Knowledge-Preserving Certain Answers for SQL-like Queries

Toussaint, Etienne; Guagliardo, Paolo; Libkin, Leonid

doi:10.24963/kr.2020/78

Cited by 2 publications

(2 citation statements)

References 14 publications

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“…Hence, the usefulness of such answers is limited. A recent attempt to provide proper substitutes for these notions was made in [41] but the shape of answers presented is quite complex for the user to comprehend. Another approach, specifically focused on numerical attributes, was presented in [10], but it does not take into account aggregation and prior knowledge on the missing data.…”

Section: Introductionmentioning

confidence: 99%

Querying Incomplete Numerical Data: Between Certain and Possibile Answers

Console

Libkin

Peterfreund

2023

Proceedings of the 42nd ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems

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Queries with aggregation and arithmetic operations, as well as incomplete data, are common in real-world database, but we lack a good understanding of how they should interact. On the one hand, systems based on SQL provide ad-hoc rules for numerical nulls, on the other, theoretical research largely concentrates on the standard notions of certain and possible answers. In the presence of numerical attributes and aggregates, however, these answers are often meaningless, returning either too little or too much. Our goal is to define a principled framework for databases with numerical nulls and answering queries with arithmetic and aggregations over them.Towards this goal, we assume that missing values in numerical attributes are given by probability distributions associated with marked nulls. This yields a model of probabilistic bag databases in which tuples are not necessarily independent since nulls can repeat. We provide a general compositional framework for query answering and then concentrate on queries that resemble standard SQL with arithmetic and aggregation. We show that these queries are measurable, and their outputs have a finite representation. Moreover, since the classical forms of answers provide little information in the numerical setting, we look at the probability that numerical values in output tuples belong to specific intervals. Even though their exact computation is intractable, we show efficient approximation algorithms to compute such probabilities.

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Section: Introductionmentioning

confidence: 99%

Querying Incomplete Numerical Data: Between Certain and Possibile Answers

Console

Libkin

Peterfreund

2023

Proceedings of the 42nd ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems

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“…A well-founded definition of certain answers for value-inventing queries under bag semantics was only recently proposed in[60].…”

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confidence: 99%

Troubles with nulls, views from the users

et al. 2022

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Incomplete data, in the form of null values, has been extensively studied since the inception of the relational model in the 1970s. Anecdotally, one hears that the way in which SQL, the standard language for relational databases, handles nulls creates a myriad of problems in everyday applications of database systems. To the best of our knowledge, however, the actual shortcomings of SQL in this respect, as perceived by database practitioners, have not been systematically documented, and it is not known if existing research results can readily be used to address the practical challenges. Our goal is to collect and analyze the shortcomings of nulls and their treatment by SQL, and to re-evaluate existing research in this light. To this end, we designed and conducted a survey on the everyday usage of null values among database users. From the analysis of the results we reached two main conclusions. First, null values are ubiquitous and relevant in real-life scenarios, but SQL's features designed to deal with them cause multiple problems. The severity of these problems varies depending on the SQL features used, and they cannot be reduced to a single issue. Second, foundational research on nulls is misdirected and has been addressing problems of limited practical relevance. We urge the community to view the results of this survey as a way to broaden the spectrum of their researches and further bridge the theory-practice gap on null values.

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Knowledge-Preserving Certain Answers for SQL-like Queries

Cited by 2 publications

References 14 publications

Querying Incomplete Numerical Data: Between Certain and Possibile Answers

Querying Incomplete Numerical Data: Between Certain and Possibile Answers

Troubles with nulls, views from the users

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