DP-900 Azure Databricks 1 — Questions and Answers
Question 1: Azure Databricks is primarily built on which open-source distributed computing framework?
- Apache Hadoop
- Apache Spark (Correct answer)
- Apache Kafka
- Apache Flink
Correct answer: Apache Spark
Azure Databricks is an analytics platform built on Apache Spark, which provides distributed data processing capabilities.
Question 2: What collaborative feature do Azure Databricks workspaces provide for data teams?
- Shared SQL Server instances
- Interactive notebooks supporting multiple languages (Correct answer)
- Shared Power BI dashboards
- Shared Azure DevOps pipelines
Correct answer: Interactive notebooks supporting multiple languages
Azure Databricks provides interactive notebooks that support multiple languages (Python, Scala, SQL, R) and allow data engineers, data scientists, and analysts to collaborate.
Question 3: Which data storage layer within Azure Databricks provides ACID transaction support and versioning for data lakes?
- Azure Blob Storage
- Delta Lake (Correct answer)
- Azure Data Factory
- Azure Table Storage
Correct answer: Delta Lake
Delta Lake is an open-source storage layer in Azure Databricks that brings ACID transactions, versioning, and schema enforcement to data lakes.
Question 4: What is an Azure Databricks cluster?
- A group of Azure virtual networks
- A collection of Azure SQL databases
- A set of computation resources used to run notebooks and jobs (Correct answer)
- A group of Azure Blob Storage containers
Correct answer: A set of computation resources used to run notebooks and jobs
An Azure Databricks cluster is a set of computation resources (VMs) that run Apache Spark workloads including notebooks, jobs, and streaming applications.
Question 5: Which programming languages are natively supported in Azure Databricks notebooks?
- Python, Java, C#, and Go
- Python, Scala, SQL, and R (Correct answer)
- Python, JavaScript, TypeScript, and Ruby
- SQL, T-SQL, PL/SQL, and MySQL
Correct answer: Python, Scala, SQL, and R
Azure Databricks notebooks natively support Python, Scala, SQL, and R, allowing data professionals from different backgrounds to collaborate in the same workspace.
Question 6: How does Azure Databricks integrate with Azure Data Lake Storage Gen2?
- It cannot connect to Azure Data Lake Storage Gen2
- It requires a dedicated Azure Data Factory pipeline to read data
- It can mount ADLS Gen2 as a file system or access it directly via Spark (Correct answer)
- It only supports reading data, not writing to ADLS Gen2
Correct answer: It can mount ADLS Gen2 as a file system or access it directly via Spark
Azure Databricks can mount Azure Data Lake Storage Gen2 as a file system or access it directly via Spark APIs using service principal or managed identity authentication.
Question 7: What is the primary advantage of using Azure Databricks for large-scale data processing compared to a single-node approach?
- Lower storage costs
- Ability to process data in parallel across multiple nodes (Correct answer)
- Built-in data visualization
- Native integration with Excel
Correct answer: Ability to process data in parallel across multiple nodes
Azure Databricks distributes data processing across multiple cluster nodes in parallel using Apache Spark, enabling it to handle large-scale datasets much faster than single-node solutions.
DP-900 Azure Databricks 1
Azure Databricks is primarily built on which open-source distributed computing framework?