Minimal Sets of Functional Dependencies
16.1.3 Minimal Sets of Functional Dependencies
Informally, a minimal cover of a set of functional dependencies E is a set of func- tional dependencies F that satisfies the property that every dependency in E is in the closure F + of F. In addition, this property is lost if any dependency from the set F is
removed; F must have no redundancies in it, and the dependencies in F are in a standard form. To satisfy these properties, we can formally define a set of functional dependencies F to be minimal if it satisfies the following conditions:
1. Every dependency in F has a single attribute for its right-hand side.
2. We cannot replace any dependency X → A in F with a dependency Y → A, where Y is a proper subset of X, and still have a set of dependencies that is
equivalent to F.
3. We cannot remove any dependency from F and still have a set of dependen- cies that is equivalent to F.
We can think of a minimal set of dependencies as being a set of dependencies in a
550 Chapter 16 Relational Database Design Algorithms and Further Dependencies
every dependency in a canonical form with a single attribute on the right-hand side. 4 Conditions 2 and 3 ensure that there are no redundancies in the dependencies either by having redundant attributes on the left-hand side of a dependency (Condition 2) or by having a dependency that can be inferred from the remaining FDs in F (Condition 3).
Definition.
A minimal cover of a set of functional dependencies E is a minimal set of dependencies (in the standard canonical form and without redundancy) that is equivalent to E. We can always find at least one minimal cover F for any set of dependencies E using Algorithm 16.2.
If several sets of FDs qualify as minimal covers of E by the definition above, it is cus- tomary to use additional criteria for minimality. For example, we can choose the minimal set with the smallest number of dependencies or with the smallest total length (the total length of a set of dependencies is calculated by concatenating the dependencies and treating them as one long character string).
Algorithm 16.2. Finding a Minimal Cover F for a Set of Functional Dependencies E
Input:
A set of functional dependencies E.
1. Set F := E.
2. Replace each functional dependency X → {A 1 ,A 2 , ..., A n } in F by the n func-
tional dependencies X →A 1 , X →A 2 , ..., X → A n .
3. For each functional dependency X → A in F for each attribute B that is an element of X
if { {F – {X → A} } ∪ { (X – {B} ) → A} } is equivalent to F then replace X → A with (X – {B} ) → A in F.
4. For each remaining functional dependency X → A in F
if {F – {X → A} } is equivalent to F, then remove X → A from F.
We illustrate the above algorithm with the following: Let the given set of FDs be E : {B → A, D → A, AB → D}. We have to find the mini-
mal cover of E.
All above dependencies are in canonical form (that is, they have only one attribute on the right-hand side), so we have completed step 1 of Algorithm
16.2 and can proceed to step 2. In step 2 we need to determine if AB → D has any redundant attribute on the left-hand side; that is, can it be replaced by
B → D or A → D?
4 This is a standard form to simplify the conditions and algorithms that ensure no redundancy exists in F. By using the inference rule IR4, we can convert a single dependency with multiple attributes on the
16.2 Properties of Relational Decompositions 551
Since B → A, by augmenting with B on both sides ( IR2 ), we have BB → AB, or B → AB (i). However, AB → D as given (ii).
Hence by the transitive rule ( IR3 ), we get from (i) and (ii), B → D. Thus AB → D may be replaced by B → D.
No further reduction is possible in step 2 since all FDs have a single attribute on the left-hand side.
can be eliminated.
Therefore, the minimal cover of E is {B → D, D → A}. In Section 16.3 we will see how relations can be synthesized from a given set of
dependencies E by first finding the minimal cover F for E. Next, we provide a simple algorithm to determine the key of a relation:
Algorithm 16.2(a). Finding a Key K for R Given a set F of Functional Dependencies
Input:
A relation R and a set of functional dependencies F on the attributes of R.
1. Set K := R.
2. For each attribute A in K {compute (K – A) + with respect to F;
if (K – A) + contains all the attributes in R, then set K := K – {A} }; In Algoritm 16.2(a), we start by setting K to all the attributes of R; we then remove
one attribute at a time and check whether the remaining attributes still form a superkey. Notice, too, that Algorithm 16.2(a) determines only one key out of the possible candidate keys for R; the key returned depends on the order in which attributes are removed from R in step 2.
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» Fundamentals_of_Database_Systems,_6th_Edition
» Characteristics of the Database Approach
» Advantages of Using the DBMS Approach
» A Brief History of Database Applications
» Schemas, Instances, and Database State
» The Three-Schema Architecture
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» Introduction to Triggers in SQL
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» Normal Forms Based on Primary Keys
» General Definitions of Second and Third Normal Forms
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» Inference Rules for Functional Dependencies
» Minimal Sets of Functional Dependencies
» Properties of Relational Decompositions
» Dependency-Preserving Decomposition
» Dependency-Preserving and Nonadditive (Lossless) Join Decomposition into 3NF Schemas
» Problems with NULL Values and Dangling Tuples
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» Implementing the SELECT Operation
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» The ARIES Recovery Algorithm
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» Types of Distributed Database Systems
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» Distributed Databases in Oracle 13
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» Time Representation, Calendars, and Time Dimensions
» Incorporating Time in Relational Databases Using Tuple Versioning
» Incorporating Time in Object-Oriented Databases Using Attribute Versioning
» Temporal Querying Constructs and the TSQL2 Language
» Spatial Database Concepts 24
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» Clausal Form and Horn Clauses
» Datalog Programs and Their Safety
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» Introduction to Information Retrieval
» Types of Queries in IR Systems
» Evaluation Measures of Search Relevance
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