currently have in
stock?
List items with more than 15 items in
stock.
List all of the orders for April, 1999.
How many customers do we have in
each state?
64
Select Activity (cont’d)




List the cost, item name and item
number for all items.
Identify the first name, last name,
customer ID and telephone number for
all customers in New South Wales.
List all of the items that have BOLT as
part of their description.
List all of the states that have more
than 25 customers (include customer
numbers in the output).
65
Select Activity (cont’d)


List the order_ID, date and item count
of all orders that had more than five
items.
The selling price of an item is the item
cost plus 28%. List the item name, item
number and selling price for all items.
66
Select Activity (cont’d)



List the first name, last name and ID of
all customers who live in either
Queensland or Victoria.
List the item number and description of
all items where the on_hand amount is
greater than 5 and less than 25.
List those customers who live in Sydney
(New South Wales).
67