Limit Datalog: A declarative query language for data analysis

Motivated by applications in declarative data analysis, we study DatalogZ-an extension of Datalog with stratified negation and arithmetics over integers. Reasoning in this language is undecidable, so we present a fragment, called limit DatalogZ, that is powerful enough to naturally capture many impo...

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Հիմնական հեղինակներ: Grau, BC, Horrocks, I, Kaminski, M, Kostylev, EV, Motik, B
Ձևաչափ: Journal article
Լեզու:English
Հրապարակվել է: Association for Computing Machinery 2020
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author Grau, BC
Horrocks, I
Kaminski, M
Kostylev, EV
Motik, B
author_facet Grau, BC
Horrocks, I
Kaminski, M
Kostylev, EV
Motik, B
author_sort Grau, BC
collection OXFORD
description Motivated by applications in declarative data analysis, we study DatalogZ-an extension of Datalog with stratified negation and arithmetics over integers. Reasoning in this language is undecidable, so we present a fragment, called limit DatalogZ, that is powerful enough to naturally capture many important data analysis tasks. In limit DatalogZ, all intensional predicates with a numeric argument are limit predicates that keep only the maximal or minimal bounds on numeric values. Reasoning in limit DatalogZ is decidable if multiplication is used in a way that satisfies our linearity condition. Moreover, fact entailment in limit-linear DatalogZ is ΔEXP 2 -complete in combined and ΔP2 -complete in data complexity, and it drops to coNEXP and coNP, respectively, if only (semi-)positive programs are considered. We also propose an additional stability requirement, for which the complexity drops to EXP and P, matching the bounds for usual Datalog. Limit DatalogZ thus provides us with a unified logical framework for declarative data analysis and can be used as a basis for understanding the expressive power of the key data analysis constructs.
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spelling oxford-uuid:b6adc6e9-7a11-4a15-8bdf-4d1b844f5fcd2022-03-27T04:42:39ZLimit Datalog: A declarative query language for data analysisJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:b6adc6e9-7a11-4a15-8bdf-4d1b844f5fcdEnglishSymplectic ElementsAssociation for Computing Machinery2020Grau, BCHorrocks, IKaminski, MKostylev, EVMotik, BMotivated by applications in declarative data analysis, we study DatalogZ-an extension of Datalog with stratified negation and arithmetics over integers. Reasoning in this language is undecidable, so we present a fragment, called limit DatalogZ, that is powerful enough to naturally capture many important data analysis tasks. In limit DatalogZ, all intensional predicates with a numeric argument are limit predicates that keep only the maximal or minimal bounds on numeric values. Reasoning in limit DatalogZ is decidable if multiplication is used in a way that satisfies our linearity condition. Moreover, fact entailment in limit-linear DatalogZ is ΔEXP 2 -complete in combined and ΔP2 -complete in data complexity, and it drops to coNEXP and coNP, respectively, if only (semi-)positive programs are considered. We also propose an additional stability requirement, for which the complexity drops to EXP and P, matching the bounds for usual Datalog. Limit DatalogZ thus provides us with a unified logical framework for declarative data analysis and can be used as a basis for understanding the expressive power of the key data analysis constructs.
spellingShingle Grau, BC
Horrocks, I
Kaminski, M
Kostylev, EV
Motik, B
Limit Datalog: A declarative query language for data analysis
title Limit Datalog: A declarative query language for data analysis
title_full Limit Datalog: A declarative query language for data analysis
title_fullStr Limit Datalog: A declarative query language for data analysis
title_full_unstemmed Limit Datalog: A declarative query language for data analysis
title_short Limit Datalog: A declarative query language for data analysis
title_sort limit datalog a declarative query language for data analysis
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