Contents I. Introduction
Under the "overhaul" system of State Grid Corporation of China, an integrated power transmission and transformation condition monitoring and evaluation platform supporting fault diagnosis, condition assessment, condition base maintenance and other applications must be established. In order to ensure the safe and reliable operation of power equipment and meet the needs of smart grid for the whole life cycle management of power equipment, the working state and life of power equipment are evaluated, and the faults are analyzed, judged and predicted. The status information of power equipment is the data base for the application of status monitoring, evaluation and diagnosis of power equipment. In the unified provincial centralized substation condition monitoring and evaluation platform, due to the access to all kinds of equipment condition monitoring devices, the amount of state information data increases rapidly in geometric progression, and the types of data are gradually diversified. It includes not only real-time online condition monitoring data, but also offline information such as equipment basic information, test data, operation data, defect data, inspection record, live test data, etc., which gradually constitutes the big data of power equipment status information[1]. In the description of big data definition and characteristics, Gartner believes that big data generally has "3V" characteristics, namely volume, variety and velocity. IDC thinks it should have value, while IBM thinks it should add veracity. At present, when solving practical problems, other characteristics should be properly considered on the basis of grasping "3V" characteristics. Due to the huge amount of data, many kinds of data, high real-time requirements and low value density, the conventional data management and processing methods are difficult to meet the higher requirements of smart grid for fast query of substation equipment status information.
