introduction to schema refinement. different problems may arise when converting a relation into...
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Introduction to Schema Refinement
Introduction to Schema Refinement• Different problems may arise when converting
a relation into standard form• They are
• Data redundancy• Update Anomalies• Deletion Anomalies• Insertion Anomalies
Introduction to Schema Refinement• Data Redundancy• Storing the information repeatedly, that is, in
more than one place within a database, can lead to several problems
• Redundancy leads to inconsistency
• Inconsistency generate problem in insertion, deletion and updating
Introduction to Schema Refinement
• Problems Caused by Redundancy• Update Anomalies: If one copy of such repeated
data is updated, an inconsistency is created unless all copies similarly updated.
• Insertion Anomalies: It is not be possible to store certain information unless some other, unrelated, information is stored as well.
• Deletion Anomalies: It may not be possible to delete certain information without losing other, unrelated, information as well.
Introduction to Schema Refinement• Data Redundancy• In the student relation there are information is repeated
several times
• Update Anomalies:• If we change the name ‘Ravi’, it affects all 2 rows having
sname information too• Deletion Anomalies:• Deleting row 2 result in loss of AAA college from the
whole relation• Insertion Anomalies:• Cannot add a row which does not have value
Sid Sname Course Colleg100 Ravi CSE ABC101 Vijay MCA AAA102 Saji EEE BBB103 Ravi EC CCC
Introduction to Schema RefinementNull ValuesNull value leads to wastage of memory spaceNull value have multiple interpretations, such as• The attribute does not apply to this tuple.• The attribute value for this tuple is unknown.• The value is known but absent; that is, it has not
been recorded yet.
Introduction to Schema Refinement
• The Process of Normalisation• Normalisation is a data analysis technique to design a
database system. • It allows the database designer to understand the
current data structures in an organisation. • Furthermore, it aids any future changes and
enhancements to the system.• Normalisation is a technique for producing relational
schema with the following properties:• No Information Redundancy• No Update Anomalies
Functional dependency• It play a main role in designing good database design
from bad database design• A functional dependency (FD) is a constraint between
two sets of attributes in a relation• Describes the relationship between attributes in a
relation. • If A and B are attributes of a relation R, • B is functionally dependent on A • (denoted. A → B), if each value of A in R is associated
with exactly one value of B in R.
Functional dependency• A → B• Determinant: attribute or set of attributes on
the left hand side of the arrow.
• In the above example A is determinant
• Determinant may be attribute or group of attribute
Functional dependency• From the relation Customer
• Cid Cname
Because Cid is the primary key of the tableIt is always uniqueSo Cid uniquely determines the customer name even in the case of duplicate
CnameSo Cname is functionally dependent to Cid
CnamecidIt is not always trueBecause name of the customer may be same for different CidSo Cname not uniquely determines the customer
Cid age trueCid salary trueAgeCid false
Cid Cname Age Salary101 Jeet 65 7000102 Seet 44 8000103 Swet 34 6000104 Abc 23 5000
Functional dependency• Unnormalized form (UNF): A table that contains one or
more repeating groups.
• Repeating group: an attribute or group of attributes within a table that occurs with multiple values in a single row
• An unnormalized relation contains non atomic values
• Example• The row corresponding to Jeet• Have more than one phone no• So this table is unnormalized • relation
Cid Cname Phone
101 Jeet 233567234568
102 Seet 44103 Swet 34104 Abc 23
Functional dependency• First normal form (1NF): A relation in which the
each row and column contains one and only one value.
• Is does not contain multivalued attribute• Every attribute value is atomic• Ie all cells are single values
• A relation is in 1NF if and only if all underlying domains contain atomic values only
• Or• One value is associated with each attribute
Functional dependency• Converting UNF to 1NF• Remove repeating groups(multivalue) • Entering appropriate data in the empty columns
of rows. • For each repeating field value, create a new
tuple
Cid Cname Phone101 Jeet 233567101 Jeet 234568102 Seet 44103 Swet 34104 Abc 23
Cid Cname Phone
101 Jeet 233567234568
102 Seet 44103 Swet 34104 Abc 23
Functional dependency• Types of FD• Full FD
• Partial Dependency
• Transitive Dependency
• Trival and Non-Trival Dependencies
Functional dependency• Types of FD• Full FD• For a relation schema R and FD• X Y, Y is fully functional dependent on X if
there is no Z, where Z is the proper subset of A, such that ZY
• Or• XY is a full FD if the removal of any attribute A
from X removes the dependency
Functional dependency• Types of FD• Full FD• An attribute is fully functionally dependent on a
set of attributes X if it is• Functionally dependent on X, and• Not functionally dependent on any proper
subset of X.
Functional dependency• Types of FD• Partial Dependency• A FD XY is partial dependency if some attribute A can
be removed from X and the dependency sill hold for some attribute, then that dependency is called partial dependency
• Or• if there is some attribute that can be removed from A
and the dependency still holds. • Example• {Cid, Phone} Cname• Is partial because• Cid Cname• Is full FD
Cid Cname Phone101 Jeet 233567101 Jeet 234568102 Seet 44103 Swet 34104 Abc 23
Functional dependency• Types of FD• Transitive dependency: • A condition where A, B and C are attributes of a
relation such that • if A → B and B → C, then C is transitively dependent
on A via B • (provided that A is not functionally dependent on B
or C). • Is • XY• YZ• Then• XZ
Functional dependency• Types of FD• Trival & Non Trival Dependency• Some FD are said to be trival, because they are satisfied by all
relations• Example• A is satisfied by all relations involving attribute A• Similarly ABA is satisfied by all relations involving attribute A• FD is trival if right hand side is a subset of the left hand side
• Non-trival dependency are one that is not trival• XY is non trival if and only if Y X• Example• Car(carno,carname,color,weight) FD of the relation car is• Carnocarname• Carnocolor
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