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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

If we want to create a constant string 1 as a new column ‘new_column’ in the dataframe df, which code block should we select ?

Options :

A : df.withColumn(new_column, lit(1))

B : df.withColumn(“new_column”, 1)

C : df.withColumn(“new_column”, lit(1))

D : df.withColumnRenamed('new_column', lit(1))

E : df.withColumn(”new_column”, lit(“1”))

Answer: A

Question 3

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 4

Which of the following code blocks efficiently converts DataFrame transactionsDf from 12 into 24 partitions?

Options :

A : transactionsDf.repartition(24, boost=True)

B : transactionsDf.repartition()

C : transactionsDf.repartition("itemId", 24)

D : transactionsDf.coalesce(24)

E : transactionsDf.repartition(24)

Answer: A

Question 5

Which of the following describes a difference between Spark's cluster and client execution modes?

Options :

A : In cluster mode, the cluster manager resides on a worker node, while it resides on an edge node in client mode.

B : In cluster mode, executor processes run on worker nodes, while they run on gateway nodes in client mode.

C : In cluster mode, the driver resides on a worker node, while it resides on an edge node in client mode.

D : In cluster mode, a gateway machine hosts the driver, while it is co-located with the executor in client mode.

E : In cluster mode, the Spark driver is not co-located with the cluster manager, while it is co-located in client mode.

Answer: C