3.1. Distinguish between functional reliance and multivalued reliance. Ans. Functional reliance A functional reliance, denoted by X Y, between two sets of attributes X and Y that are subsets of R specifies a constraint on the possible tuples that can form a relation, state r orR. Multivalued reliance( MVD) MVD occurs when two or further independent multivalued data about the same trait do within the same relation. MVD is denoted by X Y specified on relation schema R, where X and Y are both subsets ofR. . When are two sets of functional dependences said to be original? Ans. Two sets F1 and F2 of FDs are said to be original, if F1 = F2 that is, every FD in F1 is inferred by F2 and every FD in F2 is inferred by F1. . Define the following Full functional reliance Partial reliance Ans. a. A reliance X Y in a relational schema R is said to be a completely functionally reliance if there’s no A, where A is the proper subset of X similar that A Y. It implies junking of any trait from X means that the reliance doesn’t hold any further. b. A reliance X Y in a relational schema R is said to be a partial reliance if there’s any trait A where A is the proper subset of X similar that A Y. The trait Y is said to be incompletely dependent on the traitX. . What’s transitive reliance? Name the normal form which is grounded on the conception of transitive reliance. Ans. An trait Y of a relational schema R is said to be transitively dependent on trait X( X Y), if there’s a set of attributes A that is neither a seeker key nor a subset of any key of R and both X A and A Y hold. The normal form that’s grounded on transitive reliance is 3NF. . What’s normalization? Ans. Normalization is the process of organizing a database to reduce redundancy and ameliorate data integrity. . Define 2NF. Ans. A relation R is in alternate normal form( 2NF) if and only if it’s in 1NF and everynon-key trait is completely dependent on the primary key. A relation R is in 2NF if everynon-prime trait of R is completely functionally dependent on each relation key. . Why is BCNF considered simpler as well as stronger than 3NF? Ans. BCNF is the simpler form of 3NF as it makes unequivocal reference to neither the first and alternate normal forms nor to the conception of transitive dependence. In addition, it’s stronger than 3NF as every relation that’s in BCNF is also in 3NF but the vice versa isn’t inescapably true. . Define lossless join corruption. Ans. Let R be a relational schema and let F be a set of functional dependences onR. Let R1 and R2 form a corruption ofR. This corruption is a lossless join corruption of R if at least one of the following functionl dependences is in F. R1 R2 R1 ii. R1 R2 R2 . What do you understand by the check of a set of trait? Ans. The check of a set of attributes implies a certain subset of the check that consists of all FDs with a specified set of Z attributes as determinant. . What are the uses of the check algorithm? Ans. Besides calculating the subset of check, the check algorithm has other uses that are as follows To determine if a particular FD, say X Y is in the check F of F, without calculating the check F. This can be done by simply computing X by using the check algorithm and also checking if Y X. ii. To test if a set of attributes A is a superkey of R. This can be done by computing A and checking if A contains all the attributes ofR. . Describe the reliance preservation property. Ans. It’s a property that’s asked while corruption, that is, no FD of the original relation is lost. The reliance preservation property ensures that each FD represented by the original relation is executed by examining and single relation redounded from corruption or can be inferred from FDs in some perished
relation. . What are the colorful anomalies associated with RDBMS? OR What are the different types of anomalies associated with database? Ans. In RDBMS, certain update anomalies can arise, which are as follows Insertion anomaly It leads to a situation in which certain information can not be fitted in a relation unless some other information is stored. ii. omission anomaly It leads to a situation in which omission of data representing certain information results in losing data representing some other information that’s associated with it. iii. revision anomaly It leads to a situation in which repeated data changed at one place results in inconsistency unless the same data are also changed at other places. . Explain normalization. What’s normal form? Ans. Normalization ReferQ.3.5, runner SQ – 11A, Unit- 3, Two Marks Questions. Normal form Normal forms are grounded on the functional dependences among the attributes of a relation. These forms are simply stages of database design, with each stage applying further strict rules to the types of information which can be stored in a table. . Why do we homogenize database? Ans. We homogenize database 1. To avoid redundancy 2. To avoid update/ delete anomalies . Are normal forms alone sufficient as a condition for a good schema design? Explain. Ans. No, normal forms alone aren’t sufficient as a condition for a good schema design. There are two fresh parcels, videlicet lossless join property and reliance preservation property that must hold on corruption to qualify it as a good design.
