Journals Proceedings

Abstract

In this paper, we develop a conflict-free index generator to increase performance in a big data environment. There are several problems with the conventional hash functions, such as Minimal Perfect Hash Function (MPHF) on dynamic systems like big data. The collision-free problem occurs with an increase in the amount of data and the overhead in securing additional space to solve this problem. To solve this problem, we propose a collision evasion method using an auxiliary hash. In this paper, we divide the data into two categories by constructing a double hash to solve the problem.