Bigbench: Towards an industry standard benchmark for big data analytics A Ghazal, T Rabl, M Hu, F Raab, M Poess, A Crolotte, HA Jacobsen Proceedings of the 2013 ACM SIGMOD international conference on Management of …, 2013 | 504 | 2013 |
Solving big data challenges for enterprise application performance management T Rabl, M Sadoghi, HA Jacobsen, S Gómez-Villamor, V Muntés-Mulero, ... arXiv preprint arXiv:1208.4167, 2012 | 373 | 2012 |
Benchmarking distributed stream data processing systems J Karimov, T Rabl, A Katsifodimos, R Samarev, H Heiskanen, V Markl 2018 IEEE 34th international conference on data engineering (ICDE), 1507-1518, 2018 | 300 | 2018 |
Analyzing efficient stream processing on modern hardware S Zeuch, BD Monte, J Karimov, C Lutz, M Renz, J Traub, S Breß, T Rabl, ... Proceedings of the VLDB Endowment 12 (5), 516-530, 2019 | 118 | 2019 |
A data generator for cloud-scale benchmarking T Rabl, M Frank, HM Sergieh, H Kosch Performance Evaluation, Measurement and Characterization of Complex Systems …, 2011 | 109 | 2011 |
Pump up the volume: Processing large data on gpus with fast interconnects C Lutz, S Breß, S Zeuch, T Rabl, V Markl Proceedings of the 2020 ACM SIGMOD International Conference on Management of …, 2020 | 98 | 2020 |
TPC-DI: The First Industry Benchmark for Data Integration M Poess, T Rabl, HA Jacobsen, B Caufield Proceedings of the VLDB Endowment 7 (13), 2014 | 91 | 2014 |
Viper: An efficient hybrid pmem-dram key-value store L Benson, H Makait, T Rabl | 75 | 2021 |
Efficient Window Aggregation with General Stream Slicing. J Traub, PM Grulich, AR Cuéllar, S Breß, A Katsifodimos, T Rabl, V Markl EDBT 19, 97-108, 2019 | 74 | 2019 |
Generating custom code for efficient query execution on heterogeneous processors S Breß, B Köcher, H Funke, S Zeuch, T Rabl, V Markl The VLDB Journal 27, 797-822, 2018 | 71 | 2018 |
Benchmarking big data systems and the bigdata top100 list C Baru, M Bhandarkar, R Nambiar, M Poess, T Rabl Big Data 1 (1), 60-64, 2013 | 69 | 2013 |
Setting the direction for big data benchmark standards C Baru, M Bhandarkar, R Nambiar, M Poess, T Rabl Selected Topics in Performance Evaluation and Benchmarking: 4th TPC …, 2013 | 64 | 2013 |
Rhino: Efficient management of very large distributed state for stream processing engines B Del Monte, S Zeuch, T Rabl, V Markl Proceedings of the 2020 ACM SIGMOD International Conference on Management of …, 2020 | 63 | 2020 |
Quantifying TPC-H choke points and their optimizations M Dreseler, M Boissier, T Rabl, M Uflacker Proceedings of the VLDB Endowment 13 (8), 1206-1220, 2020 | 63 | 2020 |
Maximizing persistent memory bandwidth utilization for OLAP workloads B Daase, LJ Bollmeier, L Benson, T Rabl Proceedings of the 2021 International Conference on Management of Data, 339-351, 2021 | 61 | 2021 |
An intermediate representation for optimizing machine learning pipelines A Kunft, A Katsifodimos, S Schelter, S Breß, T Rabl, V Markl Proceedings of the VLDB Endowment 12 (11), 1553-1567, 2019 | 57 | 2019 |
Scotty: Efficient window aggregation for out-of-order stream processing J Traub, PM Grulich, AR Cuellar, S Breß, A Katsifodimos, T Rabl, V Markl 2018 IEEE 34th International Conference on Data Engineering (ICDE), 1300-1303, 2018 | 57 | 2018 |
Grizzly: Efficient stream processing through adaptive query compilation PM Grulich, B Sebastian, S Zeuch, J Traub, J Bleichert, Z Chen, T Rabl, ... Proceedings of the 2020 ACM SIGMOD International Conference on Management of …, 2020 | 54 | 2020 |
Analysis of TPC-DS: the first standard benchmark for SQL-based big data systems M Poess, T Rabl, HA Jacobsen Proceedings of the 2017 Symposium on Cloud Computing, 573-585, 2017 | 43 | 2017 |
Optimized on-demand data streaming from sensor nodes J Traub, S Breß, T Rabl, A Katsifodimos, V Markl Proceedings of the 2017 Symposium on Cloud Computing, 586-597, 2017 | 42 | 2017 |