Processing Streaming Data Using Apache Spark Structured Streaming

by Janani Ravi

Structured streaming is the scalable and fault-tolerant stream processing engine in Apache Spark 2 which can be used to process high-velocity streams.

What you'll learn

Stream processing applications work with continuously updated data and react to changes in real-time. In this course, Processing Streaming Data Using Apache Spark Structured Streaming, you'll focus on integrating your streaming application with the Apache Kafka reliable messaging service to work with real-world data such as Twitter streams.

First, you’ll explore Spark’s architecture to support distributed processing at scale. Next, you will install and work with the Apache Kafka reliable messaging service.

Finally, you'll perform a number of transformation operations on Twitter streams, including windowing and join operations.

When you're finished with this course you will have the skills and knowledge to work with high volume and velocity data using Spark and integrate with Apache Kafka to process streaming data.

Table of contents

Course Overview
2mins

About the author

Janani has a Masters degree from Stanford and worked for 7+ years at Google. She was one of the original engineers on Google Docs and holds 4 patents for its real-time collaborative editing framework. After spending years working in tech in the Bay Area, New York, and Singapore at companies such as Microsoft, Google, and Flipkart, Janani finally decided to combine her love for technology with her passion for teaching. She is now the co-founder of Loonycorn, a content studio focused on providin... more

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