Option C is the correct approach as it leverages the power of distributed processing frameworks like Spark to efficiently process data across multiple partitions. This approach ensures that the solution can handle large volumes of data and provide accurate results. Option D is incorrect because handling schema drift is not directly related to processing data across partitions.