Download SQL: Single Table Queries

SQL - Structured Query Language
ABOUT SQL
DDL: CREATE
DML: INSERT, DELETE, MODIFY
D. Christozov / G.Tuparov
INF 280 Database Systems:
SQL
1
Wikipedia: About SQL (1)
• SQL (Structured Query Language) is the most
popular computer language used to
Create, Retrieve, Update and Delete (CRUD)
data from relational database management systems.
The language has evolved beyond its original
purpose, and now supports object-relational
database management systems.
• SQL has been standardized by both ANSI and ISO.
–
–
–
–
Appeared:
Designed by:
Developer:
First commercial:
D. Christozov / G.Tuparov
1974
D. Chamberlin & R. Boyce
IBM
Oracle
INF 280 Database Systems:
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Wikipedia: About SQL (2)
• Pronunciation: SQL is commonly spoken either as
the names of the letters ess-cue-el, or like the word
sequel. Each of the major database products (or
projects) containing the letters SQL has its own
convention:
– MySQL is officially and commonly pronounced
"My Ess Cue El";
– PostgreSQL is expediently pronounced "postgres" (being
the name of the predecessor to PostgreSQL);
– Microsoft SQL Server is commonly spoken as
"Microsoft-sequel-server".
D. Christozov / G.Tuparov
INF 280 Database Systems:
SQL
3
SQL: History (1)
• An influential paper, "A Relational Model of Data for
Large Shared Data Banks", by Dr. Edgar F. Codd, was
published in June, 1970 in the Association for
Computing Machinery (ACM) journal,
Communications of the ACM, although drafts of it
were circulated internally within IBM in 1969.
• Codd's model became widely accepted as the
definitive model for relational database
management systems (RDBMS or RDMS).
• During the 1970s, a group at IBM's San Jose research
centre developed a database system "System R"
based upon, but not strictly faithful to, Codd's model.
D. Christozov / G.Tuparov
INF 280 Database Systems:
SQL
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SQL: History (2)
• Structured English Query Language (SEQL "SEQUEL") was designed to manipulate and retrieve
data stored in System R. The acronym SEQUEL was
later condensed to SQL. Although SQL was
influenced by Codd's work, Donald D. Chamberlin
and Raymond F. Boyce at IBM were the authors of
the SEQUEL language design.
• The first non-commercial, relational, non-SQL
database, Ingres, was developed in 1974 at U.C.
Berkeley.
D. Christozov / G.Tuparov
INF 280 Database Systems:
SQL
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SQL: History (3)
• Ingres spawned a number of commercial database
applications, including Sybase, Microsoft SQL Server,
HP NonStop SQL and a number of others.
• Postgres (Post Ingres), a project which started in the
mid-1980s, later evolved into PostgreSQL.
G.Tuparov
INF 280 Database Systems:
SQL
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SQL: History (4)
• In 1978, IBM began to develop commercial products
based on their System R prototype that implemented
SQL, including the System/38 (announced in 1978
and commercially available in August 1979), SQL/DS
(introduced in 1981), and DB2 (in 1983).
• At the same time Relational Software, Inc. (now
Oracle Corporation) developed their own version of a
RDBMS for the Navy, CIA and others. In the summer
of 1979 was introduced Oracle V2 (Version2) for VAX
computers as the first commercially available
implementation of SQL. In fact they only beat IBM's
release of the System/38 by a few weeks.
D. Christozov / G.Tuparov
INF 280 Database Systems:
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MySQL
• MySQL is an open source database, a SQL client/server
relational database management system originating
from Scandinavia. (Now is owned by Oracle Corp.)
• Multiplatform (Unix, Linux, Windows, Mac …)
• Pluggable storage engines (MyISAM, InnoDB, etc)
• MySQL is used mainly because it's free, reliable, easy
to setup and maintain.
Useful links:
– http://www.mysql.com
– http://www.datadisk.co.uk/html_docs/mysql/mysql.htm
– http://thinkingmonster.wordpress.com/mysql/
G.Tuparov
INF 280 Database Systems:
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MySQL Architecture
G.Tuparov
INF 280 Database Systems:
SQL
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Drop-in replacements for MySQL
• MariaDB
http://www.mariadb.org
• Percona Server
http://www.percona.com/software/percona-server
G.Tuparov
INF 280 Database Systems:
SQL
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SQL Standards
Year
Name
1986 SQL-86
Alias
SQL-87
ANSI – 1986; Refined by ISO in 1987
Minor revisions
1989 SQL-89
1992 SQL-92
Comments
SQL2
Major Revisions
1999 SQL:1999 SQL3
Added regular expression matching, recursive queries, triggers, nonscalar types and some object-oriented features. (The last two are
somewhat controversial and not yet widely supported.)
2003 SQL:2003
Introduced XML-related features, window functions, standardized
sequences and columns with auto-generated values (including
identity-columns).
2006 SQL:2006
Defines ways SQL can be used in conjunction with XML: importing
and storing XML data in an SQL database, manipulating it within the
database and publishing both XML and conventional SQL-data in
XML form; provides facilities that permit applications to integrate
into their SQL code the use of XQuery, the XML Query Language
published by the World Wide Web Consortium (W3C), to
concurrently access ordinary SQL-data and XML documents
D. Christozov / G.Tuparov
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Relational Algebra – as a fundament of SQL
• Relational algebra, an offshoot of first-order logic, is
a set of relations closed under operators. Operators
operate on one or more relations to yield a relation.
Relation algebra in pure mathematics is an algebraic
structure, relevant to mathematical logic and set
theory.
• E.F. Codd proposed such an algebra as a basis for
database query languages. SQL is loosely based on a
relational algebra, though the operands in SQL
(tables) are not exactly relations and several useful
theorems about the relational algebra do not hold in
the SQL counterpart.
D. Christozov / G.Tuparov
INF 280 Database Systems:
SQL
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Relational Algebra – Primitive operators (1)
• The six primitive operators of Codd's algebra are
– Selection;
– Projection;
– Cartesian product (also called the cross product or
cross join);
– Set union;
– Set difference;
– Rename.
• These six operators are fundamental in the sense that
none of them can be omitted without losing expressive
power.
D. Christozov / G.Tuparov
INF 280 Database Systems:
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Relational Algebra – Primitive operators
• Many other operators have been defined in terms of
these six. Among the most important are
– Set intersection;
– Division;
– Natural join.
• Altogether, the operators of relational algebra have
identical expressive power to that of domain
relational calculus or tuple relational calculus.
D. Christozov / G.Tuparov
INF 280 Database Systems:
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Relational Algebra – Set operators
• Although three of the six basic operators are taken
from set theory, there are additional constraints that
are present in their relational algebra counterparts:
– For set union and set difference, the two relations
involved must be union-compatible — that is, the
two relations must have the same set of attributes.
– As set intersection can be defined in terms of set
difference, the two relations involved in set
intersection must also be union-compatible.
D. Christozov / G.Tuparov
INF 280 Database Systems:
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Relational Algebra – Set Union
• Union: R U S
Result: Relation with tuples from R and S with
duplicates removed.
R FName LName Age
FName
LName
S
Age
John
Smith
35
John
Smith
35
Mary
Shelley
29
Mary
Shelley
29
John
Doe
45
John
Doe
45
Nicky
Little
25
Nicky
Little
25
FName
LName
Age
Peter
White
30
John
Doe
45
Nicky
Black
27
Peter
White
30
Nicky
Black
27
G.Tuparov
RUS=
Union is a commutative operation
RUS=SUR
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Relational Algebra – Set Difference
• Difference: R - S
Result: Relation with tuples from R but not from S.
R FName LName Age
S
John
Smith
35
Mary
Shelley
29
John
Doe
45
Nicky
Little
25
FName
LName
Age
John
Doe
45
Peter
White
30
Nicky
Black
27
G.Tuparov
R–S=
FName
LName
Age
John
Smith
35
Mary
Shelley
29
Nicky
Little
25
Difference is not a commutative
operation R - S ≠ S - R
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Relational Algebra – Set Intersection
• Intersection: R ∩ S
Result: Relation with tuples that appear in both R
and S.
R FName LName Age
S
John
Smith
35
Mary
Shelley
29
John
Doe
45
Nicky
Little
25
FName
LName
Age
John
Doe
45
Peter
White
30
Nicky
Black
27
G.Tuparov
R∩S=
FName
LName
Age
John
Doe
45
Intersection is a commutative
operation, i.e. R ∩ S = S ∩ R
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Relational Algebra – Cartesian product
• Cartesian product: R x S
Result: All combinations of tuples from two relations.
R FName LName Age
FName LName Age Car
Color
S
John
Smith
35
John
Smith
35
BMW Black
Mary
Shelley
29
John
Smith
35
Audi
John
Doe
45
Mary
Shelley 29
BMW Black
Nicky
Little
25
Mary
Shelley 29
Audi
John
Doe
45
BMW Black
RxS=
White
White
Car
Color
John
Doe
45
Audi
BMW
Black
Nicky
Little
25
BMW Black
Audi
White
Nicky
Little
25
Audi
D. Christozov / G.Tuparov
INF 280 Database Systems:
SQL
White
White
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Relational Algebra - Projection 
• A projection is a unary operation, where a1,...,an(R) is
a subset of attribute names of the set of all attribute
names of the relation R.
• Project only the names and cars of the employees in R
Fname, Lname, Car (R)
Result
R FName LName Age Car Color
FName LName Car
John
Smith
Mary
BMW Red
John
Smith
Shelley 29
Mini
Black
Mary
Shelley Mini
John
Doe
45
Audi
White
John
Doe
Audi
Nicky
Little
25
BMW White
Nicky
Little
BMW
Peter
White
30
Reno
Red
Peter
White
Reno
Nicky
Black
27
Seat
Green
Nicky
Black
Seat
D. Christozov / G.Tuparov
35
INF 280 Database Systems:
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BMW
20
Relational Algebra - Selection  (1)
• A selection is a unary operation, where  condition(s) (R)
selects all those tuples in R for which condition(s)
holds. The selection operation acts like a filter on a
relation.
• The resulting relation will have the same degree as
the original relation.
• The condition can be made up of any combination of
comparison or logical operators that operate on the
attributes of R.
– Comparison operators: = ≠ > < ≥ ≤
– Logical operators: ᴧ (AND) v (OR) ┐ (NOT)
D. Christozov / G.Tuparov
INF 280 Database Systems:
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Relational Algebra - Selection  (2)
Example 1: Select only those tuples from R that have
BMW car:
 Car=‘BMW’ (R)
Result
FName LName Age
Car
John
Smith
FName LName Age
Car
BMW Red
John
Smith
35
BMW Red
Mary
Shelley 29
Mini
Black
Nicky
Little
25
BMW White
John
Doe
45
Audi
White
Nicky
Little
25
BMW White
Peter
White
30
Reno
Red
Nicky
Black
27
Seat
Green
G.Tuparov
35
Color
INF 280 Database Systems:
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Color
22
Relational Algebra - Selection  (3)
Example 2: Select only those tuples from R that have
white BMW car :
 Car=‘BMW’ ᴧ Color=‘White’ (R)
Result
FName LName Age
Car
John
Smith
BMW Red
Mary
Shelley 29
Mini
Black
John
Doe
45
Audi
White
Nicky
Little
25
BMW White
Peter
White
30
Reno
Red
Nicky
Black
27
Seat
Green
G.Tuparov
35
Color
FName LName Age
Car
Nicky
BMW White
INF 280 Database Systems:
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Little
25
Color
23
Relational Algebra - Selection  (4)
Example 3: Select only those tuples from R that have
BMW or green car :
 Car=‘BMW’ V Color=‘Green’ (R)
Result
FName LName Age
Car
John
Smith
FName LName Age
Car
BMW Red
John
Smith
35
BMW Red
Mary
Shelley 29
Mini
Black
Nicky
Little
25
BMW White
John
Doe
45
Audi
Blue
Nicky
Black
27
Seat
Nicky
Little
25
BMW White
Peter
White
30
Reno
Red
Nicky
Black
27
Seat
Green
G.Tuparov
35
Color
INF 280 Database Systems:
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Color
Green
24
Relational Algebra - Selection  (5)
Example 4: Select only those tuples from R that have
not BMW or not black car :
 ┐(Car=‘BMW’ ᴧ Color=‘Black’) (R)
Result
FName LName Age
Car
John
Smith
FName LName Age
Car
Color
BMW Red
John
Doe
45
Audi
White
Mary
Shelley 29
Mini
Black
Peter
White
30
Reno
Red
John
Doe
45
Audi
White
Nicky
Black
27
Seat
Green
Nicky
Little
25
BMW White
Peter
White
30
Reno
Red
Nicky
Black
27
Seat
Green
G.Tuparov
35
Color
INF 280 Database Systems:
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Relational Algebra –
Combining Selection and Projection
Example: Show only the names of the employees in R
that drive red cars.
Fname, Lname ( Color=‘Red’ (R))
Result
FName LName Age
Car
John
Smith
BMW Red
John
Smith
Mary
Shelley 29
Mini
Black
Peter
White
John
Doe
45
Audi
White
Nicky
Little
25
BMW White
Peter
White
30
Reno
Red
Nicky
Black
27
Seat
Green
G.Tuparov
35
Color
INF 280 Database Systems:
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FName LName
26
Relational Algebra - The aggregation operation
• There are five aggregate functions that are included
with most databases. These operations are
– Sum
– Count
– Average
– Maximum
– Minimum
• Aggregate functions could be written using
– the Projection operator or
– the Script F (F) character (in Elmasri/Navathe book)
D. Christozov / G.Tuparov
INF 280 Database Systems:
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Relational Algebra - Sum
Example: Show the sum of all salaries from R
F SUM (Salary) (R)
Result:
FName LName Salary
SUM (Salary)
John
Smith
12000
Mary
Shelley 2500
John
Doe
2000
Nicky
Little
2000
Peter
White
3000
Nicky
Black
1000
D. Christozov / G.Tuparov
1500
INF 280 Database Systems:
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Relational Algebra - Count
Example: Count the number of employees from R
F COUNT (FName) (R)
Result:
FName LName Salary
COUNT (FName)
John
Smith
6
Mary
Shelley 2500
John
Doe
2000
Nicky
Little
2000
Peter
White
3000
Nicky
Black
1000
D. Christozov / G.Tuparov
1500
INF 280 Database Systems:
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Relational Algebra - Average
Example: Show the average of all salaries from R
F AVG (Salary) (R)
Result:
FName LName Salary
AVG (Salary)
John
Smith
2000
Mary
Shelley 2500
John
Doe
2000
Nicky
Little
2000
Peter
White
3000
Nicky
Black
1000
D. Christozov / G.Tuparov
1500
INF 280 Database Systems:
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Relational Algebra - Min
Example: Show the minimum Salary from R:
F MIN (Salary) (R)
Result:
FName LName Salary
MIN (Salary)
John
Smith
1000
Mary
Shelley 2500
John
Doe
2000
Nicky
Little
2000
Peter
White
3000
Nicky
Black
1000
D. Christozov / G.Tuparov
1500
INF 280 Database Systems:
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Relational Algebra - Max
Example: Show the maximum Salary from R:
F MAX (Salary) (EMP)
Result:
FName LName Salary
MAX(Salary)
John
Smith
3000
Mary
Shelley 2500
John
Doe
2000
Nicky
Little
2000
Peter
White
3000
Nicky
Black
2500
D. Christozov / G.Tuparov
1500
INF 280 Database Systems:
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Relational Algebra – Natural Join
• Join operations bring together two relations and
combine their attributes and tuples in a specific
fashion (according to specific condition).
• The generic join operator (Theta Join) is: ⋈
• It takes as arguments the attributes from the two
relations that are to be joined.
• The join condition can be = ≠ > < ≥ ≤
• When the join condition operator is = then we call
this an Equijoin
D. Christozov / G.Tuparov
INF 280 Database Systems:
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Relational Algebra – Natural Join
Example: R ⋈ R.Dept = S.Dept S
R
S
FName
LName Dept
John
Smith
Mary
Shelley HR
John
Doe
IT
FName
LName
Dept Office
Peter
White
IT
John
Smith
IT
203
Nicky
Black
PR
Mary
Shelley
HR
201
John
Doe
IT
203
Peter
White
IT
203
Nicky
Black
PR
202
Dept Office
HR
201
PR
202
IT
203
G.Tuparov
IT
Result
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SQL DDL: Creating Environment, Schema, DBSpace
Environment
Database
Schema
DBspace
Storage pool
D. Christozov / G.Tuparov
Holds a single database.
Consists of the set of all schemes defined in that
environment.
Consists of zero or more tables, views, and
privileges, belonging to a user.
Logical allocation of space in the database portion
of total database. A user must have access to at
least one DBspace. Different DBspaces may have
different locking levels.
Consists of dbextents, provided by the DB
administrator.
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SQL DDL: Creating Environment, Schema, DBSpace
CREATE DATABASE database_name
DROP DATABASE database_name
ACQUIRE [ PUBLIC | PRIVATE ] DBSPACE
NAMED dbspace_name [ (option [, option] ...)]
Option:LOCK = { DBSPACE | PAGE | ROW }
specifies the locking level. DBMS locked the
specified resource, for simultaneous access
by a second user.
PRIVATE DB are locked on entire dbspace level.
D. Christozov / G.Tuparov
INF 280 Database Systems:
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SQL DDL: Creating Environment, Schema, DBSpace
ALTER DBSPACE dbspace_name
DROP DBSPACE dbspace_name
Activating a Database:
USE database_name or START database_name
D. Christozov / G.Tuparov
INF 280 Database Systems:
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SQL DDL: Create Table
• Before creating a table, the following must be
completed:
– a database (environment) to hold the schema
(tables) must exists;
– a dbspace, to hold the tables must exists;
– the database chosen to hold the table must be
active;
– the user must have the authority to create
schemes (table);
D. Christozov / G.Tuparov
INF 280 Database Systems:
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SQL DDL: Create Schema, Table
CREATE SCHEMA database_schema_name
AUTHORIZATION owner_name;
MySQL Dialect
CREATE DATABASE database_name;
USE database_name;
GRANT list_of_privilegies
ON database_name
TO user_name@host_name
IDENTIFIED BY some_password;
D. Christozov / G.Tuparov
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SQL DDL: Create Table
CREATE TABLE table_name (
column_name data_type [null_specifier],
...
PRIMARY KEY (column_name [,...]),
FOREIGN KEY (column_name)
REFERENCES table_name (column_name) );
DROP TABLE table_name CASCADE;
ALTER TABLE table_name ADD column_name ...;
DROP column_name;
ALTER column_name SET ... … …. ;
D. Christozov / G.Tuparov
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SQL DDL: Data Types, Domain
Standard SQL Data type
CHARACTER (length)
left_justified, truncated or
rejected
VARCHAR (max_length)
probably a given limit
exists
LONG VARCHAR - without
specifying the max_length
MySQL Data Type
CHAR(length) 1-255 characters
DATE
TIME
DATE, DATETIME
TIMESTAMP, TIME
YEAR
D. Christozov / G.Tuparov
VARCHAR(length) 1-65535 chars
TINYTEXT(length) up to 255 chars
TEXT(length) up to 65535 chars
MEDIUMTEXT(length)
LONGTEXT(length)
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SQL DDL: Data Types, Domain
Standard SQL
Whole numbers:
INTEGER
SMALLINT
Floating point
numbers:
FLOAT
D. Christozov / G.Tuparov
MySQL
General format:
INT_DATA_TYPE [size] [unsigned]
TINYINT [-128 to 127] or 255 unsign.
SMALLINT [-32768 to 32767]
MEDIUMINTINT …
INT or INTEGER …
BIGINT …
FLOAT(length, dec)
length – number of digits
dec – number of decimal places
DOUBLE(length, dec)
DECIMAL(length, dec)
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SQL DML: Insert
EMPLOYEE
Fname
Minit
Lname
SSN
Bdate
Address
Sex
Salary
SupSSN
DNO
INSERT INTO EMPLOYEE
VALUES (‘Richard’,‘K’, ‘Marini’,‘653298653’,‘1962-12-30’,
’98 Oak Forest,Katy,TX’,‘M’,37000,‘987654321’,4);
INSERT INTO EMPLOYEE (Fname, Lname, DNO, SSN)
VALUES (‘Richard’, ‘Marini’, 4, ‘653298653’);
INSERT INTO EMPLOYEE (Fname, Lname, SSN, DNO)
VALUES (‘Robert’, ‘Hatcher’, ‘980760540’, 2);
INSERT INTO EMPLOYEE (Fname, Lname, DNO)
VALUES (‘Robert’, ‘Hatcher’, 5);
D. Christozov / G.Tuparov
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SQL DML: Delete (1)
EMPLOYEE
Fname
Minit
Lname
SSN
Bdate
Address
Sex
Salary
SupSSN
DNO
John
B
Smith
123456789
1965-01-09
…TX…
M
30000
3334455555
5
Franklin
T
Wong
333445555
1956-12-08
…TX…
M
40000
888665555
5
Alicia
J
Zelaya
999887777
1968-01-19
…TX…
F
25000
987654321
4
Jennifer
S
Wallace
987654321
1941-06-02
…TX…
F
43000
888665555
4
Ramesh
K
Narayan
666884444
1962-09-15
…TX…
M
38000
333445555
5
Joyce
A
English
453453453
1972-07-31
…TX…
F
25000
333445555
5
Ahmad
V
Jabbar
987987987
1969-03-29
…TX…
M
25000
987654321
4
James
E
Borg
888665555
1937-11-10
…TX…
M
55000
Null
1
DEPARTMENT
DELETE FROM EMPLOYEE
WHERE Lname=‘Zelaya’;
DELETE FROM EMPLOYEE
WHERE SSN=‘123456789’;
D. Christozov / G.Tuparov
Dname
Dnumber
MGRSSN
MGRSDate
Research
5
333445555
1988-05-22
Administration
4
987654321
1995-01-01
Headquarter
1
888665555
1981-06-19
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SQL DML: Delete (2)
EMPLOYEE
Fname
Minit
Lname
SSN
Bdate
Address
Sex
Salary
SupSSN
DNO
John
B
Smith
123456789
1965-01-09
…TX…
M
30000
3334455555
5
Franklin
T
Wong
333445555
1956-12-08
…TX…
M
40000
888665555
5
Alicia
J
Zelaya
999887777
1968-01-19
…TX…
F
25000
987654321
4
Jennifer
S
Wallace
987654321
1941-06-02
…TX…
F
43000
888665555
4
Ramesh
K
Narayan
666884444
1962-09-15
…TX…
M
38000
333445555
5
Joyce
A
English
453453453
1972-07-31
…TX…
F
25000
333445555
5
Ahmad
V
Jabbar
987987987
1969-03-29
…TX…
M
25000
987654321
4
James
E
Borg
888665555
1937-11-10
…TX…
M
55000
Null
1
DELETE FROM EMPLOYEE
WHERE DNO IN
(SELECT Dnumber
FROM DEPARTMENT
WHERE Dname=‘Headquarter’);
DELETE FROM EMPLOYEE;
D. Christozov / G.Tuparov
DEPARTMENT
Dname
Dnumber
MGRSSN
MGRSDate
Research
5
333445555
1988-05-22
Administration
4
987654321
1995-01-01
Headquarter
1
888665555
1981-06-19
INF 280 Database Systems:
SQL
45
SQL DML: Modify (1)
EMPLOYEE
Fname
Minit
Lname
SSN
Bdate
Address
Sex
Salary
SupSSN
DNO
John
B
Smith
123456789
1965-01-09
…TX…
M
30000
3334455555
5
Franklin
T
Wong
333445555
1956-12-08
…TX…
M
40000
888665555
5
Alicia
J
Zelaya
999887777
1968-01-19
…TX…
F
25000
987654321
4
Jennifer
S
Wallace
987654321
1941-06-02
…TX…
F
43000
888665555
4
Ramesh
K
Narayan
666884444
1962-09-15
…TX…
M
38000
333445555
5
Joyce
A
English
453453453
1972-07-31
…TX…
F
25000
333445555
5
Ahmad
V
Jabbar
987987987
1969-03-29
…TX…
M
25000
987654321
4
James
E
Borg
888665555
1937-11-10
…TX…
M
55000
Null
1
UPDATE EMPLOYEE
SET Salary = Salary *1.1
WHERE DNO IN
(SELECT Dnumber
FROM DEPARTMENT
WHERE Dname=‘Research’);
D. Christozov / G.Tuparov
DEPARTMENT
Dname
Dnumber
MGRSSN
MGRSDate
Research
5
333445555
1988-05-22
Administration
4
987654321
1995-01-01
Headquarter
1
888665555
1981-06-19
INF 280 Database Systems:
SQL
46
SQL DML: Modify
PROJECT
Pname
Pnumber
Plocation
DNum
UPDATE PROJECT
SET Plocation = ‘Bellaire’, DNum = 5
WHERE PNumber = 10;
UPDATE EMPLOYEE
DEPARTMENT
SET Salary = Salary *1.1
Dname
Dnumber
WHERE DNO IN
(SELECT Dnumber
FROM DEPARTMENT
WHERE Dname=‘Research’);
D. Christozov / G.Tuparov
INF 280 Database Systems:
SQL
MGRSSN
MGRSDate
47
Questions?
D. Christozov / G.Tuparov
INF 280 Database Systems:
SQL
48