Multidimensional data index method of energy big data center based on space filling curve

Abstract:
In order to solve the problems of small data index range and high node failure rate in the index structure in traditional methods, a multi-dimensional data index method for energy big data centers based on space filling curves is proposed. This paper designs a two-tier index framework for the energy big data center, and divides energy data into data blocks according to certain rules. At the same time, a multi-dimensional data retrieval model of the energy big data center is established, and the data is simulated using fuzzy theory. with similar characteristics in the energy big data center, and minimize the divergence of sample data through this operation. Use the least square method to mine the non-significant data characteristics of the multi-dimensional data of the energy big data center, filter the multi-dimensional data, and finally realize the multi-dimensional data index through the space filling curve. The experimental results show that the data index range of this method is large, and the node failure rate in the index structure is low.