9 citations · 12 across the 4 of their papers we have counts for
3 papers · 1 filter
Magpie: Automatically Tuning Static Parameters for Distributed File Systems using Deep Reinforcement Learning
Houkun Zhu, Dominik Scheinert, Lauritz Thamsen +2
Distributed file systems are widely used nowadays, yet using their default configurations is often not optimal. At the same time, tuning configuration parameters is typically chall…
Enel: Context-Aware Dynamic Scaling of Distributed Dataflow Jobs using Graph Propagation
Dominik Scheinert, Houkun Zhu, Lauritz Thamsen +4
Distributed dataflow systems like Spark and Flink enable the use of clusters for scalable data analytics. While runtime prediction models can be used to initially select appropriat…
Bellamy: Reusing Performance Models for Distributed Dataflow Jobs Across Contexts
Dominik Scheinert, Lauritz Thamsen, Houkun Zhu +4
Distributed dataflow systems enable the use of clusters for scalable data analytics. However, selecting appropriate cluster resources for a processing job is often not straightforw…