1. 1 Basic SQL Prof. Sin-Min Lee Department of Computer Science

2. 2 In this chapter, you will learn:  The basic commands and functions of SQL  How SQL is used for data manipulation (to add, modify, delete, and retrieve data)  How to use SQL to query a database to extract useful information  About more advanced SQL features such as updatable views, stored procedures, and triggers

3. 3 Introduction to SQL  Ideal database language Create database and table structures Perform basic data management chores (add, delete, and modify) Perform complex queries to transform data into useful information  SQL is the ideal DB language Data definition language Data manipulation language

4. 4 Background  IBM developed the original version of SQL at its San Jose Research Laboratory  Evolved as The Sequel language, its name has changed to SQL (Structured Query Language)  SQL has clearly established itself as the standard relational-database language

5. 5 Good Reasons to Study SQL  ANSI standardization effort led to de facto query standard for relational database  Forms basis for present and future DBMS integration efforts  Becomes catalyst in development of distributed databases and database client/server architecture

6. 6 Basic Structure of SQL  Consists of three clauses: (i)Select - Used to list the attributes desired in the result of a query. (ii)From - Lists the relations to be scanned in the evaluation of the expression. (iii)Where - Consists of a predicate involving attributes of the relations that appear in the from clause.

7. 7 SQL a Short Introduction  SQL stands for Structured Query Language Queries are used to extract information from the database. An SQL expression/block consists of three main clauses: select (projection operation) : Lists the attributes desired in the result of a query from (Cartesian-product operation) : List the relation to be scanned in the evaluation of the expression. where (selection predicate) : Consists of predicate involving attributes of the relations that appear in the from clause Example: select name from students where gpa = '4.0' attribute relation condition

8. 8 A typical SQL query form  Select: A 1, A 2,….A n A i represents an attribute.  From: r 1, r 2,….r m r i is a relation  Where: P P represents a predicate.

9. 9 The Select Clause  Example of a Simple Query:  “Find the names of all branches in the loan relation” select branch-name from loan

10. 10 Creating Table Structure  Tables store end-user data  May be based on data dictionary entries CREATE TABLE ( );

11. 11 Data Definition Commands  Create database structure Holds all tables and is a collection of physical files stored on disk DBMS automatically creates tables to store metadata Database administrator creates structure or schema Logical group of tables or logical database Groups tables by owner Enforces security CREATE SCHEMA AUTHORIZATION Example: CREATE SCHEMA AUTHORIZATION JONES

12. 12 Using Domains  Domain is set of permissible values for a column  Definition requires: Name Data type Default value Domain constraint or condition CREATE DOMAIN AS DATA_TYPE [DEFAULT ] [CHECK ( )]

13. 13 Different parts of SQL  Data-definition language  Interactive data-manipulation language  View definition  Transaction Control  Embedded SQL and dynamic SQL  Integrity  Authorization

14. 14 More examples continued  Inserting keyword distinct after select we can eliminate duplication  For instance: select distinct branch-name from loan  Inserting keyword all after select helps restoring duplication.

15. 15 The where clause  Example: “Find all loan numbers for loans made at the Perryridge branch with loan amounts greater than $ 1200.” select loan-number from loan where branch-name = ‘Perryridge’ and amount > 1200

16. 16 More examples of Where clause  Logical connectives like and, or, and not are used in the where clause  Example:  Loan number of those loans with loan amounts between $90,000 & $ 100,000 select loan number from loan where amount between 90000 and 100000

17. 17 The from Clause  Defines a Cartesian product of the relations in the clause.  Example:  “For all customers who have a loan from the bank, find their names, loan numbers and loan amount”

18. 18 The from Clause (Con’d) select customer-name, borrower.loan- number, amount from borrower, loan where borrower.loan-number = loan.loan-number

19. 19 The Rename Operation  Uses as clause to rename both, relations and attributes  The as clause takes the form in SQL: old-name as new-name

20. 20 The Rename Operation (Con’d)  Example:  To change attribute name loan-number to be replaced with name loan-id : select customer-name, borrower.loan-number as loan- id, amount from borrower, loan where borrower.loan-number = loan.loan-number

21. 21 String Operations  SQL specifies by enclosing in single quotes, for example, ‘Perryridge’  “%” character is use to match any substring.  “_” character is use to match any character  It expresses patterns by using the like comparison operator

22. 22 String Operations (Con’d)  Example:  Find the names of all customers whose street address includes the substring ‘Main’ select customer-name from customer where customer-street like ‘%Main%’

23. 23 Set Operations  Operations such as union, intersect, ad except operate on relations.  Corresponds to relational-algebra operations ,  and .  Relations participating in the operations must be compatible; i.e. must have same set of attributes.

24. 24 Union Operation  Example:  To find all customers having a loan, an account, or both at bank: (select customer-name from depositor) union (select customer-name from borrower)

25. 25 Intersect Operation  Example:  To find all customers who have both a loan and an account at the bank: (select distinct customer-name from depositor) intersect (select distinct customer-name from borrower)

26. 26 Except Operation  Example:  To find all customers who have an account but no loan at the bank: (select distinct customer-name) from depositor) except (select customer-name from borrower)

27. 27 Aggregate Functions  These functions take a collection of values as input and return a single value.  SQL offers five built-in aggregate functions: Average: avg Minimum: min Maximum: max Total: sum Count: count

28. 28 Aggregate Functions (Con’d)  Example:  Find the average account balance at the Perryridge branch.” select avg (balance) from account where branch-name =‘Perryridge’

29. 29 Null Values  Used to indicate absence of information about the value of an attribute.  Can use special keyword null in a predicate to test for a null value.

30. 30 Null Values (Con’d)  Example: select loan-number from loan where amount is null

31. 31 Nested Subqueries  A subquery is a select-from-where expression that is nested within another query.  Common use includes: Perform tests for set membership Make set comparisons Determine set cardinality

32. 32 Nested Subqueries (Con’d)  Example:  Find those customers who are borrowers from the bank and who appear in the list of account holders obtained in the subquery select distinct customer-name from borrower where customer-name in (select customer- name from depositor)

33. 33 Views  We define a view in SQL by using the create view command.  To define a view, we must give the view a name and must state the query that computes the view.

34. 34 Views (Con’d)  Example:  Using view all-customer, we can find all customers of the Perryridge branch: select customer-name from all-customer where branch-name = ‘Perryridge’

35. 35 Complex Queries  What are complex queries? Queries that are hard to write as a single SQL block.  Way to compose multiple SQL blocks: Derived Relations:  Subquery expression to be used in the from clause.  The result relation must be given a name and the attributes can be renamed. Example: To find the average account balance of those branches where the avg acct balance is > 1200 select branch-name, avg-balance from (select branch-name, avg(balance) from account group by branch-name) as branch-avg (branch-name, avg-balance) where avg-balance > 1200 result relation renamed attribute ( Note: balance is an attribute in the relation. Since we're calculating the average balance it's more meaningful to rename balance to avg-balance )

36. 36 Complex Queries cont'd  With clause: Makes the query logic clearer by providing ways to define temporary views view, like procedures ( in structure programming ), can be broken up into smaller views for clarity and reusability. Permits view definition to be used in multiple places within a query.

37. 37 Modification of the Database  Add, Remove, and Change information. Insertion ( add ) : Insert data ( tuple or set of tuples ) into a relation Ex: insert into Students values ( 'Jane Doe', '4.0', 'honor'); inserts the student Jane Doe into Students whose GPA 4.0 and who is an honor student. Deletion ( remove ) : Deletes the entire tuple from a relation. Ex: delete from Students where name="Jane Doe"; Update ( change ): Changes a value in a tuple without changing all values in the tuple. Ex: 1. update Students set gpa = 3.5 where name = 'Jane Doe' 2. update Students set dean_list = case when gpa < 4.0 then 'regular' else 'honor' end

38. 38 Joined Relations  SQL provides mechanisms for joining relations, including condition joins and natural joins.  Ways to join relations: Inner join - Combines two relations which contain a common field and eliminating tuples that don't match. left outer join - Combines two relations which contain a common field that results in tuples in left relation to be preserved and the unmatched tuples in the right relation filled with null values. right outer join - Combines two relations which contain a common field that results in tuples in right relation to be preserved and the unmatched tuples in the left relation filled with null values. natural join – Similar to inner join, however, the common attributes of the relations will appear only once.

39. 39 Examples of joined relations:  Suppose we have two relations loan and borrower: Inner join relation: loan inner join borrower on loan.loan-num = borrower.loan-num Natural inner join: loan natural inner join borrower loan-num branch-name amountcust-name loan-num Loan Borrower loan-num branch-nameamountcust-name L-170 L-230 L-260 Downtown Redwood ` PerryRidge1700 4000 3000 Jones Smith Hayes L-170 L-230 L-155 L-170 L-230 Downtown Redwood 3000 4000 Jones Smith loan-num amountcust-name L-170 L-230 3000 4000 Jones Smith branch-nameamountcust-name loan-num L-170 L-230 Downtown Redwood 3000 4000 Jones Smith L-170 L-230 branch-nameamount L-170 L-230 Downtown Redwood 3000 4000

40. 40 Joined relations cont’d  left outer join: Syntax: loan left outer join borrower on loan.loan-num = borrower.loan-num  Right outer join: Syntax: loan right outer join borrower on loan.loan-num = borrower.loan-num branch-nameamountcust-name loan-num L-170 L-230 Downtown Redwood 3000 4000 Jones Smith L-170 L-230 branch-nameamount L-170 L-230 Downtown Redwood 3000 4000 loan-num L-260Perryridge 1700 null branch-nameamountcust-name loan-num L-170 L-230 Downtown Redwood 3000 4000 Jones Smith L-170 L-230 branch-nameamount L-170 L-230 Downtown Redwood 3000 4000 loan-num null HayesL-155

41. 41 SQL Integrity Constraints  Adherence to entity integrity and referential integrity rules is crucial Entity integrity enforced automatically if primary key specified in CREATE TABLE command sequence Referential integrity can be enforced in specification of FOREIGN KEY Other specifications to ensure conditions met: ON DELETE RESTRICT ON UPDATE CASCADE

42. 42 Data Manipulation Commands Common SQL Commands Table 5.3

43. 43 Data Entry and Saving  Enters data into a table  Saves changes to disk INSERT INTO VALUES (attribute 1 value, attribute 2 value, … etc.); COMMIT ;

44. 44 Listing Table Contents and Other Commands  Allows table contents to be listed  UPDATE command makes data entry corrections  ROLLBACK command restores database back to previous condition if COMMIT hasn’t been used  DELETE command removes table row SELECT FROM ;

45. 45 Queries  Creating partial listings of table contents SELECT FROM WHERE ; Table 5.4 Mathematical Operators

46. 46 Examples  Mathematical operators  Mathematical operators on character attributes  Mathematical operators on dates SELECT P_DESCRIPT, P_INDATE, P_PRICE, V_CODE FROM PRODUCT WHERE V_CODE <> 21344; SELECT P_CODE,P_DESCRIPT,P_ONHAND,P_MIN,P_PRICE FROM PRODUCT WHERE P_CODE < ‘1558-QWI’; SELECT P_DESCRIPT,P_ONHAND,P_MIN,P_PRICE,PINDATE FROM PRODUCT WHERE P_INDATE >= ‘01/20/2002’;

47. 47 Computed Columns  New columns can be created through valid computations or formulas Formulas may contain mathematical operators May contain attributes of any tables specified in FROM clause  Alias is alternate name given to table or column in SQL statement SELECT P_DESCRIPT,P_ONHAND,P_PRICE,P_ONHAND*P_PRICE AS TOTVALUE FROM PRODUCT;

48. 48 Operators  Logical: AND, OR, NOT  Rules of precedence Conditions within parenthesis executed first Boolean algebra  Special BETWEEN - defines limits IS NULL - checks for nulls LIKE - checks for similar string IN - checks for value in a set EXISTS - opposite of IS NULL SELECT * FROM PRODUCT WHERE V_CODE = 21344 OR V_CODE = 24288;

49. 49 Advanced Data Management Commands  ALTER - changes table structure  ADD - adds column  MODIFY - changes column characteristics Entering data into new column ALTER TABLE ADD ( ); ALTER TABLE MODIFY ( ); UPDATE PRODUCT SET P_SALECODE = ‘2’ WHERE P_CODE = ‘1546-QQ2’;

50. 50 Advanced Data Management Commands (con’t.)  Dropping a column  Arithmetic operators and rules of precedence ALTER TABLE VENDOR DROP COLUMN V_ORDER; Table 5.5

51. 51 Advanced Data Management Commands (con’t.)  Copying parts of tables  Deleting a table from database  Primary and foreign key designation INSERT INTO SELECT FROM ; DROP TABLE PART; ALTER TABLE LINE ADD PRIMARY KEY (INV_NUMBER, LINE_NUMBER) ADD FOREIGN KEY (INV_NUMBER) REFERENCES INVOICE ADD FOREIGN KEY (PROD_CODE) REFERENCES PRODUCT;

52. 52 Example Aggregate Function Operations  COUNT  MAX and MIN SELECT COUNT(DISTINCT V_CODE) FROM PRODUCT; SELECT COUNT(DISTINCT V_CODE) FROM PRODUCT WHERE P_PRICE <= 10.00; SELECT MIN(P_PRICE) FROM PRODUCT; SELECT P_CODE, P_DESCRIPT, P_PRICE FROM PRODUCT WHERE P_PRICE = MAX(P_PRICE);

53. 53 Example Aggregate Function Operations (con’t.)  SUM  AVG SELECT SUM(P_ONHAND * P_PRICE) FROM PRODUCT; SELECT P_DESCRIPT, P_ONHAND, P_PRICE, V_CODE FROM PRODUCT WHERE P_PRICE > (SELECT AVG(P_PRICE) FROM PRODUCT) ORDER BY P_PRICE DESC;

54. 54 More Complex Queries and SQL Functions  Ordering a listing  Results ascending by default Descending order uses DESC  Cascading order sequence ORDER BY ORDER BY DESC ORDER BY

55. 55 More Complex Queries and SQL Functions (con’t.)  Listing unique values DISTINCT clause produces list of different values  Aggregate functions Mathematical summaries SELECT DISTINCT V_CODE FROM PRODUCT;

56. 56 More Complex Queries and SQL Functions (con’t.)  Grouping data Creates frequency distributions Only valid when used with SQL arithmetic functions HAVING clause operates like WHERE for grouping output SELECT P_SALECODE, MIN(P_PRICE) FROM PRODUCT_2 GROUP BY P_SALECODE; SELECT V_CODE,COUNT(DISTINCT(P_CODE)),AVG(P_PRICE) FROM PRODUCT_2 GROUP BY V_CODE HAVING AVG(P_PRICE) < 10;

57. 57 More Complex Queries and SQL Functions (con’t.)  Virtual tables: creating a view CREATE VIEW command Creates logical table existing only in virtual memory SQL indexes CREATE VIEW PRODUCT_3 AS SELECT P_DESCRIPT, P_ONHAND, P_PRICE FROM PRODUCT WHERE P_PRICE > 50.00; CREATE INDEX P_CODEX ON PRODUCT(P_CODE);

58. 58 More Complex Queries and SQL Functions (con’t.)  Joining database tables Data are retrieved from more than one table Recursive queries joins a table to itself Outer joins can be used when ‘null’ values need to be included in query result SELECT PRODUCT.P_DESCRIPT, PRODUCT.P_PRICE, VENDOR.V_NAME, VENDOR.V_CONTACT, VENDOR.V_AREACODE, VENDOR.V_PHONE FROM PRODUCT, VENDOR WHERE PRODUCT.V_CODE = VENDOR.V_CODE; SELECT A.EMP_NUM,A.EMP_LNAME,A.EMP_MGR, B.EMP_LNAME FROM EMP A, EMP B WHERE A.EMP_MGR=B.EMP_NUM ORDER BY A.EMP_MGR