Exam Databricks-Certified-Data-Engineer-Professional Topic 1 Question 57 Discussion

Actual exam question for Databricks's Databricks-Certified-Data-Engineer-Professional exam
Question #: 57
Topic #: 1
A data engineer is attempting to execute the following PySpark code:
df = spark.read.table("sales")
result = df.groupBy("region").agg(sum("revenue"))
However, upon inspecting the execution plan and profiling the Spark job, they observe excessive data shuffling during the aggregation phase.
Which technique should be applied to reduce shuffling during the groupBy aggregation operation?

Suggested Answer: B Vote an answer

Repartitioning the DataFrame by the grouping key ensures that records with the same region are colocated in the same partitions before the aggregation runs. This significantly reduces the amount of data shuffled during the groupBy operation, leading to more efficient execution.

by Alva at Aug 25, 2026, 11:53 AM

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