Query optimisation in real-time data warehouses. (15th January 2020)

• Record Type: Journal Article
• Authors: Hamdi, Issam; Bouazizi, Emna; Feki, Jamel
• Is Part Of: International journal of intelligent information and database systems. Volume 12:Number 4(2019)
• Page Start: 245
• Page End: 278
• Publication Date: 2020-01-15
• Subjects: real-time data warehouse -- RTDW -- real-time transactions -- materialised views -- data partitioning -- extract-transform-load -- ETL; Database management -- Computer programs -- Periodicals; Information retrieval -- Computer programs -- Periodicals; Information storage and retrieval systems -- Computer programs -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Intelligent agents (Computer software) -- Periodicals; 006.33
• Languages: English
• ISSNs: 1751-5858

Abstract

A real-time data warehouse (RTDW) allows decision makers to analyse fresh data as fast as possible in order to support real-time decision processes. In this paper, we focus on optimisation techniques to speed up query processing; in particular, we propose a dynamic selection of materialised views algorithm (DynaSeV) which selects views from results of incoming queries. Secondly, we suggest a new update policy to dynamically maintain materialised views. In addition, we propose a novel data partitioning approach for RTDW, called 2LPA-RTDW (Two-Level data Partitioning Approach for RTDW) by allowing unbalance of data amount in each partition. Then, we present our architecture called DETL-(m, k)-firm-RTDW architecture (decentralised extract-transform-load approach based on (m, k)-Firm constraints for RTDW) which deals with diversity and disparities in data source systems to reduce the time for ETL. Finally, we evaluate our contributions using the TPC-DS (TPC, 2014) benchmark; the preliminary results are quite promising.