Technical predictive analysis of big data for Apache Spark-based resource planning

Abstract

The large database analysis is a substantial form of research that is presently expanding immensely in current technologies, and it also affects numerous aspects of life. Powerful, scalable, and customizable platforms are required to win the challenges in the field and increase effectiveness of analysing the data. Apache Spark is one of the most trending high-performance computing engines to process big data and thus deliver a revolutionary approach to data science and engineering. Big data analytics involve Apache Spark and its application is increasing at lightning speed both in academic and business spheres. It has established itself in the field of data analytics as it can support various kinds of loads within a single architecture. The development of Apache Spark continues with new developments of data analysis, hence bringing it to the notice of researchers and practitioners as a high utility tool to solve the problem of big data. The Apache Spark is a big data processing system which has proven effective in numerous applications of analysing big data; this paper examines the working process of Apache Spark, its advantages and area of application and provides an examination of the future outlook of this platform.