Prof. Dr. Tilmann Rabl

About the Talk

Data processing systems face a challenge to support increasingly diverse workloads efficiently. At the same time, they are already bloated with internal complexity and it is not clear how new hardware can be supported sustainably.

We propose a layered query compilation framework with open intermediate representations that applies traditional query optimizations as compiler passes. This enables us to support cross-domain optimizations. Furthermore, we introduce a unified abstraction layer based on declarative sub-operators, as a step towards a future-proof execution of diverse workloads on modern hardware. We demonstrate the benefits by implementing the ideas into our compiling query engine, LingoDB. We show that our system can support a variety of workloads and complex operations with relatively low implementation effort, while also providing competitive performance to state-of-the-art systems.


About the Speaker

Jana Giceva conducts research in the areas of data management and computer systems. Her research interests are in systems support for data-intensive applications to enable efficient use of modern and future hardware. Prof. Giceva’s research spans across multiple system sub-fields: data processing layer, compilers, operating systems, and hardware accelerators for data processing. Prof. Giceva got her Ph.D. in Computer Science from ETH Zurich in 2017. From 2017 to 2019 she was a Lecturer in the Department of Computing at Imperial College London. She has been a professor for Database Systems at TUM since 2020.