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Databricks Certified Professional Data Engineer Exam Sample Questions (Q33-Q38):

NEW QUESTION # 33
Which of the statement is correct about the cluster pools?

• A. Cluster pools allow you to create a cluster
• B. Cluster pools allow you to perform load balancing
• C. Cluster pools are used to share resources among multiple teams
• D. Cluster pools allow you to save time when starting a new cluster
• E. Cluster pools allow you to have all the nodes in the cluster from single physical server rack

Answer: D

NEW QUESTION # 34
A data engineer has created a Delta table as part of a data pipeline. Downstream data analysts now need
SELECT permission on the Delta table.
Assuming the data engineer is the Delta table owner, which part of the Databricks Lakehouse Plat-form can
the data engineer use to grant the data analysts the appropriate access?

• A. Jobs
  B Dashboards
• B. Repos
• C. Databricks Filesystem
• D. Data Explorer

Answer: B

NEW QUESTION # 35
You are noticing job cluster is taking 6 to 8 mins to start which is delaying your job to finish on time, what steps you can take to reduce the amount of time cluster startup time

• A. Reduce the size of the cluster, smaller the cluster size shorter it takes to start the clus-ter
• B. Setup a second job ahead of first job to start the cluster, so the cluster is ready with re-sources when the job starts
• C. Use cluster pools to reduce the startup time of the jobs
• D. Use SQL endpoints to reduce the startup time
• E. Use All purpose cluster instead to reduce cluster start up time

Answer: C

Explanation:
Explanation
The answer is, Use cluster pools to reduce the startup time of the jobs.
Cluster pools allow us to reserve VM's ahead of time, when a new job cluster is created VM are grabbed from the pool. Note: when the VM's are waiting to be used by the cluster only cost incurred is Azure. Databricks run time cost is only billed once VM is allocated to a cluster.
Here is a demo of how to setup and follow some best practices,
https://www.youtube.com/watch?v=FVtITxOabxg&ab_channel=DatabricksAcademy

NEW QUESTION # 36
You noticed that a team member started using an all-purpose cluster to develop a notebook and used the same all-purpose cluster to set up a job that can run every 30 mins so they can update un-derlying tables which are used in a dashboard. What would you recommend for reducing the overall cost of this approach?

• A. Reduce the size of the cluster
• B. Reduce the number of nodes and enable auto scale
• C. Enable auto termination after 30 mins
• D. Change the cluster all-purpose to job cluster when scheduling the job
• E. Change the cluster mode from all-purpose to single-mode

Answer: D

Explanation:
Explanation
While using an all-purpose cluster is ok during development but anytime you don't need to interact with a notebook, especially for a scheduled job it is less expensive to use a job cluster. Using an all-purpose cluster can be twice as expensive as a job cluster.
Please note: The compute cost you pay the cloud provider for the same cluster type and size be-tween an all-purpose cluster and job cluster is the same the only difference is the DBU cost.
The total cost of cluster = Total cost of VM compute(Azure or AWS or GCP) + Cost per DBU The per DBU cost varies between all-purpose and Job Cluster Here is the recent cost estimate from AWS between Jobs Cluster and all-purpose Cluster, for jobs compute its
$0.15 cents per DBU v$0.55 cents per DBU for all-purpose
Graphical user interface Description automatically generated

How do I check how much the DBU cost for my cluster?
When you click on an exister cluster or when you look at the cluster details you will see this in the top right corner Graphical user interface, text, application, email Description automatically generated

NEW QUESTION # 37
A data engineering team needs to query a Delta table to extract rows that all meet the same condi-tion.
However, the team has noticed that the query is running slowly. The team has already tuned the size of the
data files. Upon investigating, the team has concluded that the rows meeting the condition are sparsely located
throughout each of the data files.
Based on the scenario, which of the following optimization techniques could speed up the query?

• A. Tuning the file size
• B. Bin-packing
• C. Data skipping
• D. Z-Ordering
• E. Write as a Parquet file

Answer: D

NEW QUESTION # 38
......

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