1. © 2007 by Prentice Hall 1 Chapter 7: Introduction to SQL Modern Database Management 8 th Edition Jeffrey A. Hoffer, Mary B. Prescott, Fred R. McFadden

2. Chapter 7 © 2007 by Prentice Hall 2 Objectives Definition of terms Definition of terms Interpret history and role of SQL Interpret history and role of SQL Define a database using SQL data definition language Define a database using SQL data definition language Write single table queries using SQL Write single table queries using SQL Establish referential integrity using SQL Establish referential integrity using SQL Discuss SQL:1999 and SQL:2003 standards Discuss SQL:1999 and SQL:2003 standards

3. Chapter 7 © 2007 by Prentice Hall 3 SQL Overview Structured Query Language Structured Query Language The standard for relational database management systems (RDBMS) The standard for relational database management systems (RDBMS) RDBMS: A database management system that manages data as a collection of tables in which all relationships are represented by common values in related tables RDBMS: A database management system that manages data as a collection of tables in which all relationships are represented by common values in related tables

4. Chapter 7 © 2007 by Prentice Hall 4 History of SQL 1970–E. Codd develops relational database concept 1970–E. Codd develops relational database concept 1974-1979–System R with Sequel (later SQL) created at IBM Research Lab 1974-1979–System R with Sequel (later SQL) created at IBM Research Lab 1979– Oracle markets first relational DB with SQL 1979– Oracle markets first relational DB with SQL 1986– ANSI SQL standard released 1986– ANSI SQL standard released 1989, 1992, 1999, 2003– Major ANSI standard updates 1989, 1992, 1999, 2003– Major ANSI standard updates Current– SQL is supported by most major database vendors Current– SQL is supported by most major database vendors

5. Chapter 7 © 2007 by Prentice Hall 5 Purpose of SQL Standard Specify syntax/semantics for data definition and manipulation Specify syntax/semantics for data definition and manipulation Define data structures Define data structures Enable portability Enable portability Specify minimal (level 1) and complete (level 2) standards Specify minimal (level 1) and complete (level 2) standards Allow for later growth/enhancement to standard Allow for later growth/enhancement to standard

6. Chapter 7 © 2007 by Prentice Hall 6 Benefits of a Standardized Relational Language Reduced training costs Reduced training costs Productivity Productivity Application portability Application portability Application longevity Application longevity Reduced dependence on a single vendor Reduced dependence on a single vendor Cross-system communication Cross-system communication

7. Chapter 7 © 2007 by Prentice Hall 7 SQL Environment Catalog Catalog A set of schemas that constitute the description of a database A set of schemas that constitute the description of a database Schema Schema The structure that contains descriptions of objects created by a user (base tables, views, constraints) The structure that contains descriptions of objects created by a user (base tables, views, constraints) Data Definition Language (DDL) Data Definition Language (DDL) Commands that define a database, including creating, altering, and dropping tables and establishing constraints Commands that define a database, including creating, altering, and dropping tables and establishing constraints Data Manipulation Language (DML) Data Manipulation Language (DML) Commands that maintain and query a database Commands that maintain and query a database Data Control Language (DCL) Data Control Language (DCL) Commands that control a database, including administering privileges and committing data Commands that control a database, including administering privileges and committing data

8. Chapter 7 © 2007 by Prentice Hall 8 Figure 7-1 A simplified schematic of a typical SQL environment, as described by the SQL-2003 standard

9. Chapter 7 © 2007 by Prentice Hall 9 Some SQL Data types

10. Chapter 7 © 2007 by Prentice Hall 10 Figure 7-4 DDL, DML, DCL, and the database development process

11. Chapter 7 © 2007 by Prentice Hall 11 SQL Database Definition Data Definition Language (DDL) Data Definition Language (DDL) Major CREATE statements: Major CREATE statements: CREATE SCHEMA –defines a portion of the database owned by a particular user CREATE SCHEMA –defines a portion of the database owned by a particular user CREATE TABLE –defines a table and its columns CREATE TABLE –defines a table and its columns CREATE VIEW –defines a logical table from one or more views CREATE VIEW –defines a logical table from one or more views Other CREATE statements: CHARACTER SET, COLLATION, TRANSLATION, ASSERTION, DOMAIN Other CREATE statements: CHARACTER SET, COLLATION, TRANSLATION, ASSERTION, DOMAIN

12. Chapter 7 © 2007 by Prentice Hall 12 Table Creation Figure 7-5 General syntax for CREATE TABLE Steps in table creation: 1.Identify data types for attributes 2.Identify columns that can and cannot be null 3.Identify columns that must be unique (candidate keys) 4.Identify primary key – foreign key mates 5.Determine default values 6.Identify constraints on columns (domain specifications) 7.Create the table and associated indexes

13. Chapter 7 © 2007 by Prentice Hall 13 The following slides create tables for this enterprise data model

14. Chapter 7 © 2007 by Prentice Hall 14 Figure 7-6 SQL database definition commands for Pine Valley Furniture Overall table definitions

15. Chapter 7 © 2007 by Prentice Hall 15 Defining attributes and their data types

16. Chapter 7 © 2007 by Prentice Hall 16 Non-nullable specification Identifying primary key Primary keys can never have NULL values

17. Chapter 7 © 2007 by Prentice Hall 17 Non-nullable specifications Primary key Some primary keys are composite– composed of multiple attributes

18. Chapter 7 © 2007 by Prentice Hall 18 Default value Domain constraint Controlling the values in attributes

19. Chapter 7 © 2007 by Prentice Hall 19 Primary key of parent table Identifying foreign keys and establishing relationships Foreign key of dependent table

20. Chapter 7 © 2007 by Prentice Hall 20 Data Integrity Controls Referential integrity – constraint that ensures that foreign key values of a table must match primary key values of a related table in 1:M relationships Referential integrity – constraint that ensures that foreign key values of a table must match primary key values of a related table in 1:M relationships Restricting: Restricting: Deletes of primary records Deletes of primary records Updates of primary records Updates of primary records Inserts of dependent records Inserts of dependent records

21. Chapter 7 © 2007 by Prentice Hall 21 Relational integrity is enforced via the primary- key to foreign- key match Figure 7-7 Ensuring data integrity through updates

22. Chapter 7 © 2007 by Prentice Hall 22 Changing and Removing Tables The ALTER TABLE statement allows you to rename an existing table. The ALTER TABLE statement allows you to rename an existing table. It can also be used to add, modify, or drop a column from an existing table It can also be used to add, modify, or drop a column from an existing table DROP TABLE statement allows you to remove tables from your schema: DROP TABLE statement allows you to remove tables from your schema: DROP TABLE CUSTOMER_T DROP TABLE CUSTOMER_T

23. Chapter 7 © 2007 by Prentice Hall Alter Table Statement Renaming a table Renaming a table The basic syntax for renaming a table is: The basic syntax for renaming a table is: ALTER TABLE table_name RENAME TO new_table_name; For example: For example: ALTER TABLE suppliers RENAME TO vendors; This will rename the suppliers table to vendors. This will rename the suppliers table to vendors. 23

24. Chapter 7 © 2007 by Prentice Hall Alter Table Statement Adding column(s) to a table Adding column(s) to a table To add a column to an existing table, the ALTER TABLE syntax is: To add a column to an existing table, the ALTER TABLE syntax is: ALTER TABLE table_name ADD column_name column-definition; For example: For example: ALTER TABLE supplier ADD supplier_name varchar2(50); This will add a column called supplier_name to the supplier table. This will add a column called supplier_name to the supplier table. 24

25. Chapter 7 © 2007 by Prentice Hall Alter Table Statement Modifying column(s) in a table Modifying column(s) in a table To modify a column in an existing table, the ALTER TABLE syntax is: To modify a column in an existing table, the ALTER TABLE syntax is: ALTER TABLE table_name MODIFY column_name column_type; For example: For example: ALTER TABLE supplier MODIFY supplier_name varchar2(100) not null; This will modify the column called supplier_name This will modify the column called supplier_name to be a data type of varchar2(100) and force the column to not allow null values. to be a data type of varchar2(100) and force the column to not allow null values. 25

26. Chapter 7 © 2007 by Prentice Hall Alter Table Statement Drop column(s) in a table Drop column(s) in a table To drop a column in an existing table, the ALTER TABLE syntax is: To drop a column in an existing table, the ALTER TABLE syntax is: ALTER TABLE table_name DROP COLUMN column_name; For example: For example: ALTER TABLE supplier DROP COLUMN supplier_name; This will drop the column called supplier_name This will drop the column called supplier_name from the table called supplier. from the table called supplier. 26

27. Chapter 7 © 2007 by Prentice Hall Alter Table Statement Rename column(s) in a table (NEW in Oracle 9i Release 2) Rename column(s) in a table (NEW in Oracle 9i Release 2) To rename a column in an existing table, the ALTER TABLE syntax is: To rename a column in an existing table, the ALTER TABLE syntax is: ALTER TABLE table_name RENAME COLUMN old_name to new_name; For example: For example: ALTER TABLE supplier RENAME COLUMN supplier_name to sname; This will rename the column called supplier_name to sname. This will rename the column called supplier_name to sname. 27

28. Chapter 7 © 2007 by Prentice Hall 28 Insert Statement Adds data to a table Adds data to a table Inserting into a table Inserting into a table INSERT INTO CUSTOMER_T VALUES (001, ‘Contemporary Casuals’, ‘1355 S. Himes Blvd.’, ‘Gainesville’, ‘FL’, 32601); INSERT INTO CUSTOMER_T VALUES (001, ‘Contemporary Casuals’, ‘1355 S. Himes Blvd.’, ‘Gainesville’, ‘FL’, 32601); Inserting a record that has some null attributes requires identifying the fields that actually get data Inserting a record that has some null attributes requires identifying the fields that actually get data INSERT INTO PRODUCT_T (PRODUCT_ID, PRODUCT_DESCRIPTION,PRODUCT_FINISH, STANDARD_PRICE, PRODUCT_ON_HAND) VALUES (1, ‘End Table’, ‘Cherry’, 175, 8); INSERT INTO PRODUCT_T (PRODUCT_ID, PRODUCT_DESCRIPTION,PRODUCT_FINISH, STANDARD_PRICE, PRODUCT_ON_HAND) VALUES (1, ‘End Table’, ‘Cherry’, 175, 8); Inserting from another table Inserting from another table INSERT INTO CA_CUSTOMER_T SELECT * FROM CUSTOMER_T WHERE STATE = ‘CA’; INSERT INTO CA_CUSTOMER_T SELECT * FROM CUSTOMER_T WHERE STATE = ‘CA’;

29. Chapter 7 © 2007 by Prentice Hall 29 Creating Tables with Identity Columns Inserting into a table does not require explicit customer ID entry or field list INSERT INTO CUSTOMER_T VALUES ( ‘Contemporary Casuals’, ‘1355 S. Himes Blvd.’, ‘Gainesville’, ‘FL’, 32601); New with SQL:2003

30. Chapter 7 © 2007 by Prentice Hall 30 Delete Statement Removes rows from a table Removes rows from a table Delete certain rows Delete certain rows DELETE FROM CUSTOMER_T WHERE STATE = ‘HI’; DELETE FROM CUSTOMER_T WHERE STATE = ‘HI’; Delete all rows Delete all rows DELETE FROM CUSTOMER_T; DELETE FROM CUSTOMER_T;

31. Chapter 7 © 2007 by Prentice Hall 31 Update Statement Modifies data in existing rows Modifies data in existing rows UPDATE PRODUCT_T SET UNIT_PRICE = 775 WHERE PRODUCT_ID = 7; UPDATE PRODUCT_T SET UNIT_PRICE = 775 WHERE PRODUCT_ID = 7;

32. Chapter 7 © 2007 by Prentice Hall Creating Indexes Indexes are used to provide rapid access to tables data. Indexes are used to provide rapid access to tables data. Although, users don’t directly refer to indexes, the RDMS recognizes which indexes would improve the query performance. Although, users don’t directly refer to indexes, the RDMS recognizes which indexes would improve the query performance. Indexes can usually be created for primary and foreign keys ( simple and composite) Indexes can usually be created for primary and foreign keys ( simple and composite) 32

33. Chapter 7 © 2007 by Prentice Hall Create Index To create an alphabetical index on customer name in Customer Table: To create an alphabetical index on customer name in Customer Table: Create index Name_IDX on Customer_T(Customer_Name); once an index is created, it will be updated as data are entered, updated, or deleted. To remove Index: Drop Index Name_IDX; 33

34. Chapter 7 © 2007 by Prentice Hall 34 SELECT Statement Used for queries on single or multiple tables Used for queries on single or multiple tables Clauses of the SELECT statement: Clauses of the SELECT statement: SELECT SELECT List the columns (and expressions) that should be returned from the query List the columns (and expressions) that should be returned from the query FROM FROM Indicate the table(s) or view(s) from which data will be obtained Indicate the table(s) or view(s) from which data will be obtained WHERE WHERE Indicate the conditions under which a row will be included in the result Indicate the conditions under which a row will be included in the result GROUP BY GROUP BY Indicate categorization of results Indicate categorization of results HAVING HAVING Indicate the conditions under which a category (group) will be included Indicate the conditions under which a category (group) will be included ORDER BY ORDER BY Sorts the result according to specified criteria Sorts the result according to specified criteria

35. Chapter 7 © 2007 by Prentice Hall 35 Figure 7-10 SQL statement processing order (adapted from van der Lans, p.100)

36. Chapter 7 © 2007 by Prentice Hall 36 SELECT Example Find products with standard price less than $275 Find products with standard price less than $275 SELECT PRODUCT_NAME, STANDARD_PRICE FROM PRODUCT_V WHERE STANDARD_PRICE < 275; Table 7-3: Comparison Operators in SQL

37. Chapter 7 © 2007 by Prentice Hall 37 SELECT Example Using Alias Alias is an alternative column or table name Alias is an alternative column or table name SELECT CUST.CUSTOMER AS NAME, CUST.CUSTOMER_ADDRESS FROM CUSTOMER_V CUST WHERE NAME = ‘Home Furnishings’;

38. Chapter 7 © 2007 by Prentice Hall 38 SELECT Example Using a Function Using the COUNT aggregate function to find totals Using the COUNT aggregate function to find totals SELECT COUNT(*) FROM ORDER_LINE_V WHERE ORDER_ID = 1004; Note: with aggregate functions you can’t have single-valued columns included in the SELECT clause

39. Chapter 7 © 2007 by Prentice Hall 39 SELECT Example–Boolean Operators AND, OR, and NOT Operators for customizing conditions in WHERE clause AND, OR, and NOT Operators for customizing conditions in WHERE clause SELECT PRODUCT_DESCRIPTION, PRODUCT_FINISH, STANDARD_PRICE FROM PRODUCT_V WHERE (PRODUCT_DESCRIPTION LIKE ‘%Desk’ OR PRODUCT_DESCRIPTION LIKE ‘%Table’) AND UNIT_PRICE > 300; Note: the LIKE operator allows you to compare strings using wildcards. For example, the % wildcard in ‘%Desk’ indicates that all strings that have any number of characters preceding the word “Desk” will be allowed

40. Chapter 7 © 2007 by Prentice Hall 40 Venn Diagram from Previous Query

41. Chapter 7 © 2007 by Prentice Hall 41 SELECT Example – Sorting Results with the ORDER BY Clause Sort the results first by STATE, and within a state by CUSTOMER_NAME Sort the results first by STATE, and within a state by CUSTOMER_NAME SELECT CUSTOMER_NAME, CITY, STATE FROM CUSTOMER_V WHERE STATE IN (‘FL’, ‘TX’, ‘CA’, ‘HI’) ORDER BY STATE, CUSTOMER_NAME; Note: the IN operator in this example allows you to include rows whose STATE value is either FL, TX, CA, or HI. It is more efficient than separate OR conditions

42. Chapter 7 © 2007 by Prentice Hall 42 SELECT Example– Categorizing Results Using the GROUP BY Clause For use with aggregate functions For use with aggregate functions Scalar aggregate: single value returned from SQL query with aggregate function Scalar aggregate: single value returned from SQL query with aggregate function Vector aggregate: multiple values returned from SQL query with aggregate function (via GROUP BY) Vector aggregate: multiple values returned from SQL query with aggregate function (via GROUP BY) SELECT CUSTOMER_STATE, COUNT(CUSTOMER_STATE) FROM CUSTOMER_V GROUP BY CUSTOMER_STATE; Note: you can use single-value fields with aggregate functions if they are included in the GROUP BY clause

43. Chapter 7 © 2007 by Prentice Hall 43 SELECT Example– Qualifying Results by Categories Using the HAVING Clause For use with GROUP BY For use with GROUP BY SELECT CUSTOMER_STATE, COUNT(CUSTOMER_STATE) FROM CUSTOMER_V GROUP BY CUSTOMER_STATE HAVING COUNT(CUSTOMER_STATE) > 1; Like a WHERE clause, but it operates on groups (categories), not on individual rows. Here, only those groups with total numbers greater than 1 will be included in final result Here, only those groups with total numbers greater than 1 will be included in final result

44. Chapter 7 © 2007 by Prentice Hall 44 Using and Defining Views Views provide users controlled access to tables Views provide users controlled access to tables Base Table –table containing the raw data Base Table –table containing the raw data Dynamic View Dynamic View A “virtual table” created dynamically upon request by a user A “virtual table” created dynamically upon request by a user No data actually stored; instead data from base table made available to user No data actually stored; instead data from base table made available to user Based on SQL SELECT statement on base tables or other views Based on SQL SELECT statement on base tables or other views Materialized View Materialized View Copy or replication of data Copy or replication of data Data actually stored Data actually stored Must be refreshed periodically to match the corresponding base tables Must be refreshed periodically to match the corresponding base tables

45. Chapter 7 © 2007 by Prentice Hall 45 Sample CREATE VIEW CREATE VIEW EXPENSIVE_STUFF_V AS SELECT PRODUCT_ID, PRODUCT_NAME, UNIT_PRICE FROM PRODUCT_T WHERE UNIT_PRICE >300 WITH CHECK_OPTION;  View has a name  View is based on a SELECT statement  CHECK_OPTION works only for updateable views and prevents updates that would create rows not included in the view

46. Chapter 7 © 2007 by Prentice Hall 46 Advantages of Views Simplify query commands Simplify query commands Assist with data security (but don't rely on views for security, there are more important security measures) Assist with data security (but don't rely on views for security, there are more important security measures) Enhance programming productivity Enhance programming productivity Contain most current base table data Contain most current base table data Use little storage space Use little storage space Provide customized view for user Provide customized view for user Establish physical data independence Establish physical data independence

47. Chapter 7 © 2007 by Prentice Hall 47 Disadvantages of Views Use processing time each time view is referenced Use processing time each time view is referenced May or may not be directly updateable May or may not be directly updateable

48. Chapter 7 © 2007 by Prentice Hall 48 Schema Definition Control processing/storage efficiency Control processing/storage efficiency Some techniques used to tune dbase performance: Some techniques used to tune dbase performance: Choosing to index keys to increase the speed of row selection, table joining, and row ordering. Choosing to index keys to increase the speed of row selection, table joining, and row ordering. Selecting File organizations for base tables that match type of processing (keeping table physically sorted by a frequently used sort key) Selecting File organizations for base tables that match type of processing (keeping table physically sorted by a frequently used sort key) Selecting File organizations for indexes appropriate to the way the indexes are used. Selecting File organizations for indexes appropriate to the way the indexes are used. Data clustering so that related rows of frequently joined tables are stored close together in secondary storage Data clustering so that related rows of frequently joined tables are stored close together in secondary storage Statistics maintenance about tables and their indexes so that DBMS can find the most efficient ways to perform various database operations. Statistics maintenance about tables and their indexes so that DBMS can find the most efficient ways to perform various database operations.

49. Chapter 7 © 2007 by Prentice Hall Creating indexes Creating indexes DBMS uses Indexes to Speed up random/sequential access to base table data DBMS uses Indexes to Speed up random/sequential access to base table data Although users do not directly refer to indexes when writing any SQL command, the DBMS recognizes which existing indexes would improve query performance Although users do not directly refer to indexes when writing any SQL command, the DBMS recognizes which existing indexes would improve query performance Indexes are usually created for both primary and foreign keys and both single and compound keys Indexes are usually created for both primary and foreign keys and both single and compound keys Indexes could be in ascending or descending sequence Indexes could be in ascending or descending sequence Example Example CREATE INDEX NAME_IDX ON CUSTOMER_T(CUSTOMER_NAME) CREATE INDEX NAME_IDX ON CUSTOMER_T(CUSTOMER_NAME) This makes an index for the CUSTOMER_NAME field of the CUSTOMER_T table This makes an index for the CUSTOMER_NAME field of the CUSTOMER_T table To remove the index To remove the index Drop INDEX NAME_IDX Drop INDEX NAME_IDX 49