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Databricks-Certified-Data-Engineer-Associate Latest Study Materials & Databricks-Certified-Data-Engineer-Associate Practical Information

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Databricks Certified Data Engineer Associate Exam Sample Questions (Q85-Q90):

NEW QUESTION # 85
A data analysis team has noticed that their Databricks SQL queries are running too slowly when connected to their always-on SQL endpoint. They claim that this issue is present when many members of the team are running small queries simultaneously. They ask the data engineering team for help. The data engineering team notices that each of the team's queries uses the same SQL endpoint.
Which of the following approaches can the data engineering team use to improve the latency of the team's queries?

A. They can turn on the Serverless feature for the SQL endpoint.
B. They can increase the maximum bound of the SQL endpoint's scaling range.
C. They can turn on the Serverless feature for the SQL endpoint and change the Spot Instance Policy to
"Reliability Optimized."
D. They can turn on the Auto Stop feature for the SQL endpoint.
E. They can increase the cluster size of the SQL endpoint.

Answer: B

NEW QUESTION # 86
A single Job runs two notebooks as two separate tasks. A data engineer has noticed that one of the notebooks is running slowly in the Job's current run. The data engineer asks a tech lead for help in identifying why this might be the case.
Which of the following approaches can the tech lead use to identify why the notebook is running slowly as part of the Job?

A. They can navigate to the Tasks tab in the Jobs UI and click on the active run to review the processing notebook.
B. They can navigate to the Runs tab in the Jobs UI and click on the active run to review the processing notebook.
C. They can navigate to the Tasks tab in the Jobs UI to immediately review the processing notebook.
D. There is no way to determine why a Job task is running slowly.
E. They can navigate to the Runs tab in the Jobs UI to immediately review the processing notebook.

Answer: A

Explanation:
The Tasks tab in the Jobs UI shows the list of tasks that are part of a job, and allows the user to view the details of each task, such as the notebook path, the cluster configuration, the run status, and the duration. By clicking on the active run of a task, the user can access the Spark UI, the notebook output, and the logs of the task. These can help the user to identify the performance bottlenecks and errors in the task. The Runs tab in the Jobs UI only shows the summary of the job runs, such as the start time, the end time, the trigger, and the status. It does not provide the details of the individual tasks within a job run. Reference: Jobs UI, Monitor running jobs with a Job Run dashboard, How to optimize jobs performance

NEW QUESTION # 87
A data engineer needs to apply custom logic to string column city in table stores for a specific use case. In order to apply this custom logic at scale, the data engineer wants to create a SQL user-defined function (UDF).
Which of the following code blocks creates this SQL UDF?

Answer: C

Explanation:
https://www.databricks.com/blog/2021/10/20/introducing-sql-user-defined-functions.html

NEW QUESTION # 88
Which of the following can be used to simplify and unify siloed data architectures that are specialized for specific use cases?

A. Data lake
B. Data warehouse
C. All of these
D. None of these
E. Data lakehouse

Answer: E

Explanation:
A data lakehouse is a new paradigm that can be used to simplify and unify siloed data architectures that are specialized for specific use cases. A data lakehouse combines the best of both data lakes and data warehouses, providing a single platform that supports diverse data types, open standards, low-cost storage, high-performance queries, ACID transactions, schema enforcement, and governance. A data lakehouse enables data engineers to build reliable and scalable data pipelines that can serve various downstream applications and users, such as data science, machine learning, analytics, and reporting. A data lakehouse leverages the power of Delta Lake, a storage layer that brings reliability and performance to data lakes. References: What is a data lakehouse?, Delta Lake, Lakehouse: A New Generation of Open Platforms that Unify Data Warehousing and Advanced Analytics

NEW QUESTION # 89
A data engineer needs to apply custom logic to string column city in table stores for a specific use case. In order to apply this custom logic at scale, the data engineer wants to create a SQL user-defined function (UDF).
Which of the following code blocks creates this SQL UDF?

Answer: E

NEW QUESTION # 90
......

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