Smartly Prepare Exam with Free Online Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 Practice Test

We offer the latest Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 practice test designed for free and effective online Databricks Certified Associate Developer for Apache Spark 3.0 certification preparation. It's a simulation of the real Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 exam experience, built to help you understand the structure, complexity, and topics you'll face on exam day.

Question 1

We want to drop any rows that how a null value. Choose the correct order in order to achieve this goal.

1. 1. df.

2. 2. drop.

3. 3. na()

4. 4. drop(how=’all’)

5. 5. dropna(how=’any’)

Options :

A : 1, 5

B : 1, 2, 6

C : 1, 2, 3

D : 1, 4

Answer: A

Question 2

The code block displayed below contains an error. The code block should return DataFrame transactionsDf,

but with the column storeId renamed to storeNumber. Find the error.

Code block:

transactionsDf.withColumn("storeNumber", "storeId")

Options :

A : Instead of withColumn, the withColumnRenamed method should be used.

B : Arguments "storeNumber" and "storeId" each need to be wrapped in a col() operator.

C : Argument "storeId" should be the first and argument "storeNumber" should be the second argument to the withColumn method

D : The withColumn operator should be replaced with the copyDataFrame operator.

E : Instead of withColumn, the withColumnRenamed method should be used and argument "storeId" should be the first and argument "storeNumber" should be the second argument to that method.

Answer: A

Question 3

Choose invalid execution mode in the following responses.

Options :

A : Local

B : Standalone

C : Cluster

D : Client

Answer: B

Question 4

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

Options :

A : orderBy()

B : cache()

C : distinct()

D : drop()

E : filter()

F : repartition()

Answer:

Question 5

What are the possible strategies in order to decrease garbage collection time ?

Options :

A : Persist objects in serialized form

B : Create fewer objects

C : Increase java heap space size

Answer: A,B,C