Publikation Test

1.

Hurdelhey B, Weisgut M, Boissier M. Workload-Driven Data Placement for Tierless In-Memory Database Systems. In BTW 2023. Gesellschaft für Informatik e.V.; 2023. p. 47-70.

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2.

Boissier M. Robust and Budget-Constrained Encoding Configurations for In-Memory Database Systems. In Proceedings of the VLDB Endowment. 2022. p. 780-93.

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3.

Weisgut M, Ritter D, Boissier M, Perscheid M. Separated Allocator Metadata in Disaggregated In-Memory Databases: Friend or Foe?. In 1st Workshop on Composable Systems (COMPSYS@IPDPS), awarded as best paper. 2022.

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4.

Richly K, Schlosser R, Boissier M. Budget-Conscious Fine-Grained Configuration Optimization for Spatio-Temporal Applications. In Proceedings of the VLDB Endowment. 2022. p. 4079-92.

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5.

Heinzl L, Hurdelhey B, Boissier M, Perscheid M, Plattner H. Evaluating Lightweight Integer Compression Algorithms in Column-Oriented In-Memory DBMS. In 12th International Workshop on Accelerating Analytics and Data Management Systems Using Modern Processor and Storage Architectures, ADMS@VLDB 2021, Copenhagen, Denmark, August 16, 2021. 2021.

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6.

Kossmann J, Boissier M, Dubrawski A, Heseding F, Mandel C, Pigorsch U, Schneider M, Schniese T, Sobhani M, Tsayun P, Wille K, Perscheid M, Uflacker M, Plattner H. A Cockpit for the Development and Evaluation of Autonomous Database Systems. In 37th IEEE International Conference on Data Engineering, ICDE. 2021. p. 2685-8.

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@inproceedings{kossmann2021cockpit,
  abstract = {Databases are highly optimized complex systems with a multitude of configuration options. Especially in cloud scenarios with thousands of database deployments, determining optimized database configurations in an automated fashion is of increasing importance for database providers. At the same time, due to increased system complexity, it becomes more challenging to identify well-performing configurations. Therefore, research interest in autonomous or self-driving database systems has increased enormously in recent years. Such systems promise both performance improvements and cost reductions. In the literature, various fully or partially autonomous optimization mechanisms exist that optimize single aspects, e.g., index selection. However, database administrators and developers often distrust autonomous approaches, and there is a lack of practical experimentation opportunities that could create a better understanding. Moreover, the interplay of different autonomous mechanisms under complex workloads remains an open question. The presented cockpit enables an interactive assessment of the impact of autonomous components for database systems by comparing (autonomous) systems with different configurations side by side. Thereby, the cockpit enables users to build trust in autonomous solutions by experimenting with such technologies and observing their effects in practice.},
  author = {Kossmann, Jan and Boissier, Martin and Dubrawski, Alexander and Heseding, Fabian and Mandel, Caterina and Pigorsch, Udo and Schneider, Max and Schniese, Til and Sobhani, Mona and Tsayun, Petr and Wille, Katharina and Perscheid, Michael and Uflacker, Matthias and Plattner, Hasso},
  booktitle = {37th IEEE International Conference on Data Engineering, ICDE},
  keywords = {in-memory_database myown database self-managing autonomous mboissierselected self-driving adm hyrise},
  pages = {2685-2688},
  title = {A Cockpit for the Development and Evaluation of Autonomous Database Systems},
  year = 2021
}

7.

Richly K, Schlosser R, Boissier M. Joint Index, Sorting, and Compression Optimization for Memory-Efficient Spatio-Temporal Data Management. In 37th IEEE International Conference on Data Engineering, ICDE 2021, Chania, Greece, April 19-22, 2021. 2021. p. 1901-6.

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8.

Dreseler M, Boissier M, Rabl T, Uflacker M. Quantifying TPC-H Choke Points and Their Optimizations. In Proceedings of the VLDB Endowment. 2020. p. 1206-20.

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9.

Boissier M, Jendruk M. Workload-Driven and Robust Selection of Compression Schemes for Column Stores. In 22nd International Conference on Extending Database Technology (EDBT). 2019. p. 674-7.

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10.

Schlosser R, Kossmann J, Boissier M. Efficient Scalable Multi-Attribute Index Selection Using Recursive Strategies. In IEEE 35th International Conference on Data Engineering (ICDE 2019). IEEE; 2019. p. 1238-49.

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11.

Dreseler M, Kossmann J, Boissier M, Klauck S, Uflacker M, Plattner H. Hyrise Re-engineered: An Extensible Database System for Research in Relational In-Memory Data Management. In 22nd International Conference on Extending Database Technology (EDBT). 2019. p. 313-24.

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12.

Schlosser R, Walther C, Boissier M, Uflacker M. Automated Repricing and Ordering Strategies in Competitive Markets. AI Communications. 2019;32:15-29.

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13.

Schlosser R, Walther C, Boissier M, Uflacker M. Data-Driven Inventory Management and Dynamic Pricing Competition on Online Marketplaces. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI 2018). 2018. p. 5856-8.

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14.

Schlosser R, Boissier M. Optimal Repricing Strategies in a Stochastic Infinite Horizon Duopoly. In Communications in Computer and Information Science (CCIS). Springer; 2018. p. 129-50.

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15.

Boissier M, Schlosser R, Uflacker M. Hybrid Data Layouts for Tiered HTAP Databases with Pareto-Optimal Data Placements. In IEEE 34th International Conference on Data Engineering (ICDE 2018). 2018. p. 209-20.

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16.

Boissier M, Kurzynski D. Workload-Driven Horizontal Partitioning and Partition Pruning for Large HTAP Systems. In 2018 IEEE 34th International Conference on Data Engineering Workshops. 2018. p. 116-21.

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17.

Schlosser R, Boissier M. Dynamic Pricing under Competition on Online Marketplaces: A Data-Driven Approach. In KDD ’18 Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. 2018. p. 705-14.

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18.

Schlosser R, Boissier M. Dealing with the Dimensionality Curse in Dynamic Pricing Competition: Using Frequent Repricing to Compensate Imperfect Market Anticipations. Computers and Operations Research. 2018;100:26-42.

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19.

Boissier M. Reducing the Footprint of Main Memory HTAP Systems: Removing, Compressing, Tiering, and Ignoring Data. In PhD Workshop at VLDB. CEUR-WS.org; 2018.

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20.

Ruhrländer RP, Boissier M, Uflacker M. Improving Box Office Result Predictions for Movies Using Consumer-Centric Models. In KDD ’18 Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. 2018. p. 655-64.

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21.

Serth S, Podlesny N, Bornstein M, Lindemann J, Latt J, Selke J, Schlosser R, Boissier M, Uflacker M. An Interactive Platform to Simulate Dynamic Pricing Competition on Online Marketplaces. In 21st IEEE International Enterprise Distributed Object Computing Conference, EDOC 2017, Quebec City, QC, Canada, October 10-13, 2017. IEEE; 2017. p. 61-6.

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22.

Boissier M, Schlosser R, Podlesny N, Serth S, Bornstein M, Latt J, Lindemann J, Selke J, Uflacker M. Data-Driven Repricing Strategies in Competitive Markets: An Interactive Simulation Platform. In Proceedings of the Eleventh ACM Conference on Recommender Systems (RecSys ’17). New York, NY, USA: ACM; 2017. p. 355-7.

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23.

Zimmermann T, Djürken T, Mayer A, Janke M, Boissier M, Schwarz C, Schlosser R, Uflacker M. Detecting Fraudulent Advertisements on a Large E-Commerce Platform. In Proceedings of the Nineteenth International Workshop on Data Warehousing and OLAP, DOLAP, Venice, Italy, March 21, 2017. 2017.

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24.

Schlosser R, Boissier M. Optimal Price Reaction Strategies in the Presence of Active and Passive Competitors. In Proceedings of the 6th International Conference on Operations Research and Enterprise Systems (ICORES), Porto, Portugal. 2017. p. 47-56.

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25.

Boissier M, Spivak A, Meyer C. Improving Materialization for Tiered Column Stores: A Workload-Aware Ansatz Based on Table Reordering. In ACSW ’17 Proceedings of the Australasian Computer Science Week Multiconference, ACSW ’17. New York, NY, USA: ACM; 2017. p. 25:1-25:10.

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26.

Faust M, Boissier M, Keller M, Schwalb D, Bischoff H, Eisenreich K, Färber F, Plattner H. Footprint Reduction and Uniqueness Enforcement with Hash Indices in SAP HANA. In Database and Expert Systems Applications: 27th International Conference, DEXA 2016, Porto, Portugal, September 5-8, 2016, Proceedings, Part II. 2016. p. 137-51.

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27.

Boissier M, Djürken T, Schlosser R, Faust M. A Cost-Aware and Workload-Based Index Advisor for Columnar In-Memory Databases. In 22nd International Conference, ICIST 2016, Druskininkai, Lithuania, October 13-15, 2016, Proceedings, CCIS 639. 2016. p. 285-99.

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28.

Schlosser R, Boissier M, Schober A, Uflacker M. How To Survive Dynamic Pricing Competition in E-commerce. In Proceedings of the Poster Track of the 10th ACM Conference on Recommender Systems (RecSys 2016), Boston, USA, September 17, 2016. 2016.

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29.

Boissier M, Meyer C, Djürken T, Lindemann J, Mao K, Reinhardt P, Specht T, Zimmermann T, Uflacker M. Analyzing Data Relevance and Access Patterns of Live Production Database Systems. In Proceedings of the 25th ACM International on Conference on Information and Knowledge Management, CIKM 2016. New York, NY, USA: ACM; 2016. p. 2473-5.

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30.

Boissier M, Meyer C, Uflacker M, Tinnefeld C. And all of a sudden: Main Memory Is Less Expensive Than Disk. In: Rabl T, Sachs K, Poess M, K. Baru C, Jacobsen H-A, redakteurs. Big Data Benchmarking. 1st ed Springer International Publishing; 2015. p. 132-44.

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31.

Meyer C, Boissier M, Michaud A, Vollmer JO, Taylor K, Schwalb D, Uflacker M, Roedszus K. Dynamic and Transparent Data Tiering for In-Memory Databases in Mixed Workload Environments. In International Workshop on Accelerating Data Management Systems Using Modern Processor and Storage Architectures - ADMS @ VLDB 2015. 2015.

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32.

Boissier M. Optimizing Main Memory Utilization of Columnar In-Memory Databases Using Data Eviction. In Proceedings of Phd Workshop @ VLDB 2014, Hangzhou. 2014.

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33.

Boissier M, Krüger J, Wust J, Plattner H. An Integrated Data Management for Enterprise Systems. In ICEIS 2014 - Proceedings of the 16th International Conference on Enterprise Information Systems. 2014. p. 410-8.

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34.

Krüger J, Hübner F, Wust J, Boissier M, Zeier A, Plattner H. Main Memory Databases for Enterprise Applications. In IEEE 18Th International Conference on Industrial Engineering and Engineering Management (IE&EM), 2011. 2011.

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35.

Krüger J, Grund M, Boissier M, Zeier A, Plattner H. Data Structures for Mixed Workloads in In-Memory Databases. In 5th International Conference on Computer Sciences and Convergence Information Technology (ICCIT), 2010. 2010.

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Publications (copy 1)

News

22.09.2023 | Trends and Concepts in the Softwareindustry Seminar offered in WiSe 2023/2024

22.05.2023 | Christopher Hagedorn Successfully Defended His PhD Thesis

03.03.2023 | Last Trends and Concepts course of Prof. Hasso Plattner

01.03.2023 | Jan Kossmann Successfully Defended His PhD Thesis

26.02.2023 | Paper on Data Tiering in Hyrise Published in BTW Proceedings

24.02.2023 | Paper on EPIC Research Group Published in SIGMOD Record

30.11.2022 | Paper on Database Optimizations for Spatio-Temporal Data published in PVLDB

04.10.2022 | Günter Hesse Successfully Defended His PhD Thesis

08.07.2022 | Successful PhD Defense by Markus Dreseler

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