Hasso-Plattner-Institut
Prof. Dr. Tilmann Rabl
  
 

Publications

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Publications of the years 2020, 2019, 2018, 20172016, 2015, 2014, 2013, 2012, 2011, 2010, 2009, 2008, 2007

Efficient Window Aggregation with General Stream Slicing

Traub, Jonas; Grulich, Philipp M.; Cuellar, Alejandro Rodriguez; Breß, Sebastian; Katsifodimos, Asterios; Rabl, Tilmann; Markl, Volker in Advances in Database Technology - 22nd International Conference on Extending Database Technology, EDBT 2019, Lisbon, Portugal, March 26-29, 2019 Seite 97-108 . 2019 .

Window aggregation is a core operation in data stream processing. Existing aggregation techniques focus on reducing latency, eliminating redundant computations, and minimizing memory usage. However, each technique operates under different assumptions with respect to workload characteristics such as properties of ag-gregation functions (e.g., invertible, associative), window types (e.g., sliding, sessions), windowing measures (e.g., time-or count-based), and stream (dis)order. Violating the assumptions of a technique can deem it unusable or drastically reduce its performance. In this paper, we present the first general stream slicing technique for window aggregation. General stream slicing automatically adapts to workload characteristics to improve performance without sacrificing its general applicability. As a prerequisite, we identify workload characteristics which affect the performance and applicability of aggregation techniques. Our experiments show that general stream slicing outperforms alternative concepts by up to one order of magnitude.
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TagsEDBT2019  modernhardware