Surprise Benchmarking: The Why, What, and How

Lawrence Benson, Carsten Binnig, Jan-Micha Bodensohn, Federico Lorenzi, Jigao Luo, Danica Porobic, Tilmann Rabl, Anupam Sanghi, Russell Sears, Pinar Tözün, Tobias Ziegler

Publikation: Konference artikel i Proceeding eller bog/rapport kapitelKonferencebidrag i proceedingsForskningpeer review

Abstract

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.
OriginalsprogEngelsk
TitelProceedings of the Tenth International Workshop on Testing Database Systems, DBTest 2024, Santiago, Chile, 9 June 2024
Antal sider8
ForlagAssociation for Computing Machinery
Publikationsdato2024
Sider1-8
DOI
StatusUdgivet - 2024

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