By Leopoldo Bertossi, M. Tamer Ozsu
Integrity constraints are semantic stipulations database may still fulfill so as to be a suitable version of exterior truth. In perform, and for plenty of purposes, a database won't fulfill these integrity constraints, and as a result it really is stated to be inconsistent. in spite of the fact that, and probably, a wide component to the database remains to be semantically right, in a feeling that should be made special. After having supplied a proper characterization of constant information in an inconsistent database, the common challenge emerges of extracting that semantically right information, as question solutions. The constant info in an inconsistent database is generally characterised because the info that persists throughout all of the database circumstances which are constant and minimally fluctuate from the inconsistent example. these are the so-called maintenance of the database. specifically, the constant solutions to a question posed to the inconsistent database are these solutions that may be at the same time bought from the entire database upkeep. As anticipated, the proposal of fix calls for an enough inspiration of distance that permits for the comparability of databases with recognize to how a lot they range from the inconsistent example. in this foundation, the minimality on maintenance might be accurately formulated. during this monograph we current and talk about those primary innovations, diversified fix semantics, algorithms for computing constant solutions to queries, and in addition complexity-theoretic effects concerning the computation of upkeep and doing constant question answering. desk of Contents: advent / The Notions of fix and constant solution / Tractable CQA and question Rewriting / Logically Specifying upkeep / choice difficulties in CQA: Complexity and Algorithms / upkeep and information cleansing
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Database Repairing and Consistent Query Answering
Integrity constraints are semantic stipulations database should still fulfill to be able to be a suitable version of exterior fact. In perform, and for lots of purposes, a database would possibly not fulfill these integrity constraints, and hence it really is acknowledged to be inconsistent. notwithstanding, and probably, a wide section of the database continues to be semantically right, in a feeling that should be made distinct.
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Actually, there are cases where tractability of CQA based on project-join repairs can be achieved while tuple-based repairs applied directly to the original instance lead to an intractable CQA problem (cf. Chapter 5). Some comparisons of different repair semantics can be found in [Lopatenko and Bertossi, 2007] and [Afrati and Kolaitis, 2009]. 5. However, all the semantics superficially described in this section will be revisited in Chapter 5. 1 RESIDUE-BASED REWRITING A first attempt to do query rewriting was proposed by Arenas et al.
Denial constraint violations can be solved only by tuple deletions, but inclusion dependency violations by both tuple deletions and 30 3. TRACTABLE CQA AND QUERY REWRITING insertions. However, Chomicki and Marcinkowski [2005] consider only tuple deletions for inclusion dependencies. With denial constraints we may have to generate an hypergraph instead of a graph. Consider the denial constraint, δ : ∀xyz¬(P (x, y) ∧ P (x, z) ∧ R(y, z)), and the inconsistent instance D = {P (a, b), P (a, c), P (e, f ), R(b, c), R(e, f )}.
First, consider the query Q1 (x) : R(x) about the tuples in the table for R. In this case, if a tuple belongs to R, say R(d) ∈ D, no violation can be produced wrt ϕ. So, we do not modify the atom in Q1 . Now, consider the query Q2 (x) : P (x) about the tuples in P . In this case, if a tuple belongs to P , say P (d) ∈ D, then that tuple is involved in a violation if R(d) ∈ / D. In consequence, for P (d) to be a consistent answer, R(d) should also be in D. Thus, we modify the query by adding this additional condition: Q2 (x) : P (x) ∧ R(x).