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CS 380 Introduction to Database Systems (Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views) Outline • Introduction • Data Definition Language • CREATE TABLE • ALTER TABLE • DROP TABLE • Data Manipulation Language • SELECT Statement • INSERT Statement • DELETE Statement • UPDATE Statement • Assertions • Views Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 1 Introduction • SQL: Structured Query Language. • Standard for commercial relational DBMSs, a joint effort by ANSI & ISO. • Benefits of a standardized relational language: • Reduced training costs. • Productivity. • Application portability. • Application longevity. • Reduced dependence on a single vendor. • Cross-system communication. Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 2 “Declarative” Versus “Procedural” • Most DBMSs provide the user with a high-level declarative language interface. • The user has just to specify “what” results he/she would like, leaving the “how” to the DBMS. Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 3 Schema and Catalog Concepts in SQL • The concept of an SQL Schema was incorporated to group together tables & other constructs that belong to the same database application. • Schema: the structure that contains descriptions of objects created by the user (tables, constraints, views, domains, character sets, triggers, rules). • Catalog: a set of schemas that constitute the description of a database. Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 4 Types of SQL Statements • Data Definition Language (DDL): • Commands that define a database. • E.g. CREATE, ALTER, DROP, ...etc. • Data manipulation language (DML): • Commands that maintain and query a database. • E.g. SELECT, INSERT, UPDATE, DELETE. • Data Control Language (DCL): • Commands that control a database, including administering privileges and committing data. • E.g. CONNECT, GRANT, REVOKE, ...etc. Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 5 CREATE Statements • Major CREATE statements: • CREATE SCHEMA: • Defines a portion of the database owned by a particular user. • CREATE SCHEMA COMPANY AUTHORIZATION JSMITH; • CREATE TABLE: • Defines a table and its columns. • CREATE VIEW: • Defines a logical table from one or more views. • Other CREATE statements: DOMAIN, CHARACTER SET, COLLATION, TRANSLATION, ASSERTION. Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 6 CREATE TABLE Construct • CREATE TABLE [schema.] name (column-1 TYPE [DEFAULT value] [constraints], column-2 TYPE [DEFAULT value] [constraints], column-n TYPE [DEFAULT value] [constraints], [table-constraints]); • Where: • [schema.]: schema name followed by a dot. • name: table name. • column-1 to column-n: column names. • TYPE: data type. • [DEFAULT value]: optional default value. • [constraints]: optional constraints, can be specified at column level or at table level. Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 7 Some SQL Data Types (From Oracle) • CHAR(n): a fixed-length string n characters long (default 1, max 255 character). • VARCHAR(n): a variable string up to n character long (max 2000). • INT: an integer number. • DECIMAL(n,d): a number n digits long including d decimal places. • DATE: a valid date YYYY-MM-DD. Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 8 CREATE DOMAIN Construct • A domain can be declared, and the domain name is used with the attribute specification. • This makes it easier to change the data type for a domain that is used by numerous attributes in a schema, and improves schema readability. • Examples: • CREATE DOMAIN SSN_TYPE AS CHAR(9); • CREATE DOMAIN D_NUM AS INT CHECK (D_NUM>0 AND D_NUM<21); Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 9 Constraints • There are essentially five types of constraints: • NOT NULL constraints. • UNIQUE value constraints. • PRIMARY KEY constraints. • FOREIGN KEY constraints. • CHECK constraints. • The syntax of these constraints varies according to whether they are specified at column level or at table level. • Any constraints which apply to multiple columns must be defined as table level constraints. Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 10 Constraints • The syntax for each of the column level constraints is: • NOT NULL • UNIQUE • PRIMARY KEY • REFERENCES table (key) • CHECK (condition) Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 11 Constraints • The syntax for each of the table level constraints is: • UNIQUE (column-list) • [CONSTRAINT name] PRIMARY KEY (column-list) • [CONSTRAINT name] FOREIGN KEY (column-list) REFERENCES table (column-list) • CHECK (condition) • An additional ON DELETE clause may be applied to a foreign key constraint: • ON DELETE CASCADE causes all referencing child records to be deleted whenever a parent record is deleted. • ON DELETE SET NULL causes all referencing child records to be set to NULL whenever a parent record is deleted. Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 12 Steps in Table Creation • Identify data types for attributes. • Determine default values. • Identify columns that can and cannot be null. • Identify columns that must be unique (candidate keys). • Identify primary key - foreign key mates. • Identify constraints on columns (domain specifications). • Create the table and associated indexes. To improve access speed Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 13 CREATE TABLE Example • CREATE TABLE EMPLOYEE (Fname VARCHAR(15) NOT NULL, Minit CHAR, Lname VARCHAR(15) NOT NULL, Ssn CHAR(9) NOT NULL, Bdate DATE, Address VARCHAR(30), Sex CHAR CHECK (LOWER(SEX) IN ('m', 'f')), Salary DECIMAL(10,2), Super_ssn CHAR(9), Dno INT NOT NULL, CONSTRAINT EMPPK PRIMARY KEY (Ssn), CONSTRAINT EMPSUPERFK FOREIGN KEY (Super_ssn) REFERENCES EMPLOYEE (Ssn) ON DELETE SET NULL, CONSTRAINT EMPDEPTFK FOREIGN KEY (Dno) REFERENCES DEPARTMENT (Dnumber) ON DELETE SET NULL); Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 14 ALTER TABLE Construct • Tables can be changed in a number of ways using the SQL statement ALTER TABLE. • Possible actions include: • Adding or dropping a column. • Adding or dropping a constraint. • Changing a column definition. Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 15 ALTER TABLE Construct • To add a column to the EMPLOYEE table: ALTER TABLE EMPLOYEE ADD Job VARCHAR(12); • To add a constraint to the DEPARTMENT table: ALTER TABLE DEPARTMENT ADD CONSTRAINT DEPTMGRFK FOREIGN KEY (Mgr_ssn) REFERENCES EMPLOYEE (Ssn) ON DELETE SET NULL; Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 16 ALTER TABLE Construct • To drop the attribute Address from the EMPLOYEE table: ALTER TABLE EMPLOYEE DROP COLUMN Address CASCADE CONSTRAINTS; • To drop a constraint named EMPSUPERFK from EMPLOYEE table: ALTER TABLE EMPLOYEE DROP CONSTRAINT EMPSUPERFK CASCADE; Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 17 ALTER TABLE Construct • To increase the width of Lname column: ALTER TABLE EMPLOYEE MODIFY Lname VARCHAR2(20); • To add a NOT NULL constraint to the Address column: ALTER TABLE EMPLOYEE MODIFY Address NOT NULL; •To drop an existing default clause: ALTER TABLE DEPARTMENT ALTER Mgr_ssn DROP DEFAULT; • To define a new default clause: ALTER TABLE DEPARTMENT ALTER Mgr_ssn SET DEFAULT '333445555'; Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 18 DROP SCHEMA Construct • The DROP SCHEMA command can be used to drop a schema. • Syntax: DROP SCHEMA name [CASCADE or RESTRICT] • Where: • name: is the name of the schema. • CASCADE: removes the schema and all its tables, domains, and other elements. • RESTRICT: removes the schema only if it has no elements. Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 19 DROP TABLE Construct • The DROP TABLE command deletes all information about the dropped relation from the database. • Syntax: DROP TABLE name [CASCADE CONSTRAINTS] • Where: • name: is the name of the table to be dropped. • CASCADE CONSTRAINTS: drops all referential integrity constraints which refer to keys in the dropped table. Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 20 Basic Queries in SQL • SQL has one basic statement for retrieving data from a database, the SELECT statement. • This is not the same as the SELECT operation of the relational algebra. Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 21 The SQL SELECT Statement • It consists of the following basic clauses: Mandatory SELECT specifies the columns which are to be retrieved FROM specifies the tables from which data is to be retrieved WHERE defines any selection criteria required GROUP BY specifies how output is to be grouped & summarized HAVING determines which group summaries to include in the output ORDER BY defines how the output will be stored Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 22 The SELECT-FROM-WHERE Structure • The basic form of the SELECT statement is: SELECT [DISTINCT] <attribute-list> FROM <table-list> WHERE <condition> • Where: • item-list: a comma-separated list of items to be retrieved. (database attributes, functions, fixed text, ...etc.) • table-list: a comma-separated list of tables from which the attributes are to be retrieved. • condition: a conditional (Boolean) expression that identifies the tuples to be retrieved by the query. • [DISTINCT]: ensures only unique tuples will be returned. • The result of an SQL query is a relation (can be a multiset) Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 23 The SELECT-FROM-WHERE Structure • Query: retrieve the birthdate and address of the employee(s) whose name is ‘John B. Smith’. SELECT FROM WHERE Bdate, Address EMPLOYEE Fname='John' AND Minit='B' AND Lname='Smith'; • Is it similar to a tuple relational expression? Any differences? SELECT Statement Relational Algebra SELECT clause FROM clause WHERE clause project operation cartesian product operation select condition Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 24 The SELECT-FROM-WHERE Structure • Query: retrieve the name and address of all employees who work for the ‘Research’ department. SELECT Fname, Lname, Address FROM EMPLOYEE, DEPARTMENT WHERE Dname='Research' AND Dnumber=Dno; • Query: for every project located in ‘Stafford’, list the project number, the controlling department number, and the department manager’s last name, address, and birthdate. SELECT FROM WHERE Pnumber, Dnum, Lname, Address, Bdate PROJECT, DEPARTMENT, EMPLOYEE Dnum=Dnumber AND Mgr_ssn=ssn AND Plocation='Stafford'; Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 25 Ambiguous Attribute Names, Aliasing, and Tuple Variables • In SQL if the same attribute name is used in more than one relation, the attribute names must be qualified. • Assume that DNO attribute of the EMPLOYEE relation was called DNUMBER. • Query: retrieve the name and address of all employees who work for the ‘Research’ department. SELECT FROM WHERE Fname, Lname, Address EMPLOYEE, DEPARTMENT Dname='Research' AND EMPLOYEE.Dnumber=DEPARTMENT.Dnumber; Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 26 Ambiguous Attribute Names, Aliasing, and Tuple Variables • Ambiguity also arise in the case of queries that refer to the same relation twice, as in the following example. • Query: for each employee, retrieve the employee’s first and last name and the first and last name of his or her immediate supervisor. SELECT E.Fname, E.Lname, S.Fname, S.Lname FROM EMPLOYEE E, EMPLOYEE S WHERE E.Super_ssn=S.Ssn; Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 27 Unspecified WHERE Clause • Query: select all EMPLOYEE SSNs. SELECT Ssn FROM EMPLOYEE; • Query: select all combinations of EMPLOYEE SSN and DEPARTMENT DNAME. SELECT Ssn, Dname FROM EMPLOYEE, DEPARTMENT; Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 28 The Use of Asterisk • Query: retrieve all the attribute values of any EMPLOYEE who work in DEPARTMENT 5. SELECT * FROM EMPLOYEE WHERE Dno =5; • Query: retrieve all the attributes of an EMPLOYEE and all the attributes of the DEPARTMENT in which he or she works for every employee of the ‘Research’ department. SELECT * FROM EMPLOYEE, DEPARTMENT WHERE Dname='Research' AND Dno=Dnumber; Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 29 Tables as Sets in SQL • Query: retrieve the salary of every employee. SELECT Salary FROM EMPLOYEE; • Query: retrieve all distinct salary values. SELECT DISTINCT Salary FROM EMPLOYEE; A set Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 30 The UNION, INTERSECT, & MINUS SET OPERATORS • The relations resulting from these set operations are sets of tuples; that is, duplicate tuples are eliminated from the result. • Query: make a list of all project numbers for projects that involve an employee whose last name is ‘Smith’, either as a worker or as a manager of the department that controls the project. SELECT FROM WHERE UNION SELECT FROM WHERE DISTINCT Pnumber PROJECT, DEPARTMENT, EMPLOYEE Dnum=Dnumber AND Mgr_ssn=Ssn AND Lname='Smith' Union compatible DISTINCT Pnumber PROJECT, WORKS_ON, EMPLOYEE Pnumber=Pno AND Essn=Ssn AND Lname='Smith'; Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 31 Conditional Operators • Main conditional operators include: =, <>, >, <, >=, <=. • Other conditional operators: • IN: tests if an item value appears in a specified list of values. • BETWEEN: tests if an item value lies (inclusively) between two specified values. • IS NULL: tests if an item has a Null value. Null is neither zero (in a numeric item), nor spaces (in a character item). • LIKE: tests if an item value matches a string containing wildcard characters. The wildcard characters are: • %: meaning zero or more occurrences of any character. • _: meaning a single occurrence of any characters. • The keyword NOT can be used in conjunction with all the above operators to revise the test. Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 32 Conditional Operators • Query: retrieve the names of all employees whose salary is not (20000, 30000, or 40000). SELECT Fname, Lname FROM EMPLOYEE WHERE Salary NOT IN (20000, 30000, 40000); • Query: retrieve all employees in department 5 whose salary is between $30,000 and $40,000. SELECT * FROM EMPLOYEE WHERE (Salary BETWEEN 30000 AND 40000) AND Dno = 5; Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 33 Conditional Operators • Query: retrieve the names of all employees who do not have supervisors. SELECT Fname, Lname FROM EMPLOYEE WHERE Super_ssn IS NULL; • Query: retrieve all employees whose address is in Houston, Texas. SELECT Fname, Lname FROM EMPLOYEE WHERE Address LIKE '%Houston, TX%'; Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 34 Arithmetic Operations • The standard arithmetic operations (+, -, *, /) can be applied to numeric values or attributes with numeric domains. • Query: show the resulting salaries if every employee working on the ‘ProductX’ project is given 10 percent raise. SELECT Fname, Lname, 1.1*Salary INCREASED_SAL FROM EMPLOYEE, WORKS_ON, PROJECT WHERE Ssn=Essn AND Pno=Pnumber AND Pname='ProductX'; Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 35 Ordering of Query Results • SQL allows the user to order the tuples in the result of a query by the values of one or more attributes, using the ORDER BY clause. • Query: retrieve a list of employees and the projects they are working on, ordered by department and, within each department, ordered alphabetically by last name, first name. SELECT FROM WHERE Dname, Lname, Fname, Pname DEPARTMENT, EMPLOYEE, WORKS_ON, PROJECT Dnumber=Dno AND Ssn=Essn AND Pno=Pnumber ORDER BY Dname, Lname, Fname; • The default order is in ascending order. • ORDER BY Dname DESC, Lname ASC, Fname ASC Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 36 Nested Queries • Some queries require that existing values in the database be fetched and then used in a comparison condition. • Such queries can be conveniently formulated by using nested queries. • Nested queries: complete select-from-where blocks usually within the WHERE clause of another query. That other query is called the outer query. Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 38 Nested Queries • Query: make a list of all project numbers for projects that involve an employee whose last name is ‘Smith’, either as a worker or as a manager of the department that controls the project. SELECT FROM WHERE DISTINCT Pnumber PROJECT Pnumber IN (SELECT Pnumber FROM PROJECT, EMPLOYEE, DEPARTMENT WHERE Dnum=Dnumber AND Mgr_ssn=Ssn AND Lname='Smith') OR Pnumber IN (SELECT Pno FROM WORKS_ON, EMPLOYEE WHERE Essn=Ssn AND Lname='Smith'); Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 39 Nested Queries • SQL allows the use of tuples of values in comparisons by placing them within parentheses. • Example: SELECT FROM WHERE DISTINCT WORKS_ON (Pno, Hours) Essn IN (SELECT FROM WHERE Pno, Hours WORKS_ON Essn='123456789'); Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 40 Nested Queries • In addition to the IN operator, a number of other comparison operators can be used to compare a single value (attribute) to a set or multiset. • The keywords ANY or ALL can be combined with the following operators: >, >=, <, <=, <>. (= ANY is equivalent to IN) • Query: list the names of employees whose salary is greater than the the salary of all the employees in department 5. SELECT Lname, Fname FROM EMPLOYEE WHERE Salary > ALL (SELECT Salary FROM EMPLOYEE WHERE Dno=5); Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 41 The EXISTS Function in SQL • This function checks whether the result of a correlated nested query is empty (contains no tuples) or not. • Query: retrieve the name of each employee who has a dependent with the same first name and same sex as the employee. SELECT FROM WHERE E.Fname, E.Lname EMPLOYEE E EXISTS (SELECT FROM WHERE * DEPENDENT E.Ssn=Essn AND E.Sex=Sex AND E.Fname=Dependent_name); Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 44 The EXISTS Function in SQL • Query: retrieve the names of employees who have no dependents. SELECT Fname, Lname FROM EMPLOYEE WHERE NOT EXISTS (SELECT * FROM DEPENDENT WHERE Ssn=Essn); Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 45 Aggregate Function in SQL • A number of built-in functions exist: COUNT, SUM, MAX, MIN, and AVG. • These functions can be used in the SELECT clause or in the HAVING clause. • The functions SUM, MAX, MIN, and AVG are applied to a set or multiset of numeric values. • The functions MAX and MIN can also be used with attributes that have nonnumeric domains if the domain values have a total ordering among one another. • Null values are discarded when aggregate functions are applied to a particular attribute. Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 50 Aggregate Function in SQL • Query: find the sum of the salaries of all employees, the maximum salary, the minimum salary, and the average salary. SELECT FROM SUM (Salary), MAX (Salary), MIN (Salary), AVG (Salary) EMPLOYEE; • Query: find the sum of the salaries of all employees of the ‘Research’ department, as well as the maximum salary, the minimum salary, and the average salary in this department. SELECT SUM (Salary), MAX (Salary), MIN (Salary), AVG (Salary) FROM EMPLOYEE, DEPARTMENT WHERE Dno=Dnumber AND Dname='Research'; Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 51 Aggregate Function in SQL • Query: retrieve the total number of employees in the company. SELECT COUNT(*) FROM EMPLOYEE; • Query: retrieve the total number of employees in the ‘Research’ department. SELECT COUNT(*) FROM EMPLOYEE, DEPARTMENT WHERE Dno=Dnumber AND Dname='Research'; Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 52 Aggregate Function in SQL • Query: Count the number of distinct salary values in the database. SELECT COUNT(DISTINCT Salary) FROM EMPLOYEE; • Query: retrieve the names of all employees who have two or more dependents. SELECT Lname, Fname FROM EMPLOYEE WHERE (SELECT COUNT(*) FROM DEPENDENT WHERE Ssn=Essn) >= 2; Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 53 The GROUP BY Clause • This clause enables aggregates to be accumulated and grouped on output. • Query: for each department, retrieve the department number, the number of employees in the department, and their average salary. SELECT DNO, COUNT(*), AVG(Salary) FROM EMPLOYEE GROUP BY Dno; • If Nulls exist in the grouping attribute, then a separate group is created for all tuples with a NULL value in the grouping attribute. Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 54 The HAVING Clause • This clause specifies which groups are to be selected for output. • Groups are only output if they match the condition(s) specified by the HAVING clause. • Query: for each project on which more than two employees work, retrieve the project number, the project name, and the number of employees who work on the project. SELECT Pnumber, Pname, COUNT(*) FROM PROJECT, WORKS_ON WHERE Pnumber=Pno GROUP BY Pnumber, Pname HAVING COUNT(*) >2; Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 56 INSERT, DELETE, and UPDATE Statements • In SQL, three commands can be used to modify the database: • INSERT. • DELETE. • UPDATE. Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 59 The INSERT Statement • Using the SQL INSERT statement, rows may be inserted into tables in two ways: • As lists of values, one row at a time. • From another table using a query. Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 60 INSERT Using a Value List • Syntax: INSERT INTO table [(attribute-list)] VALUES (value-list) • Where: • table: the name of the table to update. • attribute-list: a list of attributes in the specified table. • value-list: the list of values to be inserted for the row. Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 61 INSERT Using a Value List • Example: INSERT INTO PROJECT VALUES ('ProductZ', 1, NULL, 2) • Example: INSERT INTO PROJECT (PNAME, PNUMBER, DNUM) VALUES ('ProductZ', 1, 2) • Example: INSERT INTO PROJECT (PNAME, PNUMBER, DNUM) VALUES ('&PN', &P_NO, &D_NO) Each time it is run, the user will be prompted for a new set of values Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 62 INSERT Using a Query • Syntax: INSERT INTO table [(attribute-list)] SELECT statement • There are no limitation concerning the SELECT statement. Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 63 INSERT Using a Query • Example: CREATE TABLE (DEPT_NAME NO_OF_EMPS TOTAL_SAL DEPTS_INFO VARCHAR(15), INTEGER, INTEGER); INSERT INTO DEPTS_INFO SELECT DNAME, COUNT(*), SUM (Salary) FROM DEPARTMENT, EMPLOYEE WHERE Dnumber=Dno GROUP BY Dname; Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 64 The DELETE Statement • Syntax: DELETE FROM table [WHERE conditions] • Example: DELETE WHERE • Example: DELETE WHERE • Example: DELETE FROM EMPLOYEE Lname='Brown'; FROM EMPLOYEE Dno IN (SELECT Dnumber FROM DEPARTMENT WHERE Dname='Research'); FROM EMPLOYEE; Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 65 The UPDATE Statement • The UPDATE statement can be used: • With individual values. • In conjunction with a SELECT statement. Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 66 UPDATE Using Fixed Values • Syntax: UPDATE SET table attribute-1 = value-1, attribute-2 = value-2, : attribute-n = value-n [WHERE conditions] • Example: UPDATE SET WHERE PROJECT Plocation = 'Bellaire' Pnumber=10; • Example: UPDATE SET EMPLOYEE Salary = Salary * 1.25; Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 67 UPDATE Using a Query • Syntax: UPDATE table SET (attribute-list) = (SELECT statement) [WHERE conditions] • Example: Update SET = ( SELECT FROM WHERE WHERE EMPLOYEE (Salary) Salary EMPLOYEE Ssn='987654321') Fname = 'John' AND Lname='Smith'; Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 68 Concept of a View (Virtual Table) in SQL • A view is a customized representation of one or more underlying tables or other views (or a mixture of both). • A view does not necessarily exist in physical form. • Allows full query operations. • Allows limited update operations (since the table may not physically be stored). • Convenience for expressing certain operations. Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 70 Concept of a View (Virtual Table) in SQL • Advantages of views: • Simplify query commands. • Provide data security. • Enhance programming productivity. Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 71 Specification of Views in SQL • Example: CREATE SELECT FROM WHERE VIEW WORKS_ON1 AS Fname, Lname, Pname, Hours EMPLOYEE, PROJECT, WORKS_ON Ssn=Essn AND Pno=Pnumber; • Example: CREATE VIEW DEPT_INFO(Dept_name, No_of_emps, Total_sal) AS SELECT Dname, COUNT(*), SUM(Salary) FROM DEPARTMENT, EMPLOYEE WHERE Dnumber=Dno GROUP BY Dname; Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 72 Specification of Views in SQL • Query: retrieve the last name and first name of all employees who work on ‘ProjectX’. SELECT Fname, Lname FROM WORKS_ON1 WHERE Pname='ProjectX'; • A view is supposed to be always up to date. • When no longer needed, a view can be dropped: DROP VIEW name Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 73 Effective View Implementation • Two main approaches have been suggested: • Query modification: involves modifying the view query into a query on the underlying base tables. I.e, the previous query would be automatically modified to: SELECT Fname, Lname FROM EMPLOYEE, PROJECT, WORKS_ON WHERE Ssn=Essn AND Pno=Pnumber AND Pname='ProjectX'; • View Materialization: involves physically creating a temporary view table (should be kept up to date). Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 74 View Update • A view with a single defining table is updatable if the view attributes contain the primary key of the base relation, as well as all attributes with the NOT NULL constraint that do not have default values specified. • Views defined on multiple tables using joins are generally not updatable. • Views defined using grouping and aggregate functions are not updatable. Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 75 View Update • In SQL, the clause WITH CHECK OPTION must be added at the end of the new definition if the view is to be updated. Chapter 8: SQL-99: Schema Definition, Constraints, Queries, and Views 76