Question 1

Which of the following statements regarding the retention policy of Delta lake CDF is correct ?

Options :

A : Running the VACUUM command on the table deletes CDF data as well

B : Running the VACUUM command on the table does not deletes CDF data

C : Running the VACUUM command on the table does not deletes CDF data unless CASCADE clause is set to true

D : CDF data files can be purged by running VACUUM CHANGES command

E : CDF data files can never be permanently purged from Delta Lake

Answer: A

Question 2

An upstream system has been configured to pass the date for a given batch of data to the Databricks Jobs API as a parameter. The notebook to be scheduled will use this parameter to load data with the following code: df = spark.read.format("parquet").load(f"/mnt/source/(date)") Which code block should be used to create the date Python variable used in the above code block?

Options :

A : date = spark.conf.get("date")

B :

input_dict = input() date= input_dict["date"]

C :

import sys date = sys.argv[1]

D : date = dbutils.notebooks.getParam("date")

E :

dbutils.widgets.text("date", "null") date = dbutils.widgets.get("date")

Answer: E

Question 3

A developer has successfully configured their credentials for Databricks Repos and cloned a remote Git repository. They do not have privileges to make changes to the main branch, which is the only branch currently visible in their workspace.

Which approach allows this user to share their code updates without the risk of overwriting the work of their teammates?

Options :

A : Use Repos to create a new branch, commit all changes, and push changes to the remote Git repository.

B : Use Repos to create a fork of the remote repository, commit all changes, and make a pull request on the source repository.

C : Use Repos to pull changes from the remote Git repository; commit and push changes to a branch that appeared as changes were pulled.

D : Use Repos to merge all differences and make a pull request back to the remote repository.

Answer: A

Question 4

Where in the Spark UI can one diagnose a performance problem induced by not leveraging predicate pushdown?

Options :

A : In the Executor’s log file, by grepping for "predicate push-down"

B :

In the Stage’s Detail screen, in the Completed Stages table, by noting the size of data read from the Input column

C : In the Storage Detail screen, by noting which RDDs are not stored on disk

D : In the Delta Lake transaction log. by noting the column statistics

E : In the Query Detail screen, by interpreting the Physical Plan

Answer: E

Question 5

Which of the following statements correctly describes End-to-End Testing ?

Options :

A : It’s an approach to simulate a user experience to ensure that the application can run properly under real-world scenarios

B : It’s an approach to test the interaction between subsystems of an application to ensure that modules work properly as a group.

C : It’s an approach to test individual units of code to determine whether they still work as expected if new changes are made to them in the future

D : It’s an approach to verify if each feature of the application works as per the business requirements

E : It’s an approach to measure the reliability, speed, scalability, and responsiveness of an application

Answer: A

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