Mohamed H. Ali, B. Chandramouli, B. S. Raman, E. Katibah
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引用次数: 16
Abstract
Microsoft StreamInsight (StreamInsight, for brevity) is a platform for developing and deploying streaming applications that run continuous queries over high-rate streaming events. StreamInsight adopts a temporal stream model to handle imperfections in event delivery and define consistency guarantees on the output. This demo highlights the ability of StreamInsight to monitor, analyze and correlate spatio-temporal stream data that is generated by moving objects. The demo scenario is based on the Microsoft Shuttle Service where GPS readings are generated and streamed by shuttles as they move around the Microsoft main campus in Redmond, WA. The demo presents a set of relational continuous queries as well as various real-time analytics that help improve the efficiency of the shuttle service in terms of the average wait time per passenger and the average daily mileage per shuttle.
Microsoft StreamInsight(简称为StreamInsight)是一个开发和部署流应用程序的平台,它可以在高速流事件上运行连续查询。StreamInsight采用临时流模型来处理事件交付中的缺陷,并在输出上定义一致性保证。这个演示突出了StreamInsight监控、分析和关联由移动对象产生的时空流数据的能力。演示场景基于微软班车服务,当班车在微软位于华盛顿州雷德蒙德的主园区周围移动时,会生成GPS读数并传输数据。该演示展示了一组关系连续查询以及各种实时分析,这些分析有助于提高班车服务的效率,包括每位乘客的平均等待时间和每班车的平均每日里程。