Crucial Exams

Microsoft Fabric Data Engineer Associate DP-700 Practice Question

You manage a Microsoft Fabric lakehouse. In a Spark notebook you frequently join a 50-MB dimension table with a 2-TB fact table on a surrogate key. The Spark UI shows the join stage dominated by a costly shuffle hash join that increases latency. Without changing cluster size, storage format, or table partitioning, what action should you take to speed up this join?

  • Cache the fact DataFrame in memory before performing the join.

  • Use coalesce(1) on both DataFrames to force them into a single partition before the join.

  • Add a broadcast join hint to the dimension DataFrame so Spark replicates it across all executors before the join.

  • Increase the value of spark.sql.shuffle.partitions to create more shuffle partitions during the join.

Microsoft Fabric Data Engineer Associate DP-700
Monitor and optimize an analytics solution
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