Applications of SQL on Databricks


Use Spark SQL on Databricks to work with data in a variety of ways.


In the course Introduction to SQL on Databricks, we introduced Spark and Spark SQL as a solution for using common SQL syntax when working with structured or semi-structured data. In this course, you will use Spark SQL on Databricks to practice common design patterns for efficiently creating new tables, explore built-in functions that can help you explore, manipulate, and aggregate nested data.

Learning objectives

  • Use optional arguments in CREATE TABLE to define data format and location in a Databricks database.

  • Store a selection of data, temporarily in a spark session or permanently for use over multiple sessions.

  • Use window functions for aggregation.

  • Access and manipulate data in nested data structures.


  • Basic familiarity with SQL

  • Experience working with SQL in a Databricks notebook

Learning path

  • This course is part of the SQL Analyst learning path.

Proof of completion

  • Upon 80% completion of this course, you will receive a proof of completion.