A Grammar for Reproducible and Painless Extract-Transform-Load Operations on Medium Data

Benjamin S. Baumer

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arXiv · 1708.07073

A Grammar for Reproducible and Painless Extract-Transform-Load Operations on Medium Data

Benjamin S. Baumer

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Abstract

Many interesting data sets available on the Internet are of a medium size---too big to fit into a personal computer's memory, but not so large that they won't fit comfortably on its hard disk. In the coming years, data sets of this magnitude will inform vital research in a wide array of application domains. However, due to a variety of constraints they are cumbersome to ingest, wrangle, analyze, and share in a reproducible fashion. These obstructions hamper thorough peer-review and thus disrupt the forward progress of science. We propose a predictable and pipeable framework for R (the state-of-the-art statistical computing environment) that leverages SQL (the venerable database architecture and query language) to make reproducible research on medium data a painless reality.

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Benjamin S. Baumer. 2017-08-23. A Grammar for Reproducible and Painless Extract-Transform-Load Operations on Medium Data. https://arxiv.org/abs/1708.07073

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