Research
The group focuses on query optimization in database management systems. The goal of query optimization is to determine the most efficient way to execute a given query by considering the possible query plans and deciding on one of them. Whoever is interested in query compilers/
- Fent, P., Moerkotte, G. and Neumann, T. (2023). Asymptotically better query optimization using indexed algebra. Proceedings of the VLDB Endowment, 16, 3018-3030.
- Eich, M., Fender, P. and Moerkotte, G. (2018). Efficient generation of query plans containing group-by, join, and groupjoin. The VLDB Journal, 27, 617–641.
- Meister, A., Moerkotte, G. and Saake, G. (2018). Errata for “Analysis of two existing and one new dynamic programming algorithm for the generation of optimal bushy join trees without cross products”. Proceedings of the VLDB Endowment, 11, 1069-1070.
- Müller, M., Moerkotte, G. and Kolb, O. (2018). Improved selectivity estimation by combining knowledge from sampling and synopses. Proceedings of the VLDB Endowment, 11, 1016-1028.
- Eich, M., Fender, P. and Moerkotte, G. (2016). Faster plan generation through consideration of functional dependencies and keys. Proceedings of the VLDB Endowment, 9, 756–767.
- Kastrati, F. and Moerkotte, G. (2016). Optimization of conjunctive predicates for main memory column stores. Proceedings of the VLDB Endowment, 9, 1125-1136.
- Moerkotte, G., Montag, M., Repetti, A. and Steidl, G. (2015). Proximal operator of quotient functions with application to a feasibility problem in query optimization. Journal of Computational and Applied Mathematics, 285, 243–255.
- Schlather, M., Freudenberg, A., Moerkotte, G., Pook, T. and Vandenplas, J. (2023). Software project “miraculix”: Efficient computations with large genomic datasets. In , Proceedings of the 2023 Interbull Meeting, Lyon, France, 26–27 August 2023 (S. 15–22). Interbull Bulletin, Swedish University of Agricultural Sciences (SLU): Uppsala.
- Brendle, M., Weber, N., Vallyev, M., May, N., Schulze, R., Böhm, A., Moerkotte, G. and Grossniklaus, M. (2022). SAHARA: Memory footprint reduction of cloud databases with automated table partitioning. In , Proceedings of the 25th International Conference on Extending Database Technology, EDBT 2022. Edinburgh, UK, March 29 – April 1 (S. 13–26). Advances in Database Technology, OpenProceedings.org: Konstanz.
- Flachs, D., Müller, M. and Moerkotte, G. (2022). The 3D hash join: Building on non-unique join attributes. In , 12th Conference on Innovative Data Systems Research, CIDR 2022, Chaminade, Ca, USA, January 9–12, 2022 (S. 1–9). , CIDR: Chaminade.
- Müller, M. and Moerkotte, G. (2022). Translation grids for multi-way join size estimation. In , Proceedings of the 25th International Conference on Extending Database Technology, EDBT 2022. Edinburgh, UK, March 29 – April 1 (S. 378–382). Advances in Database Technology, OpenProceedings: Konstanz.
- Brendle, M., Weber, N., Valyiev, M., May, N., Schulze, R., Böhm, A., Moerkotte, G. and Grossniklaus, M. (2021). Precise, compact, and fast data access counters for automated physical database design. In , Datenbanksysteme für Business, Technologie und Web (BTW 2021) : 13.-17. September 2021 in Dresden, Deutschland (S. 79–100). GI-Edition : Lecture Notes in Informatics. Proceedings, Ges. für Informatik: Bonn.
- Hertzschuch, A., Moerkotte, G., Lehner, W., May, N., Wolf, F. and Fricke, L. (2021). Small selectivities matter: Lifting the burden of empty samples.
In , Proceedings of the 2021 International Conference on Management of Data : SIGMOD/
PODS '21 (S. 697–709). , Association for Computing Machinery: New York, NY. - Müller, M., Flachs, D. and Moerkotte, G. (2021). Memory-efficient key/
Foreign-key join size estimation via multiplicity and intersection size. In , 2021 IEEE 37th International Conference on Data Engineering (ICDE) (S. 984–995). , IEEE: Chania. - Havenstein, D., Lysakovski, P., May, N., Moerkotte, G. and Steidl, G. (2020). Fast entropy maximization for selectivity estimation of conjunctive predicates on CPUs and GPUs. In , Advances in Database Technology – EDBT 2020 : 23rd International Conference on Extending Database Technology, Copenhagen, Denkmark, March 30-April 2, 2020 : proceedings (S. 546–554). , EDBT: Kopenhagen.
- Moerkotte, G. and Hertzschuch, A. (2020). alpha to omega: the G(r)eek alphabet of sampling. In , CIDR 2020 : 10th Conference on Innovative Data Systems Research, Amsterdam, The Netherlands, January 12–15, 2020, Online Proceedings (S. 1–15). , CIDR: Amsterdam.
- Kastrati, F. and Moerkotte, G. (2018). Generating optimal plans for Boolean expressions. In , IEEE 34th International Conference on Data Engineering : ICDE 2018 : 16–19 April 2018, Paris, France : proceedings (S. 1013-1024). , IEEE Computer Soc.: Piscataway, NJ.
- Kastrati, F. and Moerkotte, G. (2017). Optimization of disjunctive predicates for main memory column stores. In , SIGMOD '17 : Proceedings of the 2017 ACM International Conference on Management of Data, May 14–19, 2017, Chicago, IL, USA (S. 731–744). , ACM: Chicago, IL.
- Eich, M. and Moerkotte, G. (2015). Dynamic programming: the next step. In , 2015 IEEE 31st International Conference on Data Engineering (ICDE 2015) : Seoul, South Korea, 13 – 17 April 2015 (S. 903–914). , IEEE: Piscataway, NJ [u.a.].
- Moerkotte, G., DeHaan, D., May, N., Nica, A. and Böhm, A. (2014). Exploiting ordered dictionaries to efficiently construct histograms with q-error guarantees in SAP HANA.
In , SIGMOD/
PODS'14 : compilation proceedings of the 2014 ACM Symposium on Principles of Database Systems; ACM SIGMOD International Conference on Management of Data, and SIGMODS/ PODS 2014 PhD Symposium; June 22 – 27, 2014, Snowbird, UT, USA (S. 361–372). , ACM: [New York, NY].
- Eich, M. and Moerkotte, G. (2014). Dynamic Programming: The Next Step.