Design of Distributed Human Resource Management System of Spark Framework Based on Fuzzy Clustering

Abstract

The construction of human resource management system is a key part of enterprise management and control. A perfect human resource management system is conducive to the long-term development of enterprises. Aiming at improving the current situation of enterprise human resource management, a distributed human resource management system is proposed in this paper based on Spark framework. Aiming at the disadvantages of traditional $k$ -means algorithm in processing massive data, such as low computational efficiency and high time complexity, an improved $k$ -means algorithm based on Spark computing framework is proposed. Through the spatial location relationship with the cluster center, redundant calculation is reduced and the ability of processing massive data is improved for the system. Combined with the actual situation of the enterprise, the human resource management system architecture is designed by using Java EE human-computer interaction. The proposed system can achieve user management, employee information, attendance, evaluation, performance, salary, personnel change, and other business management. The experimental results demonstrate that the system can effectively reduce the time complexity of calculation and improve the system efficiency.