Study on hybrid storage method of AMI mass data

Currently, the data size of Advanced Metering Infrastructure (AMI) system is leaping rapidly. The traditional data storage solution in most AMI systems utilize Relational Data Base Management System (RDBMS) However, current RDBMS can hardly meet the requirements of high-speed storage, computation and analysis when faced with mass data, which places a huge limit on potential applications. This paper proposes a method that divides AMI system data into measurement data and management data according to their respective characteristics. The method utilizes a hybrid of Hadoop Distributed File System (HDFS) and RDBMS to sort and store data as well as to gain unified data access. A detailed classification, storage and extraction process and the system design are presented in the paper. Finally, a comparative test of typical AMI business scenario is carried out. The results show that this method has a significant advantage in efficiency and good scalability for processing AMI mass data.