Wait! Exclusive 60 day trial to the world's largest digital library.
The SlideShare family just got bigger. You now have unlimited* access to books, audiobooks, magazines, and more from Scribd.Cancel anytime.
Apache Spark and its ecosystem provide many instrumentation points, metrics, and monitoring tools that you can use to improve the performance of your jobs and understand how your Spark workloads are utilizing the available system resources. Spark 3.0 comes with several important additions and improvements to the monitoring system. This talk will cover the new features, review some readily available solutions to use them, and will provide examples and feedback from production usage at the CERN Spark service. Topics covered will include Spark executor metrics for fine-grained memory monitoring and extensions to the Spark monitoring system using Spark 3.0 Plugins. Plugins allow us to deploy custom metrics extending the Spark monitoring system to measure, among other things, I/O metrics for cloud file systems like S3, OS metrics, and custom metrics provided by external libraries.