Getting Started with Apache™ Spark SQL — 1 user / 1 year

Getting Started with Apache™ Spark SQL — 1 user / 1 year

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This hands-on self-paced training course targets Analysts and Data Scientists getting started using Databricks to analyze big data with Apache Spark™ SQL. The course ends with a capstone project demonstrating Exploratory Data Analysis with Spark SQL on Databricks.

What's New

Version 1.3.5: Bug fixes to the Optional/01-WhySpark module.


3-6 hours, 75% hands-on

Format: Self-paced

The course is a series of six self-paced lessons plus a final capstone project performing Exploratory Data Analysis using Spark SQL on Databricks. Each lesson includes hands-on exercises.


Supported platforms include Azure Databricks, Databricks Community Edition, and non-Azure Databricks.

  • If you're planning to use the course on Azure Databricks, select the "Azure Databricks" Platform option.
  • If you're planning to use the course on Databricks Community Edition or on a non-Azure version of Databricks, select the "Other Databricks" Platform option.

Learning Objectives

During this course learners

  • Use the interactive Databricks notebook environment.
  • Examine external data sets.
  • Query existing data sets using Spark SQL.
  • Visualize query results and data using the built-in Databricks visualization features.
  • Perform exploratory data analysis using Spark SQL.


  • Getting Started and Accessing the Course
  • Querying Files with SQL
  • Aggregations, JOINs and Nested Queries
  • Uploading and Accessing Data
  • Querying JSON & Hierarchical Data with SQL
  • Querying Data Lakes with SQL
  • Capstone Project: Exploratory Data Analysis

Target Audience

  • Primary Audience: Data Analysts
  • Secondary Audiences: Data Scientists and Engineers


  • Knowledge of SQL — required.

Lab Requirements

License Limitations

This self-paced training course may be used by 1 user for 12 months from the date of purchase.  It may not be transferred or shared with any other user.


The use of the self-paced training course is subject to the Terms of Service and the Databricks Privacy Policy.