Stat!: an interactive analytics environment for big data

Mike Barnett, B. Chandramouli, R. Deline, S. Drucker, Danyel Fisher, J. Goldstein, P. Morrison, John C. Platt
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引用次数: 41

Abstract

Exploratory analysis on big data requires us to rethink data management across the entire stack -- from the underlying data processing techniques to the user experience. We demonstrate Stat! -- a visualization and analytics environment that allows users to rapidly experiment with exploratory queries over big data. Data scientists can use Stat! to quickly refine to the correct query, while getting immediate feedback after processing a fraction of the data. Stat! can work with multiple processing engines in the backend; in this demo, we use Stat! with the Microsoft StreamInsight streaming engine. StreamInsight is used to generate incremental early results to queries and refine these results as more data is processed. Stat! allows data scientists to explore data, dynamically compose multiple queries to generate streams of partial results, and display partial results in both textual and visual form.
统计!:大数据交互式分析环境
对大数据的探索性分析要求我们重新思考整个堆栈的数据管理——从底层数据处理技术到用户体验。我们演示一下,开始!—一个可视化和分析环境,允许用户快速试验对大数据的探索性查询。数据科学家可以使用Stat!快速细化到正确的查询,同时在处理一小部分数据后获得即时反馈。统计!可以在后端使用多个处理引擎;在这个演示中,我们使用Stat!微软StreamInsight流媒体引擎。StreamInsight用于为查询生成增量的早期结果,并在处理更多数据时改进这些结果。统计!允许数据科学家探索数据,动态组合多个查询以生成部分结果流,并以文本和视觉形式显示部分结果。
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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