Title: NoSQL-based approach in data warehousing and OLAP cube computation

Authors: Abdelhak Khalil; Mustapha Belaissaoui

Addresses: LEFCG-SIAD Laboratory, Hassan First University, Settat, Morocco ' LEFCG-SIAD Laboratory, Hassan First University, Settat, Morocco

Abstract: Over the last few years, Not only SQL (NoSQL) databases are gaining increasingly significant ground and are considered as the future of data storage. In this paper, we are interested in implementing NoSQL-OLAP systems by defining mapping rules from the multidimensional conceptual level to logical key-value model, and providing a set of online analysis operators. We consider two different approaches in order to implement a big data warehouse within key value stores. The first one uses SQL-like table structure layered on top of the key-value schema, the second one uses a simple key-value pair structure. Then we provide aggregation operators (Map-Reduce Cube and Bit-Encoded Cube) for key value models in order to perform OLAP cube computation. We implemented OLAP operator using Oracle NoSQL database and LevelDB, and we conducted experiments on a fictional data warehouse produced by an existing benchmark that considers NoSQL models. Thus, results showed clearly the performance of OLAP implementations under NoSQL key value stores in terms of efficiency and scalability.

Keywords: OLAP; data warehouse; NoSQL; big data; cube model.

DOI: 10.1504/IJIDS.2023.134794

International Journal of Information and Decision Sciences, 2023 Vol.15 No.4, pp.408 - 430

Received: 27 Jan 2021
Accepted: 29 May 2021
Published online: 13 Nov 2023 *

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