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36 results on '"Neven, Frank"'

11. BonXai

Author

Martens, Wim, primary, Neven, Frank, additional, Niewerth, Matthias, additional, and Schwentick, Thomas, additional

Published
2017
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12. Research Directions for Principles of Data Management (Abridged)

Author

Abiteboul, Serge, primary, Arenas, Marcelo, additional, Barceló, Pablo, additional, Bienvenu, Meghyn, additional, Calvanese, Diego, additional, David, Claire, additional, Hull, Richard, additional, Hüllermeier, Eyke, additional, Kimelfeld, Benny, additional, Libkin, Leonid, additional, Martens, Wim, additional, Milo, Tova, additional, Murlak, Filip, additional, Neven, Frank, additional, Ortiz, Magdalena, additional, Schwentick, Thomas, additional, Stoyanovich, Julia, additional, Su, Jianwen, additional, Suciu, Dan, additional, Vianu, Victor, additional, and Yi, Ke, additional

Published
2017
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18. Discovering XSD Keys from XML Data

Author

Arenas, Marcelo, primary, Daenen, Jonny, additional, Neven, Frank, additional, Ugarte, Martin, additional, Bussche, Jan Van Den, additional, and Vansummeren, Stijn, additional

Published
2014
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35. BonXai

Author

Frank Neven, Thomas Schwentick, Wim Martens, Matthias Niewerth, MARTENS, Wim, NEVEN, Frank, Niewerth, Matthias, and Schwentick, Thomas

Subjects
Document Structure Description, XML Encryption, Schematron, Computer science, computer.internet_protocol, Efficient XML Interchange, XML, BonXai, XML Schema, schema languages, XML Signature, 02 engineering and technology, computer.software_genre, Logical schema, XML Schema Editor, 020204 information systems, Schema (psychology), Streaming XML, 0202 electrical engineering, electronic engineering, information engineering, RELAX NG, XML schema, computer.programming_language, Programming language, cXML, XML validation, computer.file_format, XML framework, XML database, XML Schema (W3C), Document Schema Definition Languages, Star schema, Document Definition Markup Language, ComputingMethodologies_DOCUMENTANDTEXTPROCESSING, 020201 artificial intelligence & image processing, Data mining, computer, Information Systems
Abstract

While the migration from DTD to XML Schema was driven by a need for increased expressivity and flexibility, the latter was also significantly more complex to use and understand. Whereas DTDs are characterized by their simplicity, XML Schema Documents are notoriously difficult. In this article, we introduce the XML specification language BonXai, which incorporates many features of XML Schema but is arguably almost as easy to use as DTDs. In brief, the latter is achieved by sacrificing the explicit use of types in favor of simple patterns expressing contexts for elements. The goal of BonXai is not to replace XML Schema but rather to provide a simpler alternative for users who want to go beyond the expressiveness and features of DTD but do not need the explicit use of types. Furthermore, XML Schema processing tools can be used as a back-end for BonXai, since BonXai can be automatically converted into XML Schema. A particularly strong point of BonXai is its solid foundation rooted in a decade of theoretical work around pattern-based schemas. We present a formal model for a core fragment of BonXai and the translation algorithms to and from a core fragment of XML Schema. We prove that BonXai and XML Schema can be converted back-and-forth on the level of tree languages and we formally study the size trade-offs between the two languages. We acknowledge the financial support of grant number MA 4938/2-1 from the Deutsche Forschungsgemeinschaft (Emmy Noether Nachwuchsgruppe). We further acknowledge the financial support of the Future and Emerging Technologies (FET) programme within the Seventh Framework Programme for Research of the European Commission, under the FET-Open grant agreement FOX, number FP7-ICT-233599.

Published
2017

36. Reasoning on data partitioning for single-round multi-join evaluation in massively parallel systems

Author

Bas Ketsman, Tom J. Ameloot, Frank Neven, Gaetano Geck, Thomas Schwentick, Software Languages Lab, Informatics and Applied Informatics, AMELOOT, Tom, GECK, Gaetano, KETSMAN, Bas, NEVEN, Frank, and Schwentick, Thomas

Subjects
Sequence, Theoretical computer science, General Computer Science, business.industry, Computer science, Distributed computing, Computation, Big data, Joins, 0102 computer and information sciences, 02 engineering and technology, 01 natural sciences, 010201 computation theory & mathematics, 020204 information systems, Server, Transfer (computing), Spark (mathematics), 0202 electrical engineering, electronic engineering, information engineering, business, Computer Science(all)
Abstract

Evaluating queries over massive amounts of data is a major challenge in the big data era. Modern massively parallel systems, such as, Spark, organize query answering as a sequence of rounds each consisting of a distinct communication phase followed by a computation phase. The communication phase redistributes data over the available servers, while in the subsequent computation phase each server performs the actual computation on its local data. There is a growing interest in single-round algorithms for evaluating multiway joins where data is first reshuffled over the servers and then evaluated in a parallel but communication-free way. As the amount of communication induced by a reshuffling of the data is a dominating cost in such systems, we introduce a framework for reasoning about data partitioning to detect when we can avoid the data reshuffling step. Specifically, we formalize the decision problems parallel-correctness and transfer of parallel-correctness, provide semantical characterizations, and obtain tight complexity bounds.

Published
2017

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