As data volumes continue to rise, manual inspection is becoming increasingly untenable. In response, we present MacroBase, a data analytics engine that prioritizes end-user attention in high-volume fast data streams. MacroBase enables efficient, accurate, and modular analyses that highlight and aggregate important and unusual behavior, acting as a search engine for fast data. MacroBase is able to deliver order-of-magnitude speedups over alternatives by optimizing the combination of explanation and classification tasks and by leveraging a new reservoir sampler and heavy-hitters sketch specialized for fast data streams. As a result, MacroBase delivers accurate results at speeds of up to 2M events per second per query on a single core. The system has delivered meaningful results in production, including at a telematics company monitoring hundreds of thousands of vehicles.
@article{arxiv.1603.00567,
title = {MacroBase: Prioritizing Attention in Fast Data},
author = {Peter Bailis and Edward Gan and Samuel Madden and Deepak Narayanan and Kexin Rong and Sahaana Suri},
journal= {arXiv preprint arXiv:1603.00567},
year = {2017}
}