Apache Spark Certification Practice Test

Setting the "master" to local[2] specifically tells Apache Spark to utilize two cores in your local environment. This notation indicates that Spark should run in local mode and leverage the specified number of cores, allowing you to take full advantage of the computational resources available to you.

This configuration helps in executing tasks in parallel across the specified number of cores, improving performance during processing. By using local[2], you are effectively enabling Spark to distribute workloads across those two cores, optimizing resource utilization and potentially reducing execution time compared to using a single core.

In contrast, other options do not precisely define the use of two cores: using just "local" would run the application on a single core, "2 cores" is not a recognized setting in Spark, and "local[*]" would run the application using all available cores in the environment, which in this case may not align with the intention of specifically using two cores. Hence, local[2] is the most suitable choice for effectively utilizing the two cores available in the local environment.