Q::16. The E-R model is expressed in terms of:
(i) Entities
(ii) The relationship among entities
(iii) The attributes of the entities
Then
(A) (i) and (iii)
(B) (i), (ii) and (iii)
(C) (ii) and (iii)
(D) None of the above
Answer: B
Explanation:
The entity-relationship (E-R) data model perceives the real world as consisting of basic objects, called entities, and relationships among these objects. It was developed to facilitate database design by allowing specification of an enterprise schema, which represents the overall logical structure of a database. The E-R data model is one of several semantic data models; the semantic aspect of the model lies in its representation of the meaning of the data. The E-R model is very useful in mapping the meanings and interactions of real-world enterprises onto a conceptual schema. Because of this usefulness, many database-design tools draw on concepts from the E-R model.
Q::17. Specialization is a ............... process.
(A) Top - down (B) Bottom -Up
(C) Both (A) and (B) (D) None of the above
Answer: A
Explanation:
The process of designating subgroupings within an entity set is called specialization.An entity set may include subgroupings of entities that are distinct in some way from other entities in the set. For instance, a subset of entities within an entity set may have attributes that are not shared by all the entities in the entity set. The E-R model provides a means for representing these distinctive entity groupings. Consider an entity set person, with attributes name, street, and city.
The process of designating subgroupings within an entity set is called specialization.An entity set may include subgroupings of entities that are distinct in some way from other entities in the set. For instance, a subset of entities within an entity set may have attributes that are not shared by all the entities in the entity set. The E-R model provides a means for representing these distinctive entity groupings. Consider an entity set person, with attributes name, street, and city.
A person may be further classified as one of the following:
• customer
• employee
Each of these person types is described by a set of attributes that includes all the attributes of entity set person plus possibly additional attributes. For example, customer entities may be described further by the attribute customer-id, whereas employee entities may be described further by the attributes employee-id and salary.The specialization of person allows us to distinguish among persons according to whether they are employees or customers.
Q::18. The completeness constraint has rules:
Q::18. The completeness constraint has rules:
(A) Supertype, Subtype
(B) Total specialization, Partial specialization
(C) Specialization, Generalization
(D) All of the above
Answer: B
Explanation:
The completeness constraint on a generalization or specialization, specifies whether or not an entity in the higher-level entity set must belong to at least one of the lower-level entity sets within the generalization/specialization. This constraint may be one of the following:
• Total generalization or specialization:Each higher-level entity must belong to a lower-level entity set.
• Partial generalization or specialization: Some higher-level entities may not belong to any lower-level entity set.
Partial generalization is the default.We can specify total generalization in an E-R diagram by using a double line to connect the box representing the higher-level entity set to the triangle symbol.
We can see that certain insertion and deletion requirements follow from the constraints that apply to a given generalization or specialization. For instance, when a total completeness constraint is in place, an entity inserted into a higher-level entity set must also be inserted into at least one of the lower-level entity sets. With a condition-defined constraint, all higher-level entities that satisfy the condition must be inserted into that lower-level entity set. Finally, an entity that is deleted from a higher-level entity set also is deleted from all the associated lower-level entity sets to which it belongs.
Q::19. The entity type on which the ................. type depends is called the identifying owner.
(A) Strong entity (B) Relationship
(C) Weak entity (D) E - R
Answer: C
Explanation:
An entity set may not have sufficient attributes to form a primary key. Such an entity set is termed a weak entity set. An entity set that has a primary key is termed a strong entity set. As an illustration, consider the entity set payment, which has the three attributes: {payment-number, payment-date, payment-amount}. Payment numbers are typically sequential numbers, starting from 1, generated separately for each loan. Thus, although each payment entity is distinct, payments for different loans may share the same payment number. Thus, this entity set does not have a primary key; it is a weak
entity set. For a weak entity set to be meaningful, it must be associated with another entity set, called the identifying or owner entity set. Every weak entity must be associated with an identifying entity; that is, the weak entity set is said to be existence dependent on the identifying entity set. The identifying entity set is said to own the weak entity set that it identifies. The relationship associating the weak entity set with the identifying entity set is called the identifying relationship. The identifying relationship is many to one from the weak entity set to the identifying entity set, and the participation of the weak entity set in the relationship is total. In our example, the identifying entity set for payment is loan, and a relationship loan-payment that associates payment entities with their corresponding loan entities is the identifying relationship. Although a weak entity set does not have a primary key, we nevertheless need a means of distinguishing among all those entities in the weak entity set that depend on one particular strong entity. The discriminator of a weak entity set is a set of attributes that allows this distinction to be made. For example, the discriminator of the weak entity set payment is the attribute payment-number, since, for each loan, a payment number uniquely identifies one single payment for that loan. The discriminator of a weak entity set is also called the partial key of the entity set. The primary key of a weak entity set is formed by the primary key of the identifying entity set, plus the weak entity set’s discriminator. In the case of the entity set payment, its primary key is {loan-number, payment-number}, where loan-number is the primary key of the identifying entity set, namely loan, and payment-number distinguishes payment entities within the same loan.
Q::20. Match the following:
(i) 5 NF (a) Transitive dependencies eliminated
(ii) 2 NF (b) Multivalued attribute removed
(iii) 3 NF (c) Contains no partial functional dependencies
(iv) 4 NF (d) Contains no join dependency
(A) i-a, ii-c, iii-b, iv-d
(B) i-d, ii-c, iii-a, iv-b
(C) i-d, ii-c, iii-b, iv-a
(D) i-a, ii-b, iii-c, iv-d
Answer: B
Explanation:
First Normal Form
The first of the normal forms that we study, first normal form, imposes a very basic requirement on relations; unlike the other normal forms, it does not require additional information such as functional dependencies. A domain is atomic if elements of the domain are considered to be indivisible units. We say that a relation schema R is in first normal form (1NF) if the domains of all attributes of R are atomic. A set of names is an example of a nonatomic value. For example, if the schema of a relation employee included an attribute children whose domain elements are sets of names, the schema would not be in first normal form. Composite attributes, such as an attribute address with component attributes street and city, also have non-atomic domains.
Second Normal Form
A table that is in first normal form (1NF) must meet additional criteria if it is to qualify for second normal form. Specifically: a table is in 2NF if it is in 1NF and no non-prime attribute is dependent on any proper subset of any candidate key of the table. A non-prime attribute of a table is an attribute that is not a part of any candidate key of the table.A functional dependency on part of any candidate key is a violation of 2NF. In addition to the primary key, the table may contain other candidate keys; it is necessary to establish that no non-prime attributes have part-key dependencies on any of these candidate keys.
Third Normal Form
A relation schema R is in third normal form (3NF) with respect to a set F of functional
dependencies if, for all functional dependencies in F+ of the form α → β,
where α ⊆ R and β ⊆ R, at least one of the following holds:
• α → β is a trivial functional dependency.
• α is a superkey for R.
• Each attribute A in β − α is contained in a candidate key for R.
Note that the third condition above does not say that a single candidate key should
contain all the attributes in β − α; each attribute A in β − α may be contained in a
different candidate key.
The first two alternatives are the same as the two alternatives in the definition of
BCNF. The third alternative of the 3NF definition seems rather unintuitive, and it is
not obvious why it is useful. It represents, in some sense, a minimal relaxation of the
BCNF conditions that helps ensure that every schema has a dependency-preserving
decomposition into 3NF. Any schema that satisfies BCNF also satisfies 3NF, since each of its
functional dependencies would satisfy one of the first two alternatives. BCNF is therefore
a more restrictive constraint than is 3NF.
The definition of 3NF allows certain functional dependencies that are not allowed
in BCNF. A dependency α → β that satisfies only the third alternative of the 3NF
definition is not allowed in BCNF, but is allowed in 3NF.
For more please refer to Silberschatz−Korth−Sudarshan:Database System Concepts.
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