JAR Tasks on Serverless Compute Now Generally Available in Databricks Lakeflow
Databricks has announced the general availability of JAR tasks on serverless compute within Lakeflow Jobs. This allows users to package Scala or Java code and run it directly as a job task, enhancing flexibility for custom code execution. Developers can now leverage serverless compute for their compiled Scala and Java applications. A key prerequisite is ensuring the JAR's Scala, JDK, and Databricks Connect versions match the serverless environment.
Features (1) ›
- JAR tasks on serverless compute now generally available
Users can now package Scala or Java code into a JAR and run it as a task in a Lakeflow Job on serverless compute. This capability is generally available, providing a production-ready option for executing custom code. Ensure your JAR's Scala, Java Development Kit (JDK), and Databricks Connect versions align with your serverless environment.
https://docs.databricks.com/aws/en/release-notes/serverless#jar-tasks-on-serverless-compute-are-now-generally-available
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