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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. In: ACM SIGMOD International Conference on Management of Data, Portland, OR, USA, 14 June 2020 - 19 June 2020. ACM, 2573-2587.

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:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Scopus Subject Areas:Physical Sciences > Software
Physical Sciences > Information Systems
Scope:Discipline-based scholarship (basic research)
Language:English
Event End Date:19 June 2020
Deposited On:01 Mar 2021 08:29
Last Modified:06 Mar 2024 14:34
Publisher:ACM
OA Status:Green
Publisher DOI:https://doi.org/10.1145/3318464.3389747
Other Identification Number:merlin-id:20727
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