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When dealing with large datasets (approximately 1GB or more) in Hyperopt with SparkTrials, what is the recommended method to efficiently manage the dataset, and why?
A
Utilize Databricks Runtime 6.4 ML or higher for optimal large dataset management.
B
Explicitly broadcast the dataset using Spark and access it via the broadcasted variable within the objective function.
C
Store the dataset in DBFS and reload it onto workers using the DBFS local file interface.
D
Directly load the dataset on the driver and reference it from the objective function.
