DeepO: A Learned Query Optimizer

Abstract

Query optimization is crucial for the query performance of database systems. Despite decades of efforts from both research and industrial communities, query optimization remains one of the most challenging problems. Thanks to the advances in artificial intelligence, data-driven and learning-based techniques are seeing traction in database research recently. However, most former learning-based works perform less practical because they are evasive about the interaction between learning components and database systems. In this demonstration, we introduce DeepO, a novel deep-learning-based query optimizer that offers high-quality and fine-grained query optimization efficiently and practically. We implement DeepO and incorporate it into PostgreSQL, and we also provide a web user interface, where users can carry out the optimization operations interactively and evaluate the optimization performance. Preliminary results show that DeepO outperforms the baseline PostgreSQL optimizer.