1. STRUCTURED QUERY LANGUAGE Chandra S. Amaravadi 1

2. IN THIS PRESENTATION Codd’s rules for relational systems Types of SQL DDL and DML Examples 2

3. CODD’S RULES AND TYPES OF SQL 3

4. CODD’S RULES FOR RDBMSs Information representation Guaranteed access Dynamic on-line catalog Comprehensive data sub-language View updating Note: Codd was a research fellow at IBM in the ’70s Codd has written a paper in which he outlined the rules for relational systems. These are as follows: 4

5. High-level insert, update and delete Physical data independence Logical data independence Integrity independence Distribution independence Non-subversion CODD’S RULES FOR RDBMSs.. 5

6. CODD’S RULES FOR RDBMSs Information representation -- all information should be represented as atomic values in tables. Guaranteed access -- given a row, column and table name we should be able to access values in the table. Online catalog -- the system catalog (data dictionary) should be online and accessible by the system. Comp. data lang. -- there should be a language for data definition and data manipulation. View updating -- the system must be able to automatically update views based on a base table. 6

7. CODD’S RULES FOR RDBMSs High level insertion, update.. -- insertion, deletion and update should operate on a table. Physical data independence -- should be able to change internal storage structures without affecting application programs. Logical data independence -- should be able to change logical scheama without affecting application programs. Integrity independence -- integrity controls must be independent of appln. prog. Distribution independence -- the users/appln. programs should not be affected by where the data is physically stored. Non subversion -- should not be able to bypass integrity rules by using the data sub language. 7

8. based on relational calculus (uses select, project, join etc.) standardized in ’82,’95, ‘05 Embedded SQL a standard in ‘89 Two major types and three other types DDL, DML SQL/T, SQL/I, DCL Embedded SQL STRUCTURED QUERY LANGUAGE Structured Query Language originated from SEQEL (early 1980’s). SQL (is/was): 8

9. There are five types of SQL as follows: DDL- Creating / modifying tables, views and indexes DML - Retrieving / inserting / updating information SQL/T - Transaction boundaries SQL/I - Integrity constraints DCL. - To authorize access to the database objects STRUCTURED QUERY LANGUAGE 9

10. DATA DEFINITION LANGUAGE 10

11. DATA DEFINITION LANGUAGE Create/Open Database (not discussed) Create Schema Employee; Create/Alter/Drop Table Create/Drop View Create/Drop Index DDL is the language used to define/modify the database Schema. 11

12. DATA DEFINITION LANGUAGE.. Action DatabaseComponent ComponentName… TYPICAL FORMAT Create Drop Table View Index Cust….. Emp….. ………… 12 AlterTableEmp…..

13. CREATE TABLE Table name (attribute attr. type, attribute attr.type..) [CONSTRAINT Constr name TYPE attr]; ALTER TABLE Table name ADD attr. attr. type, attr. attr. type; DATA DEFINITION LANGUAGE.. Command used to create tables Command used to change attributes in tables Command used to delete table definitions DROP TABLE Table name ; 13

14. CREATE TABLE Dept. d_no d_name d_mgr_ssn d_phone CREATE TABLE DEPT. ( d_no Integer, d_name VarChar(15), d_mgr_SSN Char(9), d_phone Char(12)); Creates a table (schema) 14

15. ALTER, DROP TABLE Dept. d_no d_name d_mgr_ssn d_phone no_of_emp ALTER TABLE DEPT. ADD no_of_emp Integer; DROP TABLE Dept.; Alter table adds/drops attributes; Drop table drops the entire table. 15 ALTER TABLE DEPT. DROP no_of_emp;

16. CREATE VIEW Viewname AS SELECT... CREATE VIEW Command used to create VIEWS A view is the way a user looks at the data. Views are subsets of the data in the database. A view could include data from more than one table. All application programs access data via views. Views provide logical data independence. Reports can be created from views (as well as from tables) 16

17. CREATE VIEW.. Emp. e_ssn e_name e_title CREATE VIEW Analysts AS SELECT e_name, e_title FROM Emp. WHERE e_title = “analyst”; Create a view of employees who are analysts Creates a query; AS is an “alias” or name 17 DROP VIEW ANALYSTS;

18. 18 CREATE/DROP INDEX CREATE INDEX TI_INDEX ON EMP(e_title); DROP INDEX TI_INDEX; An index is an example of file organization used to facilitate retrieval

19. DATA MANIPULATION LANGUAGE 19

20. DATA MANIPULATION LANGUAGE INSERT insert a record UPDATE change values DELETE delete records SELECT choose record DML is the language used to create/modify and delete data in the database. 20

21. THE INSERT COMMAND.. INSERT INTO TABLENAME VALUES (attr1 value, attr2 value….); FORMAT Inserts a record into a table with name TABLENAME. 21

22. THE INSERT COMMAND.. INSERT INTO EMP VALUES (‘978-98-9878’, ‘Sullivan’, ‘developer’); Insert employee record EMP. e_ssn e_name e_title e_ssne_namee_title 978-98-9878Sullivandeveloper 22

23. THE UPDATE COMMAND EMP. e_ssn e_name e_title UPDATE EMP SET e_title = ‘analyst’ WHERE e_name = ‘Sullivan’; Update employee title to ‘analyst’ /* table name */ /* new values */ /* condition */ e_ssne_namee_title 978-98-9878Sullivananalyst EMP. 23

24. THE DELETE COMMAND DELETE FROM EMP. WHERE e_name = ‘Sullivan’; Delete Employee record e_ssne_namee_title EMP. e_ssne_namee_title 978-98-9878Sullivananalyst What if you were to issue, DELETE FROM EMP? EMP. 24

25. THE SELECT STATEMENT 25

26. THE SELECT STATEMENT SELECT FROM [WHERE AND/OR ] [GROUP BY ] [HAVING ] [ORDER BY DESC/ASC]; Group by is used to organize data into groups and provide summary information. Having is used for the group condition. 26

27. ADDITIONAL NOTES ON SELECT The Select part can include literals (“The number of..”) Some functions can be included in SELECT part or WHERE part More than one table and one condition can be specified Conditions are connected by logical operators -- and/or etc. When GROUP BY is used, the WHERE clause is not used. Instead the group condition is specified by HAVING. ORDER BY is optional and used if sorting is required. Notes on the select statement 27

28. DISCUSSION The output of a SELECT statement is: a) an attribute ? b) a single record ? c) table ? 28

29. FUNCTIONS IN SQL Logical Arithmetic String Date IN WHICH PART OF THE QUERY ARE FUNCTIONS USED? Operators to carry out different types of calculations 29

30. LOGICAL OPERATORS “=“, “>“, “<“ “>=“, “<=“ “<>“ OR “!=“ (NOT) BETWEEN X1 AND X2 (inclusive) LIKE “_” or “%” IN (NOT) NULL Finance Financial Records Logical operators are generally used to carry out comparison (Select….Where D_Name like “%fin%”) 30 d_named_phone Finance845-9878 Sales989-0087 Marketing787-9934 Fin. records884-5768 Dept.

31. LOGICAL OPERATORS.. Select cust.cust# From cust Where cust.zip in (61455, 60601….) Select emp#, emp name From emp Where income between 70000 and 90000; To select customers in Macomb, Chicago or Bloomington To select employees between certain income range 31 cust#zip 1156 61455 115761455 115854555 116060601 Cust.

32. BUILT-IN ARITHMETIC FUNCTIONS ABS ROUND TRUNC COUNT SUM AVG MAX MIN Select count(emp_name)… Select max(emp_salary)….. Arithmetic functions are used to carry out math operations 32

33. STRING FUNCTIONS LENGTH(string) SUBSTR(string, start, no of ch.) LOWER UPPER Select substr(prob_descr, 0, 10) ……… String functions are used to carry out string manipulation Prob_descr = “I am unable to log in…” 33

34. DATE FUNCTIONS ADD_MONTHS(1/1/15, 5) = 6/1/15 MONTHS_BETWEEN (sysdate, hiredate) NEXT_DAY(hiredate, ‘Friday’) TO_DATE(string, picture) TO_DATE(“12/09/14”, ‘DY th MM, YYYY’) = 9 th DEC, 2014 Next_day(2/20/14, ‘Friday’) = 2/21/14 Date functions are used to carry out date arithmetic 34

35. SIMPLE RETRIEVALS EMP. e_ssn e_name e_title SELECT e_name FROM EMP WHERE e_title = ‘analyst’; Select employees who are analysts 35

36. EMPLOYEE SIMPLE RETRIEVALS.. e_ssne_namee_titlee_salary 456-34-8895Smithdeveloper$35,000 459-66-6785Johnsonanalyst$27,000 467-89-8898Weintraubdeveloper$60,000 478-64-8005Dicksonmanager$64,000 489-12-5575Ferrelanalyst$47,000 492-93-4438Raoanalyst$71,000 467-89-8898McDonaldmanager $85,000 36

37. SIMPLE RETRIEVALS.. SELECT e_name FROM EMP WHERE e_name like ‘%son’ Select employees whose name ends with ‘son’ EMP. e_ssn e_name e_title 37

38. SIMPLE RETRIEVALS.. SELECT e_name FROM EMP WHERE e_name not like ‘a%’ Select employees whose name does not begin with ‘a’ EMP. e_ssn e_name e_title 38

39. RETRIEVALS WITH AGGREGATES.. SELECT COUNT(e_name) FROM EMP WHERE e_title = ‘developer’ Count the number of developers EMP. e_ssn e_name e_title 39

40. SELECT “Average Salary=“, Avg(e_salary) From EMP Where e_title = ‘developer’ or e_title = ‘analyst’ ; EMP. e_ssn e_name e_title e_salary RETRIEVALS WITH AGGREGATES.. What does this query do? 40

41. RETRIEVALS WITH EXPRESSIONS.. List employees and their witholdings (calculated as 8% of salary). EMP. e_ssn e_name e_title e_salary 41 SELECT e_name, e_salary * 0.08 AS Withholdings FROM EMP

42. RETRIEVALS WITH GROUP BY.. SELECT e_title, COUNT(e_name) FROM EMP GROUP BY e_title List all job titles and the number of emps in each EMP. e_ssn e_name e_title 42

43. GROUP BY.. EMPLOYEE 43 e_ssne_namee_titlee_salary 456-34-8895Smithdeveloper$35,000 459-66-6785Johnsonanalyst$27,000 467-89-8898Weintraubdeveloper$60,000 478-64-8005Dicksonmanager$64,000 489-12-5575Ferrelanalyst$47,000 492-93-4438Raoanalyst$71,000 467-89-8898McDonaldmanager $85,000

44. RETRIEVALS WITH HAVING.. List the number of employees in each job category with salary > $50,000 SELECT “Number of: “, e_title, “=“, COUNT(e_name) FROM EMP GROUP BY e_title HAVING e_salary > 50000 EMP. e_ssn e_name e_title e_salary 44

45. RETRIEVALS WITH HAVING.. EMP. 45 e_ssne_namee_titlee_salary 456-34-8895Smithdeveloper$35,000 459-66-6785Johnsonanalyst$27,000 467-89-8898Weintraubdeveloper$60,000 478-64-8005Dicksonmanager$64,000 489-12-5575Ferrelanalyst$47,000 492-93-4438Raoanalyst$71,000 467-89-8898McDonaldmanager $85,000

46. RETRIEVAL FROM MULTIPLE TABLES Sharing of information a key concept Normalization process leads to multiple tables When data is retrieved from > 1 table, need to link tables together This is done by equating FK values with PK values for each set of tables that need to be linked Emp. emp#, emp name, dept# Dept. dept#, dept name, mgr 46

47. RETRIEVAL FROM MULTIPLE TABLES Dept. d_name d_no d_mgr_ssn d_phone SELECT Emp.e_name, Dept.d_name FROM EMP, dept. WHERE EMP.e_ssn = dept.d_mgr_ssn EMP. e_ssn e_name e_title 47

48. RETRIEVAL FROM MULTIPLE TABLES.. DEPARTMENT EMPLOYEE d_named_nod_mgr_ssnd_phone Manugistics142467-89-8898845-9878 IMS230479-99-0045989-0087 Pilot345478-64-8005787-9934 InfoSec467898-98-0967884-5768 48 e_ssne_namee_titlee_salary 456-34-8895Smithdeveloper$35,000 459-66-6785Johnsonanalyst$27,000 467-89-8898Weintraubdeveloper$60,000 478-64-8005Dicksonmanager$64,000 489-12-5575Ferrelanalyst$47,000 492-93-4438Raoanalyst$71,000 467-89-8898McDonaldmanager $85,000

49. DISCUSSION Write SQL queries for the following: 1. Create Emp table with E_SSN, E_Name, E_title as attr. -- assume data types. 2. Add E_salary to the Employee table. 3. Create an index, “Ti_ndx” on E_title. 4. Insert Bob White with SS# 556455555 as an analyst 5. List employees and job titles in order of title. 6. List employees other than developers. 7. Create a view “hi_flier” listing developers with salary > $100K. 8. Count the #. of employees who are managers. 49

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