Publications

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Pratyush Agnihotri; Carsten Binnig; Manisha Luthra
Learning What Matters: Automated Feature Selection for Learned Performance Models in Parallel Stream Processing
In: VLDB 2025 Workshop (Hrsg.). Proceedings of the VLDB Endowment. International Conference on Very Large Data Bases (VLDB-2025), 6th Applied AI for Database Systems and Applications, located at AIDB-2025, September 1-5, London, United Kingdom, VLDB Endowment, 9/2025.
Roman Heinrich; Oleksandr Havrylov; Manisha Luthra; Johannes Wehrstein; Carsten Binnig
Opening The Black-Box: Explaining Learned Cost Models For Databases
In: Proceedings of the VLDB Endowment (PVLDB), Vol. 18, No. 12, Pages 5255-5258, arXiv, 2025.
Roman Heinrich; Manisha Luthra; Johannes Wehrstein; Harald Kornmayer; Carsten Binnig
How Good are Learned Cost Models, Really? Insights from Query Optimization Tasks
In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2502.01229, Pages 1-27, arXiv, 2025.
Pratyush Agnihotri; Boris Koldehofe; Roman Heinrich; Carsten Binnig; Manisha Luthra
PDSP-Bench: A Benchmarking System for Parallel and Distributed Stream Processing
In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2504.10704, Pages 1-22, arXiv, 2025.
Roman Heinrich; Oleksandr Havrylov; Manisha Luthra; Johannes Wehrstein; Carsten Binnig
Opening The Black-Box: Explaining Learned Cost Models For Databases
In: Computing Research Repository eprint Journal (CoRR), Vol. abs/2507.14495, Pages 1-4, arXiv, 2025.
Roman Heinrich; Carsten Binnig; Harald Kornmayer; Manisha Luthra
Costream: Learned Cost Model for Operator Placement in Edge-Cloud Environments
In: 40th IEEE International Conference on Data Engineering (ICDE 2024) (recently accepted). IEEE International Conference on Data Engineering (ICDE-2024), May 13-17, Netherlands, Pages 1-14, IEEE, 2024.
Wang Yue; Rafael Moczalla; Manisha Luthra; Tilmann Rabl
Deco: Fast and Accurate Decentralized Aggregation of Count-Based Windows in Large-Scale IoT Applications
In: Proceedings 27th International Conference on Extending Database Technology ( EDBT 2024 ). International Conference on Extending Database Technology (EDBT-2024), 27th International Conference on Extending Database Technology, March 25-28, Italy, ISBN 978-3-89318-091-2, OpenProceeedings.org, 2024.
Pratyush Agnihotri; Paul Stiegele; Roman Heinrich; Boris Koldehofe; Carsten Binnig; Manisha Luthra
ZeroTune: Learned Zero-Shot Parallelism Tuning for Distributed Stream Processing
In: 40th IEEE International Conference on Data Engineering (ICDE 2024). IEEE International Conference on Data Engineering (ICDE-2024), Pages 1-14, IEEE, 2024.
Pratyush Agnihotri; Boris Koldehofe; Roman Heinrich; Carsten Binnig; Manisha Luthra
PDSP-Bench: A Benchmarking System for Parallel and Distributed Stream Processing
In: 16th TPC Technology Conference on Performance Evaluation & Benchmarking. TPC Technology Conference (TPCTC-2024), 50th International Conference on Very Large Databases, located at TPCTC, August 26-31, Guangzhou, China, Springer, 2024.
Mikhail Fomichev; Manisha Luthra; Maik Benndorf; Pratyush Agnihotri
No One Size (PPM) Fits All: Towards Privacy in Stream Processing Systems
In: Proceedings of the 17th ACM International Conference on Distributed and Event-Based Systems. ACM International Conference on Distributed and Event-Based Systems (DEBS-2023), Europe, Switzerland, DEBS '23, ISBN 9798400701221, Association for Computing Machinery, 2023.