Database Management Systems & Programming Faculty of Information & Media Studies Summer 2000 LIS 558 - Week 6 Structured Query Language

Database Management Systems & ProgrammingDatabase Management Systems & Programming

Faculty of Information & Media StudiesFaculty of Information & Media Studies

Summer 2000Summer 2000

LIS 558 - Week 6LIS 558 - Week 6

Structured Query Structured Query LanguageLanguage

Class OutlineClass Outline

SQL -- What is it?SQL -- What is it? Basic SQL select statementsBasic SQL select statements Using expressions and functions to convert Using expressions and functions to convert

data into informationdata into information Using multiple criteria for searchingUsing multiple criteria for searching Producing output in a specific orderProducing output in a specific order Providing summary data from groups of Providing summary data from groups of

recordsrecords Displaying data from more than one tableDisplaying data from more than one table Showing data that uses the results of Showing data that uses the results of

another query as criteriaanother query as criteria

SQL - Structured Query LanguageSQL - Structured Query Language

SQL is a non-procedural data access SQL is a non-procedural data access language that is used primarily in language that is used primarily in programming by embedding it in other programming by embedding it in other languageslanguages

SQL is not a user-level languageSQL is not a user-level language

SQL accepts one or more relations as input SQL accepts one or more relations as input and produces a single relation as outputand produces a single relation as output

SQL provides functions for SQL provides functions for data definitiondata definition (creates database and table structures), (creates database and table structures), data data managementmanagement (enter, edit, delete data), and (enter, edit, delete data), and data querydata query (convert data into information) (convert data into information)

SQLSQL

Developed in mid 1970s by IBM; endorsed by Developed in mid 1970s by IBM; endorsed by ANSI (American National Standards Institute) ANSI (American National Standards Institute) as the language of choice for manipulating as the language of choice for manipulating relational databasesrelational databases

Language used by DB2, SQL/DS, ORACLE, Language used by DB2, SQL/DS, ORACLE, INGRES, SYBASE, dBase, Paradox, Access INGRES, SYBASE, dBase, Paradox, Access (each with its own dialect)(each with its own dialect)

Computer systems are able to exchange data Computer systems are able to exchange data by passing SQL requests and responses to by passing SQL requests and responses to one anotherone another

General SQL Query SyntaxGeneral SQL Query Syntax

SELECTSELECT columns to extractcolumns to extract

FROMFROM tables containing tables containing columnscolumns

WHEREWHERE search criteria to restrictsearch criteria to restrict

rows that are returnedrows that are returned

GROUP BYGROUP BY summarizes query summarizes query results results by groupsby groups

HAVINGHAVING search criteria to restrict search criteria to restrict groups that are returnedgroups that are returned

ORDER BYORDER BY sorts results by one orsorts results by one or

more columnsmore columns

• Preceding is the order in which clauses should appear• Order of processing is as follows: From, Where, Group by, Having,

Order by, Select

required

optional, must be in this order if any or all are used

ProjectionsProjections

SELECTSELECT Name, Salary Name, Salary

FROM EmployeeFROM Employee

Employee

EmpID Name Office Salary27 Rodney Jones Toronto 300044 Goro Azuma Tokyo 150035 Francine Moire Brussels 250037 Anne Abel Tokyo 150099 Mary Chen Brussels 5000

SELECTSELECT Office, EmpID, Name Office, EmpID, Name


Name SalaryRodney Jones 3000Goro Azuma 1500Francine Moire 2500Anne Abel 1500Mary Chen 5000

Office EmpID NameToronto 27 Rodney JonesTokyo 44 Goro AzumaBrussels 35 Francine MoireTokyo 37 Anne AbelBrussels 99 Mary Chen

Unique ProjectionsUnique Projections

SELECT SELECT DISTINCTDISTINCT Name, Salary Name, Salary


Employee


SELECT SELECT DISTINCTDISTINCT Office, Salary Office, Salary


Name SalaryRodney Jones 3000Goro Azuma 1500Francine Moire 2500Anne Abel 1500Mary Chen 3000

Office SalaryToronto 3000Tokyo 1500Brussels 2500Brussels 3000

appears only once

SelectionsSelections

Employee


SELECT EmpID, Name, Office, SalarySELECT EmpID, Name, Office, Salary


WHEREWHERE Office = ‘Brussels’ Office = ‘Brussels’EmpID Name Office Salary

35 Francine Moire Brussels 250099 Mary Chen Brussels 5000

SELECT *SELECT *


WHEREWHERE Office = ‘Brussels’ Office = ‘Brussels’

Combining Selections and ProjectionsCombining Selections and Projections

SELECT Name, SalarySELECT Name, Salary


WHERE Office = ‘Brussels’WHERE Office = ‘Brussels’

Employee


Name SalaryFrancine Moire 2500Mary Chen 5000

SELECT Name, Office, SalarySELECT Name, Office, Salary


WHERE EmpID = 35WHERE EmpID = 35

Name Office SalaryFrancine Moire Brussels 2500

Single quotes necessary around text and dates (but not values) in

criteria.

Comparison Search ConditionsComparison Search Conditions

Equality and Inequality OperatorsEqual to =Not equal to <> (or !=)Greater than >Less than <Less than or equal to <=Greater than or equal to >=

Employee




WHERE Salary WHERE Salary >= >= 25002500

SELECT EmpID, Name, OfficeSELECT EmpID, Name, Office


WHERE Name WHERE Name <><> ‘Anne Abel’ ‘Anne Abel’

Name SalaryRodney Jones 3000Francine Moire 2500Mary Chen 5000

EmpID Name Office27 Rodney Jones Toronto44 Goro Azuma Tokyo35 Francine Moire Brussels99 Mary Chen Brussels

Comparison Search ConditionsComparison Search Conditions

Comparison Operators

Equal to any member of the list IN(list)

Greater than or equal to one value, and less than or equal to another

BETWEEN low AND high

Matches the following pattern LIKEa string of zero or more characters *a string of one character ?

Missing value IS NULLReverses preceding operators NOT

Examples of Search ConditionsExamples of Search Conditions



WHERE Office WHERE Office ININ (‘Brussels’, ‘Tokyo’) (‘Brussels’, ‘Tokyo’)



WHERE Salary WHERE Salary betweenbetween 2000 2000 andand 3000 3000



WHERE Name WHERE Name LikeLike ‘ ‘**am’am’



WHERE Name WHERE Name LikeLike ‘Ab ‘Ab??’’



WHERE Office WHERE Office is Nullis Null



WHERE Office WHERE Office NOT INNOT IN (‘Toronto’) (‘Toronto’)

Compound Comparison Search ConditionsCompound Comparison Search Conditions



WHERE WHERE ((Office IN (‘Brussels’, ‘Tokyo’) or Salary is NullOffice IN (‘Brussels’, ‘Tokyo’) or Salary is Null))and HireDate <= ‘7/15/99’and HireDate <= ‘7/15/99’



WHERE WHERE ((Salary between 2000 and 3000 and Office <> Salary between 2000 and 3000 and Office <> ‘Tokyo’‘Tokyo’)) or or ((Name like ‘Gor*’ and EmpID > 20Name like ‘Gor*’ and EmpID > 20))



WHERE Name NOT Like ‘*Abel’ WHERE Name NOT Like ‘*Abel’ andand Salary >= 3100 Salary >= 3100



WHERE Office IN (‘Toronto’) WHERE Office IN (‘Toronto’) oror Name = ‘Anne Abel’ Name = ‘Anne Abel’

when operators are combined, brackets are evaluated first (inner to outer)

AND means that ALL conditions must be metOR means that ANY condition may be met

SortingSorting



WHERE Office = ‘Tokyo’WHERE Office = ‘Tokyo’

ORDER BYORDER BY Salary, Name Salary, Name

Employee

EmpID Name Office Salary27 Rodney Jones Toronto 150044 Goro Azuma Tokyo 150035 Francine Moire Brussels 250037 Anne Abel Tokyo 300099 Mary Chen Tokyo 1500



WHERE Salary >= 2000WHERE Salary >= 2000

ORDER BY ORDER BY EmpID EmpID DESCDESC

Name SalaryGoro Azuma 1500Mary Chen 1500Anne Abel 3000

Name Office SalaryAnne Abel Tokyo 3000Francine Moire Brussels 2500

Expressions using ArithmeticExpressions using Arithmetic

SELECT Name, Salary, SELECT Name, Salary, Commission/SalaryCommission/Salary

FROM SalespersonFROM Salesperson

WHERE WHERE Commission > .05*SalaryCommission > .05*Salary

SELECT ContactName, CompanyNameSELECT ContactName, CompanyName

FROM CustomerFROM Customer

WHERE Paid is null and OrderDate >= ‘1/1/99’WHERE Paid is null and OrderDate >= ‘1/1/99’

ORDER BY ORDER BY Date-InvoiceDateDate-InvoiceDate

SELECT ItemName, SELECT ItemName, Price*1.15Price*1.15

FROM ProductFROM Product

SELECT Name, SELECT Name, (Date-Birthdate)/365(Date-Birthdate)/365


ORDER BY NameORDER BY Name

SELECT EmpID, SELECT EmpID, Hiredate+90Hiredate+90


ORDER BY NameORDER BY Name

current system date

SQL Built-in FunctionsSQL Built-in Functions

SELECT SELECT Count(*)Count(*)FROM EmployeeFROM Employee

Count(*)5

SELECT SELECT Count(Distinct Office)Count(Distinct Office)FROM EmployeeFROM Employee

CountDistinctOffice

3

SELECT SELECT Sum(Salary)Sum(Salary)FROM EmployeeFROM Employee

SumOfSalary13500

SELECT SELECT Max(HireDate)Max(HireDate)FROM EmployeeFROM Employee

MaxOfHireDate1-Aug-97

SELECT SELECT Min(Name)Min(Name)FROM EmployeeFROM Employee

MinOfNameAnne Abel

SELECT SELECT Avg(Salary)Avg(Salary)FROM EmployeeFROM Employee

AvgOfSalary2700

Employee

EmpID Name Office Salary HireDate27 Rodney Jones Toronto 3000 12-May-9244 Goro Azuma Tokyo 1500 15-Mar-9335 Francine Moire Brussels 2500 22-Dec-8937 Anne Abel Tokyo 1500 1-Aug-9799 Mary Chen Tokyo 5000 17-Aug-95

Aggregate Functions and GroupingAggregate Functions and Grouping

Employee

EmpID Name Office Salary Status HireDate27 Rodney Jones Brussels 3000 part time 12-May-9244 Goro Azuma Tokyo 4000 full time 15-Mar-9335 Francine Moire Brussels 2500 full time 22-Dec-8937 Anne Abel Tokyo 2000 full time 1-Aug-9799 Mary Chen Tokyo 5000 full time 17-Aug-95

SELECT Office, Count(*)SELECT Office, Count(*)


GROUP BYGROUP BY Office Office

Office Count(*)Brussels 2Tokyo 3

SELECT Office, Status, Max(Salary)SELECT Office, Status, Max(Salary)


GROUP BYGROUP BY Office, Status Office, Status

Office Status MaxOfSalaryBrussels full time 2500Brussels part time 3000Tokyo full time 5000

To view the groupings, you must also select them!

More Grouping FunctionsMore Grouping Functions

SELECT Category, Avg(Price), Min(Quantity), SELECT Category, Avg(Price), Min(Quantity), Sum(Price*Quantity)Sum(Price*Quantity)


WHERE SupplierID in (1, 2) or SupplierID is nullWHERE SupplierID in (1, 2) or SupplierID is null

GROUP BYGROUP BY Category Category

ORDER BY ORDER BY Avg(Price)Avg(Price)

Category AvgOfPrice MinOfQuantity SumOfPriceQuantityAccessories 41.2 5 449.5Components 428.3 2 3850

Product

ProdID ProdDesc Category Price Quantity SupplierID

801 Shur-Lock U-Lock Accessories 75.00 5 2

802 SpeedRite CyclecomputerComponents 60.00 20 1

803 SteelHead Microshell HelmetAccessories 40.00 40 3

804 SureStop 133-MB BrakesComponents 25.00 10 2

805 Diablo ATM Mountain BikeComponents 1,200.00 2 2

806 Ultravision Helmet Mount MirrorsAccessories 7.45 10

Restrict Groups with “Having”Restrict Groups with “Having”

SELECT Category, Avg(Price), Min(Quantity), SELECT Category, Avg(Price), Min(Quantity), Sum(Price*Quantity)Sum(Price*Quantity)


WHERE SupplierID in (‘1’, ‘2’) or SupplierID is nullWHERE SupplierID in (‘1’, ‘2’) or SupplierID is null

GROUP BYGROUP BY Category Category

HAVINGHAVING Min(Quantity) < 5 Min(Quantity) < 5

Category AvgOfPrice MinOfQuantity SumOfPriceQuantityComponents 428.3 2 3850

Product

ProdID ProdDesc Category Price Quantity SupplierID





805 Diablo ATM Mountain BikeComponents 1,200.00 2 2

806 Ultravision Helmet Mount MirrorsAccessories 7.45 10

The ‘WHERE’ clause is always evaluated before the ‘HAVING’ clause.

Another ‘Having’ exampleAnother ‘Having’ example

Employee

EmpID Name Office Salary Status HireDate27 Rodney Jones Brussels 3000 part time 12-May-9244 Goro Azuma Tokyo 4000 full time 15-Mar-9335 Francine Moire Brussels 2500 full time 22-Dec-8937 Anne Abel Tokyo 2000 full time 1-Aug-9799 Mary Chen Tokyo 5000 full time 17-Aug-9525 Brigit Sanchez Toronto 10000 full time 3-Jan-0010 Joki Singh Brussels 1000 full time 3-Jan-00

SELECT Office, Max(Salary)SELECT Office, Max(Salary)


WHERE Status = ‘full-time’WHERE Status = ‘full-time’

GROUP BYGROUP BY Office Office

HAVINGHAVING Count(*) > 1 Count(*) > 1

ORDER BY OfficeORDER BY Office

Office MaxOfSalaryBrussels 2500Tokyo 5000

SubqueriesSubqueries

Supplier

SupplierID SupplierName City1 Bikes-R-Us London2 Small moter suppliersToronto3 All Bikes AllwaysLondon

Product

ProdID ProdDesc Category Price Qty SupID

801 Shur-Lock U-LockAccessories 75 5 2

802 SpeedRite CyclecomputerComponents 60 20 1

803 SteelHead Microshell HelmetAccessories 40 40 3

804 SureStop 133-MB BrakesComponents 25 10 2

805 Diablo ATM Mountain BikeAccessories1,200 2 2

SELECT ProdID, Price, QtySELECT ProdID, Price, Qty


WHERE SupID WHERE SupID ININ

(SELECT SupplierID(SELECT SupplierID

FROM SupplierFROM Supplier

WHERE City = ‘London’) WHERE City = ‘London’)

ProdID Price Qty

802 60 20

803 40 40

Subquery is always evaluated before the main query.

SELECT ProdIDSELECT ProdID


WHERE Qty > WHERE Qty >

(SELECT Avg(Qty)(SELECT Avg(Qty)


WHERE SupID IN (‘1’, ‘2’))WHERE SupID IN (‘1’, ‘2’))

ProdID

802

804

Nested SubqueriesNested Subqueries

SELECT Count(Unique PolicyNum)FROM PolicyPlanWHERE PlanCode = ‘45’ and PolicyNum

IN(SELECT PolicyNumFROM CommissionWHERE AgentNum IN

(SELECT AgentNumFROM AgentWHERE Area = 100))

Agent

AgentID AgentName Area1 Anne Abel 1002 Goro Azuma 2003 Mary Chen 100

Commission

AgentID PolicyNo. Comm1 5 5%1 9 7%3 3 3%2 7 5%

PolicyPlan

PlanCodePolicyNo. Category45 3 FG98 5 SR45 9 JR45 9 FR

CountOfPolicyNo.2

Determine the number of policies sold in area 100 of type 45:

Product






805 Diablo ATM Mountain BikeAccessories 1,200.00 2 2

Join (Natural Join)Join (Natural Join)

Supplier

SupplierID SupplierName1 Bikes-R-Us2 Small moter suppliers3 All Bikes Allways

SELECT SELECT ProductProduct ProdID, ProdID, ProductProduct ProdDesc, ProdDesc, SupplierSupplier SupplierNameSupplierName

FROMFROM Product, Supplier Product, Supplier

WHEREWHERE Product Product SupID = SupplierSupID = Supplier SupplierID SupplierID

ProdID ProdDesc SupplierName

801 Shur-Lock U-Lock Small motor suppliers

802 SpeedRite Cyclecomputer Bikes-R-Us

803 SteelHead Microshell Helmet All Bikes Allways

804 SureStop 133-MB Brakes Small motor suppliers

805 Diablo ATM Mountain Bike Small motor suppliers

Table names required in Select statement only if there’s a possibility of ambiguity

Renaming Attributes and Relations with an AliasRenaming Attributes and Relations with an Alias

Supplier

SupplierID SupplierName1 Bikes-R-Us2 Small moter suppliers3 All Bikes Allways

Product





804 SureStop 133-MB BrakesAccessories 25.00 10 2

805 Diablo ATM Mountain BikeBike 1,200.00 2 2

SELECT SupplierName, avg(price) As SELECT SupplierName, avg(price) As “Average Price”“Average Price”, count(*) As , count(*) As “# of Items”“# of Items”

FROM Product FROM Product PP, Supplier , Supplier SS

WHERE WHERE PP SupID = SupID = SS SupplierIDSupplierIDand Category = ‘Accessories’and Category = ‘Accessories’

GROUP BY SupplierNameGROUP BY SupplierName

ORDER BY SupplierIDORDER BY SupplierID

SupplierName Average Price # of ItemsSmall motor suppliers 50 2All Bikes Allways 40 1

alias

‘‘Exists’ and ‘not exists’ in SubqueriesExists’ and ‘not exists’ in SubqueriesEmployee

EmpID Name Office Sex27 Rodney Jones Brussels M44 Goro Azuma Tokyo M35 Francine Moire Brussels F

Dependent

EmpID DepName DepSex27 Jane Jones F27 Jenny Jones F35 Mary Moire F35 Melvin Moire M35 Minnie Moire F

SELECT NameFROM Employee EWHERE EXISTS

(SELECT *FROM Dependent DWHERE E.EmpID =

D.EmpIDand E.Sex = D.DepSex)Name

Francine Moire

Which employees have dependents of the same sex as themselves? Which employees have no

dependents?SELECT NameFROM Employee EWHERE NOT EXISTS

(SELECT *FROM Dependent DWHERE E.EmpID =

D.EmpID)NameGoro Azuma

Documents

Database Management Systems & Programming Faculty of Information & Media Studies Summer 2000 LIS 558 - Week 6 Structured Query Language