Hash-processing of universal quantification-like queries dealing with requirements and prohibitions
Autor: | Khaled Walid Hidouci, Noussaiba Benadjimi |
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Rok vydání: | 2021 |
Předmět: |
Universal quantification
Theoretical computer science Operator (computer programming) Computer science Modeling and Simulation Hash function Parallelism (grammar) Skew Relevance (information retrieval) Performance improvement Computer Science Applications Management Information Systems Ranking (information retrieval) |
Zdroj: | International Journal of Data Mining, Modelling and Management. 13:192 |
ISSN: | 1759-1171 1759-1163 |
DOI: | 10.1504/ijdmmm.2021.10035120 |
Popis: | This paper is focused on flexible universal quantification-like queries handling simultaneously positive and negative preferences (requirements or prohibitions). We emphasise the performance improvement of the considered operator by proposing new variants of the classical hash-division algorithm. The issue of answers ranking is also dealt with. We target in our work the in memory databases systems (also called main-memory database systems) with a very large volume of data. In these systems, all the data is primarily stored in the RAM of a computer. We have introduced a parallel implementation of the operator that takes into account the data skew issue. Our empirical analysis for both sequential and parallel versions shows the relevance of our approach. They demonstrate that the new processing of the mixed operator in a main-memory database achieves better performance compared to the conventional ones, and becomes faster through parallelism. |
Databáze: | OpenAIRE |
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