A data engineering team is migrating a Spark workload from an older version to Azure Databricks. They need to ensure compatibility with their existing Spark code that uses deprecated APIs. Which compute configuration should they consider?

Use the latest Databricks runtime version.

Enable Photon acceleration to improve performance.

Select a Databricks runtime version that matches the Spark version used in the existing code.

Use a serverless compute for the workload.

A data engineering team uses Azure Databricks to run a nightly ETL job that processes a moderate amount of data. The job is scheduled through the Jobs UI and typically takes 20 minutes. The team wants to minimize the time spent waiting for cluster startup and avoid the overhead of managing a persistent cluster. Which compute configuration should they use?

Use a classic interactive cluster that is kept running 24/7.

Create a job compute cluster with a fixed size and enable autoscaling.

Configure the job to use a serverless compute resource.

Use a shared compute resource with a pool of idle instances.

A data scientist needs to use the latest machine learning libraries and frameworks that are pre-installed on the cluster. Which Azure Databricks compute configuration should the data scientist select to ensure these libraries are available?

Databricks Runtime for Machine Learning

A company has a security policy that requires all cluster configurations to be reviewed and approved before changes are made. A data engineer needs to update the Spark configuration on a production cluster to fix a performance issue. The engineer has 'Can Manage' permission on the cluster. What is the best way to proceed?

Update the Spark configuration directly on the production cluster.

Create a new cluster with the updated configuration, test it, and then update the production cluster after approval.

Ask another engineer with 'Can Manage' permission to make the change.

Use a notebook-scoped Spark configuration to override the cluster settings for the production job.

A team runs a streaming workload on an Azure Databricks interactive cluster. The workload has unpredictable spikes in data volume, and the team wants to ensure that the cluster can handle the spikes without manual intervention while keeping costs reasonable during quiet periods. Which configuration should they set?

Set a fixed node count equal to the peak requirement.

Use a job cluster with a short termination time.

Enable autoscaling and set a minimum and maximum node count.

Enable Photon acceleration and keep the default node count.

Microsoft Certified:Azure Databricks Data Engineer Associate

Domain 1Objective 1

Select and Configure Compute in a Workspace DP-750 Practice Questions (Page 3)

Part of the Set up and configure an Azure Databricks environment domain, which accounts for 15–20% of the DP-750 exam. Microsoft does not publish an official question count, but from its 120-minute exam (~50–80 total, ~8–16 in this domain), expect 4–8 from this objective — we provide 27 practice questions to prepare you well beyond it. (estimate)

27questions here

6free pages

5concepts

15–20%of the exam

Questions 11–15

11application · medium
A data engineering team is migrating a Spark workload from an older version to Azure Databricks. They need to ensure compatibility with their existing Spark code that uses deprecated APIs. Which compute configuration should they consider?
Select an answer first
12application · medium
A data engineering team uses Azure Databricks to run a nightly ETL job that processes a moderate amount of data. The job is scheduled through the Jobs UI and typically takes 20 minutes. The team wants to minimize the time spent waiting for cluster startup and avoid the overhead of managing a persistent cluster. Which compute configuration should they use?
Select an answer first
13foundation · easy
A data scientist needs to use the latest machine learning libraries and frameworks that are pre-installed on the cluster. Which Azure Databricks compute configuration should the data scientist select to ensure these libraries are available?
Select an answer first
14expert · hard
A company has a security policy that requires all cluster configurations to be reviewed and approved before changes are made. A data engineer needs to update the Spark configuration on a production cluster to fix a performance issue. The engineer has 'Can Manage' permission on the cluster. What is the best way to proceed?
Select an answer first
15application · medium
A team runs a streaming workload on an Azure Databricks interactive cluster. The workload has unpredictable spikes in data volume, and the team wants to ensure that the cluster can handle the spikes without manual intervention while keeping costs reasonable during quiet periods. Which configuration should they set?
Select an answer first

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Select and Configure Compute in a Workspace DP-750 Practice Questions (Page 3)

Questions 11–15

A data engineering team is migrating a Spark workload from an older version to Azure Databricks. They need to ensure compatibility with their existing Spark code that uses deprecated APIs. Which compute configuration should they consider?

A data scientist needs to use the latest machine learning libraries and frameworks that are pre-installed on the cluster. Which Azure Databricks compute configuration should the data scientist select to ensure these libraries are available?

Keep studying — Set up and configure an Azure Databricks environment