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A Relational Approach to Complex Dataflows

Clouds have become an attractive platform for highly scal- able processing of Big Data, especially due to the concept of elasticity, which characterizes them. Several languages and systems for cloud-based data processing have been proposed in the past, with the most popular among them being based on MapReduce. In this paper, we present Exareme, a system for elastic large-scale data processing on the cloud that follows a more general paradigm. Exareme is an open source project 1 . The system offers a declarative language which is based on SQL with user-defined functions (UDFs) extended with parallelism primitives and an inverted syn- tax to easily express data pipelines. Exareme is designed to take advantage of clouds by dynamically allocating and deallocating compute resources, offering trade-offs between execution time and monetary cost.

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Ioannis Chronis, Yannis Foufoulas, Vaggelis Nikolopoulos, Alexandros Papadopoulos, Eleftherios Stamatogiannakis, Christoforos Svingos, Yannis Ioannidis, "A Relational Approach to Complex Dataflows ", MEDAL 2016 (EDBT Workshop), 2016
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