Working with Structured Streaming Data using Autoloader

Learning Objectives

Learn about Autoloader and how it handles schema changes automatically in streaming pipelines.

Understand how Autoloader detects new files using directory listing and file notifications.

Overview

In this scenario, John, a junior data engineer at GlobalMart, is facing issues with handling schema changes dynamically in his real-time data processing pipeline. Sharon, a senior data engineer, introduces him to Autoloader—a powerful feature exclusive to Databricks in premium workspaces. Autoloader simplifies the process by automatically handling schema evolution and detecting new files in cloud storage, enabling efficient real-time processing without manual intervention.

Prerequisites

Basic understanding of streaming data processing and pipelines
Familiarity with Databricks and cloud data lakes