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ReserarchID
CSTSDE8C6N2
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
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With the continued increase in the volume of data, the volume dimension of big data has become a significant factor in estimating query time. When all other factors are held constant, query time increases as the volume of data increases and vice versa. To enhance query time, several techniques have come out of research efforts in this direction. One of such techniques is factorisation of query predicates. Factorisation has been used as a query optimization technique for the general class of predicates but has been found inapplicable to the subclass of sargable conjunctive equality predicates. Experiments performed exposed a peculiar nature of sargable conjunctive equality predicates based on which insight, the concatenated predicate model was formulated as capable of optimising sargable conjunctive equality predicates. Equations from research results were combined in a way that theorems describing the application and optimality of the concatenated predicate model were derived and proved. The theorems proved that the novel concatenated predicate model transforms a sargable conjunctive equality predicate such that the resultant concatenated predicate is an optimal equivalent of the sargable conjunctive equality predicate from which it is derived. The model enhances conjunctive sargable equality queries making our results capable of application in software applications, majority of whose queries are of the conjunctive query type. The results are equally useful in optimising query time within the context of Big Data where the continuous increase in the volume dimension of data calls for query structures that enhance query time.
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