Real-Time Stream Processing Using Apache Spark 3 for Scala Developers
Learn to create real-time stream processing applications using Apache Spark
Created by ScholarNest
Explore how to design and build real-time stream processing applications using Apache Spark. Through practical examples and hands-on coding, you'll gain the skills needed to handle big data streams efficiently. By the end, you'll be ready to tackle real-world streaming challenges with confidence.
Packt | Feb 2022 | 203 min
What You Will Learn
You will learn by working through real-world coding demonstrations and practical exercises. Each concept is explained clearly, then put into practice with hands-on examples. Along the way, you'll set up Spark and Kafka, explore streaming APIs, and tackle common challenges faced in stream processing.
Key Features
- Integrate Apache Spark with Kafka for seamless real-time data streaming
- Implement streaming joins, aggregations, and windowing for complex analytics
- Troubleshoot and optimize memory usage in streaming applications
Target Audience
Ideal for software engineers, architects, and developers with some experience in Scala who want to deepen their understanding of real-time data processing. If you aim to build or manage big data engineering projects using Apache Spark, this learning path will help you achieve your goals.
