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Databricks-Certified-Data-Engineer-Associate Exam Dumps : Databricks Certified Data Engineer Associate Exam

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Databricks Certified Data Engineer Associate Exam Questions and Answers

Question 1

A global retail company sells products across multiple categories (e.g.. Electronics, Clothing) and regions (e.g.. North. South, East. West). The sales team has provided the data engineer with a PySpark dataframe named sales_df as below and the team wants the data engineer to analyze the sales data to help them make strategic decisions.

Options:

A.

Category_sales = sales df.groupBy("category").agg(sum("sales amount") .alias ("total sales amount"))

B.

Category_sales = sales_df.sum("3ales_amount"). g-1- upBy("categcryn).alias("toLal_sales_amount))

C.

Category_sale: .es df -agg (sum ("sales amount") .-;r*i:rRy ("category") .alias ("total sa.en amount"))

D.

Category_sales = sales_df.groupBy("reqion"). agq(sum("sales_amountn).alias(ntotal_sales_amount''))

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Question 2

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?

Options:

A.

They can navigate to the Runs tab in the Jobs UI to immediately review the processing notebook.

B.

They can navigate to the Tasks tab in the Jobs UI and click on the active run to review the processing notebook.

C.

They can navigate to the Runs tab in the Jobs UI and click on the active run to review the processing notebook.

D.

There is no way to determine why a Job task is running slowly.

E.

They can navigate to the Tasks tab in the Jobs UI to immediately review the processing notebook.

Question 3

A data engineer has realized that the data files associated with a Delta table are incredibly small. They want to compact the small files to form larger files to improve performance.

Which of the following keywords can be used to compact the small files?

Options:

A.

REDUCE

B.

OPTIMIZE

C.

COMPACTION

D.

REPARTITION

E.

VACUUM