License: Creative Commons Attribution 3.0 Unported license (CC-BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.ICDT.2020.13
URN: urn:nbn:de:0030-drops-119378
URL: https://drops.dagstuhl.de/opus/volltexte/2020/11937/
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Geck, Gaetano ; Neven, Frank ; Schwentick, Thomas

Distribution Constraints: The Chase for Distributed Data

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LIPIcs-ICDT-2020-13.pdf (0.7 MB)


Abstract

This paper introduces a declarative framework to specify and reason about distributions of data over computing nodes in a distributed setting. More specifically, it proposes distribution constraints which are tuple and equality generating dependencies (tgds and egds) extended with node variables ranging over computing nodes. In particular, they can express co-partitioning constraints and constraints about range-based data distributions by using comparison atoms. The main technical contribution is the study of the implication problem of distribution constraints. While implication is undecidable in general, relevant fragments of so-called data-full constraints are exhibited for which the corresponding implication problems are complete for EXPTIME, PSPACE and NP. These results yield bounds on deciding parallel-correctness for conjunctive queries in the presence of distribution constraints.

BibTeX - Entry

@InProceedings{geck_et_al:LIPIcs:2020:11937,
  author =	{Gaetano Geck and Frank Neven and Thomas Schwentick},
  title =	{{Distribution Constraints: The Chase for Distributed Data}},
  booktitle =	{23rd International Conference on Database Theory (ICDT 2020)},
  pages =	{13:1--13:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-139-9},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{155},
  editor =	{Carsten Lutz and Jean Christoph Jung},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2020/11937},
  URN =		{urn:nbn:de:0030-drops-119378},
  doi =		{10.4230/LIPIcs.ICDT.2020.13},
  annote =	{Keywords: tuple-generating dependencies, chase, conjunctive queries, distributed evaluation}
}

Keywords: tuple-generating dependencies, chase, conjunctive queries, distributed evaluation
Collection: 23rd International Conference on Database Theory (ICDT 2020)
Issue Date: 2020
Date of publication: 11.03.2020
Supplementary Material: Video of the Presentation: https://doi.org/10.5446/46842


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