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Towards cost-effective storage provisioning for DBMSs

Published: 01 December 2011 Publication History

Abstract

Data center operators face a bewildering set of choices when considering how to provision resources on machines with complex I/O subsystems. Modern I/O subsystems often have a rich mix of fast, high performing, but expensive SSDs sitting alongside with cheaper but relatively slower (for random accesses) traditional hard disk drives. The data center operators need to determine how to provision the I/O resources for specific workloads so as to abide by existing Service Level Agreements (SLAs), while minimizing the total operating cost (TOC) of running the workload, where the TOC includes the amortized hardware costs and the run time energy costs. The focus of this paper is on introducing this new problem of TOC-based storage allocation, cast in a framework that is compatible with traditional DBMS query optimization and query processing architecture. We also present a heuristic-based solution to this problem, called DOT. We have implemented DOT in PostgreSQL, and experiments using TPC-H and TPC-C demonstrate significant TOC reduction by DOT in various settings.

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Cited By

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  • (2024)Deep variability modeling to enhance reproducibility of database performance testingCluster Computing10.1007/s10586-024-04533-027:8(11683-11708)Online publication date: 1-Nov-2024
  • (2021)Multi-objective Optimization of Data Placement in a Storage-as-a-Service Federated CloudACM Transactions on Storage10.1145/345274117:3(1-32)Online publication date: 16-Aug-2021
  • (2017)MetricStore repositoryProceedings of the Symposium on Applied Computing10.1145/3019612.3019821(1820-1825)Online publication date: 3-Apr-2017
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Published In

cover image Proceedings of the VLDB Endowment
Proceedings of the VLDB Endowment  Volume 5, Issue 4
December 2011
120 pages

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VLDB Endowment

Publication History

Published: 01 December 2011
Published in PVLDB Volume 5, Issue 4

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View all
  • (2024)Deep variability modeling to enhance reproducibility of database performance testingCluster Computing10.1007/s10586-024-04533-027:8(11683-11708)Online publication date: 1-Nov-2024
  • (2021)Multi-objective Optimization of Data Placement in a Storage-as-a-Service Federated CloudACM Transactions on Storage10.1145/345274117:3(1-32)Online publication date: 16-Aug-2021
  • (2017)MetricStore repositoryProceedings of the Symposium on Applied Computing10.1145/3019612.3019821(1820-1825)Online publication date: 3-Apr-2017
  • (2017)Resource and performance prediction at high utilization for N-Tier cloud-based service systemsProceedings of the Australasian Computer Science Week Multiconference10.1145/3014812.3014857(1-9)Online publication date: 30-Jan-2017
  • (2016)DBMS MetrologyACM Transactions on Database Systems10.1145/299645442:1(1-42)Online publication date: 9-Nov-2016
  • (2016)OptExProceedings of the 16th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing10.1109/CCGrid.2016.10(193-202)Online publication date: 16-May-2016
  • (2016)A Cost Model for DBaaS StorageProceedings, Part I, 27th International Conference on Database and Expert Systems Applications - Volume 982710.1007/978-3-319-44403-1_14(223-239)Online publication date: 5-Sep-2016
  • (2013)DBMS metrologyProceedings of the 2013 ACM SIGMOD International Conference on Management of Data10.1145/2463676.2465331(421-432)Online publication date: 22-Jun-2013

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