Top 30 Databricks Interview Questions with Answers

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Here are 30 Databricks interview questions along with their answers:

1. What is Databricks?

Ans: Databricks is a cloud-based unified data analytics platform that combines Apache Spark with a collaborative workspace. It provides an interactive environment for data engineering, data science, and analytics.

2. How does Databricks leverage Apache Spark?

Ans: Databricks leverages Apache Spark as its underlying distributed processing engine. It provides an optimized and managed Spark environment with additional features and integrations to simplify data analytics tasks.

3. What are the key components of Databricks?

Ans: Databricks consists of several key components:

  • Databricks Workspace: A collaborative environment for data exploration and development.
  • Databricks Runtime: A managed Spark runtime optimized for performance and scalability.
  • Databricks Notebooks: An interactive interface for code development and data analysis.
  • Databricks Jobs: A scheduling and automation system for running code and workflows.
  • Databricks Libraries: A repository of external libraries and dependencies.

4. How can you create a cluster in Databricks?

Ans: To create a cluster in Databricks, go to the Clusters tab in the Databricks Workspace and click on the “Create Cluster” button. You can specify the cluster configuration, such as the number of nodes, Spark version, and hardware specifications.

5. What is the Databricks Workspace?

Ans: The Databricks Workspace is a collaborative environment where users can develop and execute code, create and manage notebooks, and collaborate with team members. It provides a central location for data exploration and development.

6. How can you share notebooks in Databricks?

Ans: In Databricks, you can share notebooks with others by exporting them as a DBC archive or by sharing the notebook URL. You can also control access to notebooks by managing the workspace access permissions.

7. What is Delta Lake in Databricks?

Ans: Delta Lake is an open-source storage layer that runs on top of existing data lakes, providing ACID transactions, data versioning, and schema enforcement capabilities. It allows you to create structured and reliable data lakes in Databricks.

8. What is the use of Databricks Jobs?

Ans: Databricks Jobs enables you to schedule and automate the execution of code and workflows in Databricks. You can create jobs to run notebooks, scripts, or jars on a specified schedule or in response to events.

9. How can you monitor and optimize Spark jobs in Databricks?

Ans: Databricks provides a web-based user interface where you can monitor the execution of Spark jobs. You can view the job history, resource utilization, and performance metrics to identify bottlenecks and optimize job performance.

10. What is the advantage of using Databricks Delta over traditional data lakes?

Ans: Databricks Delta offers several advantages over traditional data lakes, including:

  • ACID transactions for data consistency and reliability.
  • Schema enforcement and evolution to ensure data quality.
  • Optimized performance with indexing and data skipping.
  • Time travel and versioning for data auditing and rollbacks.

11. How do Databricks support machine learning workflows?

Ans: Databricks provides integrations with popular machine learning frameworks like TensorFlow, PyTorch, and scikit-learn. It offers distributed computing capabilities and supports MLflow, a machine learning lifecycle management platform.

12. Can you integrate Databricks with version control systems?

Ans: Yes, Databricks integrates with version control systems like Git. You can connect Databricks with Git repositories to manage version control and collaborate on notebooks and code.

13. How to generate a personal access token in databricks?

Ans: We can generate a personal access token in seven steps they are:

  • In the upper right corner of Databricks workspace, click the icon named: “user profile.”
  • In the second step, you have to choose “User setting.”
  • navigate to the tab called “Access Tokens.”
  • Then you can find a “Generate New Token” button. Click it.

14. How to revoke a personal access token?

Ans: We have to follow five steps to revoke a personal access token they are:

  • In the upper right corner of Databricks workspace, click the icon named: “user profile.”
  • In the second step, you have to choose “User setting.”
  • navigate to the tab called “Access Tokens.”
  • In this step, you have to click x for the token you need to revoke.
  • Finally, click the button “Revoke Token” on the Revoke Token dialog.

15. What is the purpose of Databricks runtime?

Ans: Databricks runtime is used to run the set of components on the Databricks platform.

16. Can Databricks be run on private cloud infrastructure, or must it be run on a public cloud such as AWS or Azure?

Ans: That is not the case. At this time, your only alternatives are AWS and Azure. However, Databricks runs open-source Spark. You could create your own cluster and operate it in a private cloud, but you’d be missing out on Databricks’ extensive capabilities and administration.

17. Is it possible to administer Databricks using PowerShell?

Ans: No, officially. However, Gerhard Brueckl, a fellow Data Platform MVP, has built an excellent PowerShell module.

18. How can you create a Databricks private access token?

Ans: Select the “user profile” icon in the top right corner of the Databricks desktop.
Select “User setting.”
Go to the “Access Tokens” tab.
Then, a “Generate New Token” button will appear. Simply click it.

19. What is the procedure for revoking a private access token?

Ans:

  • Select the “user profile” icon in the top right corner of the Databricks desktop.
  • Select “User setting.”
  • Go to the “Access Tokens” tab.
  • Click ‘x ‘next to the token you wish to cancel.
  • Finally, on the Revoke Token window, click the button “Revoke Token.”

20. What is the Databricks runtime used for?

Ans: The Databricks runtime is often used to execute the Databricks platform’s collection of modules.

21. Can you administer Databricks using PowerShell?

Ans: Officially, you can’t do it. But there are PowerShell modules that you can try out.

22. What is the difference between an instance and a cluster in Databricks?

Ans: An instance is a virtual machine that helps run the Databricks runtime. A cluster is a group of instances that are used to run Spark applications.

23. How to create a Databricks private access token?

Ans: To create a private access token, go to the “user profile” icon and select “User setting.” Here, you’ll need to select the “Access Tokens” tab where you can see the button “Generate New Token”. Click the button that would create the token.

24. What is the procedure for revoking a private access token?

Ans: To revoke the token, go to “user profile” and select “User setting.” Select the “Access Tokens” tab and click the ‘x’ you’ll find next to the token that you want to revoke. Finally, on the Revoke Token window, click the button “Revoke Token.”

25. What is the management plane in Azure Databricks?

Ans: The management plan is how you manage and monitor your Databricks deployment.

26. What is the control plane in Azure Databricks?

Ans: The control plane is responsible for managing Spark applications.

27. What is the data plane in Azure Databricks?

Ans: The data plane is responsible for storing and processing data.

28. What is the Databricks runtime used for?

Ans: The Databricks runtime is often used to execute the Databricks platform’s collection of modules.

29. What use do widgets serve in Databricks?

Ans: Widgets can help customize the panels and notebooks by adding variables.

30. What is a Databricks secret?

Ans: A secret is a key-value combination that can help keep secret content; it is composed of a unique key name contained within a secret context. Each scope is limited to 1000 secrets. It cannot exceed 128 KB in size.

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