Apache Spark Streaming
Apache Spark Streaming is a scalable, high-throughput, fault-tolerant streaming processing framework built on top of Apache Spark. It enables real-time processing of live data streams using micro-batch processing, where data is divided into small batches and processed using Spark's core engine. It supports data ingestion from various sources like Kafka, Flume, and HDFS, and can output to databases, dashboards, or file systems.
Developers should learn Apache Spark Streaming for building real-time analytics applications, such as fraud detection, IoT sensor monitoring, or social media sentiment analysis, where low-latency processing of continuous data streams is required. It is particularly valuable in big data environments due to its integration with the broader Spark ecosystem, allowing seamless combination of batch and streaming workloads and leveraging Spark's in-memory computing for performance.