Florian Wolf
Technische Universität Ilmenau
6 Papers
19 Citations
Florian Wolf is an academic researcher from Technische Universität Ilmenau. The author has contributed to research in topics: Computer science & Heuristics. The author has an hindex of 5, co-authored 6 publications.
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Papers
Extending database task schedulers for multi-threaded application code
Florian Wolf,Iraklis Psaroudakis,Norman May,Anastasia Ailamaki,Kai-Uwe Sattler +4 more
- 29 Jun 2015
TL;DR: It is shown that multi-threaded application code can render the database's workload scheduling ineffective and decrease the core throughput of the database by up to 50% and a general approach is presented to address this issue by integrating shared memory programming solutions into the task schedulers of databases.
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Robustness metrics for relational query execution plans
Florian Wolf,Michael Brendle,Norman May,Paul R. Willems,Kai-Uwe Sattler,Michael Grossniklaus +5 more
- 01 Jul 2018
TL;DR: Three novel metrics for the robustness of relational query execution plans w.r.t. cardinality estimation errors are presented and a novel plan selection strategy is presented that takes both, estimated cost and estimated robustness into account, when choosing a plan for execution.
Hibernating in the Cloud - Implementation and Evaluation of Object-NoSQL-Mapping.
Florian Wolf,Heiko Betz,Francis Gropengießer,Kai-Uwe Sattler +3 more
- 01 Jan 2013
TL;DR: This paper discusses and analyze the usage of a scalable NoSQL solution such as Basho’s RIAK as backend for Hibernate, and describes the necessary mapping and translation steps for an integration avoiding the detour on SQL.
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On the Calculation of Optimality Ranges for Relational Query Execution Plans
Florian Wolf,Norman May,Paul R. Willems,Kai-Uwe Sattler +3 more
- 27 May 2018
TL;DR: This paper analyzes the deviation from the estimate, and denotes the cardinality range of an intermediate result, where the optimal plan remains optimal as the optimality range, and derives theoretical worst case bounds for the number of enumerated plans required to compute the precise optimalityrange.
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Small Selectivities Matter: Lifting the Burden of Empty Samples
Axel Hertzschuch,Guido Moerkotte,Wolfgang Lehner,Norman May,Florian Wolf,Lars Fricke +5 more
- 09 Jun 2021
TL;DR: In this article, the authors present a novel approach for cardinality estimation in 0-tuple situations, which is ready to use in any DBMS capable of sampling, showing a negligible impact on optimization time.
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