J
Johann-Christoph Freytag
Researcher at Humboldt University of Berlin
Publications - 105
Citations - 3297
Johann-Christoph Freytag is an academic researcher from Humboldt University of Berlin. The author has contributed to research in topics: Query optimization & Query language. The author has an hindex of 27, co-authored 99 publications receiving 3132 citations. Previous affiliations of Johann-Christoph Freytag include Humboldt State University & IBM.
Papers
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Journal ArticleDOI
The Stratosphere platform for big data analytics
Alexander Alexandrov,Rico Bergmann,Stephan Ewen,Johann-Christoph Freytag,Fabian Hueske,Arvid Heise,Odej Kao,Marcus Leich,Ulf Leser,Volker Markl,Felix Naumann,Mathias Peters,Astrid Rheinländer,Matthias J. Sax,Sebastian Schelter,Mareike Hoger,Kostas Tzoumas,Daniel Warneke +17 more
TL;DR: The overall system architecture design decisions are presented, Stratosphere is introduced through example queries, and the internal workings of the system’s components that relate to extensibility, programming model, optimization, and query execution are dive into.
Book ChapterDOI
Executing SPARQL Queries over the Web of Linked Data
TL;DR: An approach to execute SPARQL queries over the Web of Linked Data using an iterator-based pipeline to discover data that might be relevant for answering a query during the query execution itself and an extension of the iterator paradigm is proposed.
Journal ArticleDOI
Extensible query processing in starburst
TL;DR: The design of Starburst's query language processor is described and the ways in which the language processor can be extended to achieve the project's goals are discussed.
Proceedings ArticleDOI
Quality-driven Integration of Heterogenous Information Systems
TL;DR: A framework for multidatabase query processing that fully includes the quality of information in many facets, such as completeness, timeliness, accuracy, etc, is described.
Proceedings ArticleDOI
A rule-based view of query optimization
TL;DR: This paper describes its operations by transformation rules which generate different QEPs from initial query specifications and hopes that the approach taken will contribute to the more general goal of a modular query optimizer as part of an extensible database management system.