In the context of Apache Spark, data partitioning plays a crucial role in optimizing data processing workflows. Consider a scenario where you are working with a large dataset that exhibits significant skewness in data distribution, leading to uneven workload distribution across nodes. Your goal is to optimize the performance of a Spark job by selecting an appropriate partitioning strategy. Given the constraints of minimizing processing time and ensuring balanced workload distribution, which of the following strategies would you choose and why? Please select the best option from the choices provided below.