hoffer_edm_pp_ch06.ppt

CHAPTER 6:
INTRODUCTION TO SQL
Copyright © 2014 Pearson Education, Inc.
1
Essentials of Database Management
Jeffrey A. Hoffer, Heikki Topi, V. Ramesh

Chapter 6 Copyright © 2014 Pearson Education, Inc.
OBJECTIVES
 Define terms
 Interpret history and role of SQL
 Define a database using SQL data
definition language
 Write single table queries using SQL
 Establish referential integrity using SQL
 Discuss SQL:1999 and SQL:2008
standards
2

SQL OVERVIEW
 Structured Query Language
 The standard for relational database
management systems (RDBMS)
 RDBMS: A database management system
that manages data as a collection of tables in
which all relationships are represented by
common values in related tables
3

HISTORY OF SQL
 1970–E. F. Codd develops relational database concept
 1974-1979–System R with Sequel (later SQL) created at
IBM Research Lab
 1979–Oracle markets first relational DB with SQL
 1981 – SQL/DS first available RDBMS system on
DOS/VSE
 Others followed: INGRES (1981), IDM (1982), DG/SGL
(1984), Sybase (1986)
 1986–ANSI SQL standard released
 1989, 1992, 1999, 2003, 2006, 2008–Major ANSI
standard updates
 Current–SQL is supported by most major database
vendors
4

PURPOSE OF SQL STANDARD
 Specify syntax/semantics for data definition
and manipulation
 Define data structures and basic operations
 Enable portability of database definition and
application modules
 Specify minimal (level 1) and complete (level
2) standards
 Allow for later growth/enhancement to
standard (referential integrity, transaction
management, user-defined functions,
extended join operations, national character
sets)
5

BENEFITS OF A STANDARDIZED
RELATIONAL LANGUAGE
 Reduced training costs
 Productivity
 Application portability
 Application longevity
 Reduced dependence on a single
vendor
 Cross-system communication
6

SQL ENVIRONMENT
 Catalog
 A set of schemas that constitute the description of a database
 Schema
 The structure that contains descriptions of objects created by a user
(base tables, views, constraints)
 Data Definition Language (DDL)
 Commands that define a database, including creating, altering, and
dropping tables and establishing constraints
 Data Manipulation Language (DML)
 Commands that maintain and query a database
 Data Control Language (DCL)
 Commands that control a database, including administering
privileges and committing data
7

8
Figure 6-1
A simplified schematic of a typical SQL environment, as
described by the SQL: 2008 standard
8

SQL DATA TYPES
9

10
Figure 6-4
DDL, DML, DCL, and the database development process
10

SQL DATABASE DEFINITION
 Data Definition Language (DDL)
 Major CREATE statements:
 CREATE SCHEMA–defines a portion of the
database owned by a particular user
 CREATE TABLE–defines a new table and its
columns
 CREATE VIEW–defines a logical table from one
or more tables or views
 Other CREATE statements: CHARACTER
SET, COLLATION, TRANSLATION, ASSERTION,
DOMAIN
11

STEPS IN TABLE CREATION
12
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–foreign key mates
5. Determine default values
6. Identify constraints on columns (domain
specifications)
7. Create the table and associated indexes

13
Figure 6-5 General syntax for CREATE TABLE
statement used in data definition language

THE FOLLOWING SLIDES CREATE TABLES
FOR THIS ENTERPRISE DATA MODEL
14
(from Chapter 1, Figure 1-3)

15
Figure 6-6 SQL database definition commands for Pine Valley Furniture
Company (Oracle 11g)
Overall table
definitions

16
Defining attributes and their data types
16

17
Non-nullable specification
Identifying primary key
Primary keys
can never have
NULL values
17

18
Non-nullable specifications
Primary key
Some primary keys are composite–
composed of multiple attributes
18

19
Default value
Domain constraint
Controlling the values in attributes
19

20
Primary key of
parent table
Identifying foreign keys and establishing relationships
Foreign key of dependent table
20

DATA INTEGRITY CONTROLS
 Referential integrity–constraint that
ensures that foreign key values of a
table must match primary key
values of a related table in 1:M
relationships
 Restricting:
Deletes of primary records
Updates of primary records
Inserts of dependent records
21

CHANGING TABLES
 ALTER TABLE statement allows you to
change column specifications:
 Table Actions:
 Example (adding a new column with a default value):
22

REMOVING TABLES
DROP TABLE statement allows you
to remove tables from your schema:
DROP TABLE CUSTOMER_T
23

INSERT STATEMENT
 Adds one or more rows to a table
 Inserting into a table
 Inserting a record that has some null attributes
requires identifying the fields that actually get data
 Inserting from another table
24

CREATING TABLES WITH IDENTITY COLUMNS
25
Inserting into a table does not require explicit customer ID entry or
field list
INSERT INTO CUSTOMER_T VALUES ( ‘Contemporary Casuals’,
‘1355 S. Himes Blvd.’, ‘Gainesville’, ‘FL’, 32601);
Introduced with SQL:2008

DELETE STATEMENT
 Removes rows from a table
 Delete certain rows
DELETE FROM CUSTOMER_T WHERE
CUSTOMERSTATE = ‘HI’;
 Delete all rows
DELETE FROM CUSTOMER_T;
26

UPDATE STATEMENT
 Modifies data in existing rows
27

SCHEMA DEFINITION
 Control processing/storage efficiency:
 Choice of indexes
 File organizations for base tables
 File organizations for indexes
 Data clustering
 Statistics maintenance
 Creating indexes
 Speed up random/sequential access to base table data
 Example
 CREATE INDEX NAME_IDX ON
CUSTOMER_T(CUSTOMERNAME)
 This makes an index for the CUSTOMERNAME field of the
CUSTOMER_T table
28

SELECT STATEMENT
 Used for queries on single or multiple tables
 Clauses of the SELECT statement:
 SELECT
 List the columns (and expressions) to be returned from the query
 FROM
 Indicate the table(s) or view(s) from which data will be obtained
 WHERE
 Indicate the conditions under which a row will be included in the
result
 GROUP BY
 Indicate categorization of results
 HAVING
 Indicate the conditions under which a category (group) will be
included
 ORDER BY
 Sorts the result according to specified criteria 29

30
Figure 6-9
SQL statement
processing
order (based
on van der
Lans, 2006
p.100)
30

SELECT EXAMPLE
 Find products with standard price less than
$275
31
Table 6-3: Comparison Operators in SQL

SELECT EXAMPLE USING ALIAS
 Alias is an alternative column or table
name
 Here, CUST is a table alias and Name is a
column alias
32

SELECT EXAMPLE USING A FUNCTION
 Using the COUNT aggregate function to find
totals
SELECT COUNT(*) FROM ORDERLINE_T
WHERE ORDERID = 1004;
Note: with aggregate functions you can’t have
single-valued columns included in the SELECT
clause, unless they are included in the GROUP
BY clause.
33

SELECT EXAMPLE–BOOLEAN OPERATORS
 AND, OR, and NOT Operators for customizing
conditions in WHERE clause
34
Note: the LIKE operator allows you to compare strings using
wildcards. For example, the % wildcard in ‘%Desk’ indicates
that all strings that have any number of characters preceding
the word “Desk” will be allowed.

35
Figure 6-7 Boolean query A without use of parentheses
By default,
processing order
of Boolean
operators is
NOT, then AND,
then OR

SELECT EXAMPLE–BOOLEAN OPERATORS
 With parentheses…these override the normal
precedence of Boolean operators
36
With parentheses, you can override normal precedence rules.
In this case parentheses make the OR take place before the
AND.

37
Figure 6-8 Boolean query B with use of parentheses

SORTING RESULTS WITH ORDER BY CLAUSE
 Sort the results first by STATE, and within a
state by the CUSTOMER NAME
38
Note: the IN operator in this example allows you to include rows
whose CustomerState value is either FL, TX, CA, or HI. It is
more efficient than separate OR conditions.

CATEGORIZING RESULTS USING GROUP
BY CLAUSE
 For use with aggregate functions
 Scalar aggregate: single value returned from SQL query
with aggregate function
 Vector aggregate: multiple values returned from SQL query
with aggregate function (via GROUP BY)
You can use single-value fields with aggregate
functions if they are included in the GROUP BY
clause. 39

QUALIFYING RESULTS BY CATEGORIES
USING THE HAVING CLAUSE
 For use with GROUP BY
Like a WHERE clause, but it operates on
groups (categories), not on individual rows.
Here, only those groups with total numbers
greater than 1 will be included in final result.
40

USING AND DEFINING VIEWS
 Views provide users controlled access to tables
 Base Table–table containing the raw data
 Virtual Table–constructed automatically as needed;
not maintained as real data
 Dynamic View
 A “virtual table” created dynamically upon request by a user
 No data actually stored; instead data from base table made
available to user
 Based on SQL SELECT statement on base tables or other views
 Contents materialized as a result of a query
41

SAMPLE CREATE VIEW
42
Query: What are the data elements necessary
to create an invoice for a customer?
Save this query as a view named Invoice_V.

ADVANTAGES OF VIEWS
 Simplify query commands
 Assist with data security (but don't rely on
views for security, there are more
important security measures)
 Enhance programming productivity
 Contain most current base table data
 Use little storage space
 Provide customized view for user
 Establish physical data independence
43

DISADVANTAGES OF VIEWS
 Use processing time each time view
is referenced
 May or may not be directly
updateable
44

45
All rights reserved. No part of this publication may be reproduced, stored in a
retrieval system, or transmitted, in any form or by any means, electronic,
mechanical, photocopying, recording, or otherwise, without the prior written
permission of the publisher. Printed in the United States of America.
Copyright © 2014 Pearson Education, Inc.

hoffer_edm_pp_ch06.ppt

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