报告题目：Proteus: Autonomous Adaptive Storage for Mixed Workloads

论文出处：SIGMOD 2022

作者：Michael Abebe, Horatiu Lazu, Khuzaima Daudjee

单位：Cheriton School of Computer Science, University of Waterloo

报告人：张芊

报告时间：2022年11月29日 下午 13:00

报告地点：贵州大学北校区博学楼624室

报告内容摘要：Enterprises use distributed database systems to meet the demands of mixed or hybrid transaction/analytical processing (HTAP) workloads that contain both transactional (OLTP) and analytical (OLAP) requests. Distributed HTAP systems typically maintain a complete copy of data in row-oriented storage format that is well-suited for OLTP workloads and a second complete copy in column-oriented storage format optimized for OLAP workloads. Maintaining these data copies consumes significant storage space and system resources. Conversely, if a system stores data in a single format, OLTP or OLAP workload performance suffers. This paper presents Proteus, a distributed HTAP database system that adaptively and autonomously selects and changes its storage layout to optimize for mixed workloads. Proteus generates physical execution plans that utilize storage-aware operators for efficient transaction execution. Using comprehensive HTAP workloads and state-of-the-art comparison systems, we demonstrate that Proteus delivers superior HTAP performance while providing OLTP and OLAP performance on par with designs specialized for either type of workload.