Massive Power Information Processing Scheme Based on MongoDB

Abstract

In order to solve the problem that the power consumption data presents a trend of sea quantification, and the huge power consumption data brings tremendous pressure to the system, especially slows down the speed of data query and gives users poor experience in using it, this paper proposes to use one of the non-relational databases (NoSQL) to store power consumption data instead of the traditional relational databases. To solve the problem that the collected electricity data can not meet the demand of page display, Hadoop MapReduce is proposed to preprocess the electricity data. Distributed architecture is adopted for storage and processing. MongoDB cluster and Hadoop cluster are overlapped and deployed. Combined with MongoDB's powerful storage capacity and Hadoop MapReduce's analytical and computational capability, a set of high-availability and high-performance data storage and pre-processing scheme for power-consuming universities is constructed.