Free Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 Mock Exam – Practice Online Confidently

Increase your chances of passing the Databricks Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 exam questions on your first try. Practice with our free online Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 exam mock test designed to help you prepare effectively and confidently.

Question 1

How to make sure that dataframe df has 12 partitions given that df has 4 partitions ?

Options :

A : df.repartition(12)

B : df.setPartitition(12)

C : df.repartition()

D : df.setPartitition()

Answer: A

Question 2

What won't cause a full shuffle knowing that dataframe ‘df’ has 8 partitions ?

Options :

A : df.coalesce(4)

B : df.repartition(12)

C : All of them will cause a full shuffle.

Answer: A

Question 3

Select the code block which counts distinct number of “quantity” for each “invoiceNo” in the dataframe df.

Options :

A : df.groupBy(InvoiceNo).agg( expr("count(Quantity)"))

B : df.reduceBy("InvoiceNo").agg( expr("count(Quantity)"))

C : df.groupBy("InvoiceNo").agg( expr(count(Quantity)))

D : df.groupBy(InvoiceNo).agg( expr(count(Quantity)))

E : df.groupBy("InvoiceNo").agg( expr("countDisctinct(Quantity)"))

Answer: A

Question 4

Which of the following is the idea behind dynamic partition pruning in Spark?

Options :

A : Dynamic partition pruning is intended to skip over the data you do not need in the results of a query.

B : Dynamic partition pruning concatenates columns of similar data types to optimize join performance.

C : Dynamic partition pruning performs wide transformations on disk instead of in memory.

D : Dynamic partition pruning reoptimizes physical plans based on data types and broadcast variables.

E : Dynamic partition pruning reoptimizes query plans based on runtime statistics collected during query execution.

Answer: A

Question 5

Which of the following 3 DataFrame operations are classified as a wide transformation ? Choose 3 answers:

Options :

A : orderBy()

B : drop()

C : repartition()

D : distinct()

E : filter()

F : cache()

Answer: A,C,D