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Microsoft Implementing Data Engineering Solutions Using Azure Databricks Sample Questions:

1. Which tool is best for continuous ingestion of files landing in Azure Data Lake?

A) Databricks Jobs
B) Azure Logic Apps
C) Azure Data Factory Copy Activity
D) Auto Loader

2. Hotspot Question
You have an Azure Databricks workspace.
You have an Azure key vault named kv-secure that stores a secret named storageKey. The value of storageKey is managed and updated by the cloud security team at your company.
You need to enable a Databricks notebook named Notebook1 to retrieve the value of storageKey securely at runtime. The solution must follow the principle of least privilege and always retrieve the latest value.
What should you do? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

3. Note: This section contains one or more sets of questions with the same scenario and problem. Each question presents a unique solution to the problem. You must determine whether the solution meets the stated goals. More than one solution in the set might solve the problem. It is also possible that none of the solutions in the set solve the problem.
After you answer a question in this section, you will NOT be able to return. As a result, these questions do not appear on the Review Screen.
You have an Azure Databricks workspace that is enabled for Unity Catalog and contains a Delta table named Orders.
You load the Orders table into an Apache Spark DataFrame named df.
You need to create a DataFrame that excludes rows where the order amount is null.
Solution: You run the following expression.
df.fillna(0, subset=['order_amount'])
Does this meet the goal?

A) No
B) Yes

4. You have a Lakeflow Spark Declarative Pipelines (SDP) pipeline in Azure Databricks. The pipeline ingests transaction data into a table named Table1.
You need to ensure that in the event of an invalid record, the pipeline continues to run. The solution must meet the following requirements:
- Invalid records must NOT be written to Table1.
- Invalid records must be preserved for review.
- Minimize development effort.
What should you do?

A) Implement advanced logic to quarantine the invalid records.
B) Add a CHECKconstraint to Table1.
C) Run WHEREclauses in downstream queries to filter out invalid records.
D) Define a pipeline expectation.

5. You have an Azure Databricks workspace that contains a Delta table named Table1.
Table1 has accumulated obsolete files.
You need to reduce storage costs. The solution must preserve 30 days of time travel history.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

A) Set the delta.deletedFileRetentionDuration table property to 30 days.
B) Reduce the deleted file retention period to one day.
C) Set the delta.logRetentionDuration table property to 30 days.
D) Run the OPTIMIZE command on Table1.
E) Run the vacuum command on Table1.

Solutions: