24 citations · 127 across the 21 of their papers we have counts for
7 papers · 1 filter
On the Potential of Execution Traces for Batch Processing Workload Optimization in Public Clouds
Dominik Scheinert, Alireza Alamgiralem, Jonathan Bader +3
With the growing amount of data, data processing workloads and the management of their resource usage becomes increasingly important. Since managing a dedicated infrastructure is i…
Training Data Reduction for Performance Models of Data Analytics Jobs in the Cloud
Jonathan Will, Onur Arslan, Jonathan Bader +2
Distributed dataflow systems like Apache Flink and Apache Spark simplify processing large amounts of data on clusters in a data-parallel manner. However, choosing suitable cluster…
Tarema: Adaptive Resource Allocation for Scalable Scientific Workflows in Heterogeneous Clusters
Jonathan Bader, Lauritz Thamsen, Svetlana Kulagina +3
Scientific workflow management systems like Nextflow support large-scale data analysis by abstracting away the details of scientific workflows. In these systems, workflows consist…
Dependable IoT Data Stream Processing for Monitoring and Control of Urban Infrastructures
Morgan K. Geldenhuys, Jonathan Will, Benjamin J. J. Pfister +3
The Internet of Things describes a network of physical devices interacting and producing vast streams of sensor data. At present there are a number of general challenges which exis…
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…
C3O: Collaborative Cluster Configuration Optimization for Distributed Data Processing in Public Clouds
Jonathan Will, Lauritz Thamsen, Dominik Scheinert +2
Distributed dataflow systems enable data-parallel processing of large datasets on clusters. Public cloud providers offer a large variety and quantity of resources that can be used…