Kalle Jepsen created SPARK-28484:
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Summary: spark-submit uses wrong SPARK_HOME with deploy-mode
"cluster"
Key: SPARK-28484
URL: https://issues.apache.org/jira/browse/SPARK-28484
Project: Spark
Issue Type: Bug
Components: Deploy
Affects Versions: 2.4.3
Reporter: Kalle Jepsen
When submitting an application jar to a remote Spark cluster with spark-submit
and deploy-mode = "cluster", the driver command that is issued on one of the
workers seems to be configured with the SPARK_HOME of the local machine, from
which spark-submit was called, not the one where the driver is actually running.
I.e. if I have spark installed locally under e.g. /opt/apache-spark and hadoop
under /usr/lib/hadoop-3.2.0, but the cluster administrator installs spark under
/usr/local/spark on the workers, the command that is issued on the worker still
looks sth like this:
{{"/usr/lib/jvm/java/bin/java" "-cp"
"/opt/apache-spark/conf:/etc/hadoop:/usr/lib/hadoop-3.2.0/share/hadoop/common/lib/*:/usr/lib/hadoop-3.2.0/share/hadoop/common/*:/usr/lib/hadoop-3.2.0/share/hadoop/hdfs:/usr/lib/hadoop-3.2.0/share/hadoop/hdfs/lib/*:/usr/lib/hadoop-3.2.0/share/hadoop/hdfs/*:/usr/lib/hadoop-3.2.0/share/hadoop/mapreduce/lib/*:/usr/lib/hadoop-3.2.0/share/hadoop/mapreduce/*:/usr/lib/hadoop-3.2.0/share/hadoop/yarn:/usr/lib/hadoop-3.2.0/share/hadoop/yarn/lib/*:/usr/lib/hadoop-3.2.0/share/hadoop/yarn/*"
"-Xmx1024M" "-Dspark.jars=file:///some/application.jar"
"-Dspark.driver.supervise=false" "-Dspark.submit.deployMode=cluster"
"-Dspark.master=spark://<SPARK_MASTER>:7077" "-Dspark.app.name=<APPNAME>"
"-Dspark.rpc.askTimeout=10s" "org.apache.spark.deploy.worker.DriverWrapper"
"spark://Worker@<WORKER_HOST>:65000" "/some/application.jar" "some.class.Name"}}
Is this expected behavior and/or can I somehow control that?
Steps to reproduce:
1. Install Spark locally (with a SPARK_HOME that's different on the cluster)
{{2. Run: spark-submit --deploy-mode "cluster" --master
"spark://spark.example.com:7077" --class "com.example.SparkApp"
"hdfs:/some/application.jar"}}
3. Observe that the application fails because some spark and/or hadoop classes
cannot be found
This applies to Spark Standalone, I haven't tried with YARN
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