Combine DataFrames with Operations Such as Inner Join, Left Join, Broadcast Join, Multiple Keys, Cross Join, Union, and Union All. DATA-ENGINEER-ASSOCIATE Practice Questions (Page 1)

Questions 1–5

1. 1foundation · easy

   What is the primary benefit of using a broadcast join in Spark?

   • AIt avoids shuffling the large DataFrame across the cluster
   • BIt eliminates the need for a join key
   • CIt guarantees the join result is sorted
   • DIt reduces data movement by sending a small DataFrame to all executors
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2. 2foundation · easy

   What does a cross join return?

   • AOnly rows with matching keys
   • BThe Cartesian product of the two DataFrames
   • CA vertical concatenation of the two DataFrames
   • DAll rows from the left and matching rows from the right
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4. 3expert · hard

   A data engineer is joining a large `fact_sales` DataFrame with a small `dim_product` DataFrame on `product_id`. The `dim_product` table is about 5 MB. The engineer wants to ensure the join uses a broadcast join to avoid shuffling the large table. However, the Spark configuration `spark.sql.autoBroadcastJoinThreshold` is set to 10 MB. Which action will guarantee the broadcast join?

   • AUse the broadcast hint on the dim_product DataFrame
   • BRepartition the fact_sales table by product_id
   • CUse a sort-merge join by sorting both tables by product_id
   • DIncrease the autoBroadcastJoinThreshold to 20 MB
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5. 4application · medium

   A data analyst has a `colors` DataFrame with 3 rows (red, green, blue) and a `sizes` DataFrame with 4 rows (S, M, L, XL). They need to create a DataFrame that lists all possible combinations of colors and sizes for a product catalog. Which operation should they use?

   • Acolors.crossJoin(sizes)
   • Bcolors.join(sizes, on="color", how="cross")
   • Ccolors.union(sizes)
   • Dcolors.join(sizes, how="inner")
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6. 5foundation · easy

   When is a broadcast join most appropriate?

   • AWhen both DataFrames are very large
   • BWhen the join key is not unique
   • CWhen the DataFrames have identical schemas
   • DWhen one DataFrame is small enough to fit in executor memory
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