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Chapter 5 The SQL Language. 5.1. Data Definition Language. The Data Definition Language (DDL) is used to create and destroy databases and database objects These commands will primarily be used by database administrators during the setup and removal phases of a database project

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Chapter 5 the sql language

Chapter 5The SQL Language


5 1 data definition language
5.1. Data Definition Language

  • The Data Definition Language (DDL) is used to create and destroy databases and database objects

  • These commands will primarily be used by database administrators during the setup and removal phases of a database project

  • Let's take a look at the structure and usage of four basic DDL commands:

    • CREATE

      • Installing a database management system (DBMS) such as SQL Server 2005 on a computer allows you to create and manage many independent databases


  • For example, you may want to maintain a database of customer contacts for your sales department and a personnel database for your Human Resource department

  • The CREATE command can be used to establish each of these databases on your platform

  •  For example, the command:

    CREATE DATABASE Employees 

    creates an empty database named "Employees" on your DBMS


  • After creating the database, your next step is to create tables that will contain data  

  • Another variant of the CREATE command can be used for this purpose

  • The command: 

    CREATE TABLE personal_info(first_name varchar(20) NOT NULL, last_name varchar(20) NOT NULL, employee_id int NOT NULL)

    Creates a table titled "personal_info" in the current database


  • The CREATE TABLE command specifies a new base relation by giving it a name, and specifying each of its attributes and their data types (INTEGER, FLOAT, DECIMAL(i,j), CHAR(n), VARCHAR(n), etc.)

  • A constraint NOT NULL may be specified on an attribute

    CREATE TABLE dept_info (DNAME VARCHAR(10) NOT NULL, DNUMBER INTEGER NOT NULL, EMPLOYEE_ID int );


  • The SQL language has many versions giving it a name, and specifying each of its attributes and their data types (INTEGER, FLOAT, DECIMAL(i,j), CHAR(n), VARCHAR(n), etc.)

  • In SQL2, we can use the CREATE TABLE command for specifying the primary key attributes, and referential integrity constraints (foreign keys)

  • Key attributes can be specified via the PRIMARY KEY, FOREIGN KEY, REFERENCES and UNIQUE phrases

    CREATE TABLE dept_info

    (DNAME VARCHAR(10)NOT NULL,

    DNUMBER INTEGER NOT NULL,

    EMPLOYEE_ID int ,

    PRIMARY KEY (DNUMBER),

    UNIQUE (DNAME),

    FOREIGN KEY (EMPLOYEE_ID) REFERENCES personal_info);


  • We can specify CASCADE, SET NULL or SET DEFAULT on referential integrity constraints (foreign keys)

    CREATE TABLE dept_info (DNAME VARCHAR(10) NOT NULL, DNUMBER INTEGER NOT NULL, EMPLOYEE_ID int, PRIMARY KEY (DNUMBER), UNIQUE (DNAME), FOREIGN KEY (EMPLOYEE_ID) REFERENCES personal_info ON DELETE SET DEFAULT ON UPDATE CASCADE );


  • USE referential integrity constraints (foreign keys)

    • The USE command allows you to specify the database you wish to work with within your DBMS

    • For example, if we are currently working in the sales database and if we want to issue some commands that will affect the employees database, we would preface them with the following SQL command: 

      USE Employees 


  • For example: referential integrity constraints (foreign keys)

    USE Employees

    CREATE TABLE personal_info(first_name varchar(20) NOT NULL, last_name varchar(20) NOT NULL, employee_id int NOT NULL)

    CREATE TABLE dept_info(dept_name varchar(20) NOT NULL, dept_id int NOT NULL)

    Create two tables named "personal_info" and "dept_info“ under the Employee database while you are working on the Sales database


  • ALTER

    • Once you have created a table within a database, you may wish to modify its definition

    • The ALTER command allows you to make changes to the structure of a table without deleting and recreating it


    • Take a look at the following command:  are working in before issuing SQL commands that manipulate data

      ALTER TABLE personal_infoADD salary money null 

    • This example adds a new attribute to the personal_info table -- an employee's salary

    • The "money" argument specifies that an employee's salary will be stored using a dollars and cents format

    • Finally, the "null" keyword tells the database that it's OK for this field to contain no value for any given employee


    • Used to add an attribute to one of the base relations are working in before issuing SQL commands that manipulate data

    • The new attribute will have NULLs in all the tuples of the relation right after the command is executed; hence, the NOT NULL constraint is not allowed for such an attribute

    • Example:ALTER TABLE personal_info ADD JOB VARCHAR(12);

    • The database users must still enter a value for the new attribute JOB for each EMPLOYEE tuple

    • This can be done using the UPDATE command


    • DROP  are working in before issuing SQL commands that manipulate data

      • The final command of the Data Definition Language, DROP, allows us to remove entire database objects from our DBMS

      • For example, if we want to permanently remove the personal_info table that we created, we'd use the following command: 

        DROP TABLE personal_info 

      • Similarly, the command below would be used to remove the entire employees database: 

        DROP DATABASE employees


    • Use this command with care! are working in before issuing SQL commands that manipulate data

    • Remember that the DROP command removes entire data structures from your database

    • If you want to remove individual records, use the DELETE command of the Data Manipulation Language


    5 2 data manipulation language
    5.2. Data Manipulation Language are working in before issuing SQL commands that manipulate data

    • The Data Manipulation Language (DML) is used to retrieve, insert and modify database information

    • These commands will be used by all database users during the routine operation of the database

    • Let's take a brief look at the basic DML commands:

      • INSERT

        • The INSERT command in SQL is used to add records to an existing table

        • Returning to the personal_info example from the previous section, let's imagine that our HR department needs to add a new employee to their database


    • They could use a command similar to the one shown below:  are working in before issuing SQL commands that manipulate data

      INSERT INTO personal_info values('Abebe', 'Kebede',1,$2000.00)

    • Note that there are four values specified for the record

    • These correspond to the table attributes in the order they were defined: first_name, last_name, employee_id, and salary


    • SELECT  are working in before issuing SQL commands that manipulate data

      • The SELECT command is the most commonly used command in SQL

      • It allows database users to retrieve the specific information they desire from an operational database

      • Let's take a look at a few examples, again using the personal_info table from our employees database

      • The command shown below retrieves all of the information contained within the personal_info table

        SELECT * FROM personal_info 


    • Note that the asterisk (*) is used as a wildcard in SQL are working in before issuing SQL commands that manipulate data

    • This literally means "Select everything from the personal_info table."

    • Alternatively, users may want to limit the attributes that are retrieved from the database

    • For example, the Human Resources department may require a list of the last names of all employees in the company

    • The following SQL command would retrieve only that information: 


    SELECT last_name are working in before issuing SQL commands that manipulate data FROM personal_info 

    • Finally, the WHERE clause can be used to limit the records that are retrieved to those that meet specified criteria

    • The CEO might be interested in reviewing the personnel records of all highly paid employees

    • The following command retrieves all of the data contained within personal_info for records that have a salary value greater than $50,000:

      SELECT *FROM personal_infoWHERE salary > $50,000 


    • UPDATE  are working in before issuing SQL commands that manipulate data

      • The UPDATE command can be used to modify information contained within a table, either in bulk or individually

      • Each year, our company gives all employees a 3% cost-of-living increase in their salary

      • The following SQL command could be used to quickly apply this to all of the employees stored in the database: 

        UPDATE personal_info SET salary = salary * 1.03 


    • On the other hand, our new employee Almaz Tiku has demonstrated performance above and beyond the call of duty

    • Management wishes to recognize her stellar accomplishments with a $5,000 raise

    • The WHERE clause could be used to single out Bart for this raise: 

      UPDATE personal_info SET salary = salary + $5000 WHERE employee_id = 2


    • DELETE  demonstrated performance above and beyond the call of duty

      • Finally, let's take a look at the DELETE command

      • You'll find that the syntax of this command is similar to that of the other DML commands

      • Unfortunately, our latest corporate earnings report didn't quite meet expectations and poor Almaz has been laid off

      • The DELETE command with a WHERE clause can be used to remove his record from the personal_info table: 

        DELETE FROM personal_infoWHERE employee_id = 2


    5 3 basic queries in sql
    5.3. Basic Queries in SQL demonstrated performance above and beyond the call of duty

    • SQL has one basic statement for retrieving information from a database; the SELECT statement

    • SQL relations can be constrained to be sets by specifying PRIMARY KEY or UNIQUE attributes, or by using the DISTINCT option in a query

    • Basic form of the SQL SELECT statement is called a mapping or a SELECT-FROM-WHERE block

      SELECT <attribute list>

      FROM <table list>

      WHERE <condition>




    Populated database for the relational schema
    Populated database corresponding to a COMPANY databasefor the relational schema


    • Basic SQL queries correspond to using the SELECT, PROJECT, and JOIN operations of the relational algebra

    • All subsequent examples use the COMPANY database

    • Example of a simple query on one relation

    • Query 0: Retrieve the birthdate and address of the employee whose name is 'John B. Smith'.

      Q0: SELECT BDATE, ADDRESS FROM EMPLOYEE WHERE FNAME='John' AND MINIT='B’ AND LNAME='Smith'


    • Query 1: and JOIN operations of the relational algebra Retrieve the name and address of all employees who work for the 'Research' department

      Q1: SELECT FNAME, LNAME, ADDRESS FROM EMPLOYEE, DEPARTMENT WHERE DNAME='Research' AND DNUMBER=DNO


    • Query 2: and JOIN operations of the relational algebra For every project located in 'Stafford', list the project number, the controlling department number, and the department manager's last name, address, and birthdate

      Q2: SELECT PNUMBER, DNUM, LNAME, BDATE, ADDRESS FROM PROJECT, DEPARTMENT, EMPLOYEE WHERE DNUM=DNUMBER AND MGRSSN=SSN AND PLOCATION='Stafford'In Q2, there are two join conditions


    • The join condition DNUM=DNUMBER relates a project to its controlling department

    • The join condition MGRSSN=SSN relates the controlling department to the employee who manages that department

    • A missing WHERE-clause indicates no condition; hence, all tuples of the relations in the FROM-clause are selected

    • This is equivalent to the condition WHERE TRUE

    • Query 3: Retrieve the SSN values for all employees

      Q3: SELECT SSN FROM EMPLOYEE


    • If more than one relation is specified in the FROM-clause controlling departmentand there is no join condition, then the CARTESIAN PRODUCT of tuples is selected

    • Example:Q4: SELECT SSN,DNAME FROM EMPLOYEE,DEPARTMENT

    • It is extremely important not to overlook specifying any selection and join conditions in the WHERE-clause; otherwise, incorrect and very large relations may result



    • SQL does not treat a relation as a set; a * is used, which stands for duplicate tuples can appear

    • To eliminate duplicate tuples in a query result, the keyword DISTINCT is used

    • For example, the result of Q7 may have duplicate SALARY values whereas Q8 does not have any duplicate values

      Q7: SELECT SALARY FROM EMPLOYEE

      Q8: SELECT DISTINCT SALARY FROM EMPLOYEE


    • SQL has directly incorporated some set operations a * is used, which stands for

    • There is a union operation (UNION), and in some versions of SQL there are set difference (MINUS) and intersection (INTERSECT) operations

    • The resulting relations of these set operations are sets of tuples; duplicate tuples are eliminated from the result

    • The set operations apply only to union compatible relations ; the two relations must have the same attributes and the attributes must appear in the same order


    • Query 9: a * is used, which stands for Make a list of all project numbers for projects that involve an employee whose last name is 'Smith' as a worker or as a manager of the department that controls the project

      Q9: (SELECT PNAME FROM PROJECT, DEPARTMENT, EMPLOYEE WHERE DNUM=DNUMBER AND MGRSSN=SSN AND LNAME='Smith') UNION (SELECT PNAME FROM PROJECT, WORKS_ON, EMPLOYEE WHERE PNUMBER=PNO AND ESSN=SSN AND LNAME='Smith')


    • A complete SELECT query, called a a * is used, which stands for nested query , can be specified within the WHERE-clause of another query, called the outer query

    • Many of the previous queries can be specified in an alternative form using nesting

    • Query 10: Retrieve the name and address of all employees who work for the 'Research' department

      Q10: SELECT FNAME, LNAME, ADDRESS FROM EMPLOYEE WHERE DNO IN (SELECT DNUMBER FROM DEPARTMENT WHERE DNAME='Research')


    • The nested query selects the number of the 'Research' department

    • The outer query select an EMPLOYEE tuple if its DNO value is in the result of either nested query

    • The comparison operator IN compares a value v with a set (or multi-set) of values V, and evaluates to TRUE if v is one of the elements in V

    • In general, we can have several levels of nested queries

    • A reference to an unqualified attribute refers to the relation declared in the innermost nested query

    • In this example, the nested query is not correlated with the outer query


    • If a condition in the WHERE-clause of a departmentnested query references an attribute of a relation declared in the outer query , the two queries are said to be correlated

    • The result of a correlated nested query is different for each tuple (or combination of tuples) of the relation(s) the outer query

    • Query 11: Retrieve the name of each employee who has a dependent with the same first name as the employee.Q11: SELECT E.FNAME,E.LNAME FROM EMPLOYEE AS E WHERE E.SSN IN (SELECT ESSN FROM DEPENDENT WHERE ESSN=E.SSN AND E.FNAME=DEPENDENT_NAME)


    • In Q11, the nested query has a different result departmentfor each tuple in the outer query

    • A query written with nested SELECT... FROM... WHERE... blocks and using the = or IN comparison operators can alwaysbe expressed as a single block query

    • For example, Q11 may be written as in Q12

      Q12: SELECT E.FNAME, E.LNAME FROM EMPLOYEE E, DEPENDENT D WHERE E.SSN=D.ESSN AND E.FNAME=D.DEPENDENT_NAME


    • EXISTS function is used to check whether the result of a correlated nested query is empty (contains no tuples) or not

    • Query 13: Retrieve the name of each employee who has a dependent with the same first name as the employee.Q13: SELECT FNAME, LNAME FROM EMPLOYEE WHERE EXISTS (SELECT * FROM DEPENDENT WHERE SSN=ESSN AND FNAME=DEPENDENT_NAME)


    • Query 14: correlated nested query is empty (contains no tuples) or not Retrieve the names of employees who have no dependents.

      Q14: SELECT FNAME, LNAME FROM EMPLOYEE WHERE NOT EXISTS (SELECT * FROM DEPENDENT WHERE SSN=ESSN)


    • SQL allows queries that check if a value is NULL (missing or undefined or not applicable)

    • SQL uses IS or IS NOT to compare NULLs because it considers each NULL value distinct from other NULL values, so equality comparison is not appropriate

    • Query 15: Retrieve the names of all employees who do not have supervisors

      Q15: SELECT FNAME, LNAME FROM EMPLOYEE WHERE SUPERSSN IS NULL


    • Note: undefined or not applicable) If a join condition is specified, tuples with NULL values for the join attributes are not included in the result

    • In SQL2 we can specify a "joined relation" in the FROM-clause

    • Looks like any other relation but is the result of a join

    • Allows the user to specify different types of joins (regular "theta" JOIN, NATURAL JOIN, LEFT OUTER JOIN, RIGHT OUTER JOIN, CROSS JOIN, etc)


    • Examples: undefined or not applicable)Q16: SELECT E.FNAME, E.LNAME, S.FNAME, S.LNAME FROM EMPLOYEE E S WHERE E.SUPERSSN=S.SSNcan be written as: SELECT E.FNAME, E.LNAME, S.FNAME, S.LNAME FROM (EMPLOYEE E LEFT OUTER JOIN EMPLOYEES ON E.SUPERSSN=S.SSN)Q17: SELECT FNAME, LNAME, ADDRESS FROM EMPLOYEE, DEPARTMENT WHERE DNAME='Research' AND DNUMBER=DNO


    • could be written as: undefined or not applicable)

      • SELECT FNAME, LNAME, ADDRESS FROM (EMPLOYEE JOIN DEPARTMENT ON DNUMBER=DNO) WHERE DNAME='Research’or as: SELECT FNAME, LNAME, ADDRESS FROM (EMPLOYEE NATURAL JOIN DEPARTMENT AS DEPT(DNAME, DNO, MSSN, MSDATE) WHERE DNAME='Research’


    • Aggregate functions undefined or not applicable)include COUNT, SUM, MAX, MIN, and AVG

    • They are used to summarize data in tables

    • Query 18: Find the maximum salary, the minimum salary, and the average salary among all employees

      Q18: SELECT MAX(SALARY), MIN(SALARY), AVG(SALARY) FROM EMPLOYEE

    • Some SQL implementations may not allow more than one function in the SELECT-clause


    • Query 19: undefined or not applicable) Find the maximum salary, the minimum salary, and the average salary among employees who work for the 'Research' department

      Q19: SELECT MAX(SALARY), MIN(SALARY), AVG(SALARY) FROM EMPLOYEE, DEPARTMENT WHERE DNO=DNUMBER AND DNAME='Research'


    • Queries 20: undefined or not applicable) Retrieve the total number of employees in the company

      Q20: SELECT COUNT (*) FROM EMPLOYEE

    • Queries 21: Retrieve the total number of employees in the 'Research' department

      Q21: SELECT COUNT (*) FROM EMPLOYEE, DEPARTMENT WHERE DNO=DNUMBER AND DNAME='Research'


    • In many cases, we want to apply the aggregate functions undefined or not applicable)to subgroups of tuples in a relation

    • Each subgroup of tuples consists of the set of tuples that have the same value for the grouping attribute(s)

    • The function is applied to each subgroup independently

    • SQL has a GROUP BY-clause for specifying the grouping attributes, which must also appear in the SELECT-clause

    • Query 22: For each department, retrieve the department number, the number of employees in the department, and their average salary


    Q22: SELECT DNO, COUNT (*), AVG (SALARY) undefined or not applicable) FROM EMPLOYEE GROUP BY DNO

    • In Q22, the EMPLOYEE tuples are divided into groups--each group having the same value for the grouping attribute DNO

    • The COUNT and AVG functions are applied to each such group of tuples separately

    • The SELECT-clause includes only the grouping attribute and the functions to be applied on each group of tuples

    • A join condition can be used in conjunction with grouping


    • Query 23: undefined or not applicable) For each project, retrieve the project number, project name, and the number of employees who work on that project.Q23: SELECT PNUMBER, PNAME, COUNT (*) FROM PROJECT, WORKS_ON WHERE PNUMBER=PNO GROUP BY PNUMBER, PNAME

    • In this case, the grouping and functions are applied after the joining of the two relations


    • Sometimes we want to retrieve the values of these functions for only those groups that satisfy certain conditions

    • The HAVING-clause is used for specifying a selection condition on groups (rather than on individual tuples)

    • Query 24: For each project on which more than two employees work , retrieve the project number, project name, and the number of employees who work on that project.Q24: SELECT PNUMBER, PNAME, COUNT (*) FROM PROJECT, WORKS_ON WHERE PNUMBER=PNO GROUP BY PNUMBER, PNAME HAVING COUNT (*) > 2


    • The for only those LIKE comparison operator is used to compare partial strings

    • Two reserved characters are used: '%' (or '*' in some implementations) replaces an arbitrary number of characters, and '_' replaces a single arbitrary character

      Query 25: Retrieve all employees whose address is in Houston, Texas. Here, the value of the ADDRESS attribute must contain the substring 'Houston,TX'.Q25: SELECT FNAME, LNAME FROM EMPLOYEE WHERE ADDRESS LIKE '%Houston,TX%'


    Query 26: for only those Retrieve all employees who were born during the 1950s. Here, '5' must be the 8th character of the string (according to our format for date), so the BDATE value is '_______5_', with each underscore as a place holder for a single arbitrary character

    Q26: SELECT FNAME, LNAME FROM EMPLOYEE WHERE BDATE LIKE '_______5_’

    • The LIKE operator allows us to get around the fact that each value is considered atomic and indivisible; hence, in SQL, character string attribute values are not atomic


    • The standard arithmetic operators '+', '-'. '*', and '/' (for addition, subtraction, multiplication, and division, respectively) can be applied to numeric values in an SQL query result

      Query 27: Show the effect of giving all employees who work on the 'ProductX' project a 10% raise.Q27: SELECT FNAME, LNAME, 1.1*SALARY FROM EMPLOYEE, WORKS_ON, PROJECT WHERE SSN=ESSN AND PNO=PNUMBER AND PNAME='ProductX’


    • The (for addition, subtraction, multiplication, and division, respectively) can be applied to numeric values in an SQL query resultORDER BY clause is used to sort the tuples in a query result based on the values of some attribute(s)

      Query 28: Retrieve a list of employees and the projects each works in, ordered by the employee's department, and within each department ordered alphabetically by employee last name.Q28: SELECT DNAME, LNAME, FNAME, PNAME FROM DEPARTMENT, EMPLOYEE, WORKS_ON, PROJECT WHERE DNUMBER=DNO AND SSN=ESSN AND PNO=PNUMBER ORDER BY DNAME, LNAME


    • The default order is in ascending order of values (for addition, subtraction, multiplication, and division, respectively) can be applied to numeric values in an SQL query result

    • We can specify the keyword DESC if we want a descending order; the keyword ASC can be used to explicitly specify ascending order, even though it is the default

    • A query in SQL can consist of up to six clauses, but only the first two, SELECT and FROM, are mandatory. The clauses are specified in the following order:

      SELECT <attribute list>FROM <table list>[WHERE <condition>][GROUP BY <grouping attribute(s)>][HAVING <group condition>][ORDER BY <attribute list>]


    5 4 views
    5.4. Views (for addition, subtraction, multiplication, and division, respectively) can be applied to numeric values in an SQL query result

    • A view is a "virtual" table that is derived from other tables

    • Allows for limited update operations (since the table may not physically be stored)

    • Allows full query operations

    • A convenience for expressing certain operations

    • Views can only select data

    • Views have several advantages

    • They enable you to:

      • Join data so that users can work with it easily

      • Aggregate data so that users can work with it easily

      • Customize data to users' needs


    • Hide underlying column names from users (for addition, subtraction, multiplication, and division, respectively) can be applied to numeric values in an SQL query result

    • Limit the columns and rows with which a user works

    • Easily secure data

  • View specification consists of:

    • SQL command CREATE VIEW

      • a table (view) name

      • a possible list of attribute names (for example, when arithmetic operations are specified or when we want the names to be different from the attributes in the base relations)


  • Example:

    • Specify a different WORKS_ON table

      CREATE TABLE WORKS_ON_NEW AS

      SELECT FNAME, LNAME, PNAME, HOURS

      FROM EMPLOYEE, PROJECT, WORKS_ON

      WHERE SSN=ESSN AND PNO=PNUMBER

      GROUP BY PNAME;


    • We can specify SQL queries on a newly create table (view): (for addition, subtraction, multiplication, and division, respectively) can be applied to numeric values in an SQL query result

      SELECT FNAME, LNAME

      FROM WORKS_ON_NEW

      WHERE PNAME=‘Seena’;

    • When no longer needed, a view can be dropped:

      DROP WORKS_ON_NEW;

    • Update on a single view without aggregate operations: update may map to an update on the underlying base table


    • Views involving joins: an update (for addition, subtraction, multiplication, and division, respectively) can be applied to numeric values in an SQL query resultmay map to an update on the underlying base relations

      • not always possible

    • Views defined using groups and aggregate functions are not updateable

    • Views defined on multiple tables using joins are generally not updateable

    • WITH CHECK OPTION: must be added to the definition of a view if the view is to be updated

      • to allow check for updatability and to plan for an execution strategy


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