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arXiv 2602.14263cs.DB
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面向实时环境下的混合量子-经典计算框架用于数据库优化问题

Towards a Hybrid Quantum-Classical Computing Framework for Database Optimization Problems in Real Time Setup

University of Southern California（南加州大学）

Hanwen Liu, Ibrahim Sabek

备注：
ICDE 2026 Data Engineering Future Technologies (42nd IEEE International Conference on Data Engineering)
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AI总结：

本文提出了一种实时量子增强型数据库系统，通过结合量子计算与经典数据库技术，提升大规模数据库优化问题的解决效率和质量。

摘要：

量子计算在解决数据库中的复杂优化问题，如连接顺序和索引选择方面显示出潜力。先前的工作通常将制定的问题直接提交给黑盒量子或量子启发式求解器，期望直接获得一个好的最终解决方案。由于这些求解器的黑盒性质，用户无法对求解过程进行细粒度控制，以平衡准确性和效率，这反过来限制了实时设置中大多数数据库问题的灵活性。此外，这导致处理大规模数据库优化问题的潜力有限。在本文中，我们提出了一种第一个实时量子增强型数据库系统的愿景，使数据库优化问题能够透明地得到解决。我们开发了两种互补的可扩展性策略，以解决大规模挑战、过度复杂性和过度尺寸，这些超过了硬件限制。我们将我们的方法与数据库查询优化器结合，作为初步原型，评估了现实世界的工作负载，实现了比经典查询优化器高14倍的改进。我们还实现了比黑盒量子求解器更好的效率和解决方案质量。

英文摘要：

Quantum computing has shown promise for solving complex optimization problems in databases, such as join ordering and index selection. Prior work often submits formulated problems directly to black-box quantum or quantum-inspired solvers with the expectation of directly obtaining a good final solution. Due to the black-box nature of these solvers, users cannot perform fine-grained control over the solving procedure to balance the accuracy and efficiency, which in turn limits flexibility in real-time settings where most database problems arise. Moreover, it leads to limited potential for handling large-scale database optimization problems. In this paper, we propose a vision for the first real-time quantum-augmented database system, enabling transparent solutions for database optimization problems. We develop two complementary scalability strategies to address large-scale challenges, overcomplexity, and oversizing that exceed hardware limits. We integrate our approach with a database query optimizer as a preliminary prototype, evaluating on real-world workload, achieving up to 14x improvement over the classical query optimizer. We also achieve both better efficiency and solution quality than a black-box quantum solver.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。

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