The MapReduce framework provides a massive advantage for improving performance for large datasets as we can add more nodes to get more performance. The resources such as node, memory, and disk require significant investment, thus only adding the node should not be a parameter for performance optimization. Sometimes, adding more nodes does not help in getting more performance as the application performance could be something else, such as code optimization, unwanted data transfer, and so on. In this section, we will discuss some of the best practices to optimize the MapReduce application.
The performance of the application is measured by the overall processing time taken by the application. MapReduce processes data in parallel and thus it already provides a performance advantage over your MapReduce application. The following factors play important roles in optimizing MapReduce performance.