Abstract

Today is the age of big data in which data is increased exponentially. Since the traditional computing systems unable to process these massive data, big data processing frameworks were developed. Apache Spark considers as one of the most relevant cluster computing frameworks for scalable data processing. The issue of task scheduling has been an active field of research in computing systems since its inception, and now in the age of big data, it is considered as one of the most important research fields. The main goal of this paper is to provide a comprehensive overview of the researches undertaken in the field of scheduling tasks in Apache Spark, and therefore, this study can be used as a starting point in the field of scheduling tasks in Apache Spark and as a benchmark to propose a novel improvement of job scheduling for Apache Spark.

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