Certification Databricks-Certified-Data-Engineer-Professional Sample Questions | Databricks-Certified-Data-Engineer-Professional Exam Objectives Pdf

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Databricks Databricks-Certified-Data-Engineer-Professional Exam Syllabus Topics:

Section	Weight	Objectives
Data Modeling and Storage	20%	- Storage Optimization - File Formats - Data Modeling
Data Processing	28%	- ETL Pipelines - Data Transformation - Spark SQL - Structured Streaming
Databricks Lakehouse Platform	24%	- Delta Lake - Data Management - Lakehouse Architecture - Unity Catalog
Data Quality and Governance	12%	- Data Quality - Governance - Data Lineage
Monitoring and Troubleshooting	16%	- Monitoring - Troubleshooting - Performance Optimization

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Databricks-Certified-Data-Engineer-Professional Exam Objectives Pdf - Databricks-Certified-Data-Engineer-Professional Study Test

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Databricks Certified Data Engineer Professional Exam Sample Questions (Q249-Q254):

NEW QUESTION # 249
The security team is exploring whether or not the Databricks secrets module can be leveraged for connecting to an external database.
After testing the code with all Python variables being defined with strings, they upload the password to the secrets module and configure the correct permissions for the currently active user. They then modify their code to the following (leaving all other variables unchanged).

Which statement describes what will happen when the above code is executed?

A. The connection to the external table will succeed; the string value of password will be printed in plain text.
B. The connection to the external table will succeed; the string "redacted" will be printed.
C. The connection to the external table will fail; the string "redacted" will be printed.
D. An interactive input box will appear in the notebook; if the right password is provided, the connection will succeed and the encoded password will be saved to DBFS.
E. An interactive input box will appear in the notebook; if the right password is provided, the connection will succeed and the password will be printed in plain text.

Answer: B

Explanation:
This is the correct answer because the code is using the dbutils.secrets.get method to retrieve the password from the secrets module and store it in a variable. The secrets module allows users to securely store and access sensitive information such as passwords, tokens, or API keys. The connection to the external table will succeed because the password variable will contain the actual password value. However, when printing the password variable, the string "redacted" will be displayed instead of the plain text password, as a security measure to prevent exposing sensitive information in notebooks.

NEW QUESTION # 250
A data engineer is working in an interactive notebook with many transformations before outputting the result from display(df.collect() ). The notebook includes wide transformations and a cross join.
The data engineer is getting the following error: "The spark driver has stopped unexpectedly and is restarting. Your notebook will be automatically reattached." Which action should the data engineer take?

A. Check into the Spark UI to see how many jobs are assigned to each stage as they are employing fewer executors.
B. Look at the compute metrics UI to see if the executors have higher than 90% memory utilization.
C. Run the notebook on a single node cluster to keep driver from falling.
D. Rewrite their code to avoid putting memory pressure on the driver node.

Answer: D

Explanation:
Calling df.collect() on a large DataFrame forces all data to be loaded into the driver's memory.
With wide transformations and a cross join, this can easily exceed the driver's capacity, causing it to crash. The data engineer should rewrite the code to avoid collecting large datasets on the driver, using operations like display(df) or writing to storage instead.

NEW QUESTION # 251
Review the following error traceback:
Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from

Which statement describes the error being raised?

A. The code executed was PvSoark but was executed in a Scala notebook.
B. There is a type error because a DataFrame object cannot be multiplied.
C. There is a syntax error because the heartrate column is not correctly identified as a column.
D. There is no column in the table named heartrateheartrateheartrate
E. There is a type error because a column object cannot be multiplied.

Answer: D

Explanation:
https://sparkbyexamples.com/spark/spark-cannot-resolve-given-input-columns/

NEW QUESTION # 252
The business intelligence team has a dashboard configured to track various summary metrics for retail stories. This includes total sales for the previous day alongside totals and averages for a variety of time periods. The fields required to populate this dashboard have the following schema:

For Demand forecasting, the Lakehouse contains a validated table of all itemized sales updated incrementally in near real-time. This table named products_per_order, includes the following fields:

Because reporting on long-term sales trends is less volatile, analysts using the new dashboard only require data to be refreshed once daily. Because the dashboard will be queried interactively by many users throughout a normal business day, it should return results quickly and reduce total compute associated with each materialization.
Which solution meets the expectations of the end users while controlling and limiting possible costs?

A. Populate the dashboard by configuring a nightly batch job to save the required values as a table overwritten with each update.
B. Use Structure Streaming to configure a live dashboard against the products_per_order table within a Databricks notebook.
C. Use the Delta Cache to persists the products_per_order table in memory to quickly the dashboard with each query.
D. Configure a webhook to execute an incremental read against products_per_order each time the dashboard is refreshed.
E. Define a view against the products_per_order table and define the dashboard against this view.

Answer: A

NEW QUESTION # 253
The data engineering team maintains the following code:
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Assuming that this code produces logically correct results and the data in the source tables has been de-duplicated and validated, which statement describes what will occur when this code is executed?

A. The enriched_itemized_orders_by_account table will be overwritten using the current valid version of data in each of the three tables referenced in the join logic.
B. An incremental job will leverage information in the state store to identify unjoined rows in the source tables and write these rows to the enriched_iteinized_orders_by_account table.
C. An incremental job will detect if new rows have been written to any of the source tables; if new rows are detected, all results will be recalculated and used to overwrite the enriched_itemized_orders_by_account table.
D. A batch job will update the enriched_itemized_orders_by_account table, replacing only those rows that have different values than the current version of the table, using accountID as the primary key.
E. No computation will occur until enriched_itemized_orders_by_account is queried; upon query materialization, results will be calculated using the current valid version of data in each of the three tables referenced in the join logic.

Answer: A

Explanation:
This is the correct answer because it describes what will occur when this code is executed. The Get Latest & Actual Certified-Data-Engineer-Professional Exam's Question and Answers from code uses three Delta Lake tables as input sources: accounts, orders, and order_items. These tables are joined together using SQL queries to create a view called new_enriched_itemized_orders_by_account, which contains information about each order item and its associated account details. Then, the code uses write.format("delta").mode("overwrite") to overwrite a target table called enriched_itemized_orders_by_account using the data from the view. This means that every time this code is executed, it will replace all existing data in the target table with new data based on the current valid version of data in each of the three input tables.

NEW QUESTION # 254
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