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Fundamentals, Design, and Implementation, 9/e

Chapter 7 Relational Algebra and SQL applications

Instructor: Dragomir R. Radev

Fall 2005

Chapter 7/2 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Review Relational Model Terminology Relation is a two-dimensional table Attributes are single valued Each attribute belongs to a domain

– A domain is a physical and logical description of permittable values

No two rows are identical Order is unimportant The row is called a tuple

Chapter 7/3 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Relational Algebra

Relational algebra defines a set of operators that may work on relations.

Recall that relations are simply data sets. As such, relational algebra deals with set theory.

The operators in relational algebra are very similar to traditional algebra except that they apply to sets.

Chapter 7/4 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Relational Algebra Operators

Relational algebra provides several operators:– Union– Difference– Intersection– Product– Projection– Selection– Join

Chapter 7/5 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Union Operator

The union operator adds tuples from one relation to another relation

A union operation will result in combined relation

This is similar to the logical operator ‘OR’

Chapter 7/6 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Union Operator

JUNIOR and HONOR-STUDENT relations and their union:

(a)Example of JUNIOR relation

(b)Example HONOR-STUDENT relation

(c) Union of JUNIOR and HONOR-STUDENT relations

Chapter 7/7 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Difference Operator

The difference operator produces a third relation that contains the tuples that appear in the first relation, but not the second

This is similar to a subtraction

Chapter 7/8 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Difference Operator

JUNIOR relation

HONOR-STUDENT relation

JUNIOR minus HONOR-STUDENT relation

Chapter 7/9 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Intersection Operator

An intersection operation will produce a third relation that contains the tuples that are common to the relations involved.

This is similar to the logical operator ‘AND’

Chapter 7/10 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Intersection Operator

JUNIOR relation

HONOR-STUDENT relation

Intersection of JUNIOR and HONOR-STUDENT relations

Chapter 7/11 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Product Operator

A product operator is a concatenation of every tuple in one relation with every tuple in a second relation

The resulting relation will have n x m tuples, where…

n = the number of tuples in the first relation andm = the number of tuples in the second relation

This is similar to multiplication

Chapter 7/12 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Projection Operator

A projection operation produces a second relation that is a subset of the first.

The subset is in terms of columns, not tuples

The resulting relation will contain a limited number of columns. However, every tuple will be listed.

Chapter 7/13 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Selection Operator

The selection operator is similar to the projection operator. It produces a second relation that is a subset of the first.

However, the selection operator produces a subset of tuples, not columns.

The resulting relation contains all columns, but only contains a portion of the tuples.

Chapter 7/14 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Join Operator

The join operator is a combination of the product, selection, and projection operators. There are several variations of the join operator…– Equijoin– Natural join– Outer join

• Left outer join• Right outer join

Chapter 7/15 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Data for Join Examples

SID Name Major GradeLevel

123 Jones History JR

158 Parks Math GR

271 Smith History JR

105 Anderson Management SN

StudentNumber ClassName PositionNumber

123 H350 1

105 BA490 3

123 B490 7

Chapter 7/16 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Join Examples

Equijoin

Natural Join

Left OuterJoin

Chapter 7/17 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Expressing Queries in Relational Algebra

1. What are the names of all students?

STUDENT [Name]

2. What are the student numbers of all students enrolled in a class?

ENROLLMENT [StudentNumber]

Chapter 7/18 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Expressing Queries in Relational Algebra3. What are the student numbers of all

students not enrolled in a class?STUDENT [SID] – ENROLLMENT

[StudentNumber]

4. What are the numbers of students enrolled in the class ‘BD445’?

ENROLLMENT WHERE ClassName = ‘BD445’[StudentNumber]

Chapter 7/19 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Expressing Queries in Relational Algebra

5. What are the names of the students enrolled in class ‘BD445’?

STUDENT JOIN (SID = StudentNumber) ENROLLMENT WHERE ClassName = ‘BD445’[STUDENT.Name]

Chapter 7/20 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Expressing Queries in Relational Algebra

6. What are the names and meeting times of ‘PARKS’ classes?

STUDENT WHERE Name = ‘PARKS’ JOIN (SID=StudentNumber) ENROLLMENT JOIN (ClassName = Name) CLASS

[CLASS.Name, Time]

Chapter 7/21 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Expressing Queries in Relational Algebra7. What are the grade levels and meeting

rooms of all students, including students not enrolled in a class?

STUDENT LEFT OUTER JOIN (SID = StudentNumber) ENROLLMENT JOIN (ClassName = Name) CLASS [GradeLevel, Room]

Chapter 7/22 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Summary of Relational Algebra Operators

Fundamentals, Design, and Implementation, 9/e

Using SQL in Applications

Instructor: Dragomir R. Radev

Winter 2005

Chapter 7/24 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

View Ridge Gallery

View Ridge Gallery is a small art gallery that has been in business for 30 years

It sells contemporary European and North American fine art

View Ridge has one owner, three salespeople, and two workers

View Ridge owns all of the art that it sells; it holds no items on a consignment basis

Chapter 7/25 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Application Requirements

View Ridge application requirements– Track customers and their artist interests– Record gallery's purchases– Record customers' art purchases– List the artists and works that have

appeared in the gallery– Report how fast an artist's works have

sold and at what margin– Show current inventory in a Web page

Chapter 7/26 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

View Ridge Data Model

Chapter 7/27 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

View Ridge Data Model

Problems: the keys for WORK and TRANSACTION are huge and the key for CUSTOMER is doubtful as many customers may not have an email address

Chapter 7/28 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Surrogate Key Database Design

Chapter 7/29 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Sample Values

Chapter 7/30 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Sample Values

Chapter 7/31 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Sample Values

Chapter 7/32 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Sample Values

Chapter 7/33 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Sample Values

Chapter 7/34 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

CHECK CONSTRAINT

CHECK CONSTRAINT defines limits for column values

Two common uses– Specifying a range of allowed values– Specifying an enumerated list

CHECK constraints may be used – To compare the value of one column to another– To specify the format of column values– With subqueries

Chapter 7/35 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

SQL Views

SQL view is a virtual table that is constructed from other tables or views

It has no data of its own, but obtains data from tables or other views

SELECT statements are used to define views– A view definition may not include an ORDER BY clause

SQL views are a subset of the external views– They can be used only for external views that involve

one multi-valued path through the schema

Chapter 7/36 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

SQL Views

Views may be used to – Hide columns or rows– Show the results of computed columns– Hide complicated SQL statements – Provide a level of indirection between

application programs and tables– Assign different sets of processing

permissions to tables– Assign different sets of triggers

Chapter 7/37 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Example: CREATE VIEW

CREATE VIEW CustomerNameView AS

SELECT Name AS CustomerName

FROM CUSTOMER;

SELECT *

FROM CustomerNameView

ORDER BY CustomerName;

Chapter 7/38 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Updating Views

Views may or may not be updatable Rules for updating views are both

complicated and DBMS-specific

Chapter 7/39 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Updating Views

Guidelines:

Chapter 7/40 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Embedding SQL In Program Code SQL can be embedded in triggers, stored

procedures, and program code Problem: assigning SQL table columns with

program variables Solution: object-oriented programming, PL/SQL Problem: paradigm mismatch between SQL and

application programming language– SQL statements return sets of rows; an applications work

on one row at a time

Solution: process the SQL results as pseudo-files

Chapter 7/41 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Triggers

A trigger is a stored program that is executed by the DBMS whenever a specified event occurs on a specified table or view

Three trigger types: BEFORE, INSTEAD OF, and AFTER– Each type can be declared for Insert, Update, and Delete– Resulting in a total of nine trigger types

Oracle supports all nine trigger types SQL Server supports six trigger types (only for

INSTEAD OF and AFTER triggers)

Chapter 7/42 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Firing Triggers

When a trigger is fired, the DBMS supplies– Old and new values for the update– New values for inserts– Old values for deletions

The way the values are supplied depends on the DBMS product

Trigger applications:– Checking validity (Figure 7-14)– Providing default values (Figure 7-15)– Updating views (Figure 7-16)– Enforcing referential integrity actions (Figure 7-17, 7-18)

Chapter 7/43 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Stored Procedures

A stored procedure is a program that is stored within the database and is compiled when used– In Oracle, it can be written in PL/SQL or Java– In SQL Server, it can be written in TRANSACT-SQL

Stored procedures can receive input parameters and they can return results

Stored procedures can be called from– Programs written in standard languages, e.g., Java, C#– Scripting languages, e.g., JavaScript, VBScript– SQL command prompt, e.g., SQL Plus, Query Analyzer

Chapter 7/44 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Stored Procedure Advantages

Greater security as store procedures are always stored on the database server

Decreased network traffic SQL can be optimized by the DBMS

compiler Code sharing resulting in

– Less work– Standardized processing– Specialization among developers

Chapter 7/45 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Using SQL In Application Code

SQL can be embedded in application programs

Several SQL statements need to be executed to populate an external view

The application program causes the statements to be executed and then displays the results of the query in the form’s grid controls

Chapter 7/46 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Using SQL In Application Code (cont.) The application program also processes

and coordinates user actions on a form, including– Populating a drop-down list box– Making the appropriate changes to foreign keys

to create record relationships The particulars by which SQL code is

inserted into applications depend on the language and data-manipulation methodology used

Fundamentals, Design, and Implementation, 9/e

MySQL Chapters 1 and 3Introduction to MySQL

Instructor: Dragomir R. Radev

Winter 2005

Chapter 7/48 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Overview

– TcX - Michael Widenius (MySQL)– Hughes - David Hughes (mSQL)– Features:

• Mostly ANSI SQL2 compliant• Transactions• Stored procedures• Auto_increment fields

Chapter 7/49 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

More features

Cross-database joins Outer joins API: C/C++, Eiffel, Java, PHP, Perl,

Python, TCL Runs on Windows, UNIX, and Mac High performance

Chapter 7/50 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

SQL syntax

CREATE TABLE people (name CHAR(10)) INSERT INTO people VALUES (‘Joe’) SELECT name FROM people WHERE

name like ‘J%’

Chapter 7/51 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

SQL commands

SHOW DATABASES SHOW TABLES Data types: INT, REAL, CHAR(l),

VARCHAR(l), TEXT(l), DATE, TIME ALTER TABLE mytable MODIFY

mycolumn TEXT(100) ENUM(‘cat’,’dog’,’rabbit’,’pig’)

Chapter 7/52 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

SQL commands

CREATE DATABASE dbname CREATE TABLE tname (id NOT

NULL PRIMARY KEY AUTO_INCREMENT)

CREATE INDEX part_of_name ON customer (name(10))

INSERT INTO tname (c1, …, cn) values (v1, …, vn)

Chapter 7/53 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

JOINs and ALIASing

SELECT book.title, author.nameFROM author, book

WHERE books.author = author.id

SELECT very_long_column_name AS col FROM tname WHERE col=‘5’

Chapter 7/54 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Loading text files

Comma-separated files (*.csv) LOAD DATA LOCAL INFILE

"whatever.csv" INTO TABLE tname

Chapter 7/55 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Aggregate queries

SELECT position FROM people GROUP by position

SELECT position, AVG (salary) FROM people GROUP BY position HAVING AVG (salary) > 50000.00

Chapter 7/56 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Full text search

CREATE TABLE WebCache (url VARCHAR (255) NOT NULL PRIMARY KEY,ptext TEXT NOT NULL,FULLTEXT (ptext));

INSERT INTO WebCache (url, ptext) VALUES (‘index.html’, ‘Welcome to the University of Michigan’);

SELECT url from WebCache WHERE MATCH (ptext) against (‘Michigan’);

Chapter 7/57 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Advanced features

Transactions Table locking Functions Unions Outer joins

Chapter 7/58 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Installing MySQL on Windows

http://www.mysql.com/products/mysql/

http://www.webdevelopersnotes.com/tutorials/sql/index.php3

Chapter 7/59 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

Useful pointers

Small example: http://www.itl.nist.gov/div897/ctg/dm/sql_examples.htm

MySQL documentation:http://www.mysql.com/doc/en/index.html

(official) MySQL tutorial:http://www.mysql.com/doc/en/Tutorial.html

Online, interactive tutorials:http://sqlzoo.net/http://sql.grussell.org/

Chapter 7/60 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

http://www.itl.nist.gov/div897/ctg/dm/sql_examples.htm

use test;

CREATE TABLE STATION

(ID INTEGER PRIMARY KEY,

CITY CHAR(20),

STATE CHAR(2),

LAT_N REAL,

LONG_W REAL);

DESCRIBE STATION;

INSERT INTO STATION VALUES (13, 'Phoenix', 'AZ', 33, 112);

INSERT INTO STATION VALUES (44, 'Denver', 'CO', 40, 105);

INSERT INTO STATION VALUES (66, 'Caribou', 'ME', 47, 68);

SELECT * FROM STATION;

SELECT * FROM STATION

WHERE LAT_N > 39.7;

Chapter 7/61 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

SELECT ID, CITY, STATE FROM STATION; ID CITY STATE ;

SELECT ID, CITY, STATE FROM STATION

WHERE LAT_N > 39.7;

CREATE TABLE STATS

(ID INTEGER REFERENCES STATION(ID),

MONTH INTEGER CHECK (MONTH BETWEEN 1 AND 12),

TEMP_F REAL CHECK (TEMP_F BETWEEN -80 AND 150),

RAIN_I REAL CHECK (RAIN_I BETWEEN 0 AND 100),

PRIMARY KEY (ID, MONTH));

INSERT INTO STATS VALUES (13, 1, 57.4, 0.31);

INSERT INTO STATS VALUES (13, 7, 91.7, 5.15);

INSERT INTO STATS VALUES (44, 1, 27.3, 0.18);

INSERT INTO STATS VALUES (44, 7, 74.8, 2.11);

INSERT INTO STATS VALUES (66, 1, 6.7, 2.10);

INSERT INTO STATS VALUES (66, 7, 65.8, 4.52);

SELECT * FROM STATS;

Chapter 7/62 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

SELECT * FROM STATION, STATS

WHERE STATION.ID = STATS.ID;

SELECT MONTH, ID, RAIN_I, TEMP_F

FROM STATS

ORDER BY MONTH, RAIN_I DESC;

SELECT LAT_N, CITY, TEMP_F

FROM STATS, STATION

WHERE MONTH = 7

AND STATS.ID = STATION.ID

ORDER BY TEMP_F;

SELECT MAX(TEMP_F), MIN(TEMP_F), AVG(RAIN_I), ID

FROM STATS

GROUP BY ID;

SELECT * FROM STATION

WHERE 50 < (SELECT AVG(TEMP_F) FROM STATS

WHERE STATION.ID = STATS.ID);

Chapter 7/63 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

CREATE VIEW METRIC_STATS (ID, MONTH, TEMP_C, RAIN_C) AS

SELECT ID,

MONTH,

(TEMP_F - 32) * 5 /9,

RAIN_I * 0.3937

FROM STATS;

SELECT * FROM METRIC_STATS;

SELECT * FROM METRIC_STATS

WHERE TEMP_C < 0 AND MONTH = 1

ORDER BY RAIN_C;

UPDATE STATS SET RAIN_I = RAIN_I + 0.01;

SELECT * FROM STATS;

UPDATE STATS SET TEMP_F = 74.9

WHERE ID = 44

AND MONTH = 7;

Chapter 7/64 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

SELECT * FROM STATS;

COMMIT WORK;

UPDATE STATS SET RAIN_I = 4.50

WHERE ID = 44;

SELECT * FROM STATS;

ROLLBACK WORK;

SELECT * FROM STATS;

UPDATE STATS SET RAIN_I = 4.50

WHERE ID = 44

AND MONTH = 7;

COMMIT WORK;

SELECT * FROM STATS;

Chapter 7/65 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

DELETE FROM STATS

WHERE MONTH = 7

OR ID IN (SELECT ID FROM STATION

WHERE LONG_W < 90);

DELETE FROM STATION WHERE LONG_W < 90;

COMMIT WORK;

SELECT * FROM STATION;

SELECT * FROM STATS;

SELECT * FROM METRIC_STATS;

Chapter 7/66 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

http://www.mysql.com/doc/en/Tutorial.html

CREATE TABLE animals (

id MEDIUMINT NOT NULL AUTO_INCREMENT,

name CHAR(30) NOT NULL,

PRIMARY KEY (id)

);

INSERT INTO animals (name) VALUES ("dog"),("cat"),("penguin"),

("lax"),("whale"),("ostrich");

SELECT * FROM animals;

CREATE TABLE shop (

article INT(4) UNSIGNED ZEROFILL DEFAULT '0000' NOT NULL,

dealer CHAR(20) DEFAULT '' NOT NULL,

price DOUBLE(16,2) DEFAULT '0.00' NOT NULL,

PRIMARY KEY(article, dealer));

INSERT INTO shop VALUES

(1,'A',3.45),(1,'B',3.99),(2,'A',10.99),(3,'B',1.45),(3,'C',1.69),

(3,'D',1.25),(4,'D',19.95);

SELECT * FROM shop;

Chapter 7/67 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

CREATE TABLE articles (

id INT UNSIGNED AUTO_INCREMENT NOT NULL PRIMARY KEY,

title VARCHAR(200),

body TEXT,

FULLTEXT (title,body)

);

INSERT INTO articles VALUES

(NULL,'MySQL Tutorial', 'DBMS stands for DataBase ...'),

(NULL,'How To Use MySQL Efficiently', 'After you went through a ...'),

(NULL,'Optimizing MySQL','In this tutorial we will show ...'),

(NULL,'1001 MySQL Tricks','1. Never run mysqld as root. 2. ...'),

(NULL,'MySQL vs. YourSQL', 'In the following database comparison ...'),

(NULL,'MySQL Security', 'When configured properly, MySQL ...');

SELECT * FROM articles

WHERE MATCH (title,body) AGAINST ('database');

Chapter 7/68 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

# What's the highest item number?

SELECT MAX(article) AS article FROM shop;

# Find number, dealer, and price of the most expensive article.

SELECT MAX(price) FROM shop;

SELECT article, dealer, price

FROM shop

WHERE price=19.95;

SELECT article, dealer, price

FROM shop

ORDER BY price DESC

LIMIT 1;

# What's the highest price per article?

SELECT article, MAX(price) AS price

FROM shop

GROUP BY article;

Chapter 7/69 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

CREATE TEMPORARY TABLE tmp (

article INT(4) UNSIGNED ZEROFILL DEFAULT '0000' NOT NULL,

price DOUBLE(16,2) DEFAULT '0.00' NOT NULL);

LOCK TABLES shop READ;

INSERT INTO tmp SELECT article, MAX(price) FROM shop GROUP BY article;

SELECT shop.article, dealer, shop.price FROM shop, tmp

WHERE shop.article=tmp.article AND shop.price=tmp.price;

UNLOCK TABLES;

DROP TABLE tmp;

SELECT article,

SUBSTRING( MAX( CONCAT(LPAD(price,6,'0'),dealer) ), 7) AS

dealer,

0.00+LEFT( MAX( CONCAT(LPAD(price,6,'0'),dealer) ), 6) AS price

FROM shop

GROUP BY article;

Chapter 7/70 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

# find the articles with the highest and lowest price

SELECT @min_price:=MIN(price),@max_price:=MAX(price) FROM shop;

SELECT * FROM shop WHERE price=@min_price OR price=@max_price;

# foreign keys

CREATE TABLE person (

id SMALLINT UNSIGNED NOT NULL AUTO_INCREMENT,

name CHAR(60) NOT NULL,

PRIMARY KEY (id)

);

CREATE TABLE shirt (

id SMALLINT UNSIGNED NOT NULL AUTO_INCREMENT,

style ENUM('t-shirt', 'polo', 'dress') NOT NULL,

color ENUM('red', 'blue', 'orange', 'white', 'black') NOT NULL,

owner SMALLINT UNSIGNED NOT NULL REFERENCES person(id),

PRIMARY KEY (id)

);

Chapter 7/71 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

INSERT INTO person VALUES (NULL, 'Antonio Paz');

INSERT INTO shirt VALUES

(NULL, 'polo', 'blue', LAST_INSERT_ID()),

(NULL, 'dress', 'white', LAST_INSERT_ID()),

(NULL, 't-shirt', 'blue', LAST_INSERT_ID());

INSERT INTO person VALUES (NULL, 'Lilliana Angelovska');

INSERT INTO shirt VALUES

(NULL, 'dress', 'orange', LAST_INSERT_ID()),

(NULL, 'polo', 'red', LAST_INSERT_ID()),

(NULL, 'dress', 'blue', LAST_INSERT_ID()),

(NULL, 't-shirt', 'white', LAST_INSERT_ID());

SELECT * FROM person;

SELECT * FROM shirt;

Chapter 7/72 Copyright © 2004

Database Processing: Fundamentals, Design, and Implementation, 9/e by David M. Kroenke

SELECT s.* FROM person p, shirt s

WHERE p.name LIKE 'Lilliana%'

AND s.owner = p.id

AND s.color <> 'white';

# unions

select id, style from shirt where color = 'blue' union select id,

style from shirt where color = 'orange'

# visits per day

CREATE TABLE t1 (year YEAR(4), month INT(2) UNSIGNED ZEROFILL,

day INT(2) UNSIGNED ZEROFILL);

INSERT INTO t1 VALUES(2000,1,1),(2000,1,20),(2000,1,30),(2000,2,2),

(2000,2,23),(2000,2,23);

SELECT year,month,BIT_COUNT(BIT_OR(1<<day)) AS days FROM t1

GROUP BY year,month;