1. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 1 Modern Database Management 11 th Edition Jeffrey A. Hoffer, V. Ramesh, Heikki Topi First class: Slides # 6, 8, 9, 33~53

2. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 2  Define terms  Define a database using SQL data definition language  Write single table queries using SQL  Establish referential integrity using SQL Focus: Syntax

3. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 3  Structured Query Language  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

4. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 4  1970–E. Codd develops relational database concept  1974-1979–System R with Sequel (later SQL) created at IBM Research Lab  1979–Oracle markets first relational DB with SQL  1986–ANSI SQL standard released  1989, 1992, 1999, 2003–Major ANSI standard updates  Current–SQL is supported by most major database vendors

5. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 5  Specify syntax/semantics for data definition and manipulation  Define data structures and basic operations  Enable portability of database definition and application modules  Specify minimal (level 1) and complete (level 2) standards  Allow for later growth/enhancement to standard

6. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 6  Catalog  A set of schemas that constitute the description of a database  Schema  The structure that contains descriptions of objects created by a user (base tables, views, constraints) 1. Data Definition Language (DDL) 1. Commands that define a database, including creating, altering, and dropping tables and establishing constraints 2. Data Manipulation Language (DML) – our focus 1. Commands that maintain and query a database 3. Data Control Language (DCL) 1. Commands that control a database, including administering privileges and committing data Course priority: 2, 1, 3

7. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall Figure 6-1 A simplified schematic of a typical SQL environment, as described by the SQL: 200n standard 7

8. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 1 2 3 4 5 6  SELECT Major, AVERAGE(GPA), ExpGraduateYr  FROM STUDENT  WHERE ExpGraduateYr = “2018”  GROUP BY Major  HAVING AVERAGE(GPA) >=3.0  ORDER BY Major 8 Just a quick example to show sequence of clauses Column display order can be specified here Cond for records Cond for groups Sequence !

9. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 9

10. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall Figure 6-4 DDL, DML, DCL, and the database development process 10

11. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 11  Data Definition Language (DDL)  Major CREATE statements:  CREATE SCHEMA–defines a portion of the database owned by a particular user  CREATE TABLE–defines a new table and its columns  CREATE VIEW–defines a logical table from one or more tables or views

12. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 12 Figure 6-5 General syntax for CREATE TABLE statement used in data definition language 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 In blue here: constraints, and properties, of attributes

13. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 13 (from Chapter 1, Figure 1-3) 13

14. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 14

15. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 15 Figure 6-6 SQL database definition commands for Pine Valley Furniture Company (Oracle 11g) Overall table definitions

16. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall Defining attributes and their data types Constraint name Cnstr Type Field 16 Primary keys can never have NULL values

17. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall Non-nullable specifications composite key Some primary keys are composite– composed of multiple attributes 17

18. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall Default value Domain constraint  Controlling the values in attributes 18 validation rule

19. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 19 Primary key of parent table Identifying foreign keys and establishing relationships Foreign key of dependent table Constraint name Cnstrnt Type Field REFERENCES Tbl(Key)

20. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 20  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:  Deletes of primary records  Updates of primary records  Inserts of dependent records

21. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 21 Relational integrity is enforced via the primary- key to foreign-key match Figure 6-7 Ensuring data integrity through updates

22. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 22  ALTER TABLE statement allows you to change column specifications:  Table Actions:  Example (adding a new column with a default value) : ADD COLUMN Name Type Default

23. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 23  DROP TABLE statement allows you to remove tables from your schema:  DROP TABLE CUSTOMER_T

24. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 24  Adds one or more rows to a table  Inserting into a table  VALUE – “s” Sequence!!!   Inserting a record that has some null attributes requires identifying the fields that actually get data (field-list) VALUES (value-list) INSERT INTO Table VALUES (value-list)

25. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 25  Inserting from another table  A SUBSET from another table Interpretation?

26. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 26  Removes rows from a table  Delete certain rows  DELETE FROM CUSTOMER_T WHERE CUSTOMERSTATE = ‘HI’;  Delete all rows  DELETE FROM CUSTOMER_T;  Careful!!!

27. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 27  Modifies data in existing rows  Note: the WHERE clause may be a subquery (Chap 7) UPDATE Table-name SET Attribute = Value WHERE Criteria-to-apply-the-update

28. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall  ALTER: changing the columns of the table  ALTER TABLE CUSTOMER_T ADD field…  INSERT: adding records based on the existing table  INSERT INTO CUSTOME_T VALUES (… )  UPDATE: changing the values of some fields in existing records  UPDATE CUSTOMER_T SET field = value …WHERE… 28

29. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall  ALTER: changing the structure of the table  Columns form the structure of a table; changes in columns change the structure of the table  Therefore: ALTER  INSERT: adding records based on existing table – did NOT change structure: only make table longer  Therefore INSERT  UPDATE: changing the values of some fields in existing records: did not even add  Therefore UPDATE 29 Common mistakes

30. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 30 KEY WORD / Change what SYNTAX / Example ALTER: INSERT: UPDATE: 30

31. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 31 Makes it easier to update a table…allows combination of Insert and Update in one statement Useful for updating master tables with new data Interpretation? 31

32. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 32  Control processing/storage efficiency:  Choice of indexes  File organizations for base tables  File organizations for indexes  Data clustering  Statistics maintenance  Creating indexes  Speed up random/sequential access to base table data  Example  CREATE INDEX NAME_IDX ON CUSTOMER_T(CUSTOMERNAME)  This makes an index for the CUSTOMERNAME field of the CUSTOMER_T table

33. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall  This is the CENTER section of the chapter, and the CENTER of this course  Many slides contain multiple points of concepts/skills – do NOT miss the text, and play attention to color code 33 Data manipulation

34. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 34  Find products with standard price less than $275 Every SESLECT statement returns a result table - Can be used as part of another query SELECT DISTINCT: no duplicate rows SELECT * : all columns selected Table 6-3: Comparison Operators in SQL

35. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 35  Alias is an alternative column or table name CUSTNAME SELECT CUST.CUSTOMER_NAME AS NAME, CUST.CUSTOMER_ADDRESS CUST FROM CUSTOMER_V [AS] CUST NAME WHERE NAME = ‘Home Furnishings’; Note1: Specifying source table, P. 262 Note2: Use of alias, P. 263 Table alias Colum alias Used in SELECT while defined in FROM

36. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall  P. 264  ProductStandardPrice*1.1 AS Plus10Percent  What does it look like which contents we learned in Access (in IS 312)?  Observe the result on P. 264 36

37. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 37  Using the COUNT aggregate function to find totals COUNT(*) SELECT COUNT(*) FROM ORDERLINE_T WHERE ORDERID = 1004; Note 1: COUNT(*) SELECT PRODUCT_ID, COUNT(*) FROM ORDER_LINE_V WHERE ORDER_ID = 1004; Note 2: COUNT (*) and COUNT – different  COUNT(*) counts num rows  COUNT(field) counts rows that have not-null val for the field More functions: P. 264~5 Error; P. 265 More exmpl: P. 266

38. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 38  What is average standard price for each [ examine!! ] product in inventory? AVG (STANDARD_PRICE) SELECT AVG (STANDARD_PRICE) AS AVERAGE FROM PROCUCT_V GROUP BY Product_ID;  AVG, COUNT, MAX, MIN, SUM;  LN, EXP, POWER, SQRT  More functions – P. 264  **Issues about set value and aggregates: 265-6**  Wildcards: 267, top  Null values, 268, top Can be w or w/o GROUP BY, but w different meanings

39. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall  Last line on P. 265: SQL cannot return both a row value (such as Product_ID) and a set value (such as COUNT/AVG/SUM of a group);  users must run two separate queries, one that returns row info and one that returns set info 1. SELECT S_ID FROM STUDENT √ 2. SELECT AVG(GPA) FROM STUDENT √ 3. SELECT S_ID, AVG(GPA) FROM STUDENT Χ 39 One of the above is not legitimate 39

40. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 40  IS NULL: the field has a null value – not 0, not space (_), but no value  Useful in scenarios as follows:  Sold_date in a real estate property table  Paid_date in a student registration table  Transaction_amount in a auction table  …  Syntax: WHERE field_name IS NULL  The opposite is: WHERE field_name IS NOT NULL IS NULL

41. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 41  ANDORNOT  AND, OR, and NOT Operators for customizing conditions in WHERE clause 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. Must be very, very, very, VERY careful about the Boolean operations

42. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 42 Figure 6-9 Boolean query without use of parentheses 42

43. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 43  With parentheses…these override the normal precedence of Boolean operators Note: by default, the AND operator takes precedence over the OR operator. With parentheses, you can make the OR take place before the AND.

44. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 44 Figure 6-9 Boolean query with use of parentheses 44 Precaution: Do NOT try to “translate” the logical requirements – IMPLEMENT the logic EXACTLY

45. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 45  Compare: SELECT ORDER_ID FROM ORDER_LINE_V; and – SELECT DISTINCT ORDER_ID FROM ORDER_LINE_V; But: SELECT DISTINCT ORDER_ID, ORDER_QUANTITY FROM ORDER_LINE_V; Compare three figures on 272 & 273

46. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 46  Sort the results first by STATE, and then within a state by the CUSTOMER NAME Note: the IN operator in this example allows you to include rows whose CustomerState value is either FL, TX, CA, or HI. It is more efficient than separate OR conditions. The opposite of IN is NOT IN Can order by multiple fields: primary sort, 2ndry sort, … The LAST clause in SELECT statement

47. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 47  For use with aggregate functions  Scalar aggregate: single value returned from SQL query with aggregate function – those in PP. 264~266 (aggregate of whole table)  Vector aggregate: multiple values returned from SQL query with aggregate function (via GROUP BY) P. 275 near bottom: Each column referenced in the SELECT statement must be referenced in the GROUP BY clause; if not,  it must be used as an argument for an aggregate Fn One value for a group  “vector” Result: P. 275

48. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall  When there is GROUP BY, what is in the SELECT clause should be in either one of the following two:  SELECT field1, AGGREAGTE_FUNCTION(field2)  FROM XYZ - - table  GROUP BY field3  In the above example, the only fields that are allowed are:  field 3 – the one to be grouped by, or  Field 2 – the one that is in the aggregate function  So, unless field1 is field3, it cannot be in SELECT 48 If field1 is not field3,… …it cannot be in SELECT

49. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 1. SELECT S_ID FROM STUDENT 2. SELECT MAJOR, AVG(GPA) FROM STUDENT GROUP BY MAJOR 3. SELECT S_ID, AVG(GPA) FROM STUDENT GROUP BY MAJOR 4. SELECT COUNT(S_ID), AVG(GPA) FROM STUDENT GROUP BY MAJOR 49 One of the above is not legitimate. See Slides #47 & 48 49

50. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 50  For use with GROUP BY 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. See 275-276 The tutorial has good examples on differences of WHERE and HAVING

51. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 51  Used for queries on single or multiple tables  Clauses of the SELECT statement: (Sequence!!)  SELECT  List the columns (and expressions) that should be returned from the query  FROM  Indicate the table(s) or view(s) from which data will be obtained  WHERE  Indicate the conditions under which a row will be included in the result  GROUP BY  Indicate categorization of results  HAVING  Indicate the conditions under which a category (group) will be included  ORDER BY  Sorts the result according to specified criteria Read closely PP. 275-276 Can have multiple sorts – primary, 2ndry, …

52. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 52 Figure 6-10 SQL statement processing order (adapted from van der Lans, 2006 p.100)

53. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 53  The HAVING clause acts like a WHERE clause, but it identifies groups that meet a criterion, rather than rows.  Therefore, you will usually see a HAVING clause …  WHERE qualifies a set of rows, while HAVING qualifies a set of …  There are some conditions that both a group and an individual row can satisfy (w different meaning)  Example:  There are conditions ONLY a group can satisfy  Example: HAVING clause Interpretation: example on P. 276 The whole group meets the condition

54. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 54  Views provide users controlled access to tables  Base Table–table containing the raw data  Dynamic View  A “virtual table” created dynamically upon request by a 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  Materialized View  Copy or replication of data  Data actually stored  Must be refreshed periodically to match the corresponding base tables

55. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 55  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

56. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 56  Syntax of CREATE VIEW:  CREATE VIEW view-name AS SELECT (that provides the rows and columns of the view)  Example:  CREATE VIEW ORDER_TOTALS_V AS SELECT PRODUCT_ID PRODUCT, SUM(STANDARD_PRICE*QUANTITY) TOTAL FROM INVOICE_V GROUP BY PRODUCT_ID; Views

57. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 57  Simplify query commands  Assist with data security (but don't rely on views for security, there are more important security measures)  Enhance programming productivity  Contain most current base table data  Use little storage space  Provide customized view for user  Establish physical data independence

58. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 58  Use processing time each time view is referenced  May or may not be directly updateable

59. Chapter 6 © 2013 Pearson Education, Inc. Publishing as Prentice Hall 1 2 3 4 5 6  SELECT Major, AVERAGE(GPA), (SELECT FROM…)  FROM STUDENT, (SELECT FROM…)  WHERE ExpGraduateYr = (SELECT FROM…)  GROUP BY Major  HAVING (SELECT FROM…) >=3.0  ORDER BY Major 59 Can be subquery Sequence ! Subquery can be used in: -Fields -Tables/views -conditions