Transcript Chapter 8

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Chapter 8

SQL: SchemaDefinition, Constraints, and Queries and Views

History of SQL

 SQL: Structured Query Language  In 1974, D.

Chamberlin (IBM Laboratory) defined language called English Query Language’ (SEQUEL).

San Jose ‘Structured  A revised version, SEQUEL/2, was defined in 1976 but name was subsequently changed to SQL for legal reasons.

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History of SQL

 Still pronounced pronunciation is ‘see-quel’, ‘S-Q-L’.

though official  IBM subsequently produced a prototype DBMS called

System R

, based on SEQUEL/2.

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History of SQL

      In late 70s, ORACLE appeared and was probably first commercial RDBMS based on SQL.

In 1987, ANSI and ISO published an initial standard for SQL.

In 1989, ISO published an addendum that defined an ‘Integrity Enhancement Feature’.

In 1992, first major revision to ISO standard occurred, referred to as SQL2 or SQL/92.

In 1999, SQL:1999 was released with support for object-oriented data management.

In late 2003, SQL:2003 was released.

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DBMS Languages

 Data Definition Language (DDL)  Data Manipulation Language (DML)  High-Level or Non-procedural Languages: These include the relational language SQL  May be used in a standalone  or may be embedded in a programming language  Low Level or Procedural Languages:  These must be embedded in a programming language

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DBMS Languages

Data Definition Language (DDL):

  Used by the DBA and database designers to specify the conceptual schema of a database.

In many DBMSs, the DDL is also used to define internal and external schemas (views).

 In some DBMSs, separate

storage definition language (SDL)

and

view definition language (VDL)

are used to define internal and external schemas.

 SDL is typically realized via DBMS commands provided to the DBA and database designers

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DBMS Languages

Data Manipulation Language (DML):

 Used to specify database retrievals and updates  DML commands can be

embedded

in a general purpose programming language (host language), such as C++, or Java.

 A library of functions can also be provided to access the DBMS from a programming language  Alternatively, stand-alone DML commands can be applied directly (called a

query language

).

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Types of DML

High Level or Non-procedural Language:

  For example, the SQL relational language Are “set”-oriented and specify what data to retrieve rather than how to retrieve it.  Also called

declarative

languages.

Low Level or Procedural Language:

 Retrieve data one record-at-a-time;  Constructs such as looping are needed to retrieve multiple records, along with positioning pointers.

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Objectives of SQL

   Ideally, database language should allow user to:   create the database and relation structures; perform insertion, modification, deletion of data from relations;  perform simple and complex queries.

It must be portable.

SQL is relatively easy to learn:   it is non-procedural - you specify require, rather than

how

to get it

what

information you Can be used by range of users including DBAs, management, application developers, and other types of end users.

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Objectives of SQL

 Consists of standard English words: 1) CREATE TABLE Staff( staffNo VARCHAR(5), lName VARCHAR(15), salary INTEGER); 2) INSERT INTO Staff VALUES ( ‘SG16’, ‘Brown’, 8300); 3) SELECT staffNo, lName, salary FROM Staff WHERE salary > 10000; Slide 8 11

Writing SQL Commands

 SQL statement consists of

user-defined words

.

reserved words

and  Most components of an SQL statement are

insensitive

, except for literal character data.

case

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Writing SQL Commands

Upper-case letters represent reserved words.

- Lower-case letters represent user-defined words.

- | indicates a

choice

among alternatives.

- Curly braces indicate a

required element

.

- Square brackets indicate an

optional element

.

… indicates

optional repetition

(0 or more).

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Literals

 Literals are constants used in SQL statements.

 All non-numeric literals must be enclosed in single quotes (e.g.

‘London’).

 All numeric literals must not be enclosed in quotes (e.g. 650.00).

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Attribute Data Types in SQL

 Basic

data types

Numeric

data types • Integer numbers: INTEGER and SMALLINT • Floating-point (real) numbers: FLOAT or REAL , and DOUBLE PRECISION 

Character-string

data types • Fixed length: CHAR(

n

) • Varying length : VARCHAR(

n

)

Attribute Data Types in SQL (cont ’d.)

Bit-string

data types • Fixed length: BIT(

n

) • Varying length: BIT VARYING(

n

) 

Boolean

data type • Values of TRUE or FALSE or NULL 

DATE

data type • • Ten positions Components are YEAR , MONTH , and DAY in the form YYYY-MM-DD

Attribute Data Types in SQL (cont ’d.)

 Additional data types   

TIME:

 Made up of hour:minute:second in the format hh:mm:ss

TIME(i):

 Made up of hour:minute:second plus i additional digits specifying fractions of a second  format is hh:mm:ss:ii...i

Timestamp

data type ( TIMESTAMP ) • Includes the DATE and TIME fields • • Plus a minimum of six positions for decimal fractions of seconds Optional WITH TIME ZONE qualifier

Attribute Data Types in SQL (cont ’d.)

 Additional data types 

INTERVAL

data type • • Specifies a relative value that can be used to increment or decrement an absolute value of a date, time, or timestamp Can be DAY/TIME intervals or YEAR/MONTH intervals

Data Definition, Constraints, and Schema Changes

 Used to CREATE, DROP, and ALTER the descriptions of the tables (relations) of a database

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CREATE TABLE

  CREATE TABLE command can be used for specifying the primary key attributes, secondary key, and referential integrity constraints (foreign keys).

VARCHAR(n)) and UNIQUE phrases

CREATE TABLE DEPT ( DNAME DNUMBER VARCHAR(10) INTEGER NOT NULL, NOT NULL, MGRSSN MGRSTARTDATE CHAR(9), CHAR(9), PRIMARY KEY (DNUMBER), UNIQUE (DNAME), FOREIGN KEY (MGRSSN) REFERENCES EMP ); Slide 8 20

Specifying Constraints in SQL

 Basic constraints:  Key and referential integrity constraints  Restrictions on attribute domains and NULLs  Constraints on individual tuples within a relation

Specifying Attribute Constraints and Attribute Defaults

 NOT NULL  NULL is not permitted for a particular attribute   Default value 

DEFAULT

CHECK

 clause Dnumber INT NOT NULL CHECK (Dnumber > 0 AND Dnumber < 21);

Specifying Key and Referential Integrity Constraints

PRIMARY KEY

clause    Specifies one or more attributes that make up the primary key of a relation Dnumber INT PRIMARY KEY;

UNIQUE

clause   Specifies alternate (secondary) keys Dname VARCHAR(15) UNIQUE;

Specifying Key and Referential Integrity Constraints (cont ’d.)

FOREIGN KEY

clause  Default operation: reject update on violation  Attach

referential triggered action

clause • • Options include RESTRICT , SET NULL , CASCADE , and SET DEFAULT CASCADE option suitable for “relationship” relations

REFERENTIAL INTEGRITY OPTIONS

CREATE TABLE DEPT ( DNAME VARCHAR(10) DNUMBER INTEGER NOT NULL, NOT NULL, MGRSSN CHAR(9) DEFAULT ‘NO’, MGRSTARTDATE CHAR(9), PRIMARY KEY (DNUMBER), UNIQUE (DNAME), FOREIGN KEY (MGRSSN) REFERENCES EMP ON DELETE SET DEFAULT ON UPDATE CASCADE); Slide 8 26

REFERENTIAL INTEGRITY OPTIONS (continued)

CREATE TABLE EMP( ENAME VARCHAR(30) ESSN BDATE CHAR(9), DATE, NOT NULL, DNO INTEGER DEFAULT 1, SUPERSSN CASCADE, CHAR(9), PRIMARY KEY (ESSN), FOREIGN KEY (DNO) REFERENCES DEPT ON DELETE SET DEFAULT ON UPDATE FOREIGN KEY (SUPERSSN) REFERENCES EMP ON DELETE SET NULL ON UPDATE CASCADE); Slide 8 27

Giving Names to Constraints

 Keyword

CONSTRAINT

 Name a constraint  Useful for later altering

Specifying Constraints on Tuples Using CHECK

 CHECK clauses at the end of a CREATE TABLE statement   Apply to each tuple individually CHECK (Dept_create_date <= Mgr_start_date);

The DROP Command

 DROP command  Used to remove named schema elements, such as tables, domains, or constraint  Drop behavior options:  CASCADE and RESTRICT  Examples:

DROP TABLE DEPENDENT; DROP SCHEMA COMPANY CASCADE;

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The ALTER Command

Alter table actions

include:  Adding or dropping a column (attribute)   The new attribute will have NULLs in all the tuples of the relation right after the command is executed the NOT NULL constraint is not allowed for such an attribute  Changing a column definition  Adding or dropping table constraints  Examples:  ALTER TABLE COMPANY.EMPLOYEE ADD COLUMN Job VARCHAR(12); 

Or:

ALTER TABLE EMPLOYEE ADD JOB VARCHAR(12);

The ALTER Command (cont ’d.)

  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.

To drop a column  Choose either CASCADE or RESTRICT  Change constraints specified on a table  Add or drop a named constraint

ALTER TABLE Examples

ALTER TABLE

EMPLOYEE

ADD

JOB VARCHAR(12); 

ALTER TABLE

EMPLOYEE

DROP

ADDRESS

CASCADE;

ALTER TABLE

DEPARTMENT

ALTER

MGRSSN

DROP DEFAULT;

ALTER TABLE

DEPARTMENT

ALTER

MGRSSN

SET DEFAULT

"333445555";

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Retrieval Queries in SQL

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

SELECT

statement  This is

not the same as

the SELECT operation of the relational algebra  Important distinction between SQL and the formal relational model:  SQL allows a table (relation) to have two or more tuples that are identical in all their attribute values  SQL relations can be constrained to be sets by specifying PRIMARY KEY or UNIQUE attributes, or by using the DISTINCT option in a query

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Retrieval Queries in SQL (contd.)

 Basic form of the SQL SELECT statement is called a

mapping

or a SELECT-FROM-WHERE

block

SELECT FROM WHERE

   is a list of attribute names whose values are to be retrieved by the query
is a list of the relation names required to process the query is a conditional (Boolean) expression that identifies the tuples to be retrieved by the query  Logical comparison operators: =, <, <=, >, >=, and <>

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Relational Database Schema--Figure 5.5

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Populated Database--Fig.5.6

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Simple SQL Queries

 Basic SQL queries correspond to using the following operations of the relational algebra:  SELECT  PROJECT  JOIN  All subsequent examples use the COMPANY database

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Simple SQL Queries (contd.)

  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 FROM WHERE BDATE, ADDRESS EMPLOYEE FNAME='John' AND MINIT='B ’ AND LNAME='Smith ’   Similar to a SELECT-PROJECT pair of relational algebra operations:  The SELECT-clause specifies the projection attributes and the WHERE-clause specifies the selection condition However, the result of the query may contain duplicate tuples

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Simple SQL Queries (contd.)

 Query 1: Retrieve the name and address of all employees who work for the 'Research' department.

Q1:SELECT FROM WHERE FNAME, LNAME, ADDRESS EMPLOYEE, DEPARTMENT DNAME='Research' AND DNUMBER=DNO    Similar to a SELECT-PROJECT-JOIN sequence of relational algebra operations (DNAME='Research') is a selection condition (corresponds to a SELECT operation in relational algebra) (DNUMBER=DNO) is a join condition (corresponds to a JOIN operation in relational algebra)

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Simple SQL Queries (contd.)

 Query 2: 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 FROM WHERE PNUMBER, DNUM, LNAME, BDATE, ADDRESS PROJECT, DEPARTMENT, EMPLOYEE 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

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Ambiguous Attribute Names

 In SQL, we can use the same name for two (or more) attributes as long as the attributes are in

different relations

 A query that refers to two or more attributes with the same name must

qualify

the attribute name with the relation name by

prefixing

the relation name to the attribute name  Example:

EMPLOYEE.

LNAME,

DEPARTMENT.

DNAME

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ALIASES

   Declare alternative relation names Some queries need to refer to the same relation twice  In this case,

aliases

are given to the relation name Query 8: For each employee, retrieve the employee's name, and the name of his or her immediate supervisor.

Q8: SELECT FROM WHERE E.FNAME, E.LNAME, S.FNAME, S.LNAME

EMPLOYEE E S E.SUPERSSN=S.SSN

  In Q8, the alternate relation names E and S are called

aliases

or

tuple variables

for the EMPLOYEE relation We can think of E and S as two different

copies

of EMPLOYEE; E represents employees in role of

supervisees

and S represents employees in role of

supervisors

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ALIASES (contd.)

  Aliasing can also be used in any SQL query for convenience Can also use the AS keyword to specify aliases Q8: SELECT FROM WHERE E.FNAME, E.LNAME, S.FNAME, S.LNAME

EMPLOYEE AS E, EMPLOYEE AS S E.SUPERSSN=S.SSN

 Renaming of Attributes  Rename any attribute that appears in the result of a query

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UNSPECIFIED WHERE-clause

  A

missing WHERE-clause

indicates no condition;  All tuples of the relations in the FROM-clause are selected  This is equivalent to the condition WHERE TRUE Query 9: Retrieve the SSN values for all employees.

 Q9: SELECT FROM SSN EMPLOYEE  If more than one relation is specified in the FROM-clause

and

there is no join condition, then the

CARTESIAN PRODUCT

of tuples is selected

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UNSPECIFIED WHERE-clause (contd.)

 Example: Q10: SELECT FROM SSN, DNAME 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

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USE OF ASTERISK *

 To retrieve all the attribute values of the selected tuples, a * is used, which stands for

all the attributes

Examples: Q1C: Q1D: SELECT FROM WHERE SELECT FROM WHERE * EMPLOYEE DNO=5 * EMPLOYEE, DEPARTMENT DNAME='Research' AND DNO=DNUMBER

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USE OF DISTINCT

   SQL does not treat a relation as a set; duplicate tuples can appear To eliminate duplicate tuples in a query result, the keyword

DISTINCT

is used For example, the result of Q11 may have duplicate SALARY values whereas Q11A does not have any duplicate values Q11: SELECT FROM Q11A: SELECT FROM SALARY EMPLOYEE

DISTINCT

SALARY EMPLOYEE

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SET OPERATIONS

 SQL has directly incorporated some set operations  There is a union operation (UNION), set difference (EXCEPT) 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

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SET OPERATIONS (contd.)

 Query 4: 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.

 Q4: (SELECT FROM WHERE UNION (SELECT FROM WHERE DISTINCT PNUMBER PROJECT, DEPARTMENT, EMPLOYEE DNUM=DNUMBER AND MGRSSN=SSN AND LNAME='Smith') DISTINCT PNUMBER PROJECT, WORKS_ON, EMPLOYEE PNUMBER=PNO AND ESSN=SSN AND LNAME='Smith')

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NESTING OF QUERIES

 A complete SELECT query, called a called the

outer query nested query

, can be specified within the WHERE-clause of another query,  Many of the previous queries can be specified in an alternative form using nesting  Query 1: Retrieve the name and address of all employees who work for the 'Research' department.

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

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NESTING OF QUERIES (contd.)

   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  evaluates to TRUE if v is one of the elements in V  In general, we can have several levels of nested queries

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Nested Queries

Nested Queries (cont ’d.)

 Use tuples of values in comparisons  Place them within parentheses  Other comparison operators

THE EXISTS FUNCTION AND CORRELATED NESTED QUERIES

 Query 6: Retrieve the names of employees who have no dependents.

Q6: SELECT FROM WHERE FNAME, LNAME EMPLOYEE E NOT EXISTS (SELECT FROM * DEPENDENT WHERE E.SSN=ESSN)  If a condition in the WHERE-clause of a

nested query

references an attribute of a relation declared in the

outer query

, the two queries are said to be

correlated

 In Q6, the correlated nested query retrieves all DEPENDENT tuples related to an EMPLOYEE tuple. If

none exist

, the EMPLOYEE tuple is selected

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EXPLICIT SETS

 It is also possible to use an

explicit (enumerated) set of values

in the WHERE clause rather than a nested query  Query 13: Retrieve the social security numbers of all employees who work on project number 1, 2, or 3.

Q13: SELECT FROM WHERE DISTINCT ESSN WORKS_ON PNO IN (1, 2, 3)

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NULLS IN SQL QUERIES

 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.

 Query 14: Retrieve the names of all employees who do not have supervisors.

Q14: SELECT FROM WHERE FNAME, LNAME EMPLOYEE SUPERSSN IS NULL

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Joined Relations Feature

 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, etc)

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Joined Relations Feature

 Examples: Q1:SELECT FROM WHERE FNAME, LNAME, ADDRESS EMPLOYEE, DEPARTMENT DNAME='Research' AND DNUMBER=DNO  could be written as: Q1:SELECT FNAME, LNAME, ADDRESS FROM (EMPLOYEE JOIN DEPARTMENT WHERE ON DNUMBER=DNO) DNAME='Research ’

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Joined Relations Feature (contd.)

 Another Example: Q2 could be written as follows; this illustrates multiple joins in the joined tables Q2: SELECT FROM WHERE PNUMBER, DNUM, LNAME, BDATE, ADDRESS ((PROJECT JOIN DEPARTMENT ON DNUM=DNUMBER) JOIN EMPLOYEE ON MGRSSN=SSN) PLOCATION='Stafford ’

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AGGREGATE FUNCTIONS

 Include

COUNT, SUM, MAX, MIN, and AVG

   Used to summarize information from multiple tuples into a single tuple summary Functions can be used in the SELECT clause or in a HAVING clause NULL values are discarded when aggregate functions are applied to a particular column  Query 15: Find the maximum salary, the minimum salary, and the average salary among all employees.

Q15: SELECT MAX(SALARY), MIN(SALARY), AVG(SALARY) FROMEMPLOYEE

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AGGREGATE FUNCTIONS (contd.)

 Query 16: Find the maximum salary, the minimum salary, and the average salary among employees who work for the 'Research' department.

Q16: SELECT FROM WHERE MAX(SALARY), MIN(SALARY), AVG(SALARY) EMPLOYEE, DEPARTMENT DNO=DNUMBER AND DNAME='Research'

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AGGREGATE FUNCTIONS (contd.)

 Queries 17 and 18: Retrieve the total number of employees in the company (Q17), and the number of employees in the 'Research' department (Q18).

Q17: Q18: SELECT FROM SELECT FROM WHERE COUNT (*) EMPLOYEE COUNT (*) EMPLOYEE, DEPARTMENT DNO=DNUMBER AND DNAME='Research ’

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GROUPING

 In many cases, we want to apply the aggregate functions to

subgroups of tuples

in a relation 

Partition

relation into subsets of tuples    Create subgroups of tuples before summarizing 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

 If NULLs exist in grouping attribute  Separate group is created for all tuples with a NULL value in grouping attribute

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GROUPING (contd.)

 Query 20: For each department, retrieve the department number, the number of employees in the department, and their average salary.

Q20: SELECT FROM GROUP BY DNO , COUNT (*), AVG (SALARY) EMPLOYEE DNO    In Q20, 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

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GROUPING (contd.)

 Query 21: For each project, retrieve the project number, project name, and the number of employees who work on that project.

Q21: SELECT FROM WHERE GROUP BY PNUMBER, PNAME, COUNT (*) PROJECT, WORKS_ON PNUMBER=PNO PNUMBER  In this case, the grouping and functions are applied after the joining of the two relations

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