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https://issues.apache.org/jira/browse/SPARK-34349?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Hyukjin Kwon resolved SPARK-34349.
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Resolution: Cannot Reproduce
> No python3 in docker images
> ----------------------------
>
> Key: SPARK-34349
> URL: https://issues.apache.org/jira/browse/SPARK-34349
> Project: Spark
> Issue Type: Bug
> Components: Kubernetes
> Affects Versions: 3.0.1
> Reporter: Tim Hughes
> Priority: Critical
>
> The spark-py container image doesn't receive the instruction to use python3
> and defaults to python 2.7
>
> The worker container was build using the following commands
> {code:java}
> mkdir ./tmp
> wget -qO-
> https://www.mirrorservice.org/sites/ftp.apache.org/spark/spark-3.0.1/spark-3.0.1-bin-hadoop3.2.tgz
> | tar -C ./tmp/ -xzf -
> cd ../spark-3.0.1-bin-hadoop3.2/
> ./bin/docker-image-tool.sh -r docker.io/timhughes -t
> spark-3.0.1-bin-hadoop3.2 -p
> kubernetes/dockerfiles/spark/bindings/python/Dockerfile build
> docker push docker.io/timhughes/spark-py:spark-3.0.1-bin-hadoop3.2{code}
>
> This is the code I am using to initialize the workers
>
> {code:java}
> import os
> from pyspark import SparkContext, SparkConf
> from pyspark.sql import SparkSession# Create Spark config for our Kubernetes
> based cluster manager
> sparkConf = SparkConf()
> sparkConf.setMaster("k8s://https://kubernetes.default.svc.cluster.local:443";)
> sparkConf.setAppName("spark")
> sparkConf.set("spark.kubernetes.container.image",
> "docker.io/timhughes/spark-py:spark-3.0.1-bin-hadoop3.2")
> sparkConf.set("spark.kubernetes.namespace", "spark")
> sparkConf.set("spark.executor.instances", "2")
> sparkConf.set("spark.executor.cores", "1")
> sparkConf.set("spark.driver.memory", "1024m")
> sparkConf.set("spark.executor.memory", "1024m")
> sparkConf.set("spark.kubernetes.pyspark.pythonVersion", "3")
> sparkConf.set("spark.kubernetes.authenticate.driver.serviceAccountName",
> "spark")
> sparkConf.set("spark.kubernetes.authenticate.serviceAccountName", "spark")
> sparkConf.set("spark.driver.port", "29413")
> sparkConf.set("spark.driver.host",
> "my-notebook-deployment.spark.svc.cluster.local")
> # Initialize our Spark cluster, this will actually
> # generate the worker nodes.
> spark = SparkSession.builder.config(conf=sparkConf).getOrCreate()
> sc = spark.sparkContext
> {code}
>
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