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When facing performance issues in a Spark job due to skewed data in Delta Lake, which advanced technique can effectively reduce the impact of data skew on query performance?
A
Utilizing the SALTING technique by introducing a random prefix to the join keys.
B
Applying broadcast join as a solution for automatically managing skewed datasets.
C
Executing repartition(1) to merge all data into a single partition.
D
Using coalesce() without shuffling to decrease the number of partitions.
