Surprise Benchmarking: The Why, What, and How
- Lawrence Benson,
- Carsten Binnig,
- Jan-Micha Bodensohn,
- Federico Lorenzi,
- Jigao Luo,
- Danica Porobic
- Technical University of Munich,
- Darmstadt University of Technology,
- TigerBeetle,
- Oracle Corporation,
- Hasso Plattner Institute for Software Systems Engineering,
- CrystalDB
Publikation:
Konference artikel i Proceeding eller bog/rapport kapitel
Konferencebidrag i proceedings
Forskning
Peer-reviewOpen Access
Resume
Standardized benchmarks are crucial to ensure a fair comparison of performance across systems. While extremely valuable, these benchmarks all use a setup where the workload is well-defined and known in advance. Unfortunately, this has led to overly-tuning data management systems for particular benchmark workloads such as TPC-H or TPC-C. As a result, benchmarking results frequently do not reflect the behavior of these systems in many real-world settings since workloads often significantly vary from the “known” benchmarking workloads. To address this issue, we present surprise benchmarking , a complementary approach to the current standardized benchmarking where “unknown” queries are exercised during the evaluation.
Publikation information
Produktionstype
Publikation:
Konference artikel i Proceeding eller bog/rapport kapitel
Konferencebidrag i proceedings
Forskning
Peer-reviewOriginalsprog
EngelskSider fra-til (Antal sider)
Sider 1-8 (8 sider)Publikationsmilepæle
- Udgivet - 09/06/2024
Publikationsstatus
Udgivet - 09/06/2024
Forlag
Association for Computing Machinery, USAISBN (Trykt)
9798400706691Publication IDs
- Scopus: 85197238834
Titel på værtspublikation
Proceedings of the Tenth International Workshop on Testing Database Systems, DBTest 2024, Santiago, Chile, 9 June 2024Metrikker
PlumX, åbner i en ny fane
Antal citationer
3
Hentninger
3
Relateret event
Titel
International Workshop on Testing Database Systems
Begivenhedstype
WorkshopGrad af anerkendelse
International begivenhedDato
09/06/2024 Lokation
SantiagoChile
