![]() ![]() Note that this support is currently experimental and behavioral changes around configurations, container images and entrypoints should be expected. Spark on Kubernetes: A new kubernetes scheduler backend that supports native submission of spark jobs to a cluster managed by kubernetes.We have curated a list of high level changes here, grouped by major modules. You can consult JIRA for the detailed changes. To download Apache Spark 2.3.0, visit the downloads page. In addition, this release continues to focus on usability, stability, and polish while resolving around 1400 tickets. Other major updates include the new DataSource and Structured Streaming v2 APIs, and a number of PySpark performance enhancements. This release adds support for Continuous Processing in Structured Streaming along with a brand new Kubernetes Scheduler backend. Apache Spark 2.3.0 is the fourth release in the 2.x line.
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