Title: Anomaly free search using multi table entity attribute value data model

Authors: Shivani Batra; Shelly Sachdeva

Addresses: Department of Computer Science and Engineering, Jaypee Institute of Information Technology University, Sector-128, Noida, India ' Department of Computer Science and Engineering, Jaypee Institute of Information Technology University, Sector-128, Noida, India

Abstract: In this paper, the authors are proposing a principled extension of dynamic tables (DT). It is termed multi table entity attribute value (MTEAV) model which offers a search efficient avenue for storing database. The authors present precise semantics of MTEAV and demonstrate the following: 1) MTEAV possesses consistency and availability; 2) MTEAV outperforms other existing models (entity attribute value model, dynamic tables, optimised entity attribute value and optimised column oriented model) under various query scenarios and varying datasets size; 3) MTEAV retains flavour of EAV in terms of handling sparseness and self-adapting schema changing capability. To heighten adaptability of MTEAV, authors implement a translation layer over existing SQL engine in a non-intrusive way. Translation layer transforms conventional SQL query (as per horizontal row representation) to a new SQL query (as per MTEAV structure) to maintain user friendliness. Translation layer makes user feel as if he/she is interacting with the conventional horizontal row approach. The authors also critically analyse maximum percentage of non-null density appropriate for choosing MTEAV as a storage option.

Keywords: database; dynamic tables; entity attribute value model; optimised entity attribute value; OEAV; optimised column oriented model; OCOM; search efficiency; storage efficiency.

DOI: 10.1504/IJCSE.2018.093777

International Journal of Computational Science and Engineering, 2018 Vol.16 No.4, pp.363 - 377

Received: 04 Mar 2016
Accepted: 17 Jul 2016
Published online: 06 Aug 2018 *

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