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;
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