Article

Free access

How to roll a join: asynchronous incremental view maintenance

Authors:

Kenneth Salem,

Kevin Beyer,

Bruce Lindsay,

Roberta CochraneAuthors Info & Claims

SIGMOD '00: Proceedings of the 2000 ACM SIGMOD international conference on Management of data

Pages 129 - 140

https://doi.org/10.1145/342009.335393

Published: 16 May 2000 Publication History

PDF eReader

Abstract

Incremental refresh of a materialized join view is often less expensive than a full, non-incremental refresh. However, it is still a potentially costly atomic operation. This paper presents an algorithm that performs incremental view maintenance as a series of small, asynchronous steps. The size of each step can be controlled to limit contention between the refresh process and concurrent operations that access the materialized view or the underlying relations. The algorithm supports point-in-time refresh, which allows a materialized view to be refreshed to any time between the last refresh and the present.

References

[1]

D Agrawal, A. E1 Abbadi, A. Singh, and T. Yurek. Efficient view maintenance at data warehouses. In Proceedings of the A CM SIGMOD International Conference on Management of Data, pages 417- 427, 1997.

Digital Library

Google Scholar

[2]

l#andall Bello, Karl Dias, Alan Downing, James Feenan, Jim Finnerty, William Norcott, Harry Sun, Andrew Witkowski, and Mohamed Ziauddin. Materialized views in Oracle. In Proceedings of the International Conference on Very Large Data Bases, pages 659-664, 1998.

Digital Library

Google Scholar

[3]

Jos6 A. Blakeley, Per-Ake Larson, and Frank Win. Tompa. Efficiently updating materialized views. In Proceedings of the A CM SIGMOD International Conference on Management of Data, pages 61-71, 1986.

Digital Library

Google Scholar

[4]

Latha S. Colby, Timothy Griffin, Leonid Libkin, Inderpal Singh Mumick, and Howard Trickey. Algorithms for deferred view maintenance. In Proceedings of the A CM SIGMOD International Conference on Management of Data, pages 469- 480, 1996.

Digital Library

Google Scholar

[5]

Ashish Gupta, H. V. Jagadish, and Inderpal Singh Mumick. Data integration using self-maintainable views. In International Conference on Extending Database Technology, pages 140-144, 1996.

Digital Library

Google Scholar

[6]

Ashish Gupta and Inderpal Singh Mumick. Maintenance of materialized views: Problems, techniques, and applications. Bulletin of the IEEE Technical Committee on Data Engineering, i8(2):3-i9, i995.

Google Scholar

[7]

Ashish Gupta, Inderpal Singh Mumick, and V. S. Subrahmanian. Maintaining views incrementally. In Proceedings of the A CM SIGMOD International Conference on Management of Data, pages 157- 167, 1993.

Digital Library

Google Scholar

[8]

Inderpal Singh Mumick, Dallan Quass, and Barinderpal Singh Mumick. Maintenance of data cubes and summary tables in a warehouse. In Proceedings of the A CM SIGMOD International Conference on Management of Data, pages 100-111, 1997.

Digital Library

Google Scholar

[9]

Dallan Quass, Ashish Gupta, Inderpal Singh Mumick, and Jennifer Widom. Making views selfmaintainable for data warehousing. In Conference on Parallel and Distributed Information Systems, pages 158-169, 1996.

Digital Library

Google Scholar

[10]

Dallan Quass and Jennifer Widom. On-line warehouse view maintenance. In Proceedings of the A CM SIGMOD International Conference on Management of Data, pages 393-404, 1997.

Digital Library

Google Scholar

[11]

K. Salem, K. Beyer, B. Lindsay, and It. Cochrane. How to roll a join: Asynchronous incremental view maintenance. Technical l#eport CS-2000-6, Dept. of Computer Science, University of Waterloo, February 2000.

Google Scholar

[12]

Yue Zhuge, Hector Garcia-Molina, Joachim Hammer, and Jennifer Widom. View maintenance in a warehousing environment. In Proceedings of the A CM SIGMOD International Conference on Management of Data, pages 316-327, 1995.

Digital Library

Google Scholar

[13]

Yue Zhuge, Hector Garcia-Molina, and Janet Wiener. The strobe algorithms for multi-source warehouse consistency. In Conference on Parallel and Distributed Information Systems, 1996.

Digital Library

Google Scholar

Cited By

View all

Kara ANikolic MOlteanu DZhang H(2023)F-IVM: analytics over relational databases under updatesThe VLDB Journal10.1007/s00778-023-00817-w33:4(903-929)Online publication date: 14-Nov-2023
https://doi.org/10.1007/s00778-023-00817-w
Zhang YWang YWillsey MTatlock Z(2022)Relational e-matchingProceedings of the ACM on Programming Languages10.1145/34986966:POPL(1-22)Online publication date: 12-Jan-2022
https://dl.acm.org/doi/10.1145/3498696
Anzum NSalihoglu SKalavri VYakovets N(2021)R2GSync and edge viewsProceedings of the 4th ACM SIGMOD Joint International Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA)10.1145/3461837.3464515(1-9)Online publication date: 20-Jun-2021
https://dl.acm.org/doi/10.1145/3461837.3464515
Show More Cited By

Index Terms

How to roll a join: asynchronous incremental view maintenance
1. Information systems
  1. Data management systems
    1. Database design and models
      1. Physical data models

Recommendations

How to roll a join: asynchronous incremental view maintenance

Incremental refresh of a materialized join view is often less expensive than a full, non-incremental refresh. However, it is still a potentially costly atomic operation. This paper presents an algorithm that performs incremental view maintenance as a ...
Mediator join indices
RIDE '97: Proceedings of the 7th International Workshop on Research Issues in Data Engineering (RIDE '97) High Performance Database Management for Large-Scale Applications

A mediator join index (MJI) is proposed to speed up N-way inter-database joins by reducing the amount of data transfer during evaluation. A family of algorithms, the query scrubbing algorithms (QSA), are developed to maintain MJI and to evaluate queries ...
Multi-way spatial join selectivity for the ring join graph

Efficient spatial query processing is very important since the applications of the spatial DBMS (e.g. GIS, CAD/CAM, LBS) handle massive amount of data and consume much time. Many spatial queries contain the multi-way spatial join due to the fact that ...

Comments

Information & Contributors

Information

Published In

SIGMOD '00: Proceedings of the 2000 ACM SIGMOD international conference on Management of data

May 2000

604 pages

ISBN:1581132174

DOI:10.1145/342009

Chairmen:
Maggie Dunham
Southern Methodist Univ.
,
Jeffrey F. Naughton
Univ. of Wisconsin-Madison
,
Weidong Chen
Southern Methodist Univ.
,
Nick Koudas
AT &T Labs

ACM SIGMOD Record Volume 29, Issue 2
June 2000
609 pages
ISSN:0163-5808
DOI:10.1145/335191
Editors:
Weidong Chen
Southern Methodist Univ., Dallas, TX
,
Jeffrey Naughton
Univ. of Wisconsin-Madison, Madison
,
Philip A. Bernstein
Microsoft
Issue’s Table of Contents

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]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 May 2000

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Qualifiers

Article

Conference

SIGMOD/PODS00

Sponsor:

SIGMOD

SIGMOD/PODS00: ACM International Conference on Management of Data and Symposium on Principles of Database Systems

May 15 - 18, 2000

Texas, Dallas, USA

Acceptance Rates

SIGMOD '00 Paper Acceptance Rate 42 of 248 submissions, 17%;

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

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

84
Total Citations
View Citations
380
Total Downloads

Downloads (Last 12 months)162
Downloads (Last 6 weeks)26

Reflects downloads up to 27 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

Kara ANikolic MOlteanu DZhang H(2023)F-IVM: analytics over relational databases under updatesThe VLDB Journal10.1007/s00778-023-00817-w33:4(903-929)Online publication date: 14-Nov-2023
https://doi.org/10.1007/s00778-023-00817-w
Zhang YWang YWillsey MTatlock Z(2022)Relational e-matchingProceedings of the ACM on Programming Languages10.1145/34986966:POPL(1-22)Online publication date: 12-Jan-2022
https://dl.acm.org/doi/10.1145/3498696
Anzum NSalihoglu SKalavri VYakovets N(2021)R2GSync and edge viewsProceedings of the 4th ACM SIGMOD Joint International Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA)10.1145/3461837.3464515(1-9)Online publication date: 20-Jun-2021
https://dl.acm.org/doi/10.1145/3461837.3464515
Wang LYu JWeifeng WMei FLu WChen HXu MMei Z(2020)Research on LSB-based Digital Image Information Camouflage Algorithm2020 IEEE International Conference on Advances in Electrical Engineering and Computer Applications( AEECA)10.1109/AEECA49918.2020.9213706(933-938)Online publication date: Aug-2020
https://doi.org/10.1109/AEECA49918.2020.9213706
Athanassoulis MBøgh KIdreos S(2019)Optimal column layout for hybrid workloadsProceedings of the VLDB Endowment10.14778/3358701.335870712:13(2393-2407)Online publication date: 1-Sep-2019
https://dl.acm.org/doi/10.14778/3358701.3358707
Phani ATekur CSai Krishna R(2019)Commit Time Materialized View Maintenance for Bulk Load Operations in Teradata2019 IEEE International Conference on Electrical, Computer and Communication Technologies (ICECCT)10.1109/ICECCT.2019.8869100(1-5)Online publication date: Mar-2019
https://doi.org/10.1109/ICECCT.2019.8869100
Bei YPham TAggarwal ATran NDave JBear CLeuchtenburg M(2019)Vertica Flattened Tables and Live Aggregate Projections: A Column-based Alternative to Materialized Views for Analytics2019 IEEE International Conference on Big Data (Big Data)10.1109/BigData47090.2019.9006271(1749-1758)Online publication date: Dec-2019
https://doi.org/10.1109/BigData47090.2019.9006271
Gjengset JSchwarzkopf MBehrens JAraújo LEk MKohler EKaashoek MMorris RArpaci-Dusseau AVoelker G(2018)NoriaProceedings of the 13th USENIX conference on Operating Systems Design and Implementation10.5555/3291168.3291185(213-231)Online publication date: 8-Oct-2018
https://dl.acm.org/doi/10.5555/3291168.3291185
Cai QXie ZZhang MChen GJagadish HOoi B(2018)Effective temporal dependence discovery in time series dataProceedings of the VLDB Endowment10.14778/3204028.320403311:8(893-905)Online publication date: 1-Apr-2018
https://dl.acm.org/doi/10.14778/3204028.3204033
Berti-Équille LHarmouch HNaumann FNovelli NThirumuruganathan S(2018)Discovery of genuine functional dependencies from relational data with missing valuesProceedings of the VLDB Endowment10.14778/3204028.320403211:8(880-892)Online publication date: 1-Apr-2018
https://dl.acm.org/doi/10.14778/3204028.3204032
Show More Cited By

View Options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Cited By

Index Terms

Recommendations

How to roll a join: asynchronous incremental view maintenance

Mediator join indices

Multi-way spatial join selectivity for the ring join graph