Getting Started with Apache Spark Structured Streaming Real-Time Mode

Historically, Spark Structured Streaming relied on a "micro-batch" model. Real-Time Mode (RTM) introduces a significant architectural evolution by shifting to a continuous processing paradigm to support operational workloads that require sub-second latency.

Watch this video to learn how RTM differentiates between analytical and operational workloads, targeting mission-critical applications like fraud detection and real-time personalization with end-to-end P99 latencies as low as 5 to 10 milliseconds. You will explore the three main architectural changes powering this shift: continuous execution, simultaneous scheduling, and streaming shuffle.

Finally, see how easy it is to implement. Built directly into existing Structured Streaming APIs, developers can switch to ultra-low-latency streaming with a simple, single-line code change to the trigger.