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When optimizing a Spark SQL query that involves joining multiple DataFrames and filtering based on a date range, what is the most effective strategy to enhance query performance?
A
Within the join condition to take advantage of Spark's built-in optimizations.
B
After the join operations to reduce the amount of computation required.
C
Before the join operations to minimize the data shuffling across the network.
D
Avoiding filters altogether and manually partitioning the data by date instead.
