Abstract

Optimal join order sequence significantly impacts query execution performance. Because the search space grows exponentially with the number of relations involved in the queries, DP-based approaches can compute optimal plans only for queries with a small number of relations. Many heuristic methods trade off solution quality for computational efficiency. Quantum computing excels at solving combinatorial optimization problems such as join order optimization. However, existing quantum-related methods either focus solely on left-deep join trees—thus narrowing the problem scope—or support bushy join trees but are constrained by quantum hardware and cannot scale to large queries. Importantly, neither branch has been integrated into an actual database system. In this paper, we present a hybrid quantum–classical optimization approach for bushy join trees, integrated within a real database system …

Metadata

publication

Proceedings of the 2nd Workshop on Quantum Computing and Quantum-Inspired …, 2025

year

2025

publication date

2025/6/22

authors

Hanwen Liu, Abhishek Kumar, Federico Spedalieri, Ibrahim Sabek

link

https://dl.acm.org/doi/abs/10.1145/3736393.3736695

resource_link

https://dl.acm.org/doi/pdf/10.1145/3736393.3736695

book

Proceedings of the 2nd Workshop on Quantum Computing and Quantum-Inspired Technology for Data-Intensive Systems and Applications

pages

20-24