Overview

Master Real-Time Data Processing with PySpark Structured Streaming - Even If You're Starting from Scratch Modern data platforms demand real-time insights, scalable pipelines, and fault-tolerant streaming architectures. PySpark Structured Streaming has become one of the most in-demand skills for data engineers working with Apache Spark and Kafka. This practical, hands-on guide takes you step-by-step from streaming fundamentals to production-ready pipeline design. Inside this book, you will learn how to: Build end-to-end real-time pipelines using PySpark Integrate Apache Kafka with Structured Streaming Master window functions, watermarking, and late data handling Implement stateful processing and stream-stream joins Optimize performance for large-scale workloads Monitor and troubleshoot production streaming jobs Deploy streaming pipelines on Databricks Crack PySpark Structured Streaming interview questions Unlike many theoretical books, this guide focuses on real production scenarios, hands-on labs, and interview-focused explanations that data engineers actually need on the job. Whether you are: An aspiring data engineer A Spark developer moving into streaming A professional preparing for data engineering interviews Or someone building real-time analytics systems This book will give you the practical knowledge and confidence to work with PySpark Structured Streaming in real-world environments. Start building production-ready streaming pipelines today.

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