research-article

Synthesizing view definitions from data

Authors:

Anish Das Sarma,

Aditya Parameswaran,

Hector Garcia-Molina,

Jennifer WidomAuthors Info & Claims

ICDT '10: Proceedings of the 13th International Conference on Database Theory

Pages 89 - 103

https://doi.org/10.1145/1804669.1804683

Published: 23 March 2010 Publication History

Abstract

Given a database instance and a corresponding view instance, we address the view definitions problem (VDP): Find the most succinct and accurate view definition, when the view query is restricted to a specific family of queries. We study the tradeoffs among succintness, level of approximation, and the family of queries through algorithms and complexity results. For each family of queries, we address three variants of the VDP: (1) Does there exist an exact view definition, and if so find it. (2) Find the best view definition, i.e., one as close to the input view instance as possible, and as succinct as possible. (3) Find an approximate view definition that satisfies an input approximation threshold, and is as succinct as possible.

References

[1]

R. Agrawal and R. Srikant. Fast algorithms for mining association rules. pages 487--499, 1994.

[2]

Philip A. Bernstein. Applying model management to classical meta data problems. In CIDR, 2003.

[3]

P. Bohannon, E. Elnahrawy, W. Fan, and M. Flaster. Putting context into schema matching. In VLDB '06.

Digital Library

[4]

Robert King Brayton, Alberto L. Sangiovanni-Vincentelli, Curtis T. McMullen, and Gary D. Hachtel. Logic Minimization Algorithms for VLSI Synthesis. Kluwer Academic Publishers, 1984.

[5]

R. Carr, S. Doddi, G. Konjevod, and M. Marathe. On the red-blue set cover problem. In SODA '00, pages 345--353.

Digital Library

[6]

H. G-Molina, J. Widom, and J. D. Ullman. Database Systems: The Complete Book. Prentice-Hall, 2002.

[7]

A. Gupta and I. S. Mumick. Maintenance of materialized views: Problems, techniques, and applications. IEEE Data Engineering Bulletin, 18(2), 1995.

[8]

L. Haas. The theory and practice of information integration. In Proc. of ICDT, 2007.

[9]

A. Y. Halevy. Answering queries using views: A survey. VLDB Journal, 4, 2000.

Digital Library

[10]

E. J. McCluskey. Minimization of boolean functions. The Bell System Technical Journal, 1956.

[11]

P. Miettinen. On the positive--negative partial set cover problem. Inf. Process. Lett., 108(4):219--221, 2008.

Digital Library

[12]

T. M. Mitchell. Machine Learning. McGraw-Hill, 1997.

Digital Library

[13]

Pierre Senellart and Georg Gottlob. On the complexity of deriving schema mappings from database instances. In Proc. PODS, pages 23--32, Vancouver, Canada, June 2008.

Digital Library

[14]

P. N. Tan, M. Steinbach, and V. Kumar. Introduction to Data Mining. Addison-Wesley, 2006.

Digital Library

[15]

Q. T. Tran, C. Y. Chan, and S. Parthasarathy. Query by output. In Proc. of ACM SIGMOD, 2009.

Digital Library

[16]

C. Umans, T. Villa, and A. L. Sangiovanni-Vincentelli. Complexity of two-level logic minimization. IEEE Trans. on CAD of Integrated Circuits and Systems, 25(7):1230--1246, 2006.

Digital Library

[17]

Moshe Y. Vardi. The complexity of relational query languages (extended abstract). In STOC '82.

Digital Library

[18]

V. V. Vazirani. Approximation Algorithms. Springer-Verlag, 2001.

Digital Library

Cited By

Bussotti JVeltri ESantoro DPapotti P(2023)Generation of Training Examples for Tabular Natural Language InferenceProceedings of the ACM on Management of Data10.1145/36267301:4(1-27)Online publication date: 12-Dec-2023
https://doi.org/10.1145/3626730
Gong YZhu ZGalhotra SFernandez R(2023)Ver: View Discovery in the Wild2023 IEEE 39th International Conference on Data Engineering (ICDE)10.1109/ICDE55515.2023.00045(503-516)Online publication date: Apr-2023
https://doi.org/10.1109/ICDE55515.2023.00045
Yang JHe YChaudhuri S(2021)Auto-pipelineProceedings of the VLDB Endowment10.14778/3476249.347630314:11(2563-2575)Online publication date: 27-Oct-2021
https://dl.acm.org/doi/10.14778/3476249.3476303
Show More Cited By

Index Terms

Synthesizing view definitions from data
1. Information systems
  1. Data management systems

Recommendations

GRASP with path relinking for the weighted MAXSAT problem

A GRASP with path relinking for finding good-quality solutions of the weighted maximum satisfiability problem (MAX-SAT) is described in this paper. GRASP, or Greedy Randomized Adaptive Search Procedure, is a randomized multistart metaheuristic, where, ...
Processing queries on tree-structured data efficiently
PODS '06: Proceedings of the twenty-fifth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems

This is a survey of algorithms, complexity results, and general solution techniques for efficiently processing queries on tree-structured data. I focus on query languages that compute nodes or tuples of nodes—conjunctive queries, first-order queries, ...
Containment and Optimization of Object-Preserving Conjunctive Queries

In the optimization of queries in an object-oriented database (OODB) system, a natural first step is to use the typing constraints imposed by the schema to transform a query into an equivalent one that logically accesses a minimal set of objects. We ...

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences

ICDT '10: Proceedings of the 13th International Conference on Database Theory

March 2010

260 pages

ISBN:9781605589473

DOI:10.1145/1804669

Editor:
Luc Segoufin
INRIA & ENS Chacan, France

Copyright © 2010 ACM.

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: 23 March 2010

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

Division of Information and Intelligent Systems

Conference

EDBT/ICDT '10

EDBT/ICDT '10: EDBT/ICDT '10 joint conference

March 23 - 25, 2010

Lausanne, Switzerland

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

52
Total Citations
View Citations
344
Total Downloads

Downloads (Last 12 months)17
Downloads (Last 6 weeks)2

Reflects downloads up to 14 Sep 2024

Other Metrics

View Author Metrics

Citations

Cited By

Bussotti JVeltri ESantoro DPapotti P(2023)Generation of Training Examples for Tabular Natural Language InferenceProceedings of the ACM on Management of Data10.1145/36267301:4(1-27)Online publication date: 12-Dec-2023
https://doi.org/10.1145/3626730
Gong YZhu ZGalhotra SFernandez R(2023)Ver: View Discovery in the Wild2023 IEEE 39th International Conference on Data Engineering (ICDE)10.1109/ICDE55515.2023.00045(503-516)Online publication date: Apr-2023
https://doi.org/10.1109/ICDE55515.2023.00045
Yang JHe YChaudhuri S(2021)Auto-pipelineProceedings of the VLDB Endowment10.14778/3476249.347630314:11(2563-2575)Online publication date: 27-Oct-2021
https://dl.acm.org/doi/10.14778/3476249.3476303
Li MChan C(2020)Efficient Query Reverse Engineering Using Table FragmentsDatabase Systems for Advanced Applications10.1007/978-3-030-59419-0_25(406-422)Online publication date: 22-Sep-2020
https://doi.org/10.1007/978-3-030-59419-0_25
Fariha AMeliou A(2019)Example-driven query intent discoveryProceedings of the VLDB Endowment10.14778/3342263.334226612:11(1262-1275)Online publication date: 1-Jul-2019
https://dl.acm.org/doi/10.14778/3342263.3342266
Roughgarden T(2019)Beyond worst-case analysisCommunications of the ACM10.1145/323253562:3(88-96)Online publication date: 21-Feb-2019
https://dl.acm.org/doi/10.1145/3232535
Zave PRexford J(2019)The compositional architecture of the internetCommunications of the ACM10.1145/322658862:3(78-87)Online publication date: 21-Feb-2019
https://dl.acm.org/doi/10.1145/3226588
Kimmig AMemory AMiller RGetoor L(2019)A Collective, Probabilistic Approach to Schema Mapping Using Diverse Noisy EvidenceIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2018.286578531:8(1426-1439)Online publication date: 1-Aug-2019
https://dl.acm.org/doi/10.1109/TKDE.2018.2865785
Martins D(2019)Reverse engineering database queries from examplesInformation Systems10.1016/j.is.2019.03.00283:C(89-100)Online publication date: 1-Jul-2019
https://dl.acm.org/doi/10.1016/j.is.2019.03.002
Yilmaz GWattanawaroon TXu LNigam AElmore AParameswaran ADas GJermaine CBernstein P(2018)DataDiffProceedings of the 2018 International Conference on Management of Data10.1145/3183713.3193564(1769-1772)Online publication date: 27-May-2018
https://dl.acm.org/doi/10.1145/3183713.3193564
Show More Cited By

View Options

Get Access

Login options

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

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents