Real-Time Data Streaming with Apache Kafka and Spark

While batch processing manages 80% of data workloads, the remaining 20%—including IoT telemetry, fraud detection, and real-time dashboards—necessitates streaming. The standard stack for scaling these operations is Apache Kafka combined with Spark Structured Streaming. This guide details the construction of a production real-time data pipeline, tracing the flow from Kafka ingestion through stream processing to a Delta Lake sink, providing practical code for every architectural component to ensure efficient event-driven data handling.