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DP-200 Exam - Question 68


Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.

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You plan to create an Azure Databricks workspace that has a tiered structure. The workspace will contain the following three workloads:

✑ A workload for data engineers who will use Python and SQL

✑ A workload for jobs that will run notebooks that use Python, Scala, and SQL

✑ A workload that data scientists will use to perform ad hoc analysis in Scala and R

The enterprise architecture team at your company identifies the following standards for Databricks environments:

✑ The data engineers must share a cluster.

✑ The job cluster will be managed by using a request process whereby data scientists and data engineers provide packaged notebooks for deployment to the cluster.

✑ All the data scientists must be assigned their own cluster that terminates automatically after 120 minutes of inactivity. Currently, there are three data scientists.

You need to create the Databricks clusters for the workloads.

Solution: You create a Standard cluster for each data scientist, a High Concurrency cluster for the data engineers, and a Standard cluster for the jobs.

Does this meet the goal?

Show Answer
Correct Answer: A

For the given scenario, a Standard cluster for each data scientist is appropriate as it suits individual usage and meets the standard of automatic termination after 120 minutes of inactivity. A High Concurrency cluster for data engineers is suitable for maximizing resource utilization and handling concurrent queries since they need a shared environment. Finally, a Standard cluster for the job workloads is adequate because it supports multiple languages (Python, Scala, SQL) and handles the execution of notebooks. High Concurrency clusters, while beneficial for SQL, Python, and R, do not support running Scala code, which is a requirement for the job workloads. Therefore, the proposed solution meets the requirements and goals.

Discussion

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vaseva1
Apr 5, 2021

A workload for jobs that will run notebooks that use Python, Scala, and SQL --> so Standard clusters because of Scala (High Concurrency clusters is provided by running user code in separate processes, which is not possible in Scala.)

Chiranjib
May 13, 2021

Correct. Create New Cluster UI for Jobs allows either Standard or Single Node. It does list high concurrency as an option https://docs.microsoft.com/en-us/azure/databricks/clusters/create

sharma21
Apr 28, 2021

A is correct

Wendy_DK
Apr 20, 2021

Correct answer is A

Prabhakaran94
Apr 19, 2021

Correct answer is: Yes

cadio30
May 11, 2021

appropriate answer is A

elimey
Jul 24, 2021

High Concurrency clusters can run workloads developed in SQL, Python, and R. The performance and security of High Concurrency clusters is provided by running user code in separate processes, which is not possible in Scala. means job can not be high concurrency so, ANSWER IS A

FredNoOption: A
Nov 23, 2021

Standard for jobs and high concurrency for darta scientists and data engineers