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The Data Complexity of Consistent Query Answering for Self-Join-Free Conjunctive Queries Under Primary Key Constraints

Published: 20 May 2015 Publication History

Abstract

A relational database is said to be uncertain if primary key constraints can possibly be violated. A repair (or possible world) of an uncertain database is obtained by selecting a maximal number of tuples without ever selecting two distinct tuples with the same primary key value. For any Boolean query q, CERTAINTY(q) is the problem that takes an uncertain database db as input, and asks whether q is true in every repair of db. The complexity of this problem has been particularly studied for q ranging over the class of self-join-free Boolean conjunctive queries. A research challenge is to determine, given q, whether CERTAINTY(q) belongs to complexity classes FO, P, or coNP-complete. In this paper, we combine existing techniques for studying the above complexity classification task. We show that for any self-join-free Boolean conjunctive query q, it can be decided whether or not CERTAINTY(q) is in FO. Further, for any self-join-free Boolean conjunctive query q, CERTAINTY(q) is either in P or coNP-complete, and the complexity dichotomy is effective. This settles a research question that has been open for ten years.

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      cover image ACM Conferences
      PODS '15: Proceedings of the 34th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems
      May 2015
      358 pages
      ISBN:9781450327572
      DOI:10.1145/2745754
      • General Chair:
      • Tova Milo,
      • Program Chair:
      • Diego Calvanese
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      Published: 20 May 2015

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      Author Tags

      1. conjunctive queries
      2. consistent query answering
      3. primary keys

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      • NSF

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      SIGMOD/PODS'15
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      SIGMOD/PODS'15: International Conference on Management of Data
      May 31 - June 4, 2015
      Victoria, Melbourne, Australia

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      PODS '15 Paper Acceptance Rate 25 of 80 submissions, 31%;
      Overall Acceptance Rate 642 of 2,707 submissions, 24%

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      • (2024)Naive Bayes classifiers over missing dataProceedings of the 41st International Conference on Machine Learning10.5555/3692070.3692227(3913-3934)Online publication date: 21-Jul-2024
      • (2024)Combined Approximations for Uniform Operational Consistent Query AnsweringProceedings of the ACM on Management of Data10.1145/36516002:2(1-16)Online publication date: 14-May-2024
      • (2024)Consistent Query Answering for Primary Keys on Rooted Tree QueriesProceedings of the ACM on Management of Data10.1145/36511392:2(1-26)Online publication date: 14-May-2024
      • (2023)LinCQA: Faster Consistent Query Answering with Linear Time GuaranteesProceedings of the ACM on Management of Data10.1145/35887181:1(1-25)Online publication date: 30-May-2023
      • (2022)Uniform Operational Consistent Query AnsweringProceedings of the 41st ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems10.1145/3517804.3526230(393-402)Online publication date: 12-Jun-2022
      • (2021)Consistent Query Answering for Primary Keys on Path QueriesProceedings of the 40th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems10.1145/3452021.3458334(215-232)Online publication date: 20-Jun-2021
      • (2021)Benchmarking Approximate Consistent Query AnsweringProceedings of the 40th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems10.1145/3452021.3458309(233-246)Online publication date: 20-Jun-2021
      • (2021)Consistent Query Answering for Primary Keys in DatalogTheory of Computing Systems10.1007/s00224-020-09985-665:1(122-178)Online publication date: 1-Jan-2021
      • (2020)Optimization of Answer Set Programs for Consistent Query Answering by Means of First-Order RewritingProceedings of the 29th ACM International Conference on Information & Knowledge Management10.1145/3340531.3411911(25-34)Online publication date: 19-Oct-2020
      • (2020)Approximate Query Answering over Incomplete DataComplex Pattern Mining10.1007/978-3-030-36617-9_13(213-227)Online publication date: 15-Jan-2020
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