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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.

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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MEDAL 2016 - EDBT Workshop
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