Carsten Binnig

Boosting scalable data analytics with modern programmable networks

2018

Data center networks lie at the core of distributed data analytics frameworks running in large scale environments. Recent research seek to improve the system performance by optimizing the end-host network usage, e.g., optimally use RDMA …

Progressive Data Science: Potential and Challenges

2018 · arXiv (Cornell University)

Data science requires time-consuming iterative manual activities. In particular, activities such as data selection, preprocessing, transformation, and mining, highly depend on iterative trial-and-error processes that could be sped-up significantly by providing quick feedback on the …

P4DB - The Case for In-Network OLTP

2022 · Proceedings of the 2022 International Conference on Management of Data

In this paper we present a new approach for distributed DBMSs called P4DB, that uses a programmable switch to accelerate OLTP workloads. The main idea of P4DB is that it implements a transaction processing engine …

Zero-shot cost models for out-of-the-box learned cost prediction

2022 · Proceedings of the VLDB Endowment

In this paper, we introduce zero-shot cost models, which enable learned cost estimation that generalizes to unseen databases. In contrast to state-of-the-art workload-driven approaches, which require to execute a large set of training queries on …

Steered Training Data Generation for Learned Semantic Type Detection

2023 · Proceedings of the ACM on Management of Data

In this paper, we introduce STEER to adapt learned semantic type extraction approaches to a new, unseen data lake. STEER provides a data programming framework for semantic labeling which is used to generate new labeled …

COSTREAM: Learned Cost Models for Operator Placement in Edge-Cloud Environments

2024 · arXiv (Cornell University)

In this work, we present COSTREAM, a novel learned cost model for Distributed Stream Processing Systems that provides accurate predictions of the execution costs of a streaming query in an edge-cloud environment. The cost model …

Zero-sided RDMA: Network-driven Data Shuffling for Disaggregated Heterogeneous Cloud DBMSs

2024 · Proceedings of the ACM on Management of Data

In this paper, we present a novel communication scheme called zero-sided RDMA, enabling data exchange as a native network service using a programmable switch. In contrast to one- or two-sided RDMA, in zero-sided RDMA, neither …

Opening the Black-Box: Explaining Learned Cost Models for Databases

2025 · Proceedings of the VLDB Endowment

Learned Cost Model s (LCMs) have shown superior results over traditional database cost models as they can significantly improve the accuracy of cost predictions. However, LCMs still fail for some query plans, as prediction errors …