Benchmarking the Chase

Benedikt, Michael; Konstantinidis, George; Mecca, Giansalvatore; Motik, Boris; Papotti, Paolo; Santoro, Donatello; Tsamoura, Efthymia

doi:10.1145/3034786.3034796

Cited by 79 publications

(125 citation statements)

References 40 publications

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“…Most subsequent research has been directed at identifying fragments of SQL where equivalence is decidable, under set semantics [17,47] or bag semantics [24]. This line of work, focused on theoretical aspects of the problem [51,47,41], led to very few implementations, most of which were restricted to applying the chase procedure to conjunctive queries [14].…”

Section: Introductionmentioning

confidence: 99%

Axiomatic foundations and algorithms for deciding semantic equivalences of SQL queries

et al. 2018

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Deciding the equivalence of SQL queries is a fundamental problem in data management. As prior work has mainly focused on studying the theoretical limitations of the problem, very few implementations for checking such equivalences exist. In this paper, we present a new formalism and implementation for reasoning about the equivalences of SQL queries. Our formalism, Usemiring, extends SQL's semiring semantics with unbounded summation and duplicate elimination. U-semiring is defined using only very few axioms and can thus be easily implemented using proof assistants such as Coq for automated query reasoning. Yet, they are sufficient enough to enable us reason about sophisticated SQL queries that are evaluated over bags and sets, along with various integrity constraints. To evaluate the effectiveness of U-semiring, we have used it to formally verify 68 equivalent queries and rewrite rules from both classical data management research papers and real-world SQL engines, where many of them have never been proven correct before.

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Section: Introductionmentioning

confidence: 99%

Axiomatic foundations and algorithms for deciding semantic equivalences of SQL queries

et al. 2018

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“…Recall that SPARQL is the standard language for querying the Semantic Web, 6 while OWL 2 QL is a prominent profile of the OWL 2 Web Ontology Language, the standard formalism for modeling Semantic Web ontologies. 7 We give a simple example of a warded set of TGDs, which is extracted from the set of TGDs that encodes the OWL 2 direct semantics entailment regime for OWL 2 QL. Example 3.3.…”

Section: The Logical Core Of Vadalogmentioning

confidence: 99%

The Space-Efficient Core of Vadalog

Berger

Gottlob

Pieris

et al. 2019

Proceedings of the 38th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems

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Vadalog is a system for performing complex reasoning tasks such as those required in advanced knowledge graphs. The logical core of the underlying Vadalog language is the warded fragment of tuple-generating dependencies (TGDs). This formalism ensures tractable reasoning in data complexity, while a recent analysis focusing on a practical implementation led to the reasoning algorithm around which the Vadalog system is built. A fundamental question that has emerged in the context of Vadalog is the following: can we limit the recursion allowed by wardedness in order to obtain a formalism that provides a convenient syntax for expressing useful recursive statements, and at the same time achieves space-efficiency? After analyzing several real-life examples of warded sets of TGDs provided by our industrial partners, as well as recent benchmarks, we observed that recursion is often used in a restricted way: the body of a TGD contains at most one atom whose predicate is mutually recursive with a predicate in the head. We show that this type of recursion, known as piece-wise linear in the Datalog literature, is the answer to our main question. We further show that piece-wise linear recursion alone, without the wardedness condition, is not enough as it leads to the undecidability of reasoning. We finally study the relative expressiveness of the query languages based on (piece-wise linear) warded sets of TGDs.(1) Recursion over KGs. It is able to express full recursion and joins, which are needed to express complex reasoning tasks over KGs. Moreover, navigational capabilities, empowered by recursion, are vital for graph-based structures.(2) Ontological Reasoning over KGs. After adding a very mild and easy to handle negation, the language is able to express SPARQL reasoning under the OWL 2 QL entailment regime. Recall that SPARQL is the standard language for querying

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“…With respect to mapping execution, an important category of related systems are the chase-based tools [10], designed to enforce a set of constraints (e.g., in the form of tgds) over a database instance for several goals, including data exchange and data cleaning. Native implementations of most advanced chase techniques often lead to very good performance, although their general purpose target and absence of domain-specific features (for example many even lack algebraic operations) make an evaluation over the statistical setting not promising.…”

Section: Scaling In Statistical Data Processingmentioning

confidence: 99%

“…Therefore, in (4), operator op M 1 considers twice at least a dimension tuple that in σ 2 is considered once, resulting in J = J . 10 To violate condition (b), it is sufficient to consider any two mathematical operations such that the distributivity does not hold to show that the values of the calculated measures are not correct. In effects, in these cases, distributing the application of op The above result characterizes the problem of telling whether two tgds are composable in the presence of generic operators.…”

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confidence: 99%

Executable schema mappings for statistical data processing

Atzeni

Bellomarini

Bugiotti

et al. 2017

Distrib Parallel Databases

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Data processing is the core of any statistical information system. Statisticians are interested in specifying transformations and manipulations of data at a high level, in terms of entities of statistical models. We illustrate here a proposal where a high-level language, EXL, is used for the declarative specification of statistical programs, and a translation into executable form in various target systems is available. The language is based on the theory of schema mappings, in particular those defined by a specific class of tgds, which we actually use to optimize user programs and facilitate the translation towards several target systems. The characteristics of such class guarantee good tractability properties and the applicability in Big Data settings. A concrete implementation, EXLEngine, has been carried out and is currently used at the Bank of Italy.

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Benchmarking the Chase

Cited by 79 publications

References 40 publications

Axiomatic foundations and algorithms for deciding semantic equivalences of SQL queries

Axiomatic foundations and algorithms for deciding semantic equivalences of SQL queries

The Space-Efficient Core of Vadalog

Executable schema mappings for statistical data processing

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