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When querying a large table partitioned by date in Spark, which method allows Spark to dynamically prune partitions to optimize the query execution plan?
A
Manually specifying the partition columns in the WHERE clause of the query.
B
Annotating the query with hints to explicitly specify which partitions to include.
C
Utilizing Spark‘s dynamic partition pruning feature by enabling it in Spark‘s configuration settings.
D
Leveraging broadcast variables to share partition metadata across nodes.
