Anomaly free search using multi table entity attribute value data model. (2018)

• Record Type: Journal Article
• Authors: Batra, Shivani; Sachdeva, Shelly
• Is Part Of: International journal of computational science and engineering. Volume 16:Number 4(2018)
• Page Start: 363
• Page End: 377
• Publication Date: 2018
• Subjects: database -- dynamic tables -- entity attribute value model -- optimised entity attribute value -- OEAV -- optimised column oriented model -- OCOM -- search efficiency -- storage efficiency; Computer science -- Mathematics -- Periodicals; Computer simulation -- Mathematical aspects -- Periodicals; Computational intelligence -- Periodicals; 004.015105
• Languages: English
• ISSNs: 1742-7185

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.