T
Thomas Neumann
Researcher at Technische Universität München
Publications - 270
Citations - 10998
Thomas Neumann is an academic researcher from Technische Universität München. The author has contributed to research in topics: Query optimization & Computer science. The author has an hindex of 46, co-authored 242 publications receiving 8973 citations. Previous affiliations of Thomas Neumann include Ludwig Maximilian University of Munich & Information Technology University.
Papers
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Proceedings ArticleDOI
HyPer: A hybrid OLTP&OLAP main memory database system based on virtual memory snapshots
Alfons Kemper,Thomas Neumann +1 more
TL;DR: This work presents an efficient hybrid system, called HyPer, that can handle both OLTP and OLAP simultaneously by using hardware-assisted replication mechanisms to maintain consistent snapshots of the transactional data.
Journal ArticleDOI
The RDF-3X engine for scalable management of RDF data
Thomas Neumann,Gerhard Weikum +1 more
TL;DR: The RDF-3X engine is presented, an implementation of SPARQL that achieves excellent performance by pursuing a RISC-style architecture with streamlined indexing and query processing, and can outperform the previously best alternatives by one or two orders of magnitude.
Journal ArticleDOI
RDF-3X: a RISC-style engine for RDF
Thomas Neumann,Gerhard Weikum +1 more
TL;DR: The salient points of RDF-3X are a generic solution for storing and indexing RDF triples that completely eliminates the need for physical-design tuning, a powerful yet simple query processor that leverages fast merge joins to the largest possible extent, and a query optimizer for choosing optimal join orders using a cost model based on statistical synopses for entire join paths.
Journal ArticleDOI
Efficiently compiling efficient query plans for modern hardware
TL;DR: This work presents a novel compilation strategy that translates a query into compact and efficient machine code using the LLVM compiler framework and integrates these techniques into the HyPer main memory database system and shows that this results in excellent query performance while requiring only modest compilation time.
Journal ArticleDOI
How good are query optimizers, really?
TL;DR: This paper introduces the Join Order Benchmark (JOB) and experimentally revisit the main components in the classic query optimizer architecture using a complex, real-world data set and realistic multi-join queries.