Question 1

A data engineer has a single-task Job that runs each morning before they begin working. After identifying an upstream data issue, they need to set up another task to run a new notebook prior to the original task.

Which approach can the data engineer use to set up the new task?

Options :

A : They can clone the existing task in the existing Job and update it to run the new notebook.

B :

They can create a new task in the existing Job and then add it as a dependency of the original task.

C :

They can create a new task in the existing Job and then add the original task as a dependency of the new task.

D : They can create a new job from scratch and add both tasks to run concurrently.

E : They can clone the existing task to a new Job and then edit it to run the new notebook.

Answer: C

Question 2

At the end of the inventory process a file gets uploaded to the cloud object storage, you are asked to build a process to ingest data which of the following method can be used to ingest the data incrementally, schema of the file is expected to change overtime ingestion process should be able to handle these changes automatically. Below is the auto loader to command to load the data, fill in the blanks for successful execution of below code.

spark.readStream

.format("cloudfiles")

.option("_______",”csv)

.option("_______", ‘dbfs:/location/checkpoint/’)

.load(data_source)

.writeStream

.option("_______",’ dbfs:/location/checkpoint/’)

.option("_______", "true")

.table(table_name))

Options :

A : format, checkpointlocation, schemalocation, overwrite

B : cloudfiles.format, checkpointlocation, cloudfiles.schemalocation, overwrite

C : cloudfiles.format, cloudfiles.schemalocation, checkpointlocation, mergeSchema

D : cloudfiles.format, cloudfiles.schemalocation, checkpointlocation, append

E : cloudfiles.format, cloudfiles.schemalocation, checkpointlocation, overwrite

Answer: C

Question 3

When investigating a data issue, if you are looking compare the current version of the data with the previous version, what is the best way to query historical data?

Options :

A : SELECT * FROM TIME_TRAVEL(table_name) where time_stamp = 'timestamp'

B : TIME_TRAVEL FROM table_name where time_stamp = 'timestamp'

C : SELECT * FROM table_name as of 'timestamp'

D : DISCRIBE HISTORY table_name as of 'timestmap'

E : SHOW HISTORY table_name as of 'timestmap'

Answer: C

Question 4

Which of the following SQL statement can be used to query a table by eliminating duplicate rows from the query results?

Options :

A : SELECT DISTINCT * FROM table_name

B : SELECT DISTINCT * FROM table_name HAVING COUNT(*) > 1

C : SELECT DISTINCT_ROWS (*) FROM table_name

D : SELECT * FROM table_name GROUP BY * HAVING COUNT(*) < 1

E : SELECT * FROM table_name GROUP BY * HAVING COUNT(*) > 1

Answer: A

Question 5

Data science team members are using a single cluster to perform data analysis, although cluster size was chosen to handle multiple users and auto-scaling was enabled, the team realized queries are still running slow, what would be the suggested fix for this?

Options :

A : Setup multiple clusters so each team member has their own cluster

B : Disable the auto-scaling feature

C : Use High concurrency mode instead of the standard mode

D : Increase the size of the driver node

Answer: C

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