Title :
Implementing Materialized View of Large-Scale Power Consumption Log Using MapReduce
Author :
Ise, Yuki ; Yamamoto, Seiichi ; Matsumoto, Shinichi ; Saiki, Sachio ; Nakamura, Mitsutoshi
Author_Institution :
Grad. Sch. of Syst. Inf., Kobe Univ., Kobe, Japan
Abstract :
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 :
cache storage; database management systems; power consumption; town and country planning; HBase KVS; MapReduce; application-specific data caching; city houses; city infrastructures; database; large-scale power consumption data; large-scale power consumption log; materialized view; smart city; value-added services; Cities and towns; Distributed databases; Distributed processing; Home appliances; Power demand; Time factors; Time measurement; HBase; KVS; MapReduce; high-speed and efficient data access; large-scale house log; materialized view;
Conference_Titel :
Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD), 2013 14th ACIS International Conference on
Conference_Location :
Honolulu, HI
DOI :
10.1109/SNPD.2013.60