65 research outputs found

    A dichotomy for non-repeating queries with negation in probabilistic databases

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    This paper shows that any non-repeating conjunctive rela-tional query with negation has either polynomial time or #P-hard data complexity on tuple-independent probabilis-tic databases. This result extends a dichotomy by Dalvi and Suciu for non-repeating conjunctive queries to queries with negation. The tractable queries with negation are precisely the hierarchical ones and can be recognised efficiently. 1

    The Dichotomy of Evaluating Homomorphism-Closed Queries on Probabilistic Graphs

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    We study the problem of probabilistic query evaluation on probabilistic graphs, namely, tuple-independent probabilistic databases on signatures of arity two. Our focus is the class of queries that is closed under homomorphisms, or equivalently, the infinite unions of conjunctive queries. Our main result states that all unbounded queries from this class are #P-hard for probabilistic query evaluation. As bounded queries from this class are equivalent to a union of conjunctive queries, they are already classified by the dichotomy of Dalvi and Suciu (2012). Hence, our result and theirs imply a complete data complexity dichotomy, between polynomial time and #P-hardness, for evaluating infinite unions of conjunctive queries over probabilistic graphs. This dichotomy covers in particular all fragments of infinite unions of conjunctive queries such as negation-free (disjunctive) Datalog, regular path queries, and a large class of ontology-mediated queries on arity-two signatures. Our result is shown by reducing from counting the valuations of positive partitioned 2-DNF formulae for some queries, or from the source-to-target reliability problem in an undirected graph for other queries, depending on properties of minimal models. The presented dichotomy result applies to even a special case of probabilistic query evaluation called generalized model counting, where fact probabilities must be 0, 0.5, or 1.Comment: 30 pages. Journal version of the ICDT'20 paper https://drops.dagstuhl.de/opus/volltexte/2020/11939/. Submitted to LMCS. The previous version (version 2) was the same as the ICDT'20 paper with some minor formatting tweaks and 7 extra pages of technical appendi

    OLAP over Probabilistic Data Cubes II:Parallel Materialization and Extended Aggregates

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    Rewriting with Acyclic Queries: Mind Your Head

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    The paper studies the rewriting problem, that is, the decision problem whether, for a given conjunctive query Q and a set ? of views, there is a conjunctive query Q\u27 over ? that is equivalent to Q, for cases where the query, the views, and/or the desired rewriting are acyclic or even more restricted. It shows that, if Q itself is acyclic, an acyclic rewriting exists if there is any rewriting. An analogous statement also holds for free-connex acyclic, hierarchical, and q-hierarchical queries. Regarding the complexity of the rewriting problem, the paper identifies a border between tractable and (presumably) intractable variants of the rewriting problem: for schemas of bounded arity, the acyclic rewriting problem is NP-hard, even if both Q and the views in ? are acyclic or hierarchical. However, it becomes tractable, if the views are free-connex acyclic (i.e., in a nutshell, their body is (i) acyclic and (ii) remains acyclic if their head is added as an additional atom)
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