Query Compilation Without Regrets
Philipp M. Grulich, Aljoscha P. Lepping, Dwi P. A. Nugroho, Varun Pandey, Bonaventura Del Monte, Steffen Zeuch, Volker Markl
Abstract
Engineering high-performance query execution engines is a challenging task. Query compilation provides excellent performance, but at the same time introduces significant system complexity, as it makes the engine hard to build, debug, and maintain. To overcome this complexity, we propose Nautilus, a framework that combines the ease of use of query interpretation and the performance of query compilation. On the one hand, Nautilus provides an interpretation-based operator interface that enables engineers to implement operators using imperative C++ code to ensure a familiar developer experience. On the other hand, Nautilus mitigates the performance drawbacks of interpretation by introducing a novel trace-based, multi-backend JIT compiler that translates operators into efficient code. As a result, Nautilus bridges the gap between compilation and interpretation and provides the best of both worlds, achieving high performance without sacrificing the productivity of engineers.
Ask about this paper
Ask your agent about it.
Lune has read the top-tier papers around this one, so every answer names the papers it rests on.
Your agent calls
Lunesearch_papers
Free to start. No credit card required.
Terminal
Install the CLIlune papers get abeff8c1-0aaa-45a5-be9d-1c9fd0e03769Related papers
- Incremental Fusion: Unifying Compiled and Vectorized Query ExecutionBenjamin Wagner, André Kohn, Peter Boncz, Viktor LeisICDE 2024 · 3 citations
- Charting the Design Space of Query Execution using VOILATim Gubner, Peter BonczVLDB 2021 · 17 citations
- Improving Execution Efficiency of Just-in-time Compilation based Query Processing on GPUsJohns Paul, Bingsheng He, Shengliang Lu, Chiew Tong LauVLDB 2021 · 28 citations
- Declarative Sub-Operators for Universal Data ProcessingMichael Jungmair, Jana GicevaVLDB 2023 · 17 citations
- A Compiler for Fused Relational Operations on MultisetsJames Dong, Fredrik KjolstadPLDI 2026
