lecture05sql-100311002645-phpapp02

8/8/2019 lecture05sql-100311002645-phpapp02

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2 December 2005

Introduction to Databases

Structured Query Language

Prof. Beat Signer

Department of Computer ScienceVrije Universiteit Brussel

http://vub.academia.edu/BeatSigner


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Beat Signer - Department of Computer Science - [email protected] 2March 11, 2010

Context of Today's Lecture

AccessMethods

SystemBuffers

AuthorisationControl

IntegrityChecker

CommandProcessor

ProgramObject Code

DDLCompiler

FileManager

BufferManager

RecoveryManager

Scheduler

QueryOptimiser

TransactionManager

QueryCompiler

Queries

CatalogueManager

DMLPreprocessor

DatabaseSchema

ApplicationPrograms

Database andSystem Catalog

DatabaseManager

DataManager

DBMS

Programmers Users DB Admins

Based on 'Components of a DBMS', Database Systems,

T. Connolly and C. Begg, Addison-Wesley 2010


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Structured Query Language (SQL)

Declarative query languageto create database schemas,insert, update and query information based on a datadefinition and data manipulation language

Data definition language (DDL) definition of database structure

data access control

Data manipulation language (DML)

query language to read data as well as commands to create,update and delete tuples (CRUD operations)

Transaction control

Embedded SQL and dynamic SQL


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History of SQL ...

SQL:2003 window functions, XML-related features, ...

SQL:2006 XML Query Language (XQuery) support, ...

SQL:2008


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SQL "Standard"

Each specific SQL implementation by a database vendoris called a dialect

The vendors implement parts of the SQL standard

(e.g. most implement SQL-92) but add their vendorspecific extensions

Most relational database vendors conform to a set ofCore SQL features but portability might still be limited

due to missing or additional features We will use the Extended BackusNaur Form (EBNF) to

describe different SQL concepts http://en.wikipedia.org/wiki/Extended_Backus-Naur_Form


7/59Beat Signer - Department of Computer Science - [email protected] 7March 11, 2010

Data Definition Language (DDL)

The data definition language (DDL) is used to specify therelation schemas as well as other information about therelations

relation schemas attribute domain types

integrity constraints

relation indices

access information

physical storage structure of relations



Database Creation

The concrete process of creating a new database mightdiffer for different relational database products

According to the SQL standard, an SQL environment

contains one ore more catalogues

Each catalogue manages various metadata set of schemas consisting of

- tables

- views- assertions

- indexes

users and user groups



Database Creation ...

The creation of catalogues is not covered by the SQLstandard and therefore implementation specific

Schemas can be created and deleted via the CREATE and

DROP statements

The default parameter in the DROP SCHEMA statement isRESTRICT only empty schema can be deleted

If CASCADE is specified, all objects associated with theschema will be dropped

createSchema = "CREATE SCHEMA" , name , "AUTHORIZATION" , creator ,[ ddlStatements ];

dropSchema = "DROP SCHEMA" , name , [ "RESTRICT" | "CASCADE" ];



Table Definition

createTable = "CREATE TABLE" , table , "(" ,( columnElement | tableConstraint ) ,{ "," , ( columnElement | tableConstraint ) } , ")";

columnElement = column , datatype ,

[ "DEFAULT" , ( value | "NULL" ) ] , { columnConstraint };

columnConstraint = "NOT NULL" | "UNIQUE" | "PRIMARY KEY" |( "REFERENCES" , table , [ "(" , column , ")" ] ,{ referentialAction } ) |

( "CHECK (" , searchCondition , ")" );

tableConstraint = ( ( "UNIQUE" | "PRIMARY KEY ) , "(" , column ,

{ "," , column } , ")" ) |( "FOREIGN KEY (" , column , { "," , column } , ")" ,"REFERENCES" , table , [ "(" , column , { "," , column } , ")" ] ,{ referentialAction } ) |

( "CHECK (" , searchCondition , ")" );



Table Definition ...

referentialAction = ( "ON UPDATE" | "ON DELETE" ) ,( "CASCADE" | "SET DEFAULT" | "SET NULL" | "NO ACTION" );



Table Constraints

We can have only one PRIMARY KEY constraint butmultiple UNIQUE constraints if no primary key is defined, duplicates are allowed (bag)

Referential integrity a foreign key always has to have a matching value in the

referenced table (or it can be null)

different referential actionscan be defined for update (ON UPDATE)and delete (ON DELETE) operations on the referenced candidate

key- CASCADE: propagate operations to the foreign keys which might lead to further

cascaded operations

- SET DEFAULT: set the foreign keys to their default value

- SET NULL: set the foreign keys to NULL

- NO ACTION: the operation on the candidate key will be rejected (default)



SQL Datatypes

Boolean the domain of boolean values consist of the two truth values TRUE

and FALSE

a thrid UNKNOWN truth value is used to represent NULL values

Bit data

fixed or varying sequence of binary digits (0 or 1)

boolean = "BOOLEAN";

bit = fixedBit | varyingBit;fixedBit = "BIT" , [ "(" , length , ")" ];varyingBit = "BIT VARYING" , [ "(" , length , ")" ];



SQL Datatypes ...

Character data fixed or varying sequence of characters

CHAR always requires the fixed number of characters

Large character data or binary data

char = fixedChar | varyingChar;fixedChar = "CHAR" , [ "(" , length , ")" ];varyingChar = "VARCHAR" , [ "(" , length , ")" ];

lob = clob | blob;clob = "CLOB" , [ "(" , size , ")" ];blob = "BLOB" , [ "(" , size , ")" ];



SQL Datatypes ...

Numeric data

The DECIMAL datatype is sometimes used as synonym for

the NUMERIC datatype

numeric = decimal | int | smallInt | float | real | double;decimal = "DECIMAL" , [ "(" ,precision , [ "," , scale ] , ")" ];int = "INTEGER";

smallInt = "SMALLINT";float = "FLOAT" , [ "(" , precision , ")" ];real = "REAL";double = "DOUBLE PRECISION";



SQL Datatypes ...

Datetime data

Format of the datetime values

date: YYYY-MM-DD time: hh:mm:ss.p hh:mm

timestamp: YYYY-MM-DD hh:mm:ss.p hh:mm

datetime = date | time | timestamp;date = "DATE";time = "TIME" , [ "(" ,precision , ")" ] ,

[ "WITH TIME ZONE" , timezone ];timestamp = "TIMESTAMP" , [ "(" ,precision , ")" ] ,[ "WITH TIME ZONE" , timezone ];



Example Database

cdID name duration price year

93 Falling into Place 2007 17.90 2007

117 Moudi 3156 15.50 1996

3 Chromatic 3012 16.50 1996

customerID name street postcode city

1 Urs Frei Bahnhofstrasse 7 8001 Zurich

2 Pieter de Rover Pleinlaan 25 1050 Brussels

5 Robert Michelin 12 Rue Louise 75008 Paris

53 Beat Meier Bergstrasse 18 8037 Zurich

8 Urs Frei ETH Zentrum 8092 Zurich

customer

cd



Example Database

orderID customerID cdID date amount status

1 53 93 13.02.2010 2 open

2 2 117 15.02.2010 1 delivered

order

supplierID name postcode city

5 Urs Frei 8040 Zurich

2 Franz Hohler 5000 Aarau

supplier

Customer (customerID, name, street, postcode, city)CD (cdID, name, duration, price, year)Order (orderId, customerID, cdID, date, amount, status)Supplier (supplierID, name, postcode, city)

relational database schema



Table Definition Example

CREATE TABLE Customer (customerID INTEGER CHECK (customerID > 0) PRIMARY KEY,name VARCHAR(30) NOT NULL,street VARCHAR(30) NOT NULL,postcode SMALLINT CHECK (postcode > 0),

city VARCHAR(20));

CREATE TABLE CD (cdID INTEGER PRIMARY KEY,name VARCHAR(30) NOT NULL,duration TIME,price NUMERIC(6,2),

year SMALLINT);



Table Definition Example ...

CREATE TABLE Supplier (supplierID INTEGER PRIMARY KEY,name VARCHAR(30) NOT NULL,postcode SMALLINT CHECK (postcode > 0),city VARCHAR(20)

);

CREATE TABLE Order (orderID INTEGER CHECK (orderID > 0) PRIMARY KEY,customerID INTEGER,cdID INTEGER ,date DATE,amount INTEGER,

Status VARCHAR(20) NOT NULL DEFAULT 'open',UNIQUE (customerID, cdID, date),FOREIGN KEY (customerID) REFERENCES Customer(customerID)ON UPDATE CASCADE ON DELETE SET NULL,

FOREIGN KEY (cdID) REFERENCES CD(cdID)ON UPDATE CASCADE

);


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Data Manipulation

After a table has been created, we can use the INSERTcommand to add tuples unspecified attribute values are set to the default value or NULL

Example

The DELETE statement can be used to delete tuples

INSERT INTO Customer VALUES(8, 'Urs Frei', 'ETH Zentrum', 8001, 'Zurich');

insert = "INSERT INTO" , table ,[ "(" , column , { "," , column } , ")" ] ,( "VALUES (" , expr , { "," , expr } , ")" ) | ( "(" , query , ")" );

delete = "DELETE FROM" , table [ "WHERE" , searchCondition ];


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Data Manipulation ...

Tuples can be updated via the UPDATE statement

Example

The DROP TABLE statement can be used to delete arelation from the database

UPDATE Customer SET name = 'Peter Frei' WHERE customerID = 8;

update = "UPDATE" , table , "SET" ,column , "=" , ( "NULL" | expr | "(" , query , ")" ) ,{ "," , column , "=" , ("NULL" | expr | "(" , query , ")" ) } ,

[ "WHERE" , searchCondition ];

dropTable = "DROP TABLE" , table;


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A relation schema can be modified via the ALTER TABLEcommand

Example

alterTable = "ALTER TABLE" , table , "ADD" ,

( columnElement | columnConstraint );

ALTER TABLE Customer ADD birthdate DATE;


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The CREATE INDEX statement can be used to create anindex an index provides fast access to data without reading the whole

relation

the selection of the best index attributes is very challenging- tradeoff between the faster access to indexed data and the additional effort to

maintain the indices when updating or inserting new data

Example

createIndex = "CREATE INDEX" , name , "ON" , table, "(" , column ,{ "," , column} , ")";

CREATE INDEX nameIndex ON Customer (name);


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Expressions

expr = exprElement { ( "+" | "-" | "*" | "/" ) , exprElement };

exprElement = column | value |"COUNT" , "(" ( "*" | ( [ "ALL" | "DISTINCT" ] , column ) , ")" |( "MIN" | "MAX" ) , "(" , expr , ")" |( "SUM" | "AVG" ) , "(" , [ "DISTINCT" ] , expr , ")";


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SELECT Clause

The SELECT statement can be used to retrieveinformation from one or multiple database tables can perform the relational algebra's selection, projectionandjoin

operation in a single SELECT command

query = select { ("UNION" | "INTERSECT" | "EXCEPT") , [ "ALL" ] , select};

select = "SELECT" [ "ALL" | "DISTINCT" ] ,("*" | ( expr , [ "AS" , newName ] ,{ "," , expr , [ "AS" , newName ] } ) ,

"FROM" , table , [ correlationVar ] ,

{ "," , table , [ correlationVar ] } ,[ "WHERE" , searchCondition ] ,[ "GROUP BY" , column , { "," , column } ,[ "HAVING" , searchCondition ] ];

orderedQuery = query , "ORDER BY" , column , [ "ASC" | "DESC" ] ,{ "," , column , [ "ASC" | "DESC" ] };


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SELECT Clause ...

searchCondition = [ "NOT" ] , search ,{ ( "AND" | "OR" ) , [ "NOT" ] , search };

search = ( expr , [ "NOT" ] , "BETWEEN" , expr , "AND" , expr ) |( expr , [ "NOT" ] , "LIKE" , "'" , ( string | "_" | "%" ) ,{ string | "_" | "%" } , "'" ) |

( column | ( "(" , expr , ")" ) , "IS" , [ "NOT" ] , "NULL" ) |( expr , ( "=" | "" | ">" | ">=" | "


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SELECT Clause ...

The SELECT statement contains the following maincomponents SELECT

- specifies the columns to appear in the result (projection in relational algebra)

FROM

- specifies the relations to be used (cartesian product in relational algebra)

WHERE

- filters the tuples (selection in relational algebra)

- join conditionsare explicitly specified in the WHERE clause

GROUP BY

- groups rows with the same column values

- the HAVING construct can be used to further filter the groups

ORDER BY

- defines the order of the resulting tuples


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SELECT Clause ...

The orderof clauses in the SELECT statement cannot bechanged

Note that the SELECT is equivalent to a relational algebra

projection

In contrast to the relational algebra, SQL does noteliminate duplicates automatically the automatic elimination of duplicates is time consuming

user has to eliminate duplicates explicitly via DISTINCT keyword

SELECT A1, A2,..., AnFROM r1, r2,..., rmWHERE P

pA1,A2,...,An(sP(r1 r2 ... rm)is equivalent to


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SELECT Clause ...

A '*' can be used in the SELECT clause as a shortcut toget all tuple attributes

SELECT *FROM Customer;


1 Urs Frei Bahnhofstrasse 7 8001 Zurich2 Pieter de Rover Pleinlaan 25 1050 Brussels

5 Robert Michelin 12 Rue Louise 75008 Paris




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SELECT Clause ...

Duplicate tuplesresulting from a projection to specificattributes are not eliminated by default

SELECT nameFROM Customer;

name

Urs FreiPieter de Rover

Robert Michelin

Beat Meier

Urs Frei


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SELECT Clause ...

The DISTINCT keyword can be used to eliminateduplicates

SELECT DISTINCT nameFROM Customer;

name

Urs FreiPieter de Rover

Robert Michelin

Beat Meier


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Computed Attributes and Rename

Computations can be performed in the SELECT clause

multiple numeric attributescan be used in a computation The rename operation(AS) is used to rename relations

as well as attributes computed column has no name by default

also used when multiple relations have the same attribute names

SELECT name,price * 1.5 AS newPriceFROM CD;

name newPrice

Falling into Place 26.85Moudi 23.20

Chromatic 24.75


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WHERE Clause

In the WHERE clause we can use five basic predicates(search conditions) comparison

- compare two expressions

range- check whether the value is within a specified range of values (BETWEEN)

set membership- check whether the value is equal to a value of a given set (IN)

pattern matching- test whether the expression matches a specifies string pattern (LIKE)

check forNULL values- check whether the expression is a NULL value (IS NULL)


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WHERE Clause ...

SELECT name, postcodeFROM CustomerWHERE city = 'Zurich' AND postcode >= 8040;

name postcode

Urs Frei 8092

SELECT name, priceFROM CDWHERE price BETWEEN 15.0 AND 17.0;

name price

Moudi 15.50

Chromatic 16.50


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WHERE Clause ...

Check for set membership with the IN construct

SELECT *FROM CustomerWHERE city IN ('Zurich', 'Brussels');


1 Urs Frei Bahnhofstrasse 7 8001 Zurich

2 Pieter de Rover Pleinlaan 25 1050 Brussels




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Pattern Matching

Strings are enclosed in single quotes use a double single quote for escaping

The LIKE operator is used for pattern matching

the underscore(_) is a placeholder for a single character the percentsign (%) is a placeholder for any substring

e.g. LIKE '_e%'

name

Urs Frei

Beat Meier

SELECT DISTINCT nameFROM CustomerWHERE name LIKE '%ei%';


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Null Values

In SQL missing (unknown) information is represented byNULL values three-valued logic (3VL) based on True, False and Unknown

True False Unknown

True True False Unknown

False False False False

Unknown Unknown False Unknown

ANDTrue False Unknown

True True True True

False True False Unknown

Unknown True Unknown Unknown

OR

=

True False Unknown

True True False Unknown

False False True Unknown

Unknown Unknown Unknown Unknown

NOT

True False Unknown

False True Unknown


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Null Values ...

The NULL keyword can also be used in predicates tocheck for null values

Note that a check for NULL is not the same as a check forthe empty String ''

SELECT *FROM CD

WHEREprice IS NOT NULL;


1 Falling into Place 2007 17.90 2007

2 Moudi 3156 15.50 1996

3 Chromatic 3012 16.50 1996


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FROM Clause

The FROM clause creates a cartesian product of multiplerelations and can be used to specifyjoin operations

In a previous lecture we have seen the following

relational algebra expression- "list the name and street of customers whose order is still open"

- pname, street(sstatus="open"(order customer))

- the same can be achieved in SQL by explicitly specifying the matching attributes

SELECT name, streetFROM Customer, OrderWHERE Order.customerID = Customer.customerID AND status = 'open';

name street

Beat Meier Bergstrasse 18


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Inner and Outer Joins

Note that there exist SQL extensions to perform joinoperations between two relations R and S in the FROM

clause

Inner Joins

Outer Joins

SELECT * FROM R NATURAL JOIN S;SELECT * FROM R CROSS JOIN S;SELECT * FROM R JOIN S ON R.A > S.B;

SELECT * FROM R LEFT OUTER JOIN S ON R.A = S.B;SELECT * FROM R RIGHT OUTER JOIN S ON R.A = S.B;SELECT * FROM R FULL OUTER JOIN S ON R.A = S.B;


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Correlation Variable

A correlation variable can be used as an alias for a table

Example "Find all pairs of CDs that were produced in the same year"

SELECT c1.name AS name1, c2.name AS name2FROM CD c1, CD c2WHERE c1.year = c2.year AND c1.cdID < c2.cdID;

name1 name2

Moudi Chromatic


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Sorting

The ORDER BY clause can be used to arrange the resulttuples in acending (ASC) or descending (DESC) order multiple sort keys can be specified; highest priority first

tuples with NULL values are either before or after non-NULL tuples

SELECT name, street, cityFROM CustomerORDER BY city ASC, name DESC;

name street city

Pieter de Rover Pleinlaan 25 Brussels

Robert Michelin 12 Rue Louise Paris

Urs Frei ETH Zentrum Zurich

Urs Frei Bahnhofstrasse 7 Zurich

Beat Meier Bergstrasse 18 Zurich


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Set Operations

The UNION, INTERSECT and EXCEPT operations correspondto the , and - relational algebra operations the relations have to be compatible (same attributes)

these operations remove duplicates by default- the ALL keyword has to be used to retain duplicates

(SELECT nameFROM Customer)INTERSECT(SELECT nameFROM Supplier);

name

Urs Frei


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Aggregate Functions and Grouping

In SQL there are five aggregate functions (MIN, MAX, AVG,SUM and COUNT) that take a set or multiset of values asinput and return a single value

Example "Find the number of customers in each city"

Aggregate functions (except COUNT(*)) ignore NULLvalues in the input set input set might be empty in which case NULL is returned

SELECT city, COUNT(customerID) AS numberFROM CustomerGROUP BY city;

city number

Zurich 3

Brussels 1

Paris 1


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Subqueries

A subquery is a SELECT FROM WHERE expression that isnested within another query e.g. via check for set membership (IN or NOT IN)

Example "Find all the suppliers who are no customers"

SELECT DISTINCT nameFROM SupplierWHERE name NOT IN (SELECT name

FROM Customer);

name

Franz Hohler


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Nested Subqueries ...

Example "Find all CDs with a price smaller than average"

SELECT *FROM CDWHEREprice < (SELECT AVG(price)

FROM CD;


2 Moudi 3156 15.50 1996

3 Chromatic 3012 16.50 1996


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Set Comparison

For nested queries with conditions like "greater than atleast one"we can use these set comparison operators > SOME, >= SOME, < SOME, ALL (SELECT postcode

FROM Supplier);

name postcode

Robert Michelin 75008

Urs Frei 8092


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Existence Test

The EXISTS operator can be used to check if a tupleexists in a subquery

Example

SELECT nameFROM CustomerWHERE EXISTS (SELECT *

FROM SupplierWHERE Supplier.name = Customer.name);

name

Urs Frei


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Derived Relations

As subquery expression can also be used in the FROMclause in this case a name has to be given to the relation

Example "Find the number of customers in the city with the most

customers"

SELECT MAX(noCustomers) AS maxFROM (SELECT city, COUNT(customerID)

FROM CustomerGROUP BY city) AS CityTotal(city,noCustomers);

max

3


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WITH Clause

The WITH clause can be used to improve the readabilityby introducing temporary new relations introduced only in SQL:1999 and not supported by all databases

Example "Find all customers who bought one of the most expensive CDs"

WITH Expensive(price) ASSELECT MAX(price)FROM CD

SELECT Customer.name

FROM Customer, CD, OrderWHERE CD.price = Expensive.price AND CD.cdID = Order.cdID ANDOrder.customerID = Customer.customerID;

name

Beat Meier


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Views

New virtual relations (views) can be defined on top of anexisting logical model simplify queries

provide access to only parts of the logical model (security)

Some DBMS allow views to be stored (materialisedviews) materialised views have to be updated when its relations change

createView = "CREATE VIEW" , table ,[ "(" , column , { "," , column } , ")" ] ,"AS" , query;


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Views

Example

Note that a view can be used like any other relation

Views are useful for queries but they present a seriousproblem for UPDATE, INSERT and DELETE operations

CREATE VIEW CustomerCD ASSELECT Customer.customerID, Customer.name, CD.cdID, CD.name AS cdNameFROM Customer, Order, CD

WHERE Customer.customerID = Order.customerID ANDOrder.cdID = CD.cdID;


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Transactions

A transactionconsists of a sequence of query and/orupdate statements

A transaction explicitly starts when an SQL statement is

executed and is ended by a COMMIT statement

a ROLLBACK statement

In many SQL implementations each SQL statement is a

transaction on its own this default behaviour can be disabled

SQL:1999 introduced BEGIN ATOMIC ... END blocks

Transactions will be discussed in detail later


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Homework

Study the following chapter of theDatabase System Conceptsbook chapter 3

- SQL


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Exercise 5

Structured Query Language (SQL)


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References

A. Silberschatz, H. Korth and S. Sudarshan, DatabaseSystem Concepts(Fifth Edition), McGraw-Hill, 2005


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