Research Progress in the Field of MapReduce Framework Based on Serverless Computing

In recent years, big data technology has presented a rapid development trend with each passing day, and its application in all walks of life is becoming more and more extensive and in-depth. At the same time, traditional computing frameworks are gradually showing serious challenges in performance bottlenecks and scalability in the face of massive data processing requirements, making it difficult to meet the growing needs of data processing and highly concurrent access scenarios. Firstly, this paper introduces MapReduce framework and serverless platforms, and then introduces the MapReduce framework model based on serverless platforms from several parts of implementation, application scenarios and technical principles. This paper argues that the serverless-based MapReduce framework will provide a more efficient and flexible solution for big data processing and analyzing, which is of great significance in promoting the development of data-driven decision-making and intelligent applications. The main content of this paper will be introduced from the basic overview of MapReduce computing framework and serverless platform, the implementation of serverless-based MapReduce computing framework, technical principles and application scenarios.