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Auflistung nach Autor:in "Saleh, Omran"

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  • Konferenzbeitrag
    Autostudio: A generic web application for transforming dataflow programs into action
    (Datenbanksysteme für Business, Technologie und Web (BTW 2015), 2015) Rane, Nikhil-Kishor; Saleh, Omran
    In this paper, a user-friendly, interactive, and easy-to-use web-based application, is introduced. “AutoStudio” is a generic application where the users can generate dataflow programs for different dataflow languages, such as PipeFlow and Pig, using a drag and drop functionality. Using this application, the users can assemble the operators that comprise a particular program without being an expert in the target language and without his/her awareness of its operators and constructs. Therefore, the rapid development can be achieved. Our application also provides additional functionalities which makes it a “One-Stop-App” such as compiling, saving, executing, and checking the status of the generated dataflow programs.
  • Zeitschriftenartikel
    Complex Event Processing on Linked Stream Data
    (Datenbank-Spektrum: Vol. 15, No. 2, 2015) Saleh, Omran; Hagedorn, Stefan; Sattler, Kai-Uwe
    Social networks and Sensor Web technologies typically generate a massive amount of data published as streams. In order to give these streams a meaningful sense and enrich them with semantic descriptions, the concept of Linked Stream Data (LSD) has emerged. However, to support a wide range of LSD scenarios and queries comprehensive solutions providing not only classic data stream operators such as windows, but also for processing of complex events, linking of (static) datasets, and scalable processing are required. In this paper, we present our approach for processing LSD and addressing these requirements. In contrast to existing LSD engines relying on streaming extensions to SPARQL, our PipeFlow system is a (relational) dataflow language and engine providing support for complex event processing (CEP) and a few dedicated operators for RDF data. We describe this language and particularly the CEP model as well as the system architecture for parallel CEP and LSD processing by exploiting partitioning techniques for cluster environments. Finally, we report results from experiments evaluating our system in comparison to existing LSD engines.