Building a Document-Oriented Warehouse Using NoSQL

Ines Ben Messaoud, Abdulrahman A. Alshdadi, Jamel Feki

Source Title: International Journal of Operations Research and Information Systems (IJORIS)12(2)

ISSN: 1947-9328|EISSN: 1947-9336|EISBN13: 9781799861218|DOI: 10.4018/IJORIS.20210401.oa3

MLA

Ben Messaoud, Ines, et al. "Building a Document-Oriented Warehouse Using NoSQL." IJORIS vol.12, no.2 2021: pp.33-54. http://doi.org/10.4018/IJORIS.20210401.oa3

APA

Ben Messaoud, I., Alshdadi, A. A., & Feki, J. (2021). Building a Document-Oriented Warehouse Using NoSQL. International Journal of Operations Research and Information Systems (IJORIS), 12(2), 33-54. http://doi.org/10.4018/IJORIS.20210401.oa3

Chicago

Ben Messaoud, Ines, Abdulrahman A. Alshdadi, and Jamel Feki. "Building a Document-Oriented Warehouse Using NoSQL," International Journal of Operations Research and Information Systems (IJORIS) 12, no.2: 33-54. http://doi.org/10.4018/IJORIS.20210401.oa3

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Abstract

The traditional data warehousing approaches should adapt to take into consideration novel needs and data structures. In this context, NoSQL technology is progressively gaining a place in the research and industry domains. This paper proposes an approach for building a NoSQL document-oriented warehouse (DocW). This approach has two methods, namely 1) document warehouse builder and 2) NoSQL-Converter. The first method generates the DocW schema as a galaxy model whereas the second one translates the generated galaxy into a document-oriented NoSQL model. This relies on two types of rules: structure and hierarchical rules. Furthermore, in order to help understanding the textual results of analytical queries on the NoSQL-DocW, the authors define two semantic operators S-Drill-Up and S-Drill-Down to aggregate/expand the terms of query. The implementation of our proposals uses MangoDB and Talend. The experiment uses the medical collection Clef-2007 and two metrics called write request latency and read request latency to evaluate respectively the loading time and the response time to queries.