Smart city provides various value-added services by collecting large-scale data from houses and infrastructures within a city. However, it takes a long time for individual applications to use and process the large-scale raw data directly. To reduce the response time, we use the concept of materialized view of database. For a given requirement of an application, the proposed method constructs a materialized view for caching the application-specific data. In this paper, we especially develop a method that uses MapReduce for large-scale power consumption data stored in HBase KVS. We conduct an experimental evaluation to compare the response time between cases with and without the materialized view. As a result, the proposed method with materialized view is effective especially when application repeatedly access the same data, or when the application-specific data is derived from a large set of raw data.Keywords-large-scale house log, materialized view, high-speed and efficient data access, MapReduce, KVS, HBase
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