Database System Concepts, 6th Ed.
©Silberschatz, Korth and Sudarshan
See www.db-book.com for conditions on re-use
Chapter 6:
Formal Relational Query Languages
©Silberschatz, Korth and Sudarshan6.2Database System Concepts - 6th Edition
Chapter 6: Formal Relational Query Languages
 Relational Algebra
 Tuple Relational Calculus
 Domain Relational Calculus
©Silberschatz, Korth and Sudarshan6.3Database System Concepts - 6th Edition
Relational Algebra
 Procedural language
 Six basic operators
 select: 
 project: 
 union: 
 set difference: –
 Cartesian product: 
 rename: 
 The operators take one or two relations as inputs and produce a new
relation as a result.
 E.g. : r  s s = (r)
©Silberschatz, Korth and Sudarshan6.4Database System Concepts - 6th Edition
Select Operation – Example
 Relation r
 A=B  D > 5 (r)
©Silberschatz, Korth and Sudarshan6.5Database System Concepts - 6th Edition
Select Operation
 Notation: p(r)
 p is called the selection predicate
 Defined as:
p(r) = {t | t  r and p(t)}
Where p is a formula in propositional calculus consisting of terms connected
by conjunctions:  (and),  (or),  (not)
formula := term
term <conjunction> term
( term )
term := expr
expr <op> expr
( expr )
expr := attribute
constant
<op> is one of: =, , >, , <, 
 Example of selection:
 dept_name=‘Physics’ (instructor)
©Silberschatz, Korth and Sudarshan6.6Database System Concepts - 6th Edition
Project Operation – Example
 Relation r:
 A,C (r)
©Silberschatz, Korth and Sudarshan6.7Database System Concepts - 6th Edition
Project Operation
 Notation:
where A1, A2 are attribute names and r is a relation name.
 The result is defined as the relation of k columns obtained by erasing
the columns that are not listed
 Duplicate rows removed from result, since relations are sets
 Example: instructor(ID, name, salary, dept_name)
To eliminate the dept_name attribute of instructor write:
ID, name, salary (instructor)
)(,,2,1
r
kAAA 
©Silberschatz, Korth and Sudarshan6.8Database System Concepts - 6th Edition
Union Operation – Example
 Relations r, s:
 r  s:
©Silberschatz, Korth and Sudarshan6.9Database System Concepts - 6th Edition
Union Operation
 Notation: r  s
 Defined as:
r  s = {t | t  r or t  s}
 For r  s to be valid.
1. r, s must have the same arity (same number of attributes)
2. The attribute domains must be compatible
(e.g.: 2nd column of r deals with the same type of values
as does the 2nd column of s)
 Example: to find all courses taught in the Fall 2009 semester, or in the
Spring 2010 semester, or in both
course_id ( semester=“Fall” Λ year=2009 (section)) 
course_id ( semester=“Spring” Λ year=2010 (section))
©Silberschatz, Korth and Sudarshan6.10Database System Concepts - 6th Edition
Set difference of two relations
 Relations r, s:
 r – s:
©Silberschatz, Korth and Sudarshan6.11Database System Concepts - 6th Edition
Set Difference Operation
 Notation r – s
 Defined as:
r – s = {t | t  r and t  s}
 Set differences must be taken between compatible relations.
 r and s must have the same arity
 attribute domains of r and s must be compatible
 Example: to find all courses taught in the Fall 2009 semester, but not in
the Spring 2010 semester
course_id ( semester=“Fall” Λ year=2009 (section)) −
course_id ( semester=“Spring” Λ year=2010 (section))
©Silberschatz, Korth and Sudarshan6.12Database System Concepts - 6th Edition
Cartesian-Product Operation – Example
 Relations r, s:
 r  s:
©Silberschatz, Korth and Sudarshan6.13Database System Concepts - 6th Edition
Cartesian-Product Operation
 Notation r  s
 Defined as:
r  s = {t q | t  r and q  s}
 Assume that attributes of r(R) and s(S) are disjoint.
 That is, R  S = .
 If attributes of r(R) and s(S) are not disjoint, then renaming must be
used.
©Silberschatz, Korth and Sudarshan6.14Database System Concepts - 6th Edition
Composition of Operations
 Can build expressions using multiple operations
 Example: A=C(r  s)
 r  s
 A=C(r  s)
©Silberschatz, Korth and Sudarshan6.15Database System Concepts - 6th Edition
Rename Operation
 Allows us to name, and therefore to refer to, the results of relationalalgebra
expressions.
 Allows us to refer to a relation by more than one name.
 Example:
 x (E)
returns the expression E under the name X
 If a relational-algebra expression E has arity n, then
returns the result of expression E under the name X, and with the
attributes renamed to A1 , A2 , …., An .
)(),...,2,1( E
nAAAx
©Silberschatz, Korth and Sudarshan6.16Database System Concepts - 6th Edition
Example Query
 Find the largest salary in the university
 Step 1: find instructor salaries that are less than some other
instructor salary (i.e. not maximum)
– using a copy of instructor under a new name d
 instructor.salary ( instructor.salary < d.salary
(instructor  d (instructor)))
 Step 2: Find the largest salary
 salary (instructor) –
instructor.salary ( instructor.salary < d.salary
(instructor  d (instructor)))
©Silberschatz, Korth and Sudarshan6.17Database System Concepts - 6th Edition
Example Queries
 Find the names of all instructors in the Physics department, along with the
course_id of all courses they have taught
 Query 1
instructor.name,course_id (dept_name=‘ Physics’ (
 instructor.ID=teaches.ID (instructor  teaches)))
 Query 2
instructor.name,course_id (instructor.ID=teaches.ID (
 dept_name=‘ Physics’ (instructor)  teaches))
©Silberschatz, Korth and Sudarshan6.18Database System Concepts - 6th Edition
Formal Definition
 A basic expression in the relational algebra consists of either one of the
following:
 A relation in the database
 A constant relation
 Let E1 and E2 be relational-algebra expressions; the following are all
relational-algebra expressions:
 E1  E2
 E1 – E2
 E1  E2
 p (E1), P is a predicate on attributes in E1
 s(E1), S is a list consisting of some of the attributes in E1
 x (E1), x is the new name for the result of E1
©Silberschatz, Korth and Sudarshan6.19Database System Concepts - 6th Edition
Additional Operations
We define additional operations that do not add any power to the
relational algebra, but that simplify common queries.
 Set intersection
 Natural join
 Outer join
 Assignment
©Silberschatz, Korth and Sudarshan6.20Database System Concepts - 6th Edition
Set-Intersection Operation
 Notation: r  s
 Defined as:
 r  s = { t | t  r and t  s }
 Assume:
 r, s have the same arity
 attributes of r and s are compatible
 Note: r  s = r – (r – s) = s – (s – r)
©Silberschatz, Korth and Sudarshan6.21Database System Concepts - 6th Edition
Set-Intersection Operation – Example
 Relation r, s:
 r  s
©Silberschatz, Korth and Sudarshan6.22Database System Concepts - 6th Edition
 Notation: r s
Natural-Join Operation
 Let r and s be relations on schemas R and S respectively.
Then, r s is a relation on schema R  S obtained as follows:
 Consider each pair of tuples tr from r and ts from s.
 If tr and ts have the same value on each of the attributes in R  S, add
a tuple t to the result, where
 t has the same value as tr on r
 t has the same value as ts on s
 Example:
r(R), where R = (A, B, C, D)
s(S), where S = (E, B, D)
 Result schema of r s is (A, B, C, D, E)
 r s is defined as:
r.A, r.B, r.C, r.D, s.E (r.B = s.B  r.D = s.D (r  s))
©Silberschatz, Korth and Sudarshan6.23Database System Concepts - 6th Edition
Natural Join Example
 Relations r, s:
 r s
©Silberschatz, Korth and Sudarshan6.24Database System Concepts - 6th Edition
Natural Join and Theta Join
 Find the names of all instructors in the Comp. Sci. department together with
the course titles of all the courses that the instructors teach
  name, title ( dept_name=‘Comp. Sci.’ (instructor teaches course))
 Natural join is associative
 (instructor teaches) course is equivalent to
instructor (teaches course)
 Natural join is commutative
 instructor teaches is equivalent to
teaches instructor
 The theta join operation r  s is defined as
 r  s =  (r  s)
©Silberschatz, Korth and Sudarshan6.25Database System Concepts - 6th Edition
Outer Join
 An extension of the join operation that avoids loss of information.
 Computes the join and then adds tuples form one relation that does not
match tuples in the other relation to the result of the join.
 Uses null values:
 null signifies that the value is unknown or does not exist
 All comparisons involving null are (roughly speaking) false by
definition.
 We shall study precise meaning of comparisons with nulls later
©Silberschatz, Korth and Sudarshan6.26Database System Concepts - 6th Edition
Outer Join – Example
 Relation instructor1
 Relation teaches1
ID course_id
10101
12121
76766
CS-101
FIN-201
BIO-101
Comp. Sci.
Finance
Music
ID dept_name
10101
12121
15151
name
Srinivasan
Wu
Mozart
©Silberschatz, Korth and Sudarshan6.27Database System Concepts - 6th Edition
 Left Outer Join
instructor teaches
Outer Join – Example
 Join
instructor teaches
ID dept_name
10101
12121
Comp. Sci.
Finance
course_id
CS-101
FIN-201
name
Srinivasan
Wu
ID dept_name
10101
12121
15151
Comp. Sci.
Finance
Music
course_id
CS-101
FIN-201
null
name
Srinivasan
Wu
Mozart
©Silberschatz, Korth and Sudarshan6.28Database System Concepts - 6th Edition
Outer Join – Example
 Full Outer Join
instructor teaches
 Right Outer Join
instructor teaches
ID dept_name
10101
12121
76766
Comp. Sci.
Finance
null
course_id
CS-101
FIN-201
BIO-101
name
Srinivasan
Wu
null
ID dept_name
10101
12121
15151
76766
Comp. Sci.
Finance
Music
null
course_id
CS-101
FIN-201
null
BIO-101
name
Srinivasan
Wu
Mozart
null
©Silberschatz, Korth and Sudarshan6.29Database System Concepts - 6th Edition
Outer Join using Joins
 Outer join can be expressed using basic operations
 e.g. r s can be written as
(r s) U ( r – ∏R(r s) )  {(null, …, null)}
©Silberschatz, Korth and Sudarshan6.30Database System Concepts - 6th Edition
Null Values
 It is possible for tuples to have a null value, denoted by null, for some
of their attributes
 null signifies an unknown value or that a value does not exist.
 The result of any arithmetic expression involving null is null.
 Aggregate functions simply ignore null values (as in SQL)
 For duplicate elimination and grouping, null is treated like any other
value, and two nulls are assumed to be the same (as in SQL)
©Silberschatz, Korth and Sudarshan6.31Database System Concepts - 6th Edition
Null Values
 Comparisons with null values return the special truth value: unknown
 If false was used instead of unknown, then not (A < 5)
would not be equivalent to A >= 5
 Three-valued logic using the truth value unknown:
 OR: (unknown or true) = true,
(unknown or false) = unknown
(unknown or unknown) = unknown
 AND: (true and unknown) = unknown,
(false and unknown) = false,
(unknown and unknown) = unknown
 NOT: (not unknown) = unknown
 In SQL there is a special operator “is null”, so “P is null” evaluates
to true if predicate P evaluates to unknown
 Result of select predicate is treated as false if it evaluates to unknown
©Silberschatz, Korth and Sudarshan6.32Database System Concepts - 6th Edition
Extended Relational-Algebra-Operations
 Generalized Projection
 Aggregate Functions
©Silberschatz, Korth and Sudarshan6.33Database System Concepts - 6th Edition
Generalized Projection
 Extends the projection operation by allowing arithmetic functions to be
used in the projection list.
 E is any relational-algebra expression
 Each of F1, F2, …, Fn are are arithmetic expressions involving constants
and attributes in the schema of E.
 Given relation instructor(ID, name, dept_name, salary) where salary is
annual salary, get the same information but with monthly salary
ID, name, dept_name, salary/12 (instructor)
)(,...,, 21
EnFFF
©Silberschatz, Korth and Sudarshan6.34Database System Concepts - 6th Edition
Aggregate Functions and Operations
 Aggregation function takes a collection of values and returns a single
value as a result.
avg: average value
min: minimum value
max: maximum value
sum: sum of values
count: number of values
 Aggregate operation in relational algebra
E is any relational-algebra expression
 G1, G2 …, Gn is a list of attributes on which to group (can be empty)
 Each Fi is an aggregate function
 Each Ai is an attribute name
 Note: Some books/articles use  instead of (Calligraphic G)
)()(,),(),(,,, 221121
Emmn AFAFAFGGG 
©Silberschatz, Korth and Sudarshan6.35Database System Concepts - 6th Edition
Aggregate Operation – Example
 Relation r:
A B








C
7
7
3
10
 sum(c) (r) sum(c )
27
©Silberschatz, Korth and Sudarshan6.36Database System Concepts - 6th Edition
Aggregate Operation – Example
 Find the average salary in each department
dept_name avg(salary) (instructor)
avg
©Silberschatz, Korth and Sudarshan6.37Database System Concepts - 6th Edition
Aggregate Functions (Cont.)
 Result of aggregation does not have a name
 Can use rename operation to give it a name
 For convenience, we permit renaming as part of aggregate
operation
dept_name avg(salary) as avg_sal (instructor)
©Silberschatz, Korth and Sudarshan6.38Database System Concepts - 6th Edition
Modification of the Database
 The content of the database may be modified using the following
operations:
 Deletion
 Insertion
 Updating
 All these operations can be expressed using the assignment
operator ()
©Silberschatz, Korth and Sudarshan6.39Database System Concepts - 6th Edition
Deletion
 A delete request is expressed similarly to a query, except
instead of displaying tuples to the user, the selected tuples are
removed from the database.
 Can delete only whole tuples; cannot delete values on only
particular attributes
 A deletion is expressed in relational algebra by:
r  r – E
where r is a relation and E is a relational algebra query.
 Example:
 Delete all account records in the Perryridge branch.
account  account – branch_name = “Perryridge” (account )
©Silberschatz, Korth and Sudarshan6.40Database System Concepts - 6th Edition
Insertion
 To insert data into a relation, we either:
 specify a tuple to be inserted
 write a query whose result is a set of tuples to be inserted
 in relational algebra, an insertion is expressed by:
r  r  E
where r is a relation and E is a relational algebra expression.
 The insertion of a single tuple is expressed by letting E be a constant
relation containing one tuple.
 Example:
 Insert information in the database specifying that Smith has $1200
in account A-973 at the Perryridge branch.
account  account  {(“A-973”, “Perryridge”, 1200)}
depositor  depositor  {(“Smith”, “A-973”)}
©Silberschatz, Korth and Sudarshan6.41Database System Concepts - 6th Edition
Updating
 A mechanism to change a value in a tuple without charging all values in
the tuple
 Use the generalized projection operator to do this task
 Each Fi is either
 the I th attribute of r, if the I th attribute is not updated, or,
 if the attribute is to be updated Fi is an expression, involving only
constants and the attributes of r, which gives the new value for the
attribute
 Example:
 Make interest payments by increasing all balances by 5 percent.
)(,,,, 21
rr lFFF 
account   account_number, branch_name, balance * 1.05 (account)
©Silberschatz, Korth and Sudarshan6.44Database System Concepts - 6th Edition
Multi-set Relational Algebra
 Pure relational algebra removes all duplicates
 e.g. after projection
 Multi-set relational algebra retains duplicates, to match SQL semantics
 SQL duplicate retention was initially for efficiency, but is now a
feature
 Multi-set relational algebra defined as follows
 selection: has as many duplicates of a tuple as in the input, if the
tuple satisfies the selection
 projection: one tuple per input tuple, even if it is a duplicate
 cross product: If there are m copies of t1 in r, and n copies of t2
in s, there are m  n copies of t1.t2 in r  s
 Other operators similarly defined
 E.g. union: m + n copies, intersection: min(m, n) copies
difference: max(0, m – n) copies
©Silberschatz, Korth and Sudarshan6.45Database System Concepts - 6th Edition
Relational Algebra and SQL
 Assume the following expressions in multi-set relational algebra:
  A1, .., An ( P (r1  r2  …  rm))
is equivalent to the following expression in SQL
 select A1, A2, .. An
from r1, r2, …, rm
where P
 A1, A2 sum(A3) ( P (r1  r2  …  rm)))
is equivalent to the following expression in SQL
 select A1, A2, sum(A3)
from r1, r2, …, rm
where P
group by A1, A2
©Silberschatz, Korth and Sudarshan6.46Database System Concepts - 6th Edition
SQL and Relational Algebra
 More generally, the non-aggregated attributes in the select clause
may be a subset of the group by attributes, in which case the
equivalence is as follows:
select A1, sum(A3)
from r1, r2, …, rm
where P
group by A1, A2
is equivalent to the following expression in multiset relational algebra
 A1,sumA3( A1,A2 sum(A3) as sumA3( P (r1  r2  …  rm)))
©Silberschatz, Korth and Sudarshan6.47Database System Concepts - 6th Edition
Tuple Relational Calculus
©Silberschatz, Korth and Sudarshan6.48Database System Concepts - 6th Edition
Tuple Relational Calculus
 A nonprocedural query language, where each query is of the form
{t | P (t ) }
 It is the set of all tuples t such that predicate P is true for t
 t is a tuple variable, t [A ] denotes the value of tuple t on attribute A
 t  r denotes that tuple t is in relation r
 P is a formula similar to that of the predicate calculus
©Silberschatz, Korth and Sudarshan6.49Database System Concepts - 6th Edition
Predicate Calculus Formula
1. Set of attributes and constants
2. Set of comparison operators: (e.g., , , , , , )
3. Set of connectives: and (), or ()‚ not ()
4. Implication (): x  y, if x if true, then y is true
x  y x  y
5. Set of quantifiers:
  t  r (Q (t ))  ”there exists” a tuple t in relation r
such that predicate Q (t ) is true
 t r (Q (t )) Q is true “for all” tuples t in relation r
©Silberschatz, Korth and Sudarshan6.50Database System Concepts - 6th Edition
Example Queries
 Find the ID, name, dept_name, salary for instructors whose salary is
greater than $80,000
 As in the previous query, but output only the ID attribute value
{t |  s instructor (t [ID ] = s [ID ]  s [salary ]  80000)}
Notice that a relation on schema (ID) is implicitly defined by
the query
{t | t  instructor  t [salary ]  80000}
©Silberschatz, Korth and Sudarshan6.51Database System Concepts - 6th Edition
Example Queries
 Find the names of all instructors whose department is in the Watson
building
{t | s  section (t [course_id ] = s [course_id ] 
s [semester] = “Fall”  s [year] = 2009
v u  section (t [course_id ] = u [course_id ] 
u [semester] = “Spring”  u [year] = 2010)}
 Find the set of all courses taught in the Fall 2009 semester, or in
the Spring 2010 semester, or both
{t | s  instructor (t [name ] = s [name ]
 u  department (u [dept_name ] = s[dept_name] “
 u [building] = “Watson” ))}
©Silberschatz, Korth and Sudarshan6.52Database System Concepts - 6th Edition
Safety of Expressions
 It is possible to write tuple calculus expressions that generate infinite
relations.
 For example, { t |  t r } results in an infinite relation if the domain of
any attribute of relation r is infinite
 To guard against the problem, we restrict the set of allowable
expressions to safe expressions.
 An expression {t | P (t )} in the tuple relational calculus is safe if every
component of t appears in one of the relations, tuples, or constants that
appear in P
 NOTE: this is more than just a syntax condition.
 E.g. { t | t [A] = 5  true } is not safe --- it defines an infinite set
with attribute values that do not appear in any relation or tuples
or constants in P.
©Silberschatz, Korth and Sudarshan6.53Database System Concepts - 6th Edition
Universal Quantification
 Find all students who have taken all courses offered in the
Biology department
 {t |  r  student (t [ID] = r [ID]) 
( u  course (u [dept_name]=“Biology” 
 s  takes (t [ID] = s [ID ] 
s [course_id] = u [course_id]))}
 Note that without the existential quantification on student,
the above query would be unsafe if the Biology department
has not offered any courses.
©Silberschatz, Korth and Sudarshan6.54Database System Concepts - 6th Edition
Domain Relational Calculus
©Silberschatz, Korth and Sudarshan6.55Database System Concepts - 6th Edition
Domain Relational Calculus
 A nonprocedural query language equivalent in power to the tuple
relational calculus
 Each query is an expression of the form:
{  x1, x2, …, xn  | P (x1, x2, …, xn)}
 x1, x2, …, xn represent domain variables
 P represents a formula similar to that of the predicate calculus
©Silberschatz, Korth and Sudarshan6.56Database System Concepts - 6th Edition
Example Queries
 Find the ID, name, dept_name, salary for instructors whose salary is
greater than $80,000
 {< i, n, d, s> | < i, n, d, s>  instructor  s  80000}
 As in the previous query, but output only the ID attribute value
 {< i> | < i, n, d, s>  instructor  s  80000}
 Find the names of all instructors whose department is in the Watson
building
{< n > |  i, d, s (< i, n, d, s >  instructor
  b, a (< d, b, a>  department  b = “Watson” ))}
©Silberschatz, Korth and Sudarshan6.57Database System Concepts - 6th Edition
Example Queries
{<c> |  a, s, y, b, r, t ( <c, a, s, y, b, t >  section 
s = “Fall”  y = 2009 )
v  a, s, y, b, r, t ( <c, a, s, y, b, t >  section ] 
s = “Spring”  y = 2010)}
 Find the set of all courses taught in the Fall 2009 semester, or in
the Spring 2010 semester, or both
This case can also be written as
{<c> |  a, s, y, b, r, t ( <c, a, s, y, b, t >  section 
( (s = “Fall”  y = 2009 ) v (s = “Spring”  y = 2010))}
 Find the set of all courses taught in the Fall 2009 semester, and in
the Spring 2010 semester
{<c> |  a, s, y, b, r, t ( <c, a, s, y, b, t >  section 
s = “Fall”  y = 2009 )
  a, s, y, b, r, t ( <c, a, s, y, b, t >  section ] 
s = “Spring”  y = 2010)}
©Silberschatz, Korth and Sudarshan6.58Database System Concepts - 6th Edition
Safety of Expressions
The expression:
{  x1, x2, …, xn  | P (x1, x2, …, xn )}
is safe if all of the following hold:
1. All values that appear in tuples of the expression are values
from dom (P ) (that is, the values appear either in P or in a tuple of a
relation mentioned in P ).
2. For every “there exists” subformula of the form  x (P1(x )), the
subformula is true if and only if there is a value of x in dom (P1)
such that P1(x ) is true.
3. For every “for all” subformula of the form x (P1 (x )), the subformula is
true if and only if P1(x ) is true for all values x from dom (P1).
©Silberschatz, Korth and Sudarshan6.59Database System Concepts - 6th Edition
Universal Quantification
 Find all students who have taken all courses offered in the Biology
department
 {< i > |  n, d, tc ( < i, n, d, tc >  student 
( ci, ti, dn, cr ( < ci, ti, dn, cr >  course  dn =“Biology”
  si, se, y, g ( <i, ci, si, se, y, g>  takes ))}
 Note that without the existential quantification on student, the
above query would be unsafe if the Biology department has not
offered any courses.
* Above query fixes bug in page 246, last query
Database System Concepts, 6th Ed.
©Silberschatz, Korth and Sudarshan
See www.db-book.com for conditions on re-use
End of Chapter 6