The article explores how different methods of combining data in a computer system called MapReduce can affect the program's speed and efficiency. MapReduce is a technique used to process large amounts of information quickly. When joining multiple datasets together, MapReduce can struggle. The study looks at various ways to improve this process and make it faster and more effective. By analyzing the costs of using MapReduce in terms of input-output and computing power, the research identifies strategies to optimize the data processing.