Modeling and exploiting query interactions in database systems

Mumtaz Ahmad, Ashraf Aboulanaga, Shivnath Babu, Kamesh Munagala

Research output: Chapter in Book/Report/Conference proceedingConference contribution

26 Citations (Scopus)

Abstract

The typical workload in a database system consists of a mixture of multiple queries of different types, running concurrently and interacting with each other. Hence, optimizing performance requires reasoning about query mixes and their interactions, rather than considering individual queries or query types. In this paper, we show the significant impact that query interactions can have on workload performance. We present a new approach based on planning experiments and statistical modeling to capture the impact of query interactions. This approach requires no prior assumptions about the internal workings of the database system or the nature or cause of query interactions, making it portable across systems. As a concrete demonstration of the potential of capturing, modeling, and exploiting query interactions, we develop a novel interaction-aware query scheduler that targets report-generation workloads in Business Intelligence (BI) settings. Under certain assumptions, the schedule found by this scheduler is within a constant factor of optimal. An experimental evaluation with TPC-H queries on IBM DB2 demonstrates that our scheduler consistently outperforms (up to 4x) conventional schedulers that do not account for query interactions.

Original languageEnglish
Title of host publicationInternational Conference on Information and Knowledge Management, Proceedings
Pages183-192
Number of pages10
DOIs
Publication statusPublished - 1 Dec 2008
Externally publishedYes
Event17th ACM Conference on Information and Knowledge Management, CIKM'08 - Napa Valley, CA, United States
Duration: 26 Oct 200830 Oct 2008

Other

Other17th ACM Conference on Information and Knowledge Management, CIKM'08
CountryUnited States
CityNapa Valley, CA
Period26/10/0830/10/08

Fingerprint

Interaction
Query
Modeling
Data base
Workload
Evaluation
Planning
Schedule
Factors
Experiment
Nature
Business intelligence

ASJC Scopus subject areas

  • Business, Management and Accounting(all)
  • Decision Sciences(all)

Cite this

Ahmad, M., Aboulanaga, A., Babu, S., & Munagala, K. (2008). Modeling and exploiting query interactions in database systems. In International Conference on Information and Knowledge Management, Proceedings (pp. 183-192) https://doi.org/10.1145/1458082.1458109

Modeling and exploiting query interactions in database systems. / Ahmad, Mumtaz; Aboulanaga, Ashraf; Babu, Shivnath; Munagala, Kamesh.

International Conference on Information and Knowledge Management, Proceedings. 2008. p. 183-192.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Ahmad, M, Aboulanaga, A, Babu, S & Munagala, K 2008, Modeling and exploiting query interactions in database systems. in International Conference on Information and Knowledge Management, Proceedings. pp. 183-192, 17th ACM Conference on Information and Knowledge Management, CIKM'08, Napa Valley, CA, United States, 26/10/08. https://doi.org/10.1145/1458082.1458109
Ahmad M, Aboulanaga A, Babu S, Munagala K. Modeling and exploiting query interactions in database systems. In International Conference on Information and Knowledge Management, Proceedings. 2008. p. 183-192 https://doi.org/10.1145/1458082.1458109
Ahmad, Mumtaz ; Aboulanaga, Ashraf ; Babu, Shivnath ; Munagala, Kamesh. / Modeling and exploiting query interactions in database systems. International Conference on Information and Knowledge Management, Proceedings. 2008. pp. 183-192
@inproceedings{d7834e97d2d24e04910f424389d02e4b,
title = "Modeling and exploiting query interactions in database systems",
abstract = "The typical workload in a database system consists of a mixture of multiple queries of different types, running concurrently and interacting with each other. Hence, optimizing performance requires reasoning about query mixes and their interactions, rather than considering individual queries or query types. In this paper, we show the significant impact that query interactions can have on workload performance. We present a new approach based on planning experiments and statistical modeling to capture the impact of query interactions. This approach requires no prior assumptions about the internal workings of the database system or the nature or cause of query interactions, making it portable across systems. As a concrete demonstration of the potential of capturing, modeling, and exploiting query interactions, we develop a novel interaction-aware query scheduler that targets report-generation workloads in Business Intelligence (BI) settings. Under certain assumptions, the schedule found by this scheduler is within a constant factor of optimal. An experimental evaluation with TPC-H queries on IBM DB2 demonstrates that our scheduler consistently outperforms (up to 4x) conventional schedulers that do not account for query interactions.",
author = "Mumtaz Ahmad and Ashraf Aboulanaga and Shivnath Babu and Kamesh Munagala",
year = "2008",
month = "12",
day = "1",
doi = "10.1145/1458082.1458109",
language = "English",
isbn = "9781595939913",
pages = "183--192",
booktitle = "International Conference on Information and Knowledge Management, Proceedings",

}

TY - GEN

T1 - Modeling and exploiting query interactions in database systems

AU - Ahmad, Mumtaz

AU - Aboulanaga, Ashraf

AU - Babu, Shivnath

AU - Munagala, Kamesh

PY - 2008/12/1

Y1 - 2008/12/1

N2 - The typical workload in a database system consists of a mixture of multiple queries of different types, running concurrently and interacting with each other. Hence, optimizing performance requires reasoning about query mixes and their interactions, rather than considering individual queries or query types. In this paper, we show the significant impact that query interactions can have on workload performance. We present a new approach based on planning experiments and statistical modeling to capture the impact of query interactions. This approach requires no prior assumptions about the internal workings of the database system or the nature or cause of query interactions, making it portable across systems. As a concrete demonstration of the potential of capturing, modeling, and exploiting query interactions, we develop a novel interaction-aware query scheduler that targets report-generation workloads in Business Intelligence (BI) settings. Under certain assumptions, the schedule found by this scheduler is within a constant factor of optimal. An experimental evaluation with TPC-H queries on IBM DB2 demonstrates that our scheduler consistently outperforms (up to 4x) conventional schedulers that do not account for query interactions.

AB - The typical workload in a database system consists of a mixture of multiple queries of different types, running concurrently and interacting with each other. Hence, optimizing performance requires reasoning about query mixes and their interactions, rather than considering individual queries or query types. In this paper, we show the significant impact that query interactions can have on workload performance. We present a new approach based on planning experiments and statistical modeling to capture the impact of query interactions. This approach requires no prior assumptions about the internal workings of the database system or the nature or cause of query interactions, making it portable across systems. As a concrete demonstration of the potential of capturing, modeling, and exploiting query interactions, we develop a novel interaction-aware query scheduler that targets report-generation workloads in Business Intelligence (BI) settings. Under certain assumptions, the schedule found by this scheduler is within a constant factor of optimal. An experimental evaluation with TPC-H queries on IBM DB2 demonstrates that our scheduler consistently outperforms (up to 4x) conventional schedulers that do not account for query interactions.

UR - http://www.scopus.com/inward/record.url?scp=70349329986&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=70349329986&partnerID=8YFLogxK

U2 - 10.1145/1458082.1458109

DO - 10.1145/1458082.1458109

M3 - Conference contribution

SN - 9781595939913

SP - 183

EP - 192

BT - International Conference on Information and Knowledge Management, Proceedings

ER -