Apache Spark 3 for Data Engineering and Analytics with Python - Creating our First 2 Databricks Notebooks

This video tutorial guides users through creating and managing notebooks in Databricks. It covers navigating the workspace, creating new notebooks, and setting up a Spark session. The tutorial also explains how to import necessary libraries and manage storage options for collaborative work. By the end, users will be able to create and manage notebooks, import libraries, and set up a Spark session for data processing.

What is the first step to create a new notebook from the homepage in Databricks?

• Click on the Workspace menu

• Select the Databricks logo

• Select the home button

• Navigate to the user dropdown list

Where can you find your notebooks listed in the Workspace?

• In the user dropdown list

• Under the common tasks

• On the left hand side

• On the right hand side

What is one of the options available for managing your workspace?

• Share your workspace

• Clone your workspace

• Delete your workspace

• Lock your workspace

What is the default language set for the new SQL notebook?

• Scala

• R

• SQL

• Python

Why are shared folders important in Databricks?

• For storing personal files

• For creating backups

• For collaborative work

• For exporting data

Which library is imported to create a Spark session?

• pyspark.sql

• numpy

• matplotlib

• pandas

What key combination is used to run code in Databricks?

• Shift + Enter

• Cmd + Enter

• Alt + Enter

• Ctrl + Enter