extended-abstract

CAvSAT: A System for Query Answering over Inconsistent Databases

Author:

Akhil A. DixitAuthors Info & Claims

SIGMOD '19: Proceedings of the 2019 International Conference on Management of Data

Pages 1823 - 1825

https://doi.org/10.1145/3299869.3300095

Published: 25 June 2019 Publication History

Abstract

Managing inconsistencies in databases is an old, but recurring, problem. An inconsistent database is a database that violates one or more integrity constraints. In the real-world, inconsistent databases arise in several different contexts, including data warehousing and information integration. The framework of database repairs and consistent query answering (CQA) is a principled way of handling inconsistencies. In this work, we propose a novel approach that has a potential to build a comprehensive and scalable CQA system. We report preliminary experimental results on a prototype CQA system CAvSAT (Consistent Answering via Satisfiability), implemented using this approach.

References

[1]

Marcelo Arenas, Leopoldo Bertossi, and Jan Chomicki. 1999. Consistent Query Answers in Inconsistent Databases. In Proceedings of the Eighteenth ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems (PODS '99). ACM, New York, NY, USA, 68--79.

Digital Library

[2]

Marcelo Arenas, Leopoldo E. Bertossi, and Jan Chomicki. 2003. Answer sets for consistent query answering in inconsistent databases. TPLP, Vol. 3, 4--5 (2003), 393--424.

Digital Library

[3]

Pablo Barceló and Leopoldo E. Bertossi. 2003. Logic Programs for Querying Inconsistent Databases. In Practical Aspects of Declarative Languages, 5th International Symposium, PADL 2003, New Orleans, LA, USA, January 13--14, 2003, Proceedings. 208--222.

Digital Library

[4]

Philip A. Bernstein and Laura M. Haas. 2008. Information Integration in the Enterprise. Commun. ACM, Vol. 51, 9 (Sept. 2008), 72--79.

Digital Library

[5]

Leopoldo E. Bertossi. 2011. Database Repairing and Consistent Query Answering .Morgan & Claypool Publishers.

Digital Library

[6]

Balder Cate, Gaëlle Fontaine, and Phokion G. Kolaitis. 2015. On the Data Complexity of Consistent Query Answering. Theor. Comp. Sys., Vol. 57, 4 (Nov. 2015), 843--891.

Digital Library

[7]

Jan Chomicki, Jerzy Marcinkowski, and Slawomir Staworko. 2004 a. Computing Consistent Query Answers Using Conflict Hypergraphs. In Proceedings of the Thirteenth ACM International Conference on Information and Knowledge Management (CIKM '04). ACM, New York, NY, USA, 417--426.

Digital Library

[8]

Jan Chomicki, Jerzy Marcinkowski, and Slawomir Staworko. 2004 b. Hippo: A System for Computing Consistent Answers to a Class of SQL Queries. In Advances in Database Technology - EDBT 2004. Springer Berlin Heidelberg, Berlin, Heidelberg, 841--844.

[9]

Ariel Fuxman, Elham Fazli, and Renée J. Miller. 2005 a. ConQuer: Efficient Management of Inconsistent Databases. In Proceedings of the 2005 ACM SIGMOD International Conference on Management of Data (SIGMOD '05). ACM, New York, NY, USA, 155--166.

Digital Library

[10]

Ariel Fuxman, Diego Fuxman, and Renée J. Miller. 2005 b. ConQuer: A System for Efficient Querying over Inconsistent Databases. In Proceedings of the 31st International Conference on Very Large Data Bases (VLDB '05). VLDB Endowment, 1354--1357. http://dl.acm.org/citation.cfm?id=1083592.1083774

Digital Library

[11]

Ariel Fuxman and Renée J. Miller. 2007. First-order Query Rewriting for Inconsistent Databases. J. Comput. Syst. Sci., Vol. 73, 4 (June 2007), 610--635.

Digital Library

[12]

Gianluigi Greco, Sergio Greco, and Ester Zumpano. 2003. A Logical Framework for Querying and Repairing Inconsistent Databases. IEEE Trans. on Knowl. and Data Eng., Vol. 15, 6 (Nov. 2003), 1389--1408.

Digital Library

[13]

Ihab F. Ilyas and Xu Chu. 2015. Trends in Cleaning Relational Data: Consistency and Deduplication. Found. Trends databases, Vol. 5, 4 (Oct. 2015), 281--393.

Digital Library

[14]

Phokion G. Kolaitis and Enela Pema. 2012. A Dichotomy in the Complexity of Consistent Query Answering for Queries with Two Atoms. Inf. Process. Lett., Vol. 112, 3 (Jan. 2012), 77--85.

Digital Library

[15]

Phokion G. Kolaitis, Enela Pema, and Wang-Chiew Tan. 2013. Efficient Querying of Inconsistent Databases with Binary Integer Programming. PVLDB, Vol. 6, 6 (2013), 397--408.

Digital Library

[16]

Paraschos Koutris and Jef Wijsen. 2015. The Data Complexity of Consistent Query Answering for Self-Join-Free Conjunctive Queries Under Primary Key Constraints. In Proceedings of the 34th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems (PODS '15). ACM, New York, NY, USA, 17--29.

Digital Library

[17]

Paraschos Koutris and Jef Wijsen. 2016. Consistent Query Answering for Primary Keys. SIGMOD Rec., Vol. 45, 1 (June 2016), 15--22.

Digital Library

[18]

Paraschos Koutris and Jef Wijsen. 2017. Consistent Query Answering for Self-Join-Free Conjunctive Queries Under Primary Key Constraints. ACM Trans. Database Syst., Vol. 42, 2, Article 9 (June 2017), bibinfonumpages45 pages.

Digital Library

[19]

Marco Manna, Francesco Ricca, and Giorgio Terracina. 2015. Taming Primary Key Violations to Query Large Inconsistent Data. CoRR, Vol. abs/1507.06103 (2015). arxiv: 1507.06103 http://arxiv.org/abs/1507.06103

[20]

Mó nica Caniupá n Marileo and Leopoldo E. Bertossi. 2010. The consistency extractor system: Answer set programs for consistent query answering in databases. Data Knowl. Eng., Vol. 69, 6 (2010), 545--572.

Digital Library

[21]

City of Chicago. 2011. Food Inspections. https://data.cityofchicago.org/Health-Human-Services/Food-Inspections/4ijn-s7e5 Retrieved Nov 15, 2018 from

[22]

Department of Health and Mental Hygiene (DOHMH). 2014. New York City Restaurant Inspection Results. https://data.cityofnewyork.us/Health/DOHMH-New-York-City-Restaurant-Inspection-Results/43nn-pn8j Retrieved Nov 15, 2018 from

[23]

Moshe Y. Vardi. 2009. Symbolic Techniques in Propositional Satisfiability Solving. In Theory and Applications of Satisfiability Testing - SAT 2009. Springer Berlin Heidelberg, Berlin, Heidelberg, 2--3.

Digital Library

[24]

Jef Wijsen. 2009. Consistent Query Answering Under Primary Keys: A Characterization of Tractable Queries. In Proceedings of the 12th International Conference on Database Theory (ICDT '09). ACM, New York, NY, USA, 42--52.

Digital Library

[25]

Jef Wijsen. 2010. On the First-order Expressibility of Computing Certain Answers to Conjunctive Queries over Uncertain Databases. In Proceedings of the Twenty-ninth ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems (PODS '10). ACM, New York, NY, USA, 179--190.

Digital Library

[26]

Jef Wijsen. 2012. Certain Conjunctive Query Answering in First-order Logic. ACM Trans. Database Syst., Vol. 37, 2, Article 9 (June 2012), bibinfonumpages35 pages.

Digital Library

[27]

Jef Wijsen. 2013. Charting the Tractability Frontier of Certain Conjunctive Query Answering. In Proceedings of the 32Nd ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems (PODS '13). ACM, New York, NY, USA, 189--200.

Digital Library

Cited By

Miao DZhang PLi JWang YCai Z(2022)Approximation and inapproximability results on computing optimal repairsThe VLDB Journal10.1007/s00778-022-00738-032:1(173-197)Online publication date: 12-Apr-2022
https://doi.org/10.1007/s00778-022-00738-0
Dixit AKolaitis PLi GLi ZIdreos SSrivastava D(2021)CAvSAT: Answering Aggregation Queries over Inconsistent Databases via SAT SolvingProceedings of the 2021 International Conference on Management of Data10.1145/3448016.3452749(2701-2705)Online publication date: 9-Jun-2021
https://dl.acm.org/doi/10.1145/3448016.3452749
Miao DCai ZLi JGao XLiu X(2020)The computation of optimal subset repairsProceedings of the VLDB Endowment10.14778/3407790.340780913:12(2061-2074)Online publication date: 14-Sep-2020
https://dl.acm.org/doi/10.14778/3407790.3407809

Index Terms

CAvSAT: A System for Query Answering over Inconsistent Databases

Recommendations

CAvSAT: Answering Aggregation Queries over Inconsistent Databases via SAT Solving
SIGMOD '21: Proceedings of the 2021 International Conference on Management of Data

Consistent Query Answering (CQA) is a rigorous and principled approach to answering queries posed against inconsistent databases. Computing consistent answers to a Select-Project-Join (SPJ) query or an SPJ query with aggregation operators on a given ...
First-order query rewriting for inconsistent databases

We consider the problem of retrieving consistent answers over databases that might be inconsistent with respect to a set of integrity constraints. In particular, we concentrate on sets of constraints that consist of key dependencies, and we give an ...
Benchmarking Approximate Consistent Query Answering
PODS'21: Proceedings of the 40th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems

Consistent query answering (CQA) aims to deliver meaningful answers when queries are evaluated over inconsistent databases. Such answers must be certainly true in all repairs, which are consistent databases whose difference from the inconsistent one is ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

SIGMOD '19: Proceedings of the 2019 International Conference on Management of Data

June 2019

2106 pages

ISBN:9781450356435

DOI:10.1145/3299869

General Chairs:
Peter Boncz
CWI & Vrije Universiteit Amsterdam, The Netherlands
,
Stefan Manegold
CWI & Universiteit Leiden, The Netherlands
,
Program Chairs:
Anastasia Ailamaki
EPFL, Switzerland
,
Amol Deshpande
University of Maryland, USA
,
Tim Kraska
MIT, USA

Copyright © 2019 Owner/Author.

Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Sponsors

SIGMOD: ACM Special Interest Group on Management of Data

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 June 2019

Check for updates

Author Tags

Qualifiers

Extended-abstract

Conference

SIGMOD/PODS '19

Sponsor:

SIGMOD

SIGMOD/PODS '19: International Conference on Management of Data

June 30 - July 5, 2019

Amsterdam, Netherlands

Acceptance Rates

SIGMOD '19 Paper Acceptance Rate 88 of 430 submissions, 20%;

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

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

3
Total Citations
View Citations
174
Total Downloads

Downloads (Last 12 months)5
Downloads (Last 6 weeks)0

Reflects downloads up to 05 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

Miao DZhang PLi JWang YCai Z(2022)Approximation and inapproximability results on computing optimal repairsThe VLDB Journal10.1007/s00778-022-00738-032:1(173-197)Online publication date: 12-Apr-2022
https://doi.org/10.1007/s00778-022-00738-0
Dixit AKolaitis PLi GLi ZIdreos SSrivastava D(2021)CAvSAT: Answering Aggregation Queries over Inconsistent Databases via SAT SolvingProceedings of the 2021 International Conference on Management of Data10.1145/3448016.3452749(2701-2705)Online publication date: 9-Jun-2021
https://dl.acm.org/doi/10.1145/3448016.3452749
Miao DCai ZLi JGao XLiu X(2020)The computation of optimal subset repairsProceedings of the VLDB Endowment10.14778/3407790.340780913:12(2061-2074)Online publication date: 14-Sep-2020
https://dl.acm.org/doi/10.14778/3407790.3407809

View Options

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.

Figures

Tables

Media

View Table of Conten