Certified Associate Developer for Apache Spark Exam - Free Actual Q&As, Page 1

Databricks Certified Associate Developer for Apache Spark Actual Exam Questions

Last updated on Nov. 20, 2025.

Topic 1 - Exam A

Question #1 Topic 1

Which of the following describes the Spark driver?

A. The Spark driver is responsible for performing all execution in all execution modes – it is the entire Spark application.
B. The Spare driver is fault tolerant – if it fails, it will recover the entire Spark application.
C. The Spark driver is the coarsest level of the Spark execution hierarchy – it is synonymous with the Spark application.
D. The Spark driver is the program space in which the Spark application’s main method runs coordinating the Spark entire application.
E. The Spark driver is horizontally scaled to increase overall processing throughput of a Spark application.

Reveal Solution Discussion 10

Correct Answer: D 🗳️

Question #2 Topic 1

Which of the following describes the relationship between nodes and executors?

A. Executors and nodes are not related.
B. Anode is a processing engine running on an executor.
C. An executor is a processing engine running on a node.
D. There are always the same number of executors and nodes.
E. There are always more nodes than executors.

Reveal Solution Discussion 15

Correct Answer: C 🗳️

Question #3 Topic 1

Which of the following will occur if there are more slots than there are tasks?

A. The Spark job will likely not run as efficiently as possible.
B. The Spark application will fail – there must be at least as many tasks as there are slots.
C. Some executors will shut down and allocate all slots on larger executors first.
D. More tasks will be automatically generated to ensure all slots are being used.
E. The Spark job will use just one single slot to perform all tasks.

Reveal Solution Discussion 14

Correct Answer: A 🗳️

Question #4 Topic 1

Which of the following is the most granular level of the Spark execution hierarchy?

A. Task
B. Executor
C. Node
D. Job
E. Slot

Reveal Solution Discussion 5

Correct Answer: A 🗳️

Question #5 Topic 1

Which of the following statements about Spark jobs is incorrect?

A. Jobs are broken down into stages.
B. There are multiple tasks within a single job when a DataFrame has more than one partition.
C. Jobs are collections of tasks that are divided up based on when an action is called.
D. There is no way to monitor the progress of a job.
E. Jobs are collections of tasks that are divided based on when language variables are defined.

Reveal Solution Discussion 4

Correct Answer: D 🗳️

Question #6 Topic 1

Which of the following operations is most likely to result in a shuffle?

A. DataFrame.join()
B. DataFrame.filter()
C. DataFrame.union()
D. DataFrame.where()
E. DataFrame.drop()

Reveal Solution Discussion 4

Correct Answer: A 🗳️

Question #7 Topic 1

The default value of spark.sql.shuffle.partitions is 200. Which of the following describes what that means?

A. By default, all DataFrames in Spark will be spit to perfectly fill the memory of 200 executors.
B. By default, new DataFrames created by Spark will be split to perfectly fill the memory of 200 executors.
C. By default, Spark will only read the first 200 partitions of DataFrames to improve speed.
D. By default, all DataFrames in Spark, including existing DataFrames, will be split into 200 unique segments for parallelization.
E. By default, DataFrames will be split into 200 unique partitions when data is being shuffled.

Reveal Solution Discussion 3

Correct Answer: E 🗳️

Question #8 Topic 1

Which of the following is the most complete description of lazy evaluation?

A. None of these options describe lazy evaluation
B. A process is lazily evaluated if its execution does not start until it is put into action by some type of trigger
C. A process is lazily evaluated if its execution does not start until it is forced to display a result to the user
D. A process is lazily evaluated if its execution does not start until it reaches a specified date and time
E. A process is lazily evaluated if its execution does not start until it is finished compiling

Reveal Solution Discussion 2

Correct Answer: B 🗳️

Question #9 Topic 1

Which of the following DataFrame operations is classified as an action?

A. DataFrame.drop()
B. DataFrame.coalesce()
C. DataFrame.take()
D. DataFrame.join()
E. DataFrame.filter()

Reveal Solution Discussion 3

Correct Answer: C 🗳️

Question #10 Topic 1

Which of the following DataFrame operations is classified as a wide transformation?

A. DataFrame.filter()
B. DataFrame.join()
C. DataFrame.select()
D. DataFrame.drop()
E. DataFrame.union()

Reveal Solution Discussion 4

Correct Answer: B 🗳️

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