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Exam DP-203 topic 2 question 88 discussion

Actual exam question from Microsoft's DP-203
Question #: 88
Topic #: 2
[All DP-203 Questions]

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 High Concurrency cluster for the jobs.
Does this meet the goal?

  • A. Yes
  • B. No
Show Suggested Answer Hide Answer
Suggested Answer: B 🗳️

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dfdsfdsfsd
Highly Voted 3 years, 11 months ago
High-concurrency clusters do not support Scala. So the answer is still 'No' but the reasoning is wrong. https://docs.microsoft.com/en-us/azure/databricks/clusters/configure
upvoted 46 times
Preben
3 years, 10 months ago
I agree that High concurrency does not support Scala. But they specified using a Standard cluster for the jobs, which does support Scala. Why is the answer 'No'?
upvoted 3 times
eng1
3 years, 10 months ago
Because the High Concurrency cluster for each data scientist is not correct, it should be standard for a single user!
upvoted 6 times
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mav2000
1 year, 2 months ago
High concurrency supports scala now, so the answer should be A)
upvoted 1 times
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FRAN__CO_HO
Highly Voted 3 years, 10 months ago
Answer should be NO, which Data scientist: STANDARD as need to run scala Jobs: STANDARD as need to run scala Data Engineers: High-concurrency clusters as better resource sharing
upvoted 15 times
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Sr18
Most Recent 10 months, 2 weeks ago
Down the line 3 years back No must have been correct answer but now its not. Scala is supported at High Concurrency cluster only thing it doesn't benefit with the concurrency due the JVM thingy. So ideally speaking... Data Engineers : High Concurrency - due to the fact of sharing Data Scientist : Standard - because its better to leave them in their space Job Cluster : Standard is best, but High Concurrency is also good. So answer should be Yes, because here they don't talk about cost, performance etc.
upvoted 4 times
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Azure_2023
1 year, 2 months ago
Selected Answer: B
There are potential cost and resource utilization concerns with the separate High Concurrency cluster for jobs.
upvoted 1 times
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Tactable
1 year, 6 months ago
High concurrency doesn't support Scala
upvoted 2 times
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kkk5566
1 year, 8 months ago
Selected Answer: B
Answer is No.
upvoted 1 times
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auwia
1 year, 10 months ago
Selected Answer: B
Correct answer: false (no)
upvoted 1 times
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Pais
2 years, 5 months ago
Selected Answer: B
High-concurrency cluster does not support Scala.
upvoted 1 times
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OldSchool
2 years, 5 months ago
Selected Answer: B
Jobs require Scala so the answer is B) No.
upvoted 1 times
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greenlever
2 years, 6 months ago
Selected Answer: B
Cluster for Jobs should support scala - STANDARD
upvoted 1 times
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anks84
2 years, 7 months ago
We would need a Standard cluster for the jobs to support Scala. High-concurrency cluster does not support Scala. Hence, Answer is NO
upvoted 1 times
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Hema_V
2 years, 8 months ago
Selected Answer: B
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. https://docs.microsoft.com/en-us/azure/databricks/clusters/configure
upvoted 1 times
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Deeksha1234
2 years, 8 months ago
No is correct
upvoted 1 times
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ClassMistress
2 years, 11 months ago
Selected Answer: B
High Concurrency clusters is provided by running user code in separate processes, which is not possible in Scala.
upvoted 1 times
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narendra399
3 years, 1 month ago
1 and 2 are same questions but answers are different why?
upvoted 2 times
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Hanse
3 years, 1 month ago
As per Link: https://docs.azuredatabricks.net/clusters/configure.html Standard and Single Node clusters terminate automatically after 120 minutes by default. --> Data Scientists High Concurrency clusters do not terminate automatically by default. A Standard cluster is recommended for a single user. --> Standard for Data Scientists & High Concurrency for Data Engineers Standard clusters can run workloads developed in any language: Python, SQL, R, and Scala. 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. --> Jobs needs Standard
upvoted 2 times
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lukeonline
3 years, 4 months ago
Selected Answer: B
high concurrency does not support scala
upvoted 2 times
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