Apache Spark Streaming Real-Time Mode - Latency Demo

Databricks · Intermediate ·🔄 Data Engineering ·2mo ago

Key Takeaways

Demonstrates Apache Spark Streaming Real-Time Mode for low-latency data processing with significant latency gains

Original Description

In this technical walkthrough, Frank demonstrates the significant latency gains achieved by switching from traditional Micro-Batch Mode (MBM) to Real-Time Mode (RTM) in Spark Structured Streaming. Frank uses a demo created by Neil Patel. The demo begins by deploying a Declarative Automation Bundle (DAB) in the workspace to configure the necessary environment, including volumes and automated jobs. Frank first establishes a baseline using MBM, where the data shows a P95 latency of over 1,000ms. By simply updating the trigger configuration to Real-Time Mode, the processing latency drops dramatically, bringing the P95 latency down to just 50ms. The video concludes with a deep dive into the underlying code. This comparison serves as a guide for data engineers seeking ultra-low, sub-second latency in their Databricks streaming pipelines.
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