Structured Streaming
Structured Streaming is a scalable and fault-tolerant stream processing engine built on the Spark SQL engine in Apache Spark. It provides a high-level API for continuous data processing, allowing developers to write streaming computations using the same DataFrame/Dataset APIs as batch processing. It handles event-time processing, windowing, and exactly-once semantics out-of-the-box.
Developers should learn Structured Streaming when building real-time data pipelines, such as IoT data ingestion, fraud detection, or live analytics dashboards, as it simplifies stream processing with familiar SQL-like syntax. It's particularly useful in scenarios requiring low-latency processing with strong consistency guarantees, as it integrates seamlessly with existing Spark batch jobs and supports various data sources like Kafka, HDFS, and cloud storage.