Crucial Exams

Microsoft Fabric Data Engineer Associate DP-700 Practice Question

In a Fabric lakehouse you ingest daily transactions into a Delta table named transactions that contains columns SaleDate (timestamp), CategoryId (int), and Amount (decimal). You must create a batch notebook step that produces a DataFrame with one row per CategoryId per calendar month and a column TotalAmount for loading into a dimensional aggregate table. Which PySpark transformation achieves the requirement?

  • transactions.groupBy("CategoryId", "SaleDate").sum("Amount")

  • transactions.rollup("SaleDate", "CategoryId").agg(sum("Amount").alias("TotalAmount"))

  • transactions.withColumn("SaleMonth", month(col("SaleDate"))).groupBy("CategoryId", "SaleMonth").agg(sum("Amount").alias("TotalAmount"))

  • transactions.groupBy(window(col("SaleDate"), "1 day"), "CategoryId").agg(sum("Amount").alias("TotalAmount"))

Microsoft Fabric Data Engineer Associate DP-700
Ingest and transform data
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