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Microsoft Implementing Data Engineering Solutions Using Azure Databricks Sample Questions:

1. You have an Azure Databricks workspace that contains an all-purpose cluster named Cluster1.
You need to configure Cluster1 to meet the following requirements:
- The cluster must scale up automatically when workloads increase.
- The cluster must scale down automatically when workloads decrease.
The solution must minimize costs.
Which two actions should you perform? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

A) Configure Cluster1 to terminate after 30 minutes of inactivity.
B) Specify a fixed number of workers.
C) Apply a compute policy that enables users to manage the cluster settings.
D) Disable Photon acceleration.
E) Enable autoscaling for Cluster1.

2. A Delta table receives new fields in incoming JSON data. You want to automatically adapt without breaking pipelines. What should you enable?

A) Auto Loader with schema inference and evolution
B) Disable schema enforcement
C) Manually update schema each time
D) Use overwrite mode

3. You have an Azure Databricks workspace that is enabled for Unity Catalog.
You have an Apache Spark Structured Streaming job that writes data to a Delta table.
After the cluster restarts, the streaming job reprocesses previously ingested data.
You need to prevent the streaming job from reprocessing the data after the cluster restarts.
What should you do?

A) Configure a checkpoint location for the streaming query.
B) Enable change data feed (CDF) for the target table.
C) Configure a watermark for the streaming query.
D) Increase the trigger interval of the streaming query.

4. You have an Azure Databricks workspace that is enabled for Unity Catalog.
You have a Lakeflow Spark Declarative Pipelines (SDP) pipeline that writes numerical data to a table named Table1 by using a data quality validation rule named rule1.
You need to modify rule1 to meet the following requirements:
- Ensure that amount is always greater than 0.
- Prevent an update to Table1 from being committed when data that
violates rule1 is detected.
Which statement should you execute?

A) @dlt.expect("rule1", "amount > 0")
B) @dlt.expect_all_or_drop({"rule1": "amount > 0"})
C) @dlt.expect_or_fail("rule1", "amount > 0")
D) @dlt.expect_or_drop("rule1", "amount > 0")

5. You need to deploy Databricks Asset Bundles to a development environment. The solution must support automated and repeatable deployments across environments. What should you use?

A) the Jobs UI
B) Git folders
C) the Databricks SDK for Python
D) the Databricks CLI

Solutions: