Grizzly: Efficient Stream Processing Through Adaptive Query Compilation
Summary: Adaptive, JIT query compilation enables Grizzly to reoptimize SPEs at runtime. Lightweight statistics and task-based parallelism extend query compilation to streams, enabling dynamic adaptation and order-of-magnitude throughput over state-of-the-art SPEs. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Philipp M. Grulich (Technical University of Berlin)
- 2. Sebastian Breß (Technical University of Berlin)
- 3. Steffen Zeuch (German National Research Center for Information Technology; Technical University of Berlin)
- 4. Jonas Traub (Technical University of Berlin)
- 5. Janis von Bleichert (Technical University of Berlin)
- 6. Zongxiong Chen (German National Research Center for Information Technology)
- 7. Tilmann Rabl (Hasso Plattner Institute)
- 8. Volker Markl (German National Research Center for Information Technology; Technical University of Berlin)
BibTeX Citation
@inproceedings{grulich_sigmod20,
title = {{Grizzly: Efficient Stream Processing Through Adaptive Query Compilation}},
author = {Grulich, Philipp M. and Breß, Sebastian and Zeuch, Steffen and Traub, Jonas and von Bleichert, Janis and Chen, Zongxiong and Rabl, Tilmann and Markl, Volker},
series = {{SIGMOD} '20},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3318464.3389739},
url = {https://dl.acm.org/doi/10.1145/3318464.3389739},
year = {2020}
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