Real-Time Mode Technical Deep Dive: How We Built Sub-300 Millisecond Streaming Into Apache Spark™
Description
Real-time mode is a new low-latency execution mode for Apache Spark™ Structured Streaming. It can consistently provide p99 latencies less than 300 milliseconds for a broad set of stateless and stateful streaming queries. Our talk focuses on the technical aspects of making this possible in Spark. We’ll dive into the core architecture that enables these dramatic latency improvements, including a concurrent stage scheduler and a non-blocking shuffle. We’ll explore how we maintained Spark’s fault-tolerance guarantees, and we’ll also share specific optimizations we made to our streaming SQL operators. These architectural improvements have already enabled Databricks customers to build workloads with latencies up to 10x lower than before. Early adopters in our Private Preview have successfully implemented real-time enrichment pipelines and feature engineering for machine learning — use cases that were previously impossible at these latencies. Talk By: Jerry Peng, Staff Software Engineer, Databricks ; Siying Dong, Senior Staff Software Engineer, Databricks Here’s more to explore: Production ready data pipelines for analytics and AI: https://www.databricks.com/solutions/data-engineer…
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