Shared Variables and Broadcast Joins ASSOCIATE-DEVELOPER-APACHE-SPARK Practice Questions (Page 2)

Questions 6–10

1. 6foundation · easy

   In Apache Spark, which shared variable type is designed to be read-only and distributed to all executors for efficient access?

   • AAccumulator
   • BDistributed variable
   • CBroadcast variable
   • DCache variable
   Reveal Solution Discussion Select an answer first
2. 7foundation · easy

   How can you explicitly perform a broadcast join in Spark SQL?

   • AUse the joinHint method with 'shuffle'
   • BSet spark.sql.autoBroadcastJoinThreshold to 0
   • CUse the broadcast function on the smaller DataFrame
   • DUse the repartition method on both DataFrames
   Reveal Solution Discussion Select an answer first
4. 8foundation · easy

   When is it appropriate to use a broadcast join?

   • AWhen the join is a self-join on a large table
   • BWhen both tables are very large and need to be shuffled
   • CWhen the join key is highly skewed
   • DWhen one table is small enough to fit in the memory of each executor
   Reveal Solution Discussion Select an answer first
5. 9foundation · easy

   How do you access the value of a broadcast variable in a Spark task?

   • ABy referencing the broadcast variable directly as a local variable
   • BBy calling the value method on the broadcast variable
   • CBy calling the get method on the broadcast variable
   • DBy using the broadcast variable as a function argument
   Reveal Solution Discussion Select an answer first
6. 10foundation · easy

   What is the difference between a named and an unnamed accumulator in Spark?

   • AA named accumulator is global, while an unnamed one is local to a task
   • BA named accumulator can be read by tasks, while an unnamed one cannot
   • CA named accumulator is persisted, while an unnamed one is not
   • DA named accumulator appears in the Spark UI, while an unnamed one does not
   Reveal Solution Discussion Select an answer first