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From Erik Erlandson <eerla...@redhat.com>
Subject Apache Spark on Kubernetes: New Release for Spark 2.2
Date Mon, 14 Aug 2017 23:31:35 GMT
The Apache Spark on Kubernetes Community Development Project is pleased to
announce the latest release of Apache Spark with native Scheduler Backend
for Kubernetes!  Features provided in this release include:


   -

   Cluster-mode submission of Spark jobs to a Kubernetes cluster
   -

   Support for Scala, Java and PySpark
   -

   Static and Dynamic Allocation for Executors
   -

   Automatic staging of local resources onto Driver and Executor pods
   -

   Configurable security and credential management
   -

   HDFS, running on the Kubernetes cluster or externally
   -

   Launch jobs using kubectl proxy
   -

   Built against Apache Spark 2.1 and 2.2
   -

   Support for Kubernetes 1.5 - 1.7
   -

   Pre-built docker images


Apache Spark on Kubernetes is currently being developed as an independent
community project, with several actively contributing companies in
collaboration. The project resides at the apache-spark-on-k8s GitHub
organization, and tracks upstream Apache Spark releases:

https://github.com/apache-spark-on-k8s/spark

If you have any questions or issues, we are happy to help! Please feel free
to reach out to the Spark on Kubernetes community on these channels:

   -

   Slack: https://kubernetes.slack.com #sig-big-data
   -

   User Documentation: https://apache-spark-on-k8s.github.io/userdocs/
   -

   GitHub issues: https://github.com/apache-spark-on-k8s/spark/issues
   -

   SIG: https://github.com/kubernetes/community/tree/master/sig-big-data

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