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

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

Question 2

Which of the following transformation is not evaluated lazily ?

Options :

A : repartition()

B : select()

C : None of the responses, all transformations are lazily evaluated.

D : filter()

E : sample()

Answer: C

Question 3

If spark is running in client mode, which of the following statement about is correct ?

Options :

A : Spark driver is attributed to the machine that has the most resources

B : Spark driver is randomly attributed to a machine in the cluster

C : The entire spark application is run on a single machine

D : Spark driver remainse on the client machine that submitted the application.

Answer: D

Question 4

Which of the following code blocks reads from a csv file where values are separated with ‘;’ ?

Options :

A : spark.read.format("csv").option("header", "true").option(“inferSchema”, “true”).option(“sep”, “true”).toDf(file)

B : spark.read.format("csv").option("header", "true").option(“inferSchema”, “true”).load(file)

C : spark.read.format("csv").option("header", "true").option(“inferSchema”, “true”).option(“sep”, “;”).load(file)

D : spark.load.format("csv").option("header", "true").option(“inferSchema”, “true”).read(file)

Answer: C

Question 5

Which property is used to to allocates jobs to different resource pools to achieve resources scheduling within an application ?

Options :

A : Fair Scheduler

B : Dynamic allocation

C : There is no need to set a property since spark is by default capable of resizing

Answer: A