Overview Of Relational DBMS
Presented by
Satrio Agung Wicaksono
Relational Database Concepts
 A database is a repository of data, designed to support
efficient data storage, retrieval and maintenance
 Relational databaseis a database modeled by relations
 RelationR defined over n sets D1, D2, …Dnwhere Di
represents some domain.
 n-tuple(tuple) is a set < d1, d2, …, dn> where d1εD1,
d2εD2, …
Sample Database Scheme
 The relation schemas for this database can be defined as
follows:
 EMP(ENO, ENAME, TITLE, SAL, PNO, RESP, DUR)
 PROJ(PNO,PNAME, BUDGET)
Key
 Super Key :
 uses keys to define identifiers for a relation’s tuples
 used to enforce rules and/or constraints on database data.
 Candidate Key
 is a unique identifier for the tuples of a relation
 most relations have multiple candidate keys
 Primary Key
 candidate key that is chosen to represent the relation in the database and to provide a way
to uniquely identify each tuple of the relation
 Alternate Key
 the remaining candidate keys
The problem of redundancy
 Data redundancy implies finding the same data in
more than one location within deatabase tables
 The following problems
 Repetition anomaly
 Insertion Anomalies
 Deletion Anomalies
 Update Anomalies
 Cont’d….
Repetition anomaly
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 Repetition anomaly :
 Certain information may be repeated unnecessarily
 This is obviously a waste of storage and is contrary to the spirit of
databases
Insertion Anomalies
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 insertion anomaly : happens when the insertion of a
data record is not possible unless we also add some
additional unrelated data to the record
Deletion Anomalies
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 deletion anomaly happens when deletion of a data
record results in losing some unrelated
information that was stored as part of the record
that was deleted from a table
Update Anomalies
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 An update anomaly occurs when updating data for
an entity in one place may lead to inconsistency,
with the existing redundant data in another place
in the table
Decompositions
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

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Decomposition in relational database design implies breaking down a relational
schema into smaller and simpler relations that avoid redundancy.
The idea is to be able to query the smaller relations for any information that we
were previously able to retrieve from the original relational schema
Functional Dependencies
 Functional Dependency (FD) i:
 a type of integrity constraint that extends the idea of a super key.
 It defines a dependency between subsets of attributes of a given relation
 Functional Dependency can be understood as “A determines B”, “B is
dependent on A” or “A implies B” and denoted as “A → B”.
Functional Dependencies Example
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 Set Of Functional Dependecies …?
Normal Forms
 Normalization is a procedure in relational database design that
aims at converting relational schemas into a more desirable
form
 The goal is to remove redundancy in relations and the problems
that follow from it, namely insertion, deletion and update
anomalies.
 Type of Normal Form:




First Normal Form (1NF)
Second Normal Form (2NF)
Third Normal Form (3NF)
Boyce-Codd Normal Form (BCNF
First Normal Form (1NF)
 A relation is considered to be in first normal form if all of its attributes have
domains that are indivisible or atomic
 A table is in 1NF if and only if it satisfies the following five conditions :
 There is no top-to-bottom ordering to the rows.
 There is no left-to-right ordering to the columns.
 There are no duplicate rows
 Every row-and-column intersection contains exactly one value from the applicable domain
(and nothing else).
 All columns are regular [i.e. rows have no hidden components such as row IDs, object IDs,
or hidden timestamps].
Cont’d….
First Normal Form (1NF)
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1NF transformation
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First Normal Form (1NF)
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Second Normal Form (2NF)
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 A relation is in second formal form when it is in 1NF and there is no such
non-key attribute that depends on part of the candidate key, but on the
entire candidate key
Third Normal Form (3NF)
 A relation is in third normal form if it is in 2NF and there is no such non-key
attribute that depends transitively on the candidate key.
 That is every attribute depends directly on the primary key and not through
a transitive relation where an attribute Z may depend on a non-key attribute
Y and Y in turn depends on the primary key X
 Transitivity means that when X→Y and Y→ Z, then X→Z.
Cont’d…
Third Normal Form (3NF)
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Boyce-Codd Normal Form (BCNF)
 Boyce-Codd Normal Form is a stricter version of 3NF that applies to
relations where there may be overlapping candidate keys.
 A relation is said to be in Boyce-Codd normal form if it is in 3NF and every
non-trivial FD given for this relation has a candidate key as its determinant.
 That is, for every X → Y, X is a candidate key.
Boyce-Codd Normal Form (BCNF)
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5
Relational Algebra
 Relational algebra is a set of operators to
manipulate relations
 Defined 8 such operators, two groups of 4 each:
 The traditional set operations: union, intersection,
difference and Cartesian product
 The special relational operations: select, project, join and
divide
Union

The union of two union-compatible relations R1 and R2, R1 UNION R2, is the set of all
tuples t belonging to either R1 or R2 or both

The formal notation for a union operation is U
Intersection
 The intersection of two union-compatible relations R1 and R2, R1
INTERSECT R2, is the set of all tuples t belonging to both R1 and R2.
 The formal notation for an intersect operation is ∩.
Difference
 The difference between two union-compatible relations R1 and R2, R1
MINUS R2, is the set of all tuples t belonging to R1 and not to R2.
 The formal notation for a difference operation is -
Cartesian product

The Cartesian product between two relations R1 and R2, R1 TIMES R2, is the set of all tuples t
such that t is the concatenation of a tuple r belonging to R1 and a tuple s belonging to R2. The
concatenation of a tuple r = (r1, r2, …, rm) and a tuple s = (sm+1, sm+2, …, sm+n) is the tuple t
= (r1, r2, …, rm, sm+1, sm+2, …, sm+n).

R1 and R2 don’t have to be union-compatible.

The formal notation for a Cartesian product operation is ×
Selection
 The select operation selects a subset of tuples from a relation.
 It is a unary operator, that is, it applies on a single relation.
 The tuples subset must satisfy a selection condition or predicate.
 The formal notation for a select operation is:
σ <select condition> (<relation>)
 where <select condition> is
 <attribute> <comparison operator> <constant value>/<attribute> [AND/OR/NOT
<attribute> <comparison operator> <constant value>/<attribute>…]
 The comparison operator can be <, >, <=, >=, =, <> and it depends on attribute domain or
data type constant value
Selection
Projection
 The project operation builds another relation by selecting a subset of
attributes of an existing relation.
 Duplicate tuples from the resulting relation are eliminated. It is also a unary
operator.
 The formal notation for a project operation is:
 π <attribute list> (<relation>)
 where <attribute list> is the subset attributes of an existing relation
Projection
JOIN
 The join operation concatenates two relations based on a joining condition
or predicate.
 The relations must have at least one common attribute with the same
underlying domain, and on such attributes a joining condition can be
specified.
 The formal notation for a join operation is:
 R <join condition> ►◄S
 where <join condition> is
 <attribute from R> <comparison operator> < <attribute from S>
 The comparison operator can be <, >, <=, >=, =, <> and it depends on attributes domain.
JOIN
Division
 The division operator divides a relation R1 of degree (n+m) by a relation R2
of degree m and produces a relation of degree n.
 The (n+i)th attribute of R1 and the ith attribute from R2 should be defined
on the same domain.
 The result of a division operation between R1 and R2 is another relation,
which contains all the tuples that concatenated with all R2 tuples are
belonging to R1 relation.
 The formal notation for a division operation is ÷.
Division