Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0 Practice Online

Question 1

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

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

Question 2

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 ?

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 3

You have a need to transform a column named ‘date’ to a timestamp format. Assume that the column ‘date’ is timestamp compatible. You have written the code block

down below, but it contains an error. Identify and fix it.

df.select(to_timestamp("yyyy-dd-MM", col("date"))).show()

A :

to_timestamp() is not a valid operation. Proper function is toTimestamp()

1. df.select(toTimestamp(col("date"), "yyyy-dd-MM"))

B :

to_timestamp() is not a valid operation. Proper function is toTimestamp()

1. df.select(toTimestamp("yyyy-dd-MM", col("date")))

C :

No need for the quotes.

df.select(to_timestamp(yyyy-dd-MM, col(date)))

D :

First parameter should be column and then it should be followed by the desired format.

df.select(to_timestamp(col("date"), "yyyy-dd-MM"))

Answer: D

Question 4

Which of the following transformation is not evaluated lazily ?

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

B : sample()

C : filter()

D : repartition()

E : select()

Answer: A

Question 5

How to make sure that dataframe df has 12 partitions given that df has 4 partitions ?

A : df.repartition(12)

B : df.setPartitition(12)

C : df.repartition()

D : df.setPartitition()

Answer: A

Name:	Databricks Certified Associate Developer for Apache Spark 3.0
Exam Code:	Databricks-Certified-Associate-Developer-for-Apache-Spark-3.0
Certification:	Apache Spark Associate Developer
Vendor:	Databricks
Total Questions:	420
Last Updated:	Apr 23, 2024

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