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cs.DB2026

Practical MCTS-based Query Optimization: A Reproducibility Study and new MCTS algorithm for complex queries

Vladimir Burlakov, Alena Rybakina, Sergey Kudashev +4

Monte Carlo Tree Search (MCTS) has been proposed as a transformative approach to join-order optimization in database query processing, with recent frameworks such as AlphaJoin and…

cs.DB2025

Learning-Augmented Online Caching: New Upper Bounds

Daniel Skachkov, Denis Ponomaryov, Yuri Dorn +1

We address the problem of learning-augmented online caching in the scenario when each request is accompanied by a prediction of the next occurrence of the requested page. We improv…

cs.DB2025

Training-Free Query Optimization via LLM-Based Plan Similarity

Nikita Vasilenko, Alexander Demin, Vladimir Boorlakov

Large language model (LLM) embeddings offer a promising new avenue for database query optimization. In this paper, we explore how pre-trained execution plan embeddings can guide SQ…

cs.DB2024

Adaptive Cost Model for Query Optimization

Nikita Vasilenko, Alexander Demin, Denis Ponomaryov

The principal component of conventional database query optimizers is a cost model that is used to estimate expected performance of query plans. The accuracy of the cost model has d…

cs.DB2024

EEvA: Fast Expert-Based Algorithms for Buffer Page Replacement

Alexander Demin, Yuriy Dorn, Aleksandr Katrutsa +4

Optimal page replacement is an important problem in efficient buffer management. The range of replacement strategies known in the literature varies from simple but efficient FIFO-b…