1. Lecture 3 : Structured Query Language (SQL)
MSc IT UFIE8K-15-M Data Management Prakash Chatterjee Room 3P16
Lecture 3 : Structured Query Language (SQL)

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Origins & history
Early 1970’s – IBM develops Sequel as part of the System R project at its San Hose Research Lab;
ANSI & ISO publish the standard SQL-86;
1987 – IBM publishes its own “standard” SQL called Systems Architecture Database Interface (SAA-SQL);
1989 – SQL-89 published by ANSI (extended version of SQL-86);
1992 – SQL-92 published with better support for algebraic operations;
1999 – SQL-1999 published with support for typing, stored procedures, triggers, BLOBs etc.
SQL-92 remains the most widely implemented standard
– and most database vendors also provide their own (proprietary) extensions.
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Components of SQL
The SQL language has several parts:
Data-definition language (DDL). The SQL DDL provides commands for defining relation schemas, deleting relations, and modifying relation schemas.
Interactive data-manipulation language (DML). The SQL DML includes a query language based on both the relational algebra and the tuple relational calculus. It includes also commands to insert tuples into, delete tuples from, and modify tuples in the database.
View definition. The SQL DDL includes commands for defining views.
Transaction control. SQL includes commands for specifying the beginning and ending of transactions.
Embedded SQL and dynamic SQL. Embedded and dynamic SQL define how SQL statements can be embedded within general-purpose programming languages, such as C, C++, Java, PL/I, Cobol, Pascal, and Fortran.
Integrity. The SQL DDL includes commands for specifying integrity constraints that the data stored in the database must satisfy. Updates that violate integrity constraints are disallowed.
Authorization. The SQL DDL includes commands for specifying access rights to relations and views.
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SQL Example (1)
The Supplier-and-Parts Database sp
sno
pno
qty s1 p1
300 p2
200 p3
400 p4 p5
100 p6 s2 s3 s4 s
sno
sname
status
city s1
Smith 20
London s2
Jones 10
Paris s3
Blake 30 s4
Clark s5
Adams
Athens p
pno
pname
colour
weight
city p1
Nut
Red
12.0
London p2
Bolt
Green
17.0
Paris p3
Screw
Blue
Oslo p4
14.0 p5
Cam p6
Cog
19.0
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SQL Example (2)
Project the columns
renamed columns:
SELECT sname FROM s
SELECT sname AS Supplier,
status * 5 AS 'Status times Five'
FROM s
sname
Smith
Jones
Blake
Clark
Adams
computed columns:
SELECT sname, status * 5 FROM s
Supplier
Status times Five
Smith
100
Jones 50
Blake
150
Clark
Adams
sname
status * 5
Smith
100
Jones 50
Blake
150
Clark
Adams
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SQL Example (3)
Restrict the rows
SELECT * FROM s
WHERE city=‘London’
complex condition:
SELECT * FROM s
WHERE city=‘London’ OR status = 30
sno
sname
status
city s1
Smith 20
London s4
Clark
sno
sname
status
city s1
Smith 20
London s3
Blake 30
Paris s4
Clark s5
Adams
Athens
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SQL Example (4)
Restrict & Project
SELECT city FROM s WHERE sname='smith' OR status='20'
city
London
remove duplicate rows:
SELECT DISTINCT city FROM s WHERE sname='smith' OR status='20'
city
London
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SQL Example (4)
Group By and Having
Use the ‘GROUP BY’ clause to aggregate related rows
SELECT city, SUM(status) AS 'Total Status' FROM s GROUP BY city
city
Total Status
Athens 30
London 40
Paris
Use the ‘HAVING’ clause to restrict rows aggregated with ‘GROUP BY’
SELECT city, SUM(status) AS 'Total Status' FROM s GROUP BY city HAVING SUM(status) > 30
city
Total Status
London 40
Paris
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SQL Functions
SQL provides a wide range of predefined functions to perform manipulation of data.
Four types of functions
arithmetic (sqrt(), log(), mod(), round() …)
date (sysdate(), month(), dayname() …)
character (length(), lower(), upper()…)
aggregate (min(), max(), avg(), sum() …)
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Joins (1)
The m-f Database m f id
name
age 1
tom 23 2
dick 20 3
harry 30 id
name
age 1
mary 23 2
anne 30 3
sue 34
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Joins (3)
Product (or Cartesian Product)
SELECT * FROM m, f id
name
age 1
tom 23
mary 2
dick 20 3
harry 30
anne
sue 34
Synonymous with the CROSS JOIN, hence:
SELECT * FROM m CROSS JOIN f;
would return the same result. This is not very useful but is the basis for all other joins.
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Joins (4)
Natural join
Joins tables using some shared characteristic – usually (but not necessarily) a foreign key.
SELECT * FROM m,f WHERE m.age = f.age id
name
age 1
tom 23
mary 3
harry 30 2
anne
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Joins (5)
Inner joins
The previous example, besides being a natural join, is also an example of an inner join. An inner join retrieves data only from those rows where the join condition is met.
SELECT * FROM m,f WHERE m.age > f.age id
name
age 3
harry 30 1
mary 23
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Joins (6)
Outer joins
Unmatched rows can be included in the output using as outer join.
Left outer join:
SELECT * FROM m LEFT OUTER JOIN f ON m.age = f.age id
name
age 1
tom 23
mary 2
dick 20
NULL 3
harry 30
anne
Right outer join:
SELECT * FROM m RIGHT OUTER JOIN f ON m.age = f.age id
name
age 1
tom 23
mary 3
harry 30 2
anne
NULL
sue 34
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Joins (7)
Self Join
Special case of the inner join – here the table employee shows employees and their managers. Ruth manages Joe who manages Tom, Dick and Harry.
emp_id
emp_name
mgr_id 1
Tom 4 2
Dick 3
Harry
Joe 5
Ruth
NULL
Show who manages who by name:
Employee
Manager
Tom
Joe
Dick
Harry
Ruth
SELECT E1.emp_name AS Employee, E2.emp_name AS Manager FROM employee AS E1 INNER JOIN employee AS E2 ON E1.mgr_id = E2.emp_id
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16. Bibliography / Readings / Home based activities
An Introduction to Database Systems (8th ed.), C J Date, Addison Wesley 2004
Database Management Systems, P Ward & G Defoulas, Thomson 2006
Database Systems Concepts (4th ed.), A Silberschatz, H F Korth & S Sudarshan, McGraw-Hill 2002
Readings
Introduction to SQL’ McGraw-Hill/Osbourne (handout)
Home based activities
Ensure you download xampp and install on home PC or laptop (if you have a slow home internet connection – download to data key or CD here at UWE)
Copy the SQL Workbook onto your data key or CD.
Import the tables from the SQL Workbook into your home MySQL DB. Begin working through some of the query examples in the workbook using PHPMyAdmin.
UFIE8K-15-M Data Management 2011