Question 1

There is a global temp view named ‘my_global_view’. If I want to query this view within spark, which command do we need to choose ?

Options :

A : spark.read.table("global_temp.my_global_view")

B : spark.read.view("global_temp.my_global_view")

C : spark.read.view("my_global_view")

D : spark.read.table("my_global_view")

Answer: A

Question 2

Which of the following is correct for the cluster manager ?

Options :

A : Executes code assigned to it.

B : Keeps track of the resources available.

C :

It is interchangeable with job.

D : Reports the state of the computation back to the driver.

E : All of the answers are correct.

Answer: B

Question 3

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

Options :

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

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

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

D : df.withColumn(“new_column”, 1)

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

Answer: A

Question 4

Which of the following describe optimizations enabled by adaptive query execution (AQE)? Choose two.

Options :

A : AQE allows you to dynamically reorganize query orders.

B : AQE allows you to dynamically convert physical plans to RDDs

C : AQE allows you to dynamically select physical plans based on cost.

D : AQE allows you to dynamically coalesce shuffle partitions

E : AQE allows you to dynamically switch join strategies.

Answer: A,D

Question 5

We have an unmanaged table “my_table”

If we run the code block down below

spark.sql(“DROP TABLE IF EXISTS my_table”)

What will happen to data in my_table ?

Options :

A : No data will be removed but you will no longer be able to refer to this data by the table name.

B : The data will be dropped also

C : Spark will remove the table and also associated views

D : This is not a valid code block

Answer: A