structured query language (sql) part 1rychly/public/docs/ades.sql-1/ades.sql-1.print.pdf · v8,...

Structured Query Language (SQL) – Part 1

Marek [email protected]

Strathmore University,@iLabAfrica

&

Brno University of Technology,Faculty of Information Technology

Advanced Databases and Enterprise Systems14 September 2015

Marek Rychly Structured Query Language (SQL) – Part 1 — ADES, 14 September 2015 1 / 35

[email protected]

Outline

1 Structured Query Language (SQL)History of SQL and Relational DBMSSELECT StatementSub-queries in the SELECT Statement


Structured Query Language (SQL)History of SQL and Relational DBMSSELECT StatementSub-queries in the SELECT Statement

Structured Query Language (SQL)

query, data manipulation and definition relational db. languageto create database and relation structures

to perform data management task (insert, update, delete)

to perform both simple and complex queries

standard both by specification and by usage in practicespecified by International Organization for Standardization (ISO)

utilized by DBMS vendors (Oracle, IBM, open-source, etc.)

a transform-oriented language based on relational algebra(an expression describes how to transform input relations to an output relation)

a non-procedural (declarative) language(it describes what operations of relational algebra should be applied on input data,not how it should be done in terms of input data retrieval, their processing, etc.)



Early History of SQL

1970 E. F. Codd, from IBM labs., introduced the relational database model(including relational algebra and relational calculus)

1974 D. Chamberlin, also from IBM labs., introduced SEQUEL(a relational database language called the Structured English Query Language)

1976 Chamberlin et al. introduces SEQUEL/2(later, it has been renamed to SQL for legal reasons)

IBM produced a prototype DBMS based on SEQUEL/2, called System R(also based on SQUARE (Specifying Queries As Relational Expressions), 1975)

1978–79 SDL/RSI company introduced a first versions of Oracle, V1 and V2(Oracle V2 was the first commercial RDBMS; RSI became Oracle Corp. in 1982)

1987-89 The first/initial ISO standard of SQL was published and extended later(many relational features were missing, implemented by vendors in various ways)



Current History of SQL

1992 SQL-92, the first major/usable revision to the ISO standard occurred(still, it did not cover many advanced features implemented by these days DBMSs)

1999 SQL:1999 published by ISO, SQL formalized including advanced features(such as support object-oriented data management)

Oracle8i released as an RDBMS inter-operating better within the Internet

2003 SQL:2003 published by ISO, consisted of Core SQL and SQL Packages(the core mandatory, packages optional, e.g., for object and XML data, etc.)

2003-13 SQL/MM (SQL multimedia and application packages) by ISO(full-text, spatial, and still image data, data mining, history, meta-data registries)

2006 SQL:2006 as Part 14 of SQL:2003 published by ISO(a package that defines ways in which SQL can be used in conjunction with XML)

2008 SQL:2008 published by ISO, another restructuring of the specification(Framework, Foundation, Object Language Bindings, Information and DefinitionSchemas, SQL Routines and Types Using Java, XML-Related Specifications, etc.)

2011 SQL:2008 published by ISO as an update of SQL:2008(new features include improved support for temporal databases)



Early History of RDBMS Systems

(adopted from “History of RDBMS, Data-e-Education, 2014”)


http://www.data-e-education.com/RDBMS/History_Of_RDBMS.php


Current History of RDBMS Systems

IBM Peterlee Relational Test Vehicle

IBM IS1

BAY AREA PARK

CODD RIVER

RELATIONAL CREEK

CODD RIVER

BAY AREA PARK

1970s

1980s1990s

2000s

2010s

v1, 1992

v1.0, 1987

v4.0, 1990 v10, 1993

v1, 1987 v2, 1989v3, 2011

v11.5, 1996 v11.9, 1998

v12.0, 1999 v12.5, 2001 v12.5.1, 2003 v15.0, 2005 v16.0, 2012

v1, 1989

v2, 1993

v1.0, 1980s

v5.x, 1970s

v6.0, 1986 OpenIngres 2.0, 1997 vR3, 2004

v1, 1995 v6, 1997 v7, 2000

v8, 2005 v9, 2010

v9.0, 2006 v10, 2010

v4.0, 1990 v5.0, 1992 v6.0, 1994

v9.0, 2000 v10, 2005 v11, 2007

v4.21, 1993 v6, 1994 v7, 1998

v8, 1997

v3.1, 1997 v3.21, 1998 v3.23, 2001 v4, 2003 v4.1, 2004 v5, 2005 v5.1, 2008

v5.5, 2010

v8i, 1999 v9i, 2001 v10g, 2003 v10gR2, 2005 v11g, 2007 v11gR2, 2009

v8, 2000 v9, 2005 v10, 2008 v11, 2012

v3, 1995 v4, 1997 v5, 1999 v10, 2001 v11, 2003 v12, 2007 v14, 2010

v3, 1983 v4, 1984 v5, 1985

v1, 1983

v5.1, 1986

v3, 1993

v1, 1983 v2, 1988 v3, 1993 v4, 1994

v5, 1996

v6, 1999 v7, 2001 v8, 2003 v9, 2006

alpha, 1979

v1.0, 1981

v6.1, 1997 v8.1, 1998 v10.2, 2008

v5.1, 2004 v6.0, 2005 v6.2, 2006 v12, 2007 v13.0, 2009

v13.10, 2010 v14.0, 2012

v4, 1995

v5, 1997

v6, 1999

v1, 1991 v2, 1997

v3, 1999 v4, 2001

v1.6, 2001 v1.7, 2002

v1.8, 2005

v3.0, 1988

v2.0, 2010

v5, 2010

v7, 2001 v8, 2004 v9, 2007

v10, 2010

v7, 1992

v7.0, 1995

v2, 1979

v1, 2003 v1.5, 2009

v2, 2012

v6.5, 1995

codebrand

v11, 1995v12, 1999

v15, 2009

v12c, 2013

v1, 1988 v2, 1992 v4, 1992

v6, 2008 v7, 2010

Ingres

VectorWise

MonetDB

Netezza

Greenplum

PostgreSQL

Red Brick

Microsoft SQL ServerH-Store

Informix

VoltDB

Vertica

db40

Sybase ASE

Sybase IQ

SQL Anywhere

Access

Oracle

Infobright

MySQL

TimesTen

Paradox

Teradata

Empress Embedded

RDB

DB2 for iSeries

Derby

Transbase

DB2 for z/OSDB2 for VM

Solid DB

EXASolution

dBase

Firebird

DB2 for LUWHSQLDB

BerkelyDB

SQLite

HANA

MaxDB

Nonstop SQL

AdabasD

MariaDB

v10, 2013

SQL/DS

DB2 for VM

DB2 UDB

Transbase(Transaction Software)

TinyDB

Berkeley DB

DB2 MVS

Solid DB

Gamma (Univ. Wisconsin) Mariposa (Berkeley)

dBase (Ashton Tate)

DB2

NDBM

GDBM

SQLite

HSQLDB

DBM

VDN/RDS DDB4 (Nixdorf)SAP DB MaxDB

Borland

Siemens

dBase Inc.

EMC

NCR Teradata

SAP

IBM

Oracle

Oracle

Oracle

IBM

Oracle

System-R (IBM)

AdabasD(Software AG)

SAP HANA

P*TIME

SAP

REDABAS (Robotron)

DABA (Robotron, TU Dresden)

Borland

Corel

EXASolution

InterBaseAshton Tate Firebird

HP

HP

Compaq

DB2 z/OS

Powersoft Sybase

System/38

SQL/400 DB2/400

DB2 UDB for iSeries

Sleepycat

Informix IBM

Sun

Oracle

RDB (DEC)

Teradata

Empress Embedded

TimesTen Aster Database

JBMS

Cloudscape Derby

Paradox (Ansa)

Red Brick

Multics Relational Data Store (Honeywell)

Apache Derby

Berkeley Ingres

Ingres

Postgres PostgreSQL

IllustraIBM Informix

MonetDB (CWI)

Greenplum

Volt DB

Netezza

Informix

Sybase ASE

Microsoft SQL ServerMicrosoft Access

MySQL

Sybase IQ

Nonstop SQL(Tandem) Neoview

mSQL

InnoDB (Innobase)

Infobright

H-StoreC-Store

db40

Vertica Analytic DB

VectorWise (Actian)Monet Database System (Data Distilleries)

DATAllegro

Informix

IBM Red Brick Warehouse

Expressway 103

Watcom SQL SQL Anywhere

MariaDB

Key to lines and symbols Felix Naumann, Jana Bauckmann, Claudia Exeler, Jan-Peer Rudolph, Fabian Tschirschnitz

Contact - Hasso Plattner Institut, Potsdam, [email protected]

Design - Alexander Sandt Gra�k-Design, Hamburg

Version 4.0 - August 2013

http://www.hpi.uni-potsdam.de/naumann/projekte/rdbms_genealogy.html

Publishing Date

Genealogy of Relational Database Management Systems

Discontinued Branch (intellectual and/or code)Acquisition Versionsv9, 2006CC

Crossing lines have no special semantics(adopted from “RDBMS Genealogy, Hasso-Plattner-Institut, 2015”)


https://hpi.de/naumann/projects/rdbms-genealogy.html


Web SQL (SQLite) Relational DBMS

relational DBMS provided by web-browser by HTML5 API(based on the underlying SQLite RDBMS, e.g., SQLite v3.6.1 in Google Chrome)

currently supported only by WebKit-based web-browsers:Chrome, Safari, Opera(API is deprecated by W3C since end of 2010 but it is still supported)

utilized by Try-SQL Editor in W3Schools SQL Tutorialhttp://www.w3schools.com/sql/trysql.asp?filename=trysql_select_all

supports all SQLite features (including triggers)(all but storage management and unsecure features, e.g., ATTACH/VACUUM)

suitable for practising the SQL

examples shown in this lecture will be demonstrated on Try-SQL

the examples will use tables provided by W3Schools SQL Tutorial


http://www.w3schools.com/sql/trysql.asp?filename=trysql_select_all


https://www.sqlite.org/lang.html


http://www.w3schools.com/sql/


SQL: DDL and DML Languages

SQL can be divided into two partsData Definition Language (DDL)(for defining the database structure and controlling access to the data)

Data Manipulation Language (DML)(for retrieving and updating data)

SQL statements consist of two types of words(both are used as case-insensitive, contrary to data-typed string values)

reserved words(select, from, where, order by, group by, create, table, row, primary key, etc.)

user-defined words(names of tables, columns, indices, views, etc.)

individual SQL statements/commands separated by semicolon “;”

non-numeric literals (constants) are enclosed in single quotes(for example: 123, �1:23, ’John Smith’, date(’now’), date(’2015-09-114’), . . . )



SELECT Statement

SELECT [DISTINCT | ALL] {* | columnExpression [AS newName]] [, ...]}FROM tableName [alias] [, ...]

[WHERE condition][GROUP BY columnName [, ...]] [HAVING condition][ORDER BY columnNameOrNewName [DESC | ASC] [, ...]]

columnExpression is an expression with column names(in the resulting relation, the result of the expression can be known as newName)

tableName is the name of an input table, columnName of a table column(in the select statement, the table can be referred by alias)

condition is a logical expr. with table names/aliases and column names

columnNameOrNewName is the name of a column or a column expr. above

The statement selects such data from input tables that meet “where” condition.For such, all or distinct, data rows, column expressions are computed. It thecase of the expression with an aggregate function, the data are grouped by“group by” condition, the aggregate function is applied, and results is checkedto meet “having” condition. Finally, the resulting data are ordered by values ofgiven columns in asceding or descending order.



Example of SELECT Statement

SELECT C.Country, count(C.CustomerID) AS CustomersInCountryFROM Customers CWHERE C.CustomerName LIKE ’% %’GROUP BY C.Country HAVING CustomersInCountry >= 3ORDER BY CustomersInCountry DESC;

Take all customers that have a space in their names,

group them into groups according to their country,(all members of each group will have the same value of the country column)

take just such groups that have at least 3 members (rows),

for each group, print country value and number of group members,

ordered by the number of group members descending.



Clauses in the SELECT Statement

SQL SELECT statements are processed in the following order:(note that the processing order is different from the order of the clauses in the statement)

FROM – specifies the table or tables to be used,

WHERE – filters the rows subject to some condition,

GROUP BY – forms groups of rows with the same column value,

HAVING – filters the groups subject to some condition,

SELECT – specifies which columns are to appear in the output.

ORDER BY – specifies the order of the output.

SELECT and FROM clauses are mandatory, others are optional.



The SELECT Clause

SELECT [DISTINCT | ALL] {* | columnExpression [AS newName]] [, ...]}

Specifies which columns are to appear in the output.

Represents the Projection operation of relational algebra.

The column expression consists ofcolumn names from tables in FROM clause,constants,expressions of the column names, constants, and operations.(e.g., arithmetic operations; string operations such as concatenation; etc.)

Star symbol “*” means all possible columns.(e.g., SELECT * FROM Customers; lists all values form the “Customers” table)

By default, SELECT does not eliminate duplicities.To eliminate duplicities, DISTINCT has to be used (ALL is default).(duplicate data may come from input tables or may be produced by the projection)



Examples on SELECT Clause

List all cities of customers including duplicities.

SELECT City FROM Customers;

List all cities of customers without duplicities.

SELECT DISTINCT City FROM Customers;

List all columns of all rows from table “Empployees”.

SELECT * FROM Employees;

List full names and age in days of all employees.

SELECT FirstName || ’ ’ || LastName AS FullName,julianday(’now’) - julianday(BirthDate) AS AgeInDays

FROM Employees;



The WHERE Clause

[WHERE condition]

Filters the rows subject to some condition.Represents the Selection operation of relational algebra.The condition consists of

constants, column names from tables in FROM clause,predicates applied on of the constants and column names,logical operators AND, OR, and NOT, with parentheses

There are several predefined predicates for testingcomparison: =, <>, <, >

(compare the value of one expression to the value of another expression)range: x BETWEEN a AND b, x NOT BETWEEN a AND b

(test whether the value falls within a specified range of values)set membership: x IN (a, b, c), x NOT IN (a, b, c)

(test whether the value equals one of a set of value)pattern match: x LIKE ’pattern’, x NOT LIKE ’pattern’

(test whether a string matches a specified pattern, usually case-sensitive)null: x IS NULL, x IS NOT NULL

(test whether a column has a Null (unknown) value)Marek Rychly Structured Query Language (SQL) – Part 1 — ADES, 14 September 2015 16 / 35


Pattern Matching an Null Search in WHERE Clause

columnExpression [NOT] LIKE ’pattern’ [ESCAPE ’escapeChar’]

Pattern is a text literal with two special pattern-matching symbols:

% represents any sequence of zero or more characters (a wildcard),_ represents any single character.

The special symbols can be used as common characters if escaped byescapeChar. For example:

SELECT * FROM Sale WHERE Discount LIKE ’%15#%’ ESCAPE ’#’;

columnName IS [NOT] NULL

The expression is true if and only if the column value is (not) Null.Null value used as operand in any operation will result into Null.



The ORDER BY Clause

[ORDER BY columnNameOrNewName [DESC | ASC] [, ...]]

Rows of an SQL query result table are ordered.(contrary to results of relational algebra operations)

The ORDER BY clause allows the retrieved rows to be ordered.

If unspecified by ORDER BY clause, the order is undefined.(usually, in the such cases, resulting rows are ordered by primary keys)

Result can be ordered by multiple columns and for eachASC means ascending order on a given column,

DESC means descending order on a given column.

The ORDER BY clause has to be the last clause of the statement.



Examples on WHERE and ORDER BY Clauses

List employees whose first names start with A and were born in February.

SELECT * FROM EmployeesWHERE FirstName LIKE ’A%’ AND BirthDate LIKE ’____-02-__’;

List products with non-empty supplier and price between $10 and $20arranged in descending order of price.

SELECT * FROM Products WHERE Price BETWEEN 10 AND 20AND SupplierID IS NOT NULL ORDER BY Price DESC;

List full names and birth dates of employees in ascending order of names.

SELECT LastName || ’, ’ || FirstName as FullName, BirthDateFROM Employees ORDER BY FullName ASC;

or, alternatively, . . . ORDER BY LastName ASC, FirstName ASC;

List suppliers that are neither from UK nor from USA.

SELECT * FROM Suppliers WHERE Country NOT IN (’UK’,’USA’);



Aggregation and Grouping in the SELECT Statement

SELECT [columnExpression [, ...]]{aggregateFunction(columnName) | COUNT(*)}, [, ...]

...[GROUP BY columnName [, ...]] [HAVING condition]...

With an aggr. function in SELECT clause the data are aggregated.

The aggregate function applies on all values in a given column.all non-Null values in the case of a particular column name,all values including Null values in the case of COUNT(*) function,all distinct values in the case of DISTINCT word preceding thecolumn name in the operand of the aggregate function.

By GROUP BY clause, the aggr. function aggregates data foreach group of rows with identical values of grouped columns.

In the case of non-aggregated columns in the SELECT clause,those columns must appear also in the GROUP BY clause.

By HAVING clause, aggregation results are filtered by condition.Marek Rychly Structured Query Language (SQL) – Part 1 — ADES, 14 September 2015 20 / 35


Aggregate Functions

The SQL standard by ISO defines five aggregate functions:COUNT – returns the number of values in a specified column,

SUM – returns the sum of the values in a specified column,

AVG – returns the average of the values in a specified column,

MIN – returns the smallest value in a specified column,

MAX – returns the largest value in a specified column.

Relational DBMSs usually provide additional aggregate functions.(e.g., group_concat(column,separator), stddev(column), variance(column), etc.)

To filter by aggregate function results, a condition has to be putinto HAVING clause, not into WHERE clause.(the HAVING condition may contain the aggregate functions applications or aliasesof columns from SELECT clause where the aggregation functions are)



Examples on GROUP BY Clause

For each product ID get total number of its orders, total sum and maximalordered quantity, in the cases when the total sum is 100 units or above.

SELECT ProductID, COUNT(*), SUM(Quantity), MAX(Quantity)FROM OrderDetailsGROUP BY ProductID HAVING SUM(Quantity) >= 100;

Get ID and name of products that have their prices the same or nearlysame with maximal difference of $5 as the average price of all products.

SELECT ProductID, ProductName FROM ProductsWHERE Price BETWEEN (SELECT AVG(Price)-5 FROM Products) AND (SELECT AVG(Price)+5 FROM Products);



The FROM Clause and Multi-Table Queries

... FROM tableName [alias] [, ...] ...

The FROM clause of a single query can refer to multiple tables.(then, the query will process data from all the tables)

To combine columns from several tables in the query into a resulttable we need to use a Join operation of relational algebra.

In multi-table query, columns values can be accessed astableName.columnName

(this is necessary if there is a column of the same name in several tables)

There are several different types of the Join operation.((inner) cross join, (Theta) join, natural join, left/right/full outer join, etc.)



(Inner) JOIN and CROSS JOIN Operations

... FROM OrderDetails, Products ...

... FROM OrderDetails JOIN Products ...

... FROM OrderDetails INNER JOIN Products ...

... FROM OrderDetails CROSS JOIN Products ...

The clauses above produce the same Cartesian product of tables.(i.e., they will pair all rows from the first table with all row from the second table)

To match particular rows, join criteria must be defined.(then, it wont be a plain Cartesian product but a Theta join as in relational algebra)

In multi-table query, columns values can be accessed astableName.columnName

(this is necessary if there is a column of the same name in two or more tables)

Join criteria can be put into WHERE clause or into FROM clause.(in the FROM clause, the join criteria are prefixed by “ON” word)



Examples of Multi-table Queries

List details of all orders where the ordered quantity is 10 units and more.

SELECT * FROM OrderDetails, ProductsWHERE OrderDetails.ProductID = Products.ProductIDAND Quantity >= 10;

or, alternatively,

SELECT * FROM OrderDetails JOIN ProductsON OrderDetails.ProductID = Products.ProductIDWHERE Quantity >= 10;

List all orders with their details, details of ordered products and suppliersof the products.

SELECT * FROM OrdersJOIN OrderDetails ON OrderDetails.OrderID = Orders.OrderIDJOIN Products ON Products.ProductID = OrderDetails.ProductIDJOIN Suppliers ON Products.SupplierID = Suppliers.SupplierID;



NATURAL (Inner) JOIN Operation

... FROM OrderDetails NATURAL JOIN Products ...

... FROM OrderDetails NATURAL INNER JOIN Products ...

The clauses above produce the same Natural join of tables.

Join criteria are equalities of columns of the same names.(see the Equi-join and Natural join operations in relational algebra)

For particular choice of columns of the same names, it is possibleto use JOIN USING with a list of columns for the join criteria.For example,

SELECT * FROM Orders JOIN OrderDetails USING (OrderID);



OUTER JOIN Operations

... FROM Customers LEFT OUTER JOIN OrdersON Customers.CustomerID = Orders.CustomerID ...

... FROM Customers LEFT OUTER JOIN Orders USING (CustomerID) ...

... FROM Customers NATURAL LEFT OUTER JOIN Orders ...

... FROM Orders NATURAL RIGHT OUTER JOIN Customers ...

The clauses above produce the same results.(they are a Theta-, Equi-, and Natural left-outer join operations in relational algebra)

Left (right) outer join takes all rows from the left (right) table andmatches them with respective rows of the other table if possible,or with Null values otherwise.(see the Outer join operations in relational algebra)

As the right- join and full-outer join ops. can be computed byleft-outer join op(s)., they may not be supported by some RDBMS.(e.g., SQLite, that is also Web-SQL supports only the left outer join operation)



Examples on OUTER JOIN Operations

List all orders with their customers and also customers without any orders.

SELECT * FROM Customers NATURAL LEFT OUTER JOIN Orders;

List all possible replacements of products with the same price.

SELECT Original.ProductID AS OrigID,Original.ProductName AS OrigName,Alternative.ProductID AS AltID,Alternative.ProductName AS AltName,Price

FROM Products Original LEFT OUTER JOIN Products AlternativeUSING (Price)

WHERE OrigID <> AltID;



Sub-queries in SELECT Statements (Sub-selects)

It is possible to perform an inner SELECT statement (a nestedquery) and to use its result(s) in an outer SELECT statement.

From the result(s) produced, we can distinguishscalar sub-queries – return a single column&row (a single value),row sub-queries – return a single row with multiple columns,table sub-queries – return multiple rows&columns (a table).

A scalar sub-query can be used when a single value is needed.(for example, in WHERE clause as an operand of a predicate, e.g, with equality)

Scalar sub-queries are useful especially to integrate results ofaggregate functions into complicated (outer) queries.For example,

SELECT ProductID, ProductName FROM ProductsWHERE Price BETWEEN (SELECT AVG(Price)-5 FROM Products)

AND (SELECT AVG(Price)+5 FROM Products);



Row and Table Sub-queries in SELECT Statements

Row and table sub-queries can be used with the following predicates:(these predicates exist also in their negative forms, prefixed by “NOT” word, e.g., NOT IN)

IN to test if a value is in a result set a particular sub-query

ALL to test if a predicate holds for all results of a particular sub-query

ANY to test if a predicate holds for at least one result of a sub-query1

EXISTS to test if a result set a particular sub-query is not empty

ALL and ANY (SOME) may not be supported by some RDBMS.(for example, they are not supported by SQLite, that is also by Web SQL)

1ANY predicate is also known as SOME predicate; ANY and SOME are synonymsMarek Rychly Structured Query Language (SQL) – Part 1 — ADES, 14 September 2015 30 / 35

https://www.sqlite.org/syntax/expr.html


Examples of Sub-queries

List all employees that did not take any orders.

SELECT * FROM EmployeesWHERE EmployeeID NOT IN (SELECT EmployeeID FROM Orders);

or, alternatively,

SELECT * FROM Employees E WHERE NOT EXISTS(SELECT 1 FROM Orders O WHERE O.EmployeeID = E.EmployeeID);

Get product with the highest price.

SELECT * FROM ProductsWHERE Price >= ALL (SELECT Price FROM Products);

or, alternatively,

SELECT * FROM ProductsWHERE Price >= (SELECT MAX(Price) FROM Products);



Set Operations

Table sub-queries and the whole selects can be combined by setoperations as they are defined in the relational algebra:(results combined by the set operations have to be union-compatible)

UNION to merge results of both select statements into a single results

INTERSECT to filter rows that are common to results of both statements

EXCEPT to filter rows that appear in results of the first statement but notin results of the second one

There are modifiers2 of the set ops. that can be put after their names:ALL – to include duplicate rows in the result, e.g., UNION ALL

CORRESPONDING – to perform a given set operation only on thecolumns that are common (the same names) to results of both statements

CORRESPONDING BY – to perform an op. on the named columns only

2the modifiers may not be supported by some RDBMS, e.g., by SQLite/Web SQLMarek Rychly Structured Query Language (SQL) – Part 1 — ADES, 14 September 2015 32 / 35

https://www.sqlite.org/syntax/compound-select-stmt.html


Examples on Set Operations

List cities where are both customers and suppliers.

SELECT City, Country FROM SuppliersINTERSECTSELECT City, Country FROM Customers;

Get all customers that are from Germany or UK countries or that haveordered something, or both, and count their orders or residences in thecountries.(that is, the count for a customer who is from UK and made one order will be 2while the count for a customer outside Europe who made three orders will be 3)

SELECT CustomerID, COUNT(*) AS Active FROM (SELECT CustomerID FROM CustomersWHERE Country IN (’Germany’, ’UK’)UNION ALLSELECT CustomerID FROM Orders

) GROUP BY CustomerID ORDER BY Active DESC;


Summary

Summary

SQL consists of DDL and DML languages.(DDL is for schema definition, while DML is for queries and data manipulation)

SELECT statement has several clauses.(SELECT and FROM clauses are mandatory, others are optional)

Results of SELECT queries are ordered multi-sets.(sets that keep order of its elements and may contain duplicities)

SELECT queries can be used as nested queries in other SELECTstatements.

In the next lecture:Structured Query Language (SQL) – Part 2(Common Table Expressions/CTE queries, INSERT/UPDATE/DELETE, DDL,indices, triggers, etc.)


Thanks

Thank you for your attention!

Marek Rychly<[email protected]>


[email protected]

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