Question 1

You are asked to setup the alert to notify every time once the data is loaded into a reporting table, team also asked to include the number of records in the alert email notification.

Options :

A : Use notebook and python code to run every minute, using python variables to capture send the information in an email

B : Setup an alert but use the default template to notify the message in email’s subject

C : Setup an alert but use the custom template to notify the message in email’s subject

D : Use the webhook destination instead so alert message can be customized

E : Use custom email hook to customize the message

Answer: C

Question 2

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

Question 3

A data engineer has a Job with multiple tasks that runs nightly. Each of the tasks runs slowly because the clusters take a long time to start.

Which action can the data engineer perform to improve the start up time for the clusters used for the Job?

Options :

A : They can use endpoints available in Databricks SQL

B : They can use jobs clusters instead of all-purpose clusters

C : They can configure the clusters to be single-node

D : They can use clusters that are from a cluster pool

E : They can configure the clusters to autoscale for larger data sizes

Answer: D

Question 4

When you drop a managed table using SQL syntax DROP TABLE table_name how does it impact metadata, history, and data stored in the table?

Options :

A : Drops table from meta store, drops metadata, history, and data in storage.

B : Drops table from meta store and data from storage but keeps metadata and history in storage

C : Drops table from meta store, meta data and history but keeps the data in storage

D : Drops table but keeps meta data, history and data in storage

E : Drops table and history but keeps meta data and data in storage

Answer: A

Question 5

you are currently working on creating a spark stream process to read and write in for a one-time micro batch, and also rewrite the existing target table, fill in the blanks to complete the below command sucesfully.

spark.table("source_table")

.writeStream

.option("____", “dbfs:/location/silver")

.outputMode("____")

.trigger(Once=____)

.table("target_table")

Options :

A : checkpointlocation, complete, True

B : targetlocation, overwrite, True

C : checkpointlocation, True, overwrite

D : checkpointlocation, True, complete

E : checkpointlocation, overwrite, True

Answer: A