Question 1

The code block displayed below contains an error. The code block should trigger Spark to cache DataFrame

transactionsDf in executor memory where available, writing to disk where insufficient

executor memory is available, in a fault-tolerant way. Find the error.

Code block:

transactionsDf.persist(StorageLevel.MEMORY_AND_DISK)

Options :

A : Caching is not supported in Spark, data are always recomputed.

B : Data caching capabilities can be accessed through the spark object, but not through the DataFrame API.

C : The storage level is inappropriate for fault-tolerant storage.

D : The code block uses the wrong operator for caching.

E : The DataFrameWriter needs to be invoked.

Answer: C

Question 2

Which of the following statements about lazy evaluation is incorrect?

Options :

A : Predicate pushdown is a feature resulting from lazy evaluation.

B : Execution is triggered by transformations.

C : Spark will fail a job only during execution, but not during definition.

D : Accumulators do not change the lazy evaluation model of Spark.

E : Lineages allow Spark to coalesce transformations into stages

Answer: B

Question 3

Which of the following 3 DataFrame operations are NOT classified as an action? Choose 3 answers:

Options :

A : foreach()

B : cache()

C : limit()

D : printSchema()

E : show()

F : first()

Answer: B,C,D

Question 4

The following statement will create a managed table

1. dataframe.saveAsTable("unmanaged_my_table")

Options :

A : FALSE

B : TRUE

Answer: B

Question 5

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