SELF-PACED

Getting Started with Apache Spark SQL

Overview

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.

Length

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 Databricks Community Edition, Azure Databricks and Amazon.

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.

Lessons

  • 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

Prerequisites

  • Knowledge of SQL — required.

Lab Requirements

  • Chrome or Firefox browser. Internet Explorer, Edge, and Safari are not supported.