Optimising Sargable Conjunctive Predicate Queries in the Context of Big Data

Authors

  • Veronica V.N. Akwukwuma,

  • Patrick O. Obilikwu

Keywords:

concatenated predicate, conjunctive equality predicate, sargable predicate, query, factorisation, database, software applications

Abstract

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.

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How to Cite

Veronica V.N. Akwukwuma, & Patrick O. Obilikwu. (2022). Optimising Sargable Conjunctive Predicate Queries in the Context of Big Data. Global Journal of Computer Science and Technology, 22(C1), 19–32. Retrieved from https://computerresearch.org/index.php/computer/article/view/101434

Optimising Sargable Conjunctive Predicate Queries in the Context of Big Data

Published

2022-07-16