Code Refactoring Based on MapReduce in Cloud Migration
Junfeng Zhao, Wenmeng Wang, Hongji Yang · 2018
With the advent of big data era, the response speed of traditional legacy systems can no longer meet the requirements of users. Many organizations are migrating their legacy systems from a local machine to the cloud so as to reuse the legacy systems as well as improve the performance of big data processing. The MapReduce model of cloud computing makes parallel and distributed programming over a cluster of machines more convenient. This paper presents an approach to refactor the specific sequential code into MapReduce model in cloud migration, and proposes a tool to support the process of code refactoring.