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Efficient Window Aggregation with General Stream Slicing

Jonas Traub, Philipp Grulich, Alejandro Rodríguez Cuéllar, Sebastian Breß, Asterios Katsifodimos, Tilmann Rabl, Volker Markl

22nd International Conference on Extending Database Technology (EDBT 2019). 2019

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I²: Interactive Real-Time Visualization for Streaming Data.

Jonas Traub, Nikolaas Steenbergen, Philipp Grulich, Tilmann Rabl, and Volker Markl.

in Proc. 20th International Conference on Extending Database Technology (EDBT), March 21-24, 2017. 2017

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Agora: Towards An Open Ecosystem for Democratizing Data Science & Artificial Intelligence

Jonas Traub, Jorge-Arnulfo Quiané-Ruiz, Zoi Kaoudi, Volker Markl

CoRR abs/1909.03026 2019

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Optimized On-Demand Data Streaming from Sensor Nodes

Jonas Traub, Sebastian Breß, Tilmann Rabl, Asterios Katsifodimos, Volker Markl

In Proceedings of SoCC ’17, Santa Clara, CA, USA, September 24–27, 12. 2017

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M4: A Visualization-Oriented Time Series Data Aggregation

Uwe Jugel and Zbigniew Jerzak and Gregor Hackenbroich and Volker Markl

PVLDB, 797–808. 2014

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Faster Visual Analytics through Pixel-Perfect Aggregation

Uwe Jugel and Zbigniew Jerzak and Gregor Hackenbroich and Volker Markl

PVLDB, 1705–1708. 2014

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VDDA: automatic visualization-driven data aggregation in relational databases

Uwe Jugel and Zbigniew Jerzak and Gregor Hackenbroich and Volker Markl

VLDB J., 53–77. 2016

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Demand-based Sensor Data Gathering with Multi-Query Optimization

Julius Hülsmann, Jonas Traub, Volker Markl

VLDB 2020

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Asymmetry in Large-Scale Graph Analysis, Explained

Vasiliki Kalavri and Stephan Ewen and Kostas Tzoumas and Vladimir Vlassov and Volker Markl and Seif Haridi

Second International Workshop on Graph Data Management Experiences and Systems, GRADES 2014, co-loated with SIGMOD/PODS 2014, Snowbird, Utah, USA, June 22, 2014 2014

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Demonstrating efficient query processing in heterogeneous environments

Tomas Karnagel and Matthias Hille and Mario Ludwig and Dirk Habich and Wolfgang Lehner and Max Heimel and Volker Markl

International Conference on Management of Data, SIGMOD 2014, Snowbird, UT, USA, June 22-27, 2014, 693–696. 2014

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