This session explains how we've made our Apache Spark™ versionless for end users by introducing a stable client API, environment versioning and automatic remediation. These capabilities have enabled auto-upgrade of hundreds of millions of workloads with minimal disruption for Serverless Notebooks and Jobs. We'll also introduce a new approach to dependency management using environments. Admins will learn how to speed up package installation with Default Base Environments, and users will see how to manage custom environments for their own workloads.

Every day thousands of customers choose to run business-critical Spark workloads on the Databricks Lakehouse Platform, a platform built by the creators of Apache Spark™. These customers take advantage of platform capabilities such as fully managed compute resources, dynamic autoscaling, an integrated workflow orchestration tool and of Photon, the extremely fast vectorized execution engine. All of these make the Databricks Lakehouse Platform the best place to run Spark workloads providing operational benefits as well as tremendous price/performance value.

This session which includes live demos will cover these and other platform capabilities that can help you build your next optimized Spark application.

Talk by: Justin Breese

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