demonstration

Workload optimization using SharedDB

Authors:

Georgios Giannikis,

Darko Makreshanski,

Gustavo Alonso,

Donald KossmannAuthors Info & Claims

SIGMOD '13: Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data

Pages 1045 - 1048

https://doi.org/10.1145/2463676.2463678

Published: 22 June 2013 Publication History

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Abstract

This demonstration presents SharedDB, an implementation of a relational database system capable of executing all SQL operators by sharing computation and resources across all running queries. SharedDB sidesteps the traditional query-at-a-time approach and executes queries in batches. Unlike proposed multi-query optimization ideas, in SharedDB queries do not have to contain common subexpressions in order to be part of the same batch, which allows for a higher degree of sharing. By sharing as much as possible, SharedDB avoids repeating parts of computation that is common across all running queries. The goal of this demonstration is to show the ability of shared query execution to a) answer complex and diverse workloads, and b) reduce the interaction among concurrently executed queries that is observed in traditional systems and leads to performance deterioration and instabilities.

References

[1]

G. Giannikis, G. Alonso, and D. Kossmann. SharedDB: Killing one Thousand Queries with one Stone. Proc. VLDB Endow., 5(6):526--537, Feb. 2012.

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[2]

S. Harizopoulos and A. Ailamaki. StagedDB: Designing Database Servers for Modern Hardware. IEEE Data Eng. Bull., 28(2):11--16, 2005.

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[3]

T.-I. Salomie, I. E. Subasu, J. Giceva, and G. Alonso. Database Engines on Multicores, Why Parallelize when you can Distribute? In Proc. EuroSys, pages 17--30, 2011.

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[4]

P. Unterbrunner, G. Giannikis, G. Alonso, D. Fauser, and D. Kossmann. Predictable Performance for Unpredictable Workloads. In Proc. VLDB, pages 706--717, 2009.

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Cited By

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Gurumurthy BBidarkar VBroneske DPionteck TSaake G(2024)Exploiting Shared Sub-Expression and Materialized View Reuse for Multi-Query OptimizationInformation Systems Frontiers10.1007/s10796-024-10506-wOnline publication date: 25-Jun-2024
https://doi.org/10.1007/s10796-024-10506-w
Wang JLi TWang ALiu XChen LChen JLiu JWu JLi FGao Y(2023)Real-Time Workload Pattern Analysis for Large-Scale Cloud DatabasesProceedings of the VLDB Endowment10.14778/3611540.361155716:12(3689-3701)Online publication date: 12-Sep-2023
https://doi.org/10.14778/3611540.3611557
Gurumurthy BBidarkar VBroneske DPionteck TSaake G(2023)What Happens When Two Multi-Query Optimization Paradigms Combine?Advances in Databases and Information Systems10.1007/978-3-031-42914-9_6(74-87)Online publication date: 28-Aug-2023
https://doi.org/10.1007/978-3-031-42914-9_6
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Index Terms

Workload optimization using SharedDB
1. Information systems
  1. Data management systems
2. Theory of computation
  1. Theory and algorithms for application domains
    1. Database theory
      1. Database query processing and optimization (theory)

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Information & Contributors

Information

Published In

SIGMOD '13: Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data

June 2013

1322 pages

ISBN:9781450320375

DOI:10.1145/2463676

General Chairs:
Kenneth Ross
Columbia University
,
Divesh Srivastava
AT&T Research
,
Program Chair:
Dimitris Papadias
HKUST

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: 22 June 2013

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Demonstration

Conference

SIGMOD/PODS'13

Sponsor:

SIGMOD

SIGMOD/PODS'13: International Conference on Management of Data

June 22 - 27, 2013

New York, New York, USA

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SIGMOD '13 Paper Acceptance Rate 76 of 372 submissions, 20%;

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

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Cited By

View all

Gurumurthy BBidarkar VBroneske DPionteck TSaake G(2024)Exploiting Shared Sub-Expression and Materialized View Reuse for Multi-Query OptimizationInformation Systems Frontiers10.1007/s10796-024-10506-wOnline publication date: 25-Jun-2024
https://doi.org/10.1007/s10796-024-10506-w
Wang JLi TWang ALiu XChen LChen JLiu JWu JLi FGao Y(2023)Real-Time Workload Pattern Analysis for Large-Scale Cloud DatabasesProceedings of the VLDB Endowment10.14778/3611540.361155716:12(3689-3701)Online publication date: 12-Sep-2023
https://doi.org/10.14778/3611540.3611557
Gurumurthy BBidarkar VBroneske DPionteck TSaake G(2023)What Happens When Two Multi-Query Optimization Paradigms Combine?Advances in Databases and Information Systems10.1007/978-3-031-42914-9_6(74-87)Online publication date: 28-Aug-2023
https://doi.org/10.1007/978-3-031-42914-9_6
Tu YEslami MXu ZCharkhgard H(2022)Multi-Query Optimization Revisited: A Full-Query Algebraic Method2022 IEEE International Conference on Big Data (Big Data)10.1109/BigData55660.2022.10020338(252-261)Online publication date: 17-Dec-2022
https://doi.org/10.1109/BigData55660.2022.10020338
Pietrzyk JKrause AHabich DLehner W(2022)To share or not to share vector registers?The VLDB Journal10.1007/s00778-022-00744-231:6(1215-1236)Online publication date: 28-Apr-2022
https://doi.org/10.1007/s00778-022-00744-2
Karimov JRabl TMarkl V(2020)AJoinProceedings of the VLDB Endowment10.14778/3372716.337271813:4(435-448)Online publication date: 6-Jan-2020
https://dl.acm.org/doi/10.14778/3372716.3372718
Pietrzyk JHabich DLehner WPorobic DNeumann T(2020)To share or not to share vector registers?Proceedings of the 16th International Workshop on Data Management on New Hardware10.1145/3399666.3399923(1-10)Online publication date: 15-Jun-2020
https://dl.acm.org/doi/10.1145/3399666.3399923
Leal FMusicante M(2015)Using SLA to guide database transition to NoSQL on the cloud: A systematic mapping study2015 IEEE/ACS 12th International Conference of Computer Systems and Applications (AICCSA)10.1109/AICCSA.2015.7507130(1-8)Online publication date: Nov-2015
https://doi.org/10.1109/AICCSA.2015.7507130
Unterbrunner PAlonso GKossmann D(2014)High availability, elasticity, and strong consistency for massively parallel scans over relational dataThe VLDB Journal — The International Journal on Very Large Data Bases10.1007/s00778-013-0343-923:4(627-652)Online publication date: 1-Aug-2014
https://dl.acm.org/doi/10.1007/s00778-013-0343-9

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