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A Relational Matrix Algebra and its Implementation in a Column Store

Dolmatova, Oksana; Augsten, Nikolaus; Böhlen, Michael Hanspeter (2020). A Relational Matrix Algebra and its Implementation in a Column Store. ArXiv.org 05517, Cornell University.

Abstract

Analytical queries often require a mixture of relational and linear algebra operations applied to the same data. This poses a challenge to analytic systems that must bridge the gap between relations and matrices. Previous work has mainly strived to fix the problem at the implementation level. This paper proposes a principled solution at the logical level. We introduce the relational matrix algebra (RMA), which seamlessly integrates linear algebra operations into the relational model and eliminates the dichotomy between matrices and relations. RMA is closed: All our relational matrix operations are performed on relations and result in relations; no additional data structure is required. Our implementation in MonetDB shows the feasibility of our approach, and empirical evaluations suggest that in-database analytics performs well for mixed workloads.

Additional indexing

Item Type:Working Paper
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Scope:Discipline-based scholarship (basic research)
Language:English
Date:2020
Deposited On:01 Mar 2021 08:31
Last Modified:27 May 2024 15:23
Series Name:ArXiv.org
ISSN:2331-8422
OA Status:Green
Free access at:Official URL. An embargo period may apply.
Official URL:https://arxiv.org/pdf/2004.05517.pdf
Related URLs:https://arxiv.org/abs/2004.05517
Other Identification Number:merlin-id:20725
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