English

WarpFlow: Exploring Petabytes of Space-Time Data

Databases 2019-02-14 v2

Abstract

WarpFlow is a fast, interactive data querying and processing system with a focus on petabyte-scale spatiotemporal datasets and Tesseract queries. With the rapid growth in smartphones and mobile navigation services, we now have an opportunity to radically improve urban mobility and reduce friction in how people and packages move globally every minute-mile, with data. WarpFlow speeds up three key metrics for data engineers working on such datasets -- time-to-first-result, time-to-full-scale-result, and time-to-trained-model for machine learning.

Keywords

Cite

@article{arxiv.1902.03338,
  title  = {WarpFlow: Exploring Petabytes of Space-Time Data},
  author = {Catalin Popescu and Deepak Merugu and Giao Nguyen and Shiva Shivakumar},
  journal= {arXiv preprint arXiv:1902.03338},
  year   = {2019}
}

Comments

11 pages, 12 figures

R2 v1 2026-06-23T07:36:23.296Z