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1. #Kubernetes install apache spark on kubernetes driver
2. #Kubernetes install apache spark on kubernetes code

#Kubernetes install apache spark on kubernetes driver

When I deploy this to the cluster the driver will start, but when it attempts to find executors things will fail with a socket exception, presumably because the workers can't connect back to the driver, or vice-versa? Using Spark's default log4j profile: org/apache/spark/log4j-defaults.propertiesĢ0/04/26 20:24:39 INFO SparkContext: Running Spark version 2.4.2Ģ0/04/26 20:24:40 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform. # Client service for connecting to any spark instance. Here is the kubernetes yaml used to deploy the driver program, which sits inside a StatefulSet: apiVersion: apps/v1Īnd here is the kubernetes yaml to deploy the services which sit on top of the driver program: # Headless service for stable DNS entries of StatefulSet members. The container image (spark-alluxio) was built by adding the alluxio client library to a binary spark distribution (2.4.2).

#Kubernetes install apache spark on kubernetes code

Here is the code used by the driver to bootstrap the cluster: val sparkSession = SparkSession.builder I'm trying to get a spark kubernetes install working where the spark driver node resides in its own separate pod (client mode), and uses the SparkSession.builder mechanism to bootstrap the cluster (not using spark-submit).