TY - GEN

T1 - Silentium! Run-Analyse-Eradicate the Noise out of the DB/OS Stack

AU - Mauerer, Wolfgang

AU - Ramsauer, Ralf

AU - Filho, Edson Ramiro Lucas

AU - Lohmann, Daniel

AU - Scherzinger, Stefanie

N1 - Funding Information: Acknowledgements. This work was supported by the iDev40 project and the German Research Council (DFG) under grant no. LO 1719/3-1. The information and results set out in this publication are those of the authors and do not necessarily reflect the opinion of the ECSEL Joint Undertaking. The iDev40 project has received funding from the ECSEL Joint Undertaking (JU) under grant no. 783163. The JU receives support from the European Union’s Horizon 2020 research and innovation programme. It is co-funded by the consortium members, grants from Austria, Germany, Belgium, Italy, Spain and Romania. We thank the DBToaster team, and Jan Kiszka for guidance on difficile technical issues related to Jailhouse on x86 systems.

PY - 2021

Y1 - 2021

N2 - When multiple tenants compete for resources, database performance tends to suffer. Yet there are scenarios where guaranteed sub-millisecond latencies are crucial, such as in real-time data processing, IoT devices, or when operating in safety-critical environments. In this paper, we study how to make query latencies deterministic in the face of noise (whether caused by other tenants or unrelated operating system tasks). We perform controlled experiments with an in-memory database engine in a multi-tenant setting, where we successively eradicate noisy interference from within the system software stack, to the point where the engine runs close to bare-metal on the underlying hardware. We show that we can achieve query latencies comparable to the database engine running as the sole tenant, but without noticeably impacting the workload of competing tenants. We discuss these results in the context of ongoing efforts to build custom operating systems for database workloads, and point out that for certain use cases, the margin for improvement is rather narrow. In fact, for scenarios like ours, existing operating systems might just be good enough, provided that they are expertly configured. We then critically discuss these findings in the light of a broader family of database systems (e.g. including disk-based), and how to extend the approach of this paper accordingly.

AB - When multiple tenants compete for resources, database performance tends to suffer. Yet there are scenarios where guaranteed sub-millisecond latencies are crucial, such as in real-time data processing, IoT devices, or when operating in safety-critical environments. In this paper, we study how to make query latencies deterministic in the face of noise (whether caused by other tenants or unrelated operating system tasks). We perform controlled experiments with an in-memory database engine in a multi-tenant setting, where we successively eradicate noisy interference from within the system software stack, to the point where the engine runs close to bare-metal on the underlying hardware. We show that we can achieve query latencies comparable to the database engine running as the sole tenant, but without noticeably impacting the workload of competing tenants. We discuss these results in the context of ongoing efforts to build custom operating systems for database workloads, and point out that for certain use cases, the margin for improvement is rather narrow. In fact, for scenarios like ours, existing operating systems might just be good enough, provided that they are expertly configured. We then critically discuss these findings in the light of a broader family of database systems (e.g. including disk-based), and how to extend the approach of this paper accordingly.

KW - DB-OS co-engineering

KW - Low-latency databases

KW - bounded-time query processing

KW - real-time databases

KW - tail latency

UR - http://www.scopus.com/inward/record.url?scp=85127198937&partnerID=8YFLogxK

U2 - 10.18420/BTW2021-21

DO - 10.18420/BTW2021-21

M3 - Conference contribution

SN - 978-3-88579-705-0

SN - 3-88579-705-4

T3 - Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI)

SP - 397

EP - 421

BT - Datenbanksysteme für Business, Technologie und Web (BTW 2021)

A2 - Sattler, Kai-Uwe

A2 - Herschel, Melanie

A2 - Lehner, Wolfgang

CY - Bonn

ER -