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Scalable Progressive Analytics on Big Data in the Cloud

Scalable Progressive Analytics on Big Data in the Cloud

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We propose a new progressive analytics system based on a progress model called Prism (1) allows users to communicate progressive samples to the system; (2) allows efficient and deterministic query processing over samples; (3) provides repeatable semantics and provenance to data scientists. We show that one can realize this model for atemporal relational queries using an unmodified temporal streaming engine, by re-interpreting temporal event fields to denote progress. Based on Prism, we buildb a progressive data-parallel computation framework for Windows Azure,where progress is understood as a first-class citizen in the framework.
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