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arXiv · 2604.01967

Optimizing Relational Queries over Array-Valued Data in Columnar Systems

Maroua Zeblah·Etienne Couritas·Sarah Chlyah·Pierre Genevès·Nils Gesbert·Nabil Layaïda
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Abstract

Modern analytical workloads increasingly combine relational data with array-valued attributes. While columnar database systems efficiently process such workloads, their ability to optimize queries that interleave relational operators with array manipulations remains limited. This paper introduces A3D-RA, an extended relational algebra supporting array-valued attributes, together with a comprehensive framework for algebraic reasoning and optimization. We formalize its data model and semantics, develop a complete set of equivalence-preserving transformation rules capturing pairwise interactions between relational and array operators, and propose a plan enumeration strategy with an optimality guarantee that remains polynomial in all non-join operators. We design A3D-RA as a modular, backend-independent optimization layer that can be instantiated over existing analytical database systems. Experimental results across three high-performance engines on a real-world workload show consistent performance gains enabled by the proposed algebraic optimization layer.

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Maroua Zeblah, Etienne Couritas, Sarah Chlyah, Pierre Genevès, Nils Gesbert, Nabil Layaïda. 2026-04-02. Optimizing Relational Queries over Array-Valued Data in Columnar Systems. https://arxiv.org/abs/2604.01967

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