MacroBase

Firas Abuzaid, Peter D. Bailis, Jialin Ding, Edward Gan, S. Madden, D. Narayanan, Kexin Rong, S. Suri
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引用次数: 1

Abstract

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 (i.e., feature selection) 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.
随着数据量的不断增加,人工检查变得越来越站不住脚。作为回应,我们提出了MacroBase,这是一个数据分析引擎,可以在大容量快速数据流中优先考虑最终用户的注意力。MacroBase支持高效、准确和模块化的分析,突出显示和聚合重要的和不寻常的行为,充当快速数据的搜索引擎。通过优化解释(即特征选择)和分类任务的组合,以及利用新的储层采样器和专门用于快速数据流的重量级草图,MacroBase能够提供数量级的速度提升。因此,MacroBase在单个核心上以每秒2M个事件的速度提供准确的结果。该系统已经在生产中提供了有意义的结果,包括在一家远程信息处理公司监控数十万辆汽车。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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