Which strategy is most effective for reducing shuffling and enhancing query performance when optimizing a Spark job that processes a large Delta Lake table?

Real Exam

A

Using broadcast variables to minimize data transfer

26.1%

B

Maintaining default partitioning to let Spark decide

9.9%

C

Decreasing the number of partitions using coalesce()

48.6%

D

Increasing the number of partitions to maximize parallelism

15.5%

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