Research on Hybrid Index Method of Double-Layer B+ Tree for Power Big Data Considering Knowledge Graph
Ling Chao Gao, Li Yao, Zhiwei Yang, Fei Zheng · Journal of Physics Conference Series · 2021
Abstract Efficient power data access can not only ensure the normal operation of power system, but also be one of the key supporting technologies to improve the operational efficiency of power grid enterprises. Aiming at the problem that traditional B+ tree does not take into account the relevance of power information fragments and cannot be indexed flexibly, a hybrid index structure and index method of power big data with knowledge graph is proposed, that is, the first layer uses B+ tree structure to store attributes, and the second layer uses knowledge graph to store attribute value, thus realizing the relevance index of power data. The simulation results show that the hybrid index structure can achieve the index of power big data with relevance information without affecting the index efficiency, which provides technical reference for efficient retrieval of multi-modal data in the future.