Shared Variables and Broadcast Joins ASSOCIATE-DEVELOPER-APACHE-SPARK Practice Questions (Page 1)

Questions 1–5

1. 1application · easy

   A Spark application uses a broadcast variable to share a large read-only lookup table (200 MB) with all executors. The executors have 2 GB memory each. What is the primary benefit of using a broadcast variable in this scenario?

   • AIt eliminates the need for serialization.
   • BIt allows tasks to modify the lookup table.
   • CIt automatically updates the lookup table when the source changes.
   • DIt reduces network and memory overhead by sending the data once per executor instead of per task.
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2. 2application · easy

   A developer needs to share a read-only configuration map with all executors and also count the number of processed records. Which combination of shared variables should they use?

   • ATwo broadcast variables, one for the map and one for the count.
   • BBroadcast variable for the map and an accumulator for the count.
   • CA broadcast variable for the count and an accumulator for the map.
   • DTwo accumulators, one for the map and one for the count.
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4. 3foundation · easy

   What is the primary purpose of using a broadcast variable in a Spark application?

   • ATo cache intermediate results in memory for faster recomputation
   • BTo provide a mutable shared state that tasks can update
   • CTo efficiently share a large read-only dataset across all executors, reducing network and memory overhead
   • DTo accumulate results from tasks on the driver
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5. 4application · medium

   A Spark application processes a stream of user events and needs to count the number of invalid records encountered during transformation. The count must be available on the driver after the job completes. The team uses an accumulator for this purpose. After running the job, they observe that the accumulator value is 0 even though invalid records exist. Which action would fix this issue?

   • ARegister the accumulator with SparkSession.
   • BUse a broadcast variable instead of an accumulator.
   • CIncrease the number of executors.
   • DEnsure the accumulator update is inside an action, not a transformation.
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6. 5application · easy

   A Spark job processes a large dataset and needs to track the number of records that fail a validation check. The team wants to see this count on the driver after the job finishes. Which shared variable should they use?

   • ARegular local variable
   • BBroadcast variable
   • CDataFrame column
   • DAccumulator
   Reveal Solution Discussion Select an answer first