Title: Rethinking Database Optimization for Modern Workloads
Speaker: Audrey Cheng
Advisors: Ion Stoica and Natacha Crooks
Date: Friday, May 8th
Time: 10:00-11:00 AM PT
This is a hybrid event held in person and virtually over Zoom.
Location (In-person): Soda 465H (Sky Lab)
Abstract: Data systems face unprecedented scalability demands as modern applications, especially AI workloads, evolve rapidly. These shifts make it increasingly difficult to maintain both performance and correctness, which are the core properties that databases must provide. In this talk, I discuss how to rethink database optimization by exploiting workload semantics in modern large-scale applications and how we can scale these efforts by automating this optimization with AI. First, I will present my work on reducing data contention, which remains a crucial performance bottleneck, by leveraging contention patterns in modern workloads. My research addresses this challenge via transaction scheduling: instead of resolving conflicts after they occur, I focus on preventing them by reordering transactions to avoid conflicts before execution. I will then discuss how we build on these results by leveraging AI-driven methods to enable the rapid exploration and generation of optimization methods, with the broader goal of automating performance optimization in data systems.