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demonstration

Workload optimization using SharedDB

Published:22 June 2013Publication History

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. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. S. Harizopoulos and A. Ailamaki. StagedDB: Designing Database Servers for Modern Hardware. IEEE Data Eng. Bull., 28(2):11--16, 2005.Google ScholarGoogle Scholar
  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. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. P. Unterbrunner, G. Giannikis, G. Alonso, D. Fauser, and D. Kossmann. Predictable Performance for Unpredictable Workloads. In Proc. VLDB, pages 706--717, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library

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  1. Workload optimization using SharedDB

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            cover image ACM Conferences
            SIGMOD '13: Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
            June 2013
            1322 pages
            ISBN:9781450320375
            DOI:10.1145/2463676

            Copyright © 2013 ACM

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            Association for Computing Machinery

            New York, NY, United States

            Publication History

            • Published: 22 June 2013

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            • demonstration

            Acceptance Rates

            SIGMOD '13 Paper Acceptance Rate76of372submissions,20%Overall Acceptance Rate785of4,003submissions,20%

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