Efficient Window Aggregation with General Stream Slicing
Speaker: Jonas Traub, Technische Universität Berlin
Title: Efficient Window Aggregation with General Stream Slicing
Jonas will present his work on "Efficient Window Aggregation with General Stream Slicing" which was awarded as best paper at EDBT 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 aggregation 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.
The talk introduces 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, the authors identify workload characteristics which affect the performance and applicability of aggregation techniques. Experiments show that general stream slicing outperforms alternative concepts by up to one order of magnitude.
The presented work is part of the cooperative research of TU Berlin and KTH Stockholm which startet with the paper "Cutty: Aggregate Sharing for User-Defined Windows" (CIKM 2017).
Jonas is a Research Associate at Technische Universität Berlin and the German Research Center for Artificial Intelligence (DFKI). His research interests include data stream processing, sensor data analysis, and data acquisition from sensor nodes. Jonas authored several publications related to data stream gathering, processing and transmission in the Internet of Things. Jonas defended his PhD in March 2019 under the supervision of Volker Markl. He won the best paper award at EDBT 2019 and two EDBT best demonstration awards.
Before he started his PhD, Jonas wrote his master thesis at the Royal Institute of Technology (KTH) and the Swedish Institute of Computer Science (SICS) / RISE in Stockholm under supervision of Seif Haridi and Volker Markl and advised by Paris Carbone and Asterios Katsifodimos. Prior to that, he received his B.Sc. degree at Baden-Württemberg Cooperative State University (DHBW Stuttgart) and worked several years at IBM in Germany and the USA.
Jonas is an alumnus of "Software Campus", "Studienstiftung des deutschen Volkes" and "Deutschlandstipendium". All publication and supplementary material are available at http://www.user.tu-berlin.de/powibol/.