Materialized View as a Service for Large-Scale House Log in Smart City

Shintaro Yamamoto, S. Matsumoto, S. Saiki, Masahide Nakamura
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引用次数: 3

Abstract

Smart city provides various value-added services by collecting large-scale data from houses and infrastructures within a city. To use such large-scale raw data, individual applications usually take expensive computation effort and large processing time. To reduce the effort and time, we propose Materialized View as a Service (MVaaS). Using the MVaaS, each application can easily and dynamically construct its own materialized view, in which the raw data is cached in an appropriate format for the application. Once the view is constructed, the application can quickly access necessary data. In this paper, we design a framework of MVaaS specifically for large-scale house log, managed in our smart-city data platform Scallop4SC. In the framework, each application first specifies how the raw data should be filtered, grouped and aggregated. For a given data specification, MVaaS dynamically constructs a MapReduce batch program that converts the raw data into a desired view. The batch is then executed on Hadoop, and the resultant view is stored in HBase. We conduct an experimental evaluation to compare the response time between cases with and without the proposed MVaaS.
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智慧城市中大规模房屋日志的物化视图服务
智慧城市通过收集城市内房屋和基础设施的大规模数据,提供各种增值服务。为了使用如此大规模的原始数据,单个应用程序通常需要花费昂贵的计算工作和大量的处理时间。为了减少工作量和时间,我们提出物化视图即服务(MVaaS)。使用MVaaS,每个应用程序都可以轻松动态地构造自己的物化视图,其中原始数据以适合应用程序的格式缓存。一旦构造了视图,应用程序就可以快速访问必要的数据。在本文中,我们设计了一个专门针对大规模房屋日志的MVaaS框架,并在我们的智慧城市数据平台Scallop4SC中进行管理。在框架中,每个应用程序首先指定如何过滤、分组和聚合原始数据。对于给定的数据规范,MVaaS动态地构建一个MapReduce批处理程序,将原始数据转换为所需的视图。然后在Hadoop上执行批处理,生成的视图存储在HBase中。我们进行了一个实验评估,以比较有和没有提出的MVaaS的情况下的响应时间。
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