research-article

Oracle database replay

Authors:

Leonidas Galanis,

Supiti Buranawatanachoke,

Benoît Dageville,

Jonathan Klein,

Stratos Papadomanolakis,

Venkateshwaran Venkataramani,

Graham WoodAuthors Info & Claims

SIGMOD '08: Proceedings of the 2008 ACM SIGMOD international conference on Management of data

Pages 1159 - 1170

https://doi.org/10.1145/1376616.1376732

Published: 09 June 2008 Publication History

Abstract

This paper presents Oracle Database Replay, a novel approach to testing changes to the relational database management system component of an information system (software upgrades, hardware changes etc). Database Replay makes it possible to subject a test system to a real production system workload, which helps identify all potential problems before implementing the planned changes on the production system. Any interesting workload period of a production database system can be captured with minimal overhead. The captured workload can be used to drive a test system while maintaining the concurrency and load characteristics of the real production workload. Therefore, the test results using database replay can provide very high assurance in determining the impact of changes to a production system before applying these changes. This paper presents the architecture of Database Replay as well as experimental results that demonstrate its usefulness as testing methodology.

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Cited By

Lim WMa LZhang WButrovich MArch SPavlo A(2024)Hit the Gym: Accelerating Query Execution to Efficiently Bootstrap Behavior Models for Self-Driving Database Management SystemsProceedings of the VLDB Endowment10.14778/3681954.368203017:11(3680-3693)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.14778/3681954.3682030
Geng CBlanas SBond MWang Y(2024)IsoPredict: Dynamic Predictive Analysis for Detecting Unserializable Behaviors in Weakly Isolated Data Store ApplicationsProceedings of the ACM on Programming Languages10.1145/36563918:PLDI(343-367)Online publication date: 20-Jun-2024
https://dl.acm.org/doi/10.1145/3656391
Lee WHa JHan WPark CPark MHan JLee J(2024)DoppelGanger++: Towards Fast Dependency Graph Generation for Database ReplayProceedings of the ACM on Management of Data10.1145/36393222:1(1-26)Online publication date: 26-Mar-2024
https://dl.acm.org/doi/10.1145/3639322
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Index Terms

Oracle database replay
1. Information systems
  1. Data management systems

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Published In

cover image ACM Conferences

SIGMOD '08: Proceedings of the 2008 ACM SIGMOD international conference on Management of data

June 2008

1396 pages

ISBN:9781605581026

DOI:10.1145/1376616

General Chairs:
Laks V. S. Lakshmanan
University of British Columbia, Canada
,
Raymond T. Ng
University of British Columbia, Canada
,
Dennis Shasha
New York University, USA

Copyright © 2008 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 09 June 2008

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SIGMOD/PODS '08

Sponsor:

SIGMOD/PODS '08: SIGMOD/PODS '08 - International Conference on Management of Data

June 9 - 12, 2008

Vancouver, Canada

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Overall Acceptance Rate 785 of 4,003 submissions, 20%

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Cited By

Lim WMa LZhang WButrovich MArch SPavlo A(2024)Hit the Gym: Accelerating Query Execution to Efficiently Bootstrap Behavior Models for Self-Driving Database Management SystemsProceedings of the VLDB Endowment10.14778/3681954.368203017:11(3680-3693)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.14778/3681954.3682030
Geng CBlanas SBond MWang Y(2024)IsoPredict: Dynamic Predictive Analysis for Detecting Unserializable Behaviors in Weakly Isolated Data Store ApplicationsProceedings of the ACM on Programming Languages10.1145/36563918:PLDI(343-367)Online publication date: 20-Jun-2024
https://dl.acm.org/doi/10.1145/3656391
Lee WHa JHan WPark CPark MHan JLee J(2024)DoppelGanger++: Towards Fast Dependency Graph Generation for Database ReplayProceedings of the ACM on Management of Data10.1145/36393222:1(1-26)Online publication date: 26-Mar-2024
https://dl.acm.org/doi/10.1145/3639322
Malyshkin VPerepelkin VLyamin A(2023)Trace Balancing Technique for Trace Playback in LuNA SystemParallel Computing Technologies10.1007/978-3-031-41673-6_4(42-50)Online publication date: 15-Aug-2023
https://doi.org/10.1007/978-3-031-41673-6_4
Cahoon JWang WZhu YLin KLiu STruong RSingh NWan CCiortea ANarasimhan SKrishnan S(2022)DopplerProceedings of the VLDB Endowment10.14778/3554821.355484015:12(3509-3521)Online publication date: 1-Aug-2022
https://dl.acm.org/doi/10.14778/3554821.3554840
Deep SGruenheid ANagaraj KNaito HNaughton JViglas S(2022)DIAMETRICSCommunications of the ACM10.1145/356746465:12(105-112)Online publication date: 22-Nov-2022
https://dl.acm.org/doi/10.1145/3567464
Jambigi NBach TSchabernack FFelderer M(2022)Automatic Error Classification and Root Cause Determination while Replaying Recorded Workload Data at SAP HANA2022 IEEE Conference on Software Testing, Verification and Validation (ICST)10.1109/ICST53961.2022.00041(323-333)Online publication date: Apr-2022
https://doi.org/10.1109/ICST53961.2022.00041
Qu LLi YZhang RChen TShu KQian WZhou A(2022)Application-Oriented Workload Generation for Transactional Database Performance Evaluation2022 IEEE 38th International Conference on Data Engineering (ICDE)10.1109/ICDE53745.2022.00036(420-432)Online publication date: May-2022
https://doi.org/10.1109/ICDE53745.2022.00036
Bach TAndrzejak ASeo CBierstedt CLemke CRitter DHwang DSheshi ESchabernack FRenkes FGaumnitz GMartens JHoemke LFelderer MRudolf MJambigi NMay NJoy RScheja RSchwedes SSeibel SSeifert SHaas SKraft SKroll TScheuer TLehner W(2022)Testing Very Large Database Management Systems: The Case of SAP HANADatenbank-Spektrum10.1007/s13222-022-00426-x22:3(195-215)Online publication date: 24-Nov-2022
https://doi.org/10.1007/s13222-022-00426-x
Van Aken DYang DBrillard SFiorino AZhang BBilien CPavlo A(2021)An inquiry into machine learning-based automatic configuration tuning services on real-world database management systemsProceedings of the VLDB Endowment10.14778/3450980.345099214:7(1241-1253)Online publication date: 12-Apr-2021
https://dl.acm.org/doi/10.14778/3450980.3450992
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