| Description |
1 online resource (xiv, 105 pages) : illustrations |
| Series |
Synthesis lectures on data management, 2153-5426 ; #20 |
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Synthesis lectures on data management ; #20. 2153-5418
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| Contents |
Preface -- Acknowledgments |
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1. Introduction -- 1.1 Database consistency -- 1.2 An appetizer and overview -- 1.3 Outlook |
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2. The notions of repair and consistent answer -- 2.1 Preliminaries -- 2.2 Consistent data in inconsistent databases -- 2.3 Characterizing consistent data -- 2.4 What do we do then? -- 2.5 Some repair semantics -- 2.5.1 Tuple- and set-inclusion-based repairs -- 2.5.2 Tuple-deletion- and set-inclusion-based repairs -- 2.5.3 Tuple-insertion- and set-inclusion-based repairs -- 2.5.4 Null insertions-based repairs -- 2.5.5 Tuple- and cardinality-based repairs -- 2.5.6 Attribute-based repairs -- 2.5.7 Project-join repairs |
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3. Tractable CQA and query rewriting -- 3.1 Residue-based rewriting -- 3.2 Extending query rewriting -- 3.3 Graphs, hypergraphs and repairs -- 3.4 Keys, trees, forests and roots |
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4. Logically specifying repairs -- 4.1 Specifying repairs with logic programs -- 4.1.1 Disjunctive datalog with stable model semantics -- 4.1.2 Repair programs -- 4.1.3 Magic sets for repair programs -- 4.1.4 Logic programs and referential ICs -- 4.1.5 Null-based tuple insertions -- 4.2 Repairs in annotated predicate logic -- 4.3 Second-order representations |
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5. Decision problems in CQA: complexity and algorithms -- 5.1 The decision problems -- 5.2 Some upper bounds -- 5.3 Some lower bounds -- 5.4 FO rewriting vs. PTIME and above -- 5.5 Combined decidability and complexity -- 5.6 Aggregation -- 5.7 Cardinality-based repairs -- 5.8 Attribute-based repairs -- 5.8.1 Denial constraints and numerical domains -- 5.8.2 Attribute-based repairs and aggregation constraints -- 5.9 Dynamic aspects, fixed-parameter tractability and comparisons |
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6. Repairs and data cleaning -- 6.1 Data cleaning and query answering for FD violations -- 6.2 Repairs and data cleaning under uncertainty -- 6.2.1 Uncertain duplicate elimination -- 6.2.2 Uncertain repairing of FD violations |
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Bibliography -- Author's biography |
| Summary |
Integrity constraints are semantic conditions that a database should satisfy in order to be an appropriate model of external reality. In practice, and for many reasons, a database may not satisfy those integrity constraints, and for that reason it is said to be inconsistent. However, and most likely a large portion of the database is still semantically correct, in a sense that has to be made precise. After having provided a formal characterization of consistent data in an inconsistent database, the natural problem emerges of extracting that semantically correct data, as query answers |
| Bibliography |
Includes bibliographical references (pages 93-103) |
| Notes |
Online resource; title from PDF title page (Morgan & Claypool, viewed Apr. 25, 2012) |
| Subject |
Database management.
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Querying (Computer science)
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First-order logic.
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Predicate (Logic)
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online searching.
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COMPUTERS -- Programming Languages -- SQL.
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Database management
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First-order logic
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Predicate (Logic)
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Querying (Computer science)
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| Form |
Electronic book
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| ISBN |
9781608457632 |
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160845763X |
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9783031018831 |
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3031018834 |
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