Chapter 6: Chapter 6: Introduction to SQL Modern Database Management 11 th Edition Jeffrey A. Hoffer, V. Ramesh, Heikki Topi April 13, 2014 1.

Chapter 6:Chapter 6:Introduction to SQL

Modern Database Management11th Edition

Jeffrey A. Hoffer, V. Ramesh, Heikki Topi

April 13, 2014

1

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:200n standards

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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

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History of SQL• 1970–E. 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• 1986–ANSI SQL standard released• 1989, 1992, 1999, 2003–Major ANSI standard

updates• Current–SQL is supported by most major database

vendors

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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

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Benefits of a Standardized Relational Language

• Reduced training costs• Productivity• Application portability• Application longevity• Reduced dependence on a single vendor• Cross-system communication

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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) – our focus

Commands that maintain and query a database• Data Control Language (DCL)

Commands that control a database, including administering privileges and committing data

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Figure 6-1A simplified schematic of a typical SQL environment, as described by the SQL: 200n standard

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Fig 6-2 Query syntax

• SELECT Major, AVERAGE(GPA) , ExpGraduateYr• WHERE ExpGraduateYr = “2015”• GROUP BY Major• HAVING AVERAGE(GPA) >=3.0• ORDER BY Major

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Just a quick example to show sequence of

clauses

Display order can be specified here

Cond for records

Cond for groups

SQL Data Types10

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

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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 columnsCREATE VIEW–defines a logical table from one or more

tables or views

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Table Creation13

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

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–foreign key mates

5. Determine default values

6. Identify constraints on columns (domain specifications)

7. Create the table and associated indexes

The following slides create tables for this enterprise data model

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(from Chapter 1, Figure 1-3)

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Figure 6-3: sample PVFC data

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16Figure 6-6 SQL database definition commands for Pine Valley Furniture Company (Oracle 11g)

Overall table definitions

Defining attributes and their data types

Constraint name Cnstr Type Field

Column constraint: validation rule

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Non-nullable specification

Identifying primary key

Primary keys can never have NULL values

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Non-nullable specifications

Primary key

Some primary keys are composite– composed of multiple attributes

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Default value

Domain constraint

Controlling the values in attributes20

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Primary key of parent table

Identifying foreign keys and establishing relationships

Foreign key of dependent table

Constraint name Cnstr Type Field REFERENCES Tbl(Key)

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

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Relational integrity is enforced via the primary-key to foreign-key match

Figure 6-7 Ensuring data integrity through updates

Changing Tables• ALTER TABLE statement allows you to change column specifications:

• Table Actions:

• Example (adding a new column with a default value):

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ADD COLUMN Name Type Default

Removing Tables

• DROP TABLE statement allows you to remove tables from your schema:

– DROP TABLE CUSTOMER_T

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Insert Statement• Adds one or more rows to a table• Inserting into a table

• VALUE – “s” Sequence!!! VALUE – “s” Sequence!!!

• Inserting a record that has some null attributes requires identifying the fields that actually get data

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(field-list) VALUES (value-list)

INSERT INTO Table VALUES (value-list)

Insert Statement (cont)

• Inserting from another table– A SUBSET from another tableA SUBSET from another table

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Interpretation?

Creating Tables with Identity Columns28

Inserting into a table does not require explicit customer ID entry or field Inserting into a table does not require explicit customer ID entry or field list (list (No “001” as compared w slide #26No “001” as compared w slide #26) --) --

INSERT INTO CUSTOMER_T VALUES ( ‘Contemporary Casuals’, ‘1355 S. INSERT INTO CUSTOMER_T VALUES ( ‘Contemporary Casuals’, ‘1355 S. Himes Blvd.’, ‘Gainesville’, ‘FL’, 32601);Himes Blvd.’, ‘Gainesville’, ‘FL’, 32601);

Introduced with SQL:200n

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Delete Statement

• Removes rows from a table• Delete certain rows

– DELETE FROM CUSTOMER_T DELETE FROM CUSTOMER_T WHERE CUSTOMERSTATE = ‘HI’;WHERE CUSTOMERSTATE = ‘HI’;

• Delete all rows– DELETE FROM CUSTOMER_T;DELETE FROM CUSTOMER_T;– Careful!!!Careful!!!

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Update Statement• Modifies data in existing rows

• Note: the WHERE clause may be a subquery Note: the WHERE clause may be a subquery (Chap 7)(Chap 7)

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UPDATE UPDATE Table-nameTable-nameSET SET AttributeAttribute = = ValueValueWHERE WHERE Criteria-to-apply-the-updateCriteria-to-apply-the-update

Recap of “three modifications”

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KEY WORD /Change what

SYNTAX / Example

ALTER:

INSERT:

UPDATE:

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Merge Statement32

Makes it easier to update a table…allows combination of Insert and Update in one statement

Useful for updating master tables with new data

Interp

retation?

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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

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SELECT Example• Find products with standard price less than

$275

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Table 6-3: Comparison Operators in SQL

Every SESLECT statement returns a result table - Can be used as part of another query

SELECT DISTINCT: no duplicate rowsSELECT * : all columns selected

SELECT Example Using Alias

• Alias is an alternative column or table name

SELECT CUSTCUST.CUSTOMER_NAME AS NAMENAME, CUST.CUSTOMER_ADDRESS

FROM CUSTOMER_V [AS] CUSTCUSTWHERE NAMENAME = ‘Home Furnishings’;

Note1: Specifying source table, P. 262Note2: Use of alias, P. 263

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The two alias have different usage:

Using expressions (PP. 263-264)

• P. 264– ProductStandardPrice*1.1 AS Plus10Percent

• What does it look like what we learned in Access (in IS 312)?– Observe the result on P. 264

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SELECT Example Using a Function• Using the COUNT aggregate function to find

totals

SELECT COUNT(*)COUNT(*) FROM ORDERLINE_TWHERE ORDERID = 1004;

Note 1: SELECT PRODUCT_ID, COUNT(*)COUNT(*)

FROM ORDER_LINE_V

WHERE ORDER_ID = 1004;Note 2: COUNT (*) and COUNT - different

37More functions:P. 264~5

P. 265

More exmpl:P. 266

SELECT Example Using functions• What is average standard price for each

product in inventory?

SELECT AVG (STANDARD_PRICE)AVG (STANDARD_PRICE) AS AVERAGE FROM PROCUCT_V;

• AVG, COUNT, MAX, MIN, SUM;• LN, EXP, POWER, SQRT• More functions – P. 264• Issues about set value and aggregates: 265-6• Wildcards: 267, top• Null values, 268, top

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Issues about set value and aggregates• Last line on P. 265: SQL cannot return both a row

value (such as ID) and a set value (such as COUNT/AVG/SUM of a group); users must run two separate queries, one that returns row info and one that returns set info

1.SELECT S_ID FROM STUDENT2.SELECT AVG(GPA) FROM STUDENT3.SELECT S_ID, AVG(GPA) FROM STUDENT

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One of the above is not legitimate

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SELECT Example–Boolean Operators• ANDAND, OROR, and NOTNOT Operators for customizing conditions

in WHERE clause

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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.

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Figure 6-9 Boolean query without use of parentheses

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SELECT Example–Boolean Operators• With parentheses…these override the normal With parentheses…these override the normal

precedence of Boolean operatorsprecedence of Boolean operators

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Note: by default, the AND operator takes precedence over the OR operator. With parentheses, you can make the OR take place before the AND.

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Figure 6-9 Boolean query with use of parentheses

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SELECT Example– Using distinct values

• Compare:

SELECT ORDER_IDFROM ORDER_LINE_V;

and –

SELECT DISTINCT ORDER_IDFROM ORDER_LINE_V;

But:SELECT DISTINCT ORDER_ID, ORDER_QUANTITY

FROM ORDER_LINE_V;Compare three figures on 272 & 273

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SELECT Example – Sorting Results with the ORDER BY Clause• Sort the results first by STATE, and then within a

state by the CUSTOMER NAME

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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.

The opposite is NOT IN

Can order by multiple fields: primary sort,

2ndry, …

SELECT Example– Categorizing Results Using the 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)

Note: you can use single-value fields with aggregate functions if they are included in the GROUP BY clause

Q: Can we do SELECT CustCity, COUNT(CustState)?

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One value for a group “vector”

Result: P. 275

single-value fields vs aggregate functions

1. SELECT S_ID FROM STUDENT2. SELECT MAJOR, AVG(GPA) FROM STUDENT

GROUP BY MAJOR3. SELECT S_ID, AVG(GPA) FROM STUDENT GROUP

BY MAJOR

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One of the above is not legitimate. Compare Slide #39

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SELECT Example– 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.

See 275-276

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SELECT Statement with Group by• Used for queries on single or multiple tables• Clauses of the SELECT statement: (Sequence!!)

– SELECTSELECT• List the columns (and expressions) that should be returned from the query

– FROMFROM• Indicate the table(s) or view(s) from which data will be obtained

– WHEREWHERE• Indicate the conditions under which a row will be included in the result

– GROUP BYGROUP BY• Indicate categorization of results

– HAVINGHAVING• Indicate the conditions under which a category (group) will be included

– ORDER BYORDER BY• Sorts the result according to specified criteria

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Read closely PP. 275-276

Can have multiple sorts – primary, 2ndry,

…

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Figure 6-10 SQL statement processing order (adapted from van der Lans, 2006 p.100)

– The HAVING clause acts like a WHERE clause, but it identifies groups that meet a criterion, rather than rows.• Therefore, you will usually see a HAVING clause …

– WHERE qualifies a set of rows, while HAVING qualifies a set of …

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HAVING clauseHAVING clause

Interpretation: example on P. 276

Using and Defining Views• Views provide users controlled access to tables• Base Table–table containing the raw 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

• Materialized View– Copy or replication of data– Data actually stored– Must be refreshed periodically to match the corresponding base

tables

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Sample CREATE VIEW53

View has a nameView is based on a SELECT statementCHECK_OPTION works only for updateable views and prevents updates that would create rows not included in the view

– Syntax of CREATE VIEW:– CREATE VIEW view-name AS

SELECT (that provides the rows and columns of the view)

– Example:• CREATE VIEW ORDER_TOTALS_V AS

SELECT PRODUCT_ID PRODUCT,SUM(STANDARD_PRICE*QUANTITY) TOTALFROM INVOICE_V

GROUP BY PRODUCT_ID;

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ViewsViews

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

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Disadvantages of Views• Use processing time each time view is

referenced• May or may not be directly updateable

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Addendum: Comparison of ALTER, INSERT, and UPDATE

• ALTER: changing the columns of the table– ALTER TABLE CUSTOMER_T ADD COLUMN…

• INSERT: adding records based on the existing table– INSERT INTO CUTTOME_T VALUES (… )

• UPDATE: changing the values of some fields in existing records– UPDATE PRODUCT_T SET …WHERE…

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