STAR: A Distributed Stream Warehouse System for Spatial Data

Zhida Chen, G. Cong, Walid G. Aref
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引用次数: 8

Abstract

The proliferation of mobile phones and location-based services gives rise to an explosive growth of spatial data. This spatial data contains valuable information, and calls for data stream warehouse systems that can provide real-time analytical results with the latest integrated spatial data. In this demonstration, we present the STAR (Spatial Data Stream Warehouse) system. STAR is a distributed in-memory spatial data stream warehouse system that provides low-latency and up-to-date analytical results over a fast spatial data stream. STAR supports a rich set of aggregate queries for spatial data analytics, e.g., contrasting the frequencies of spatial objects that appear in different spatial regions, or showing the most frequently mentioned topics being tweeted in different cities. STAR processes aggregate queries by maintaining distributed materialized views. Additionally, STAR supports dynamic load adjustment that makes STAR scalable and adaptive. We demonstrate STAR on top of Amazon EC2 clusters using real data sets.
STAR:空间数据的分布式流仓库系统
移动电话和定位服务的普及导致了空间数据的爆炸式增长。这些空间数据包含有价值的信息,需要能够提供实时分析结果的数据流仓库系统与最新的综合空间数据。在这个演示中,我们介绍了STAR(空间数据流仓库)系统。STAR是一个分布式内存空间数据流仓库系统,通过快速的空间数据流提供低延迟和最新的分析结果。STAR支持一组丰富的空间数据分析聚合查询,例如,对比不同空间区域中出现的空间对象的频率,或者显示不同城市中最常被提及的话题。STAR通过维护分布式物化视图来处理聚合查询。此外,STAR支持动态负载调整,使STAR可扩展和自适应。我们使用真实数据集在Amazon EC2集群之上演示STAR。
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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