Structured Streaming in Apache Spark

Processing real-time data is essential for making timely decisions in today's fast-paced world. Learn how to build and optimize real-time data processing pipelines using Apache Spark and integrate with tools like Kafka for robust, scalable solutions.

What you'll learn

Handling real-time data is a critical challenge for businesses aiming to make fast, data-driven decisions in domains like finance, e-commerce, and IoT.

In this course, Structured Streaming in Apache Spark, you’ll gain the ability to design, implement, and optimize real-time data pipelines using Apache Spark.

First, you’ll explore the fundamentals of stream processing, including reading and transforming streaming data from sources like sockets and files.

Next, you’ll discover how to leverage triggers, output modes, and checkpointing to ensure reliable and efficient stream processing workflows.

Finally, you’ll learn how to integrate Apache Spark with Apache Kafka to consume, transform, and aggregate real-time streaming data.

When you’re finished with this course, you’ll have the skills and knowledge of Apache Spark streaming needed to process and analyze real-time data for scalable, industry-ready applications.