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Microsoft DP-750 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Prepare and process data | 30-35% | - Ingest and transform data
|
| Topic 2: Secure and govern Unity Catalog objects | 15-20% | - Implement governance and security
|
| Topic 3: Set up and configure an Azure Databricks environment | 15-20% | - Create and configure Azure Databricks workspaces
|
| Topic 4: Deploy and maintain data pipelines and workloads | 30-35% | - Manage production workloads
|
Microsoft Implementing Data Engineering Solutions Using Azure Databricks Sample Questions:
1. You have an Azure Databricks workspace that is enabled for Unity Catalog.
You plan to ingest data from CSV files stored in Azure Data Lake Storage Gen2. New rows are appended frequently.
You need to implement a data ingestion solution that meets the following requirements:
* New data must be available in near-real-time (NRT).
* The data must be stored in managed Delta tables.
* The solution must minimize custom code and maintenance effort.
What should you include in the solution?
A) an Azure Data Factory pipeline
B) an external table that references the CSV files
C) Auto Loader
D) scheduled Apache Spark batch jobs
2. You have an Azure Databricks workspace that contains a Delta table named Table 1. Table 1 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 10 days
B) Set the delta. logRetentionDuration table property to 30 days.
C) Reduce the deleted file retention period to one day.
D) Run the vacuum command on Table1.
E) Run the OPTIMIZE command on Table1
3. You have an Azure Databricks workspace.
Users report that a Databricks notebook that runs each day takes longer than expected to run.
When reading the Directed Acyclic Graph (DAG), you discover the following issues concerning the Apache Spark stage:
* Most tasks in the stage finish quickly.
* A few tasks in the stage run more slowly.
* The CPU is underutilized at the end of the stage.
* The slow tasks process many more input records.
* The stage is blocked while it waits for the few slow tasks.
What is the root cause of the issues?
A) shuffling
B) caching
C) spilling
D) skewing
4. You have an Azure Databricks workspace named Workspace1 that is attached to a Unity Catalog metastore named metastore1 You need to register an Azure Storage account named account1 that has a hierarchical namespace enabled as an external location The external location must use a managed identity to authenticate to account1 and the solution must follow the principle of least privilege.
Which three actions should you perform in sequence ' To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
5. You have an Azure Databricks workspace that contains a Git folder and uses Azure Repos as the Git provider.
From the main branch, you create a branch named Branch1. You commit changes to Branch1.
You need to incorporate the changes from Branch1 into main The solution must preserve the commit history in the repository. Which command should you run?
A) rebase
B) pull
C) Push
D) merge
Solutions:
| Question # 1 Answer: C | Question # 2 Answer: A,D | Question # 3 Answer: D | Question # 4 Answer: Only visible for members | Question # 5 Answer: D |
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