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| Type | Conference or Workshop Paper |
| Scope | Discipline-based scholarship |
| Published in Proceedings | Yes |
| Title | A Relational Matrix Algebra and its Implementation in a Column Store |
| Organization Unit | |
| Authors |
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| Presentation Type | paper |
| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
| Language |
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| Page Range | 2573 - 2587 |
| Event Title | ACM SIGMOD International Conference on Management of Data |
| Event Type | conference |
| Event Location | Portland, OR, USA |
| Event Start Date | June 14 - 2020 |
| Event End Date | June 19 - 2020 |
| Publisher | ACM |
| Abstract Text | 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. |
| Digital Object Identifier | 10.1145/3318464.3389747 |
| Other Identification Number | merlin-id:20727 |
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