Experimental Setup of Apache Spark Application Execution in a Standalone Cluster Environment using Default Scheduling Mode

This paper proposes the Apache Spark application execution on a local machine using covid dataset with the standalone cluster environment using default scheduling mode. Cloud computing has been widely used in various fields of organization due to its flexibility and scalability. Efficient job scheduling technique can apply in the cloud to increases the profit of Cloud Service Provider and also reduces various optimization technique was recently applied to increases the performance of cloud computing. Experimental setup of apache spark done on a local machine in a standalone cluster environment using FIFO default scheduling mode. Existing techniques have limitations of local optimal trap, lower convergence and over fitting in prediction. This research applies First In First Out (FIFO) technique to increases the efficiency of cloud, reduce the cost, easy to configure with simplest standalone cluster manager. In this proposed framework, the first phase configure the local machine with apache spark second phase launch master node and worker node and the final phase launch the history server and run the application. The FIFO technique has a cost value of 2.5 $ based on the results recorded with two parameters execution time and resources utilized (CPU cores and memory).