© 2009 pearson education, inc. publishing as prentice hall 1 chapter 8: advanced sql modern...

© 2009 Pearson Education, Inc. Publishing as Prentice © 2009 Pearson Education, Inc. Publishing as Prentice HallHall 11

Chapter 8:Chapter 8:Advanced SQLAdvanced SQL

Modern Database Modern Database ManagementManagement

99thth Edition EditionJeffrey A. Hoffer, Mary B. Prescott, Jeffrey A. Hoffer, Mary B. Prescott,

Heikki TopiHeikki Topi

Chapter 8 © 2009 Pearson Education, Inc. Publishing as Prentice Hall© 2009 Pearson Education, Inc. Publishing as Prentice Hall 22

ObjectivesObjectives Definition of termsDefinition of terms Write single and multiple table SQL queriesWrite single and multiple table SQL queries Define and use three types of joinsDefine and use three types of joins Write noncorrelated and correlated Write noncorrelated and correlated

subqueriessubqueries Establish referential integrity in SQLEstablish referential integrity in SQL Understand triggers and stored proceduresUnderstand triggers and stored procedures Discuss SQL:200n standard and its extension Discuss SQL:200n standard and its extension

of SQL-92of SQL-92 Understand SQL use for OLTP and OLAP Understand SQL use for OLTP and OLAP


Processing Multiple Tables–Processing Multiple Tables–JoinsJoins

JoinJoin––a relational operation that causes two or more tables a relational operation that causes two or more tables with a common domain to be combined into a single table with a common domain to be combined into a single table or viewor view

Equi-joinEqui-join––a join in which the joining condition is based a join in which the joining condition is based on equality between values in the common columns; on equality between values in the common columns; common columns appear redundantly in the result tablecommon columns appear redundantly in the result table

Natural joinNatural join––an equi-join in which one of the duplicate an equi-join in which one of the duplicate columns is eliminated in the result tablecolumns is eliminated in the result table

Outer joinOuter join––a join in which rows that do not have a join in which rows that do not have matching values in common columns are nonetheless matching values in common columns are nonetheless included in the result table (as opposed to included in the result table (as opposed to innerinner join, in join, in which rows must have matching values in order to appear which rows must have matching values in order to appear in the result table)in the result table)

Union joinUnion join––includes all columns from each table in the includes all columns from each table in the join, and an instance for each row of each tablejoin, and an instance for each row of each table

The common columns in joined tables are usually the primary key of the dominant table and the foreign key of the dependent table in 1:M relationships


Figure 8-2Figure 8-2Visualization of different join types with Visualization of different join types with

results returned in shaded arearesults returned in shaded area


The following slides create tables The following slides create tables for this enterprise data modelfor this enterprise data model


These tables are used in queries that follow

Figure 8-1 Pine Valley Furniture Company Customer and Order tables with pointers from customers to their orders


For each customer who placed an order, what is For each customer who placed an order, what is the customer’s name and order number?the customer’s name and order number?

SELECT CUSTOMER_T.CUSTOMER_ID, CUSTOMER_NAME, ORDER_IDSELECT CUSTOMER_T.CUSTOMER_ID, CUSTOMER_NAME, ORDER_IDFROM CUSTOMER_T NATURAL JOIN ORDER_T ON FROM CUSTOMER_T NATURAL JOIN ORDER_T ON

CUSTOMER_T.CUSTOMER_ID = ORDER_T.CUSTOMER_ID;CUSTOMER_T.CUSTOMER_ID = ORDER_T.CUSTOMER_ID;

Join involves multiple tables in FROM clause

Natural Join ExampleNatural Join Example

ON clause performs the equality check for common columns of the two tables

Note: from Fig. 1, you see that only 10 Customers have links with orders

Only 10 rows will be returned from this INNER join


List the customer name, ID number, and order List the customer name, ID number, and order number for all customers. Include customer number for all customers. Include customer information even for customers that do have an orderinformation even for customers that do have an order

SELECT CUSTOMER_T.CUSTOMER_ID, CUSTOMER_NAME, ORDER_IDSELECT CUSTOMER_T.CUSTOMER_ID, CUSTOMER_NAME, ORDER_IDFROM CUSTOMER_T, LEFT OUTER JOIN ORDER_TFROM CUSTOMER_T, LEFT OUTER JOIN ORDER_TON CUSTOMER_T.CUSTOMER_ID = ORDER_T.CUSTOMER_ID;ON CUSTOMER_T.CUSTOMER_ID = ORDER_T.CUSTOMER_ID;

Outer Join Example Outer Join Example (Microsoft Syntax)(Microsoft Syntax)

LEFT OUTER JOIN syntax with ON causes customer data to appear even if there is no corresponding order data

Unlike INNER join, this will include customer rows with no matching order rows


Results

Unlike INNER join, this will include customer rows with no matching order rows


Assemble all information necessary to create an invoice for order Assemble all information necessary to create an invoice for order number 1006number 1006

SELECT CUSTOMER_T.CUSTOMER_ID, CUSTOMER_NAME, CUSTOMER_ADDRESS, CITY, SATE, SELECT CUSTOMER_T.CUSTOMER_ID, CUSTOMER_NAME, CUSTOMER_ADDRESS, CITY, SATE, POSTAL_CODE, ORDER_T.ORDER_ID, ORDER_DATE, QUANTITY, PRODUCT_DESCRIPTION, POSTAL_CODE, ORDER_T.ORDER_ID, ORDER_DATE, QUANTITY, PRODUCT_DESCRIPTION, STANDARD_PRICE, (QUANTITY * UNIT_PRICE)STANDARD_PRICE, (QUANTITY * UNIT_PRICE)

FROM CUSTOMER_T, ORDER_T, ORDER_LINE_T, PRODUCT_TFROM CUSTOMER_T, ORDER_T, ORDER_LINE_T, PRODUCT_T

WHERE CUSTOMER_T.CUSTOMER_ID = ORDER_LINE.CUSTOMER_ID WHERE CUSTOMER_T.CUSTOMER_ID = ORDER_LINE.CUSTOMER_ID AND AND ORDER_T.ORDER_ID = ORDER_LINE_T.ORDER_ID ORDER_T.ORDER_ID = ORDER_LINE_T.ORDER_ID

AND ORDER_LINE_T.PRODUCT_ID = PRODUCT_PRODUCT_IDAND ORDER_LINE_T.PRODUCT_ID = PRODUCT_PRODUCT_IDAND ORDER_T.ORDER_ID = 1006;AND ORDER_T.ORDER_ID = 1006;

Four tables involved in this join

Multiple Table Join Multiple Table Join ExampleExample

Each pair of tables requires an equality-check condition in the WHERE clause, matching primary keys against foreign keys


Figure 8-4 Results from a four-table join

From CUSTOMER_T table

From ORDER_T table From PRODUCT_T table


Processing Multiple Tables Processing Multiple Tables Using SubqueriesUsing Subqueries

Subquery–placing an inner query (SELECT Subquery–placing an inner query (SELECT statement) inside an outer querystatement) inside an outer query

Options:Options: In a condition of the WHERE clauseIn a condition of the WHERE clause As a “table” of the FROM clauseAs a “table” of the FROM clause Within the HAVING clauseWithin the HAVING clause

Subqueries can be:Subqueries can be: Noncorrelated–executed once for the entire Noncorrelated–executed once for the entire

outer queryouter query Correlated–executed once for each row returned Correlated–executed once for each row returned

by the outer queryby the outer query


Show all customers who have placed an Show all customers who have placed an orderorder

SELECT CUSTOMER_NAME FROM CUSTOMER_TSELECT CUSTOMER_NAME FROM CUSTOMER_TWHERE CUSTOMER_ID INWHERE CUSTOMER_ID IN

(SELECT DISTINCT CUSTOMER_ID FROM ORDER_T);(SELECT DISTINCT CUSTOMER_ID FROM ORDER_T);

Subquery ExampleSubquery Example

Subquery is embedded in parentheses. In this case it returns a list that will be used in the WHERE clause of the outer query

The IN operator will test to see if the CUSTOMER_ID value of a row is included in the list returned from the subquery


Correlated vs. Correlated vs. Noncorrelated SubqueriesNoncorrelated Subqueries

Noncorrelated subqueries:Noncorrelated subqueries: Do not depend on data from the outer queryDo not depend on data from the outer query Execute once for the entire outer queryExecute once for the entire outer query

Correlated subqueries:Correlated subqueries: Make use of data from the outer queryMake use of data from the outer query Execute once for each row of the outer queryExecute once for each row of the outer query Can use the EXISTS operatorCan use the EXISTS operator


Figure 8-6a Processing a noncorrelated subquery

No reference to data in outer query, so subquery executes once only

These are the only customers that have IDs in the ORDER_T table

1. The subquery executes and returns the customer IDs from the ORDER_T table

2. The outer query on the results of the subquery


Show all orders that include furniture finished in natural ashShow all orders that include furniture finished in natural ash

SELECT DISTINCT ORDER_ID FROM ORDER_LINE_TSELECT DISTINCT ORDER_ID FROM ORDER_LINE_TWHERE EXISTSWHERE EXISTS

(SELECT * FROM PRODUCT_T (SELECT * FROM PRODUCT_T WHERE PRODUCT_ID = ORDER_LINE_T.PRODUCT_ID WHERE PRODUCT_ID = ORDER_LINE_T.PRODUCT_ID AND PRODUCT_FINISH = ‘Natural ash’);AND PRODUCT_FINISH = ‘Natural ash’);

Correlated Subquery Correlated Subquery ExampleExample

The subquery is testing for a value that comes from the outer query

The EXISTS operator will return a TRUE value if the subquery resulted in a non-empty set, otherwise it returns a FALSE


Figure 8-6b Processing a correlated subquery

Subquery refers to outer-query data, so executes once for each row of outer query

Note: only the orders that involve products with Natural Ash will be included in the final results


Show all products whose standard price is higher than the average Show all products whose standard price is higher than the average priceprice

SELECT PRODUCT_DESCRIPTION, STANDARD_PRICE, AVGPRICESELECT PRODUCT_DESCRIPTION, STANDARD_PRICE, AVGPRICEFROMFROM

(SELECT AVG(STANDARD_PRICE) AVGPRICE FROM PRODUCT_T),(SELECT AVG(STANDARD_PRICE) AVGPRICE FROM PRODUCT_T),PRODUCT_TPRODUCT_TWHERE STANDARD_PRICE > AVG_PRICE;WHERE STANDARD_PRICE > AVG_PRICE;

Another Subquery ExampleAnother Subquery Example

The WHERE clause normally cannot include aggregate functions, but because the aggregate is performed in the subquery its result can be used in the outer query’s WHERE clause

One column of the subquery is an aggregate function that has an alias name. That alias can then be referred to in the outer query

Subquery forms the derived table used in the FROM clause of the outer query


Union QueriesUnion Queries Combine the output (union of multiple Combine the output (union of multiple

queries) together into a single result tablequeries) together into a single result table

First query

Second query

Combine


Figure 8-7 Combining queries using UNION


Conditional Expressions Using Conditional Expressions Using Case SyntaxCase Syntax

This is available with This is available with newer versions of newer versions of SQL, previously not SQL, previously not part of the part of the standardstandard

Figure 8-Figure 8-88


Tips for Developing Tips for Developing QueriesQueries

Be familiar with the data model (entities Be familiar with the data model (entities and relationships)and relationships)

Understand the desired resultsUnderstand the desired results Know the attributes desired in resultKnow the attributes desired in result Identify the entities that contain desired Identify the entities that contain desired

attributesattributes Review ERDReview ERD Construct a WHERE for each linkConstruct a WHERE for each link Fine tune with GROUP BY and HAING Fine tune with GROUP BY and HAING

clauses if neededclauses if needed Consider the effect on unusual dataConsider the effect on unusual data


Ensuring Transaction Ensuring Transaction IntegrityIntegrity

Transaction = A discrete unit of work Transaction = A discrete unit of work that must be completely processed or that must be completely processed or not processed at allnot processed at all May involve multiple updatesMay involve multiple updates If any update fails, then all other updates If any update fails, then all other updates

must be cancelledmust be cancelled SQL commands for transactionsSQL commands for transactions

BEGIN TRANSACTION/END TRANSACTIONBEGIN TRANSACTION/END TRANSACTION Marks boundaries of a transactionMarks boundaries of a transaction

COMMITCOMMIT Makes all updates permanentMakes all updates permanent

ROLLBACKROLLBACK Cancels updates since the last COMMITCancels updates since the last COMMIT


Figure 8-9 An SQL Transaction sequence (in pseudocode)


Data Dictionary FacilitiesData Dictionary Facilities

System tables that store metadataSystem tables that store metadata Users usually can view some of these tablesUsers usually can view some of these tables Users are restricted from updating themUsers are restricted from updating them Some examples in Oracle 10gSome examples in Oracle 10g

DBA_TABLES–descriptions of tablesDBA_TABLES–descriptions of tables DBA_CONSTRAINTS–description of constraintsDBA_CONSTRAINTS–description of constraints DBA_USERS–information about the users of the systemDBA_USERS–information about the users of the system

Examples in Microsoft SQL Server 2000Examples in Microsoft SQL Server 2000 SYSCOLUMNS–table and column definitionsSYSCOLUMNS–table and column definitions SYSDEPENDS–object dependencies based on foreign SYSDEPENDS–object dependencies based on foreign

keyskeys SYSPERMISSIONS–access permissions granted to usersSYSPERMISSIONS–access permissions granted to users


SQL:1999 and SQL:200SQL:1999 and SQL:200NN Enhancements/ExtensionsEnhancements/Extensions

User-defined data types (UDT)User-defined data types (UDT) Subclasses of standard types or an object typeSubclasses of standard types or an object type

Analytical functions (for OLAP)Analytical functions (for OLAP) CEILING, FLOOR, SQRT, RANK, DENSE_RANKCEILING, FLOOR, SQRT, RANK, DENSE_RANK WINDOW–improved numerical analysis WINDOW–improved numerical analysis

capabilitiescapabilities New Data TypesNew Data Types

BIGINT, MULTISET (collection), XMLBIGINT, MULTISET (collection), XML CREATE TABLE LIKE–create a new table CREATE TABLE LIKE–create a new table

similar to an existing onesimilar to an existing one MERGEMERGE


Persistent Stored Modules (SQL/PSM)Persistent Stored Modules (SQL/PSM) Capability to create and drop code Capability to create and drop code

modulesmodules New statements:New statements:

CASE, IF, LOOP, FOR, WHILE, etc.CASE, IF, LOOP, FOR, WHILE, etc. Makes SQL into a procedural languageMakes SQL into a procedural language

Oracle has propriety version called Oracle has propriety version called PL/SQL, and Microsoft SQL Server PL/SQL, and Microsoft SQL Server has Transact/SQLhas Transact/SQL

SQL:1999 and SQL:200SQL:1999 and SQL:200NN Enhancements/Extensions Enhancements/Extensions

(cont.)(cont.)


Routines and TriggersRoutines and Triggers RoutinesRoutines

Program modules that execute on demandProgram modules that execute on demand FunctionsFunctions–routines that return values and –routines that return values and

take input parameterstake input parameters ProceduresProcedures–routines that do not return –routines that do not return

values and can take input or output values and can take input or output parametersparameters

TriggersTriggers Routines that execute in response to a Routines that execute in response to a

database event (INSERT, UPDATE, or database event (INSERT, UPDATE, or DELETE)DELETE)


Figure 8-10 Triggers contrasted with stored procedures

Procedures are called explicitly

Triggers are event-drivenSource: adapted from Mullins, 1995.


Figure 8-11 Simplified trigger syntax, SQL:200n

Figure 8-12 Create routine syntax, SQL:200n


Embedded and Dynamic Embedded and Dynamic SQLSQL

Embedded SQLEmbedded SQL Including hard-coded SQL statements in Including hard-coded SQL statements in

a program written in another language a program written in another language such as C or Javasuch as C or Java

Dynamic SQLDynamic SQL Ability for an application program to Ability for an application program to

generate SQL code on the fly, as the generate SQL code on the fly, as the application is runningapplication is running


OLAP SQLOLAP SQL Online Transaction Processing (OLTP)Online Transaction Processing (OLTP)

Real-time processing of SQL transactions, characterized Real-time processing of SQL transactions, characterized by fast data entry and retrieval in multi-user by fast data entry and retrieval in multi-user environmentsenvironments

Smaller size, less data sources, many users, simpler Smaller size, less data sources, many users, simpler queries, more normalized, standard SQLqueries, more normalized, standard SQL

Online Analytical Processing (OLAP)Online Analytical Processing (OLAP) Use of graphical tools providing users with Use of graphical tools providing users with

multidimensional views of data for analysis purposesmultidimensional views of data for analysis purposes Larger size, more data sources, fewer users, complex Larger size, more data sources, fewer users, complex

queries, less normalized, OLAP SQL and statistical queries, less normalized, OLAP SQL and statistical packages (SPSS/SAS)packages (SPSS/SAS)


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© 2009 pearson education, inc. publishing as prentice hall 1 chapter 8: advanced sql modern...

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