Please follow below steps for running SparkR script via Oozie
.
1. Install R packages on all the node managers
yum -y install R R-devel libcurl-devel openssl-devel
.
2. Keep your R script ready
Here is the sample script
library(SparkR)
sc <- sparkR.init(appName="SparkR-sample")
sqlContext <- sparkRSQL.init(sc)
localDF <- data.frame(name=c("ABC", "blah", "blah"), age=c(39, 32, 81))
df <- createDataFrame(sqlContext, localDF)
printSchema(df)
sparkR.stop() .
3. Create workflow.xml
Here is the working example:
<workflow-app xmlns='uri:oozie:workflow:0.5' name='SparkFileCopy'>
<global>
<configuration>
<property>
<name>oozie.launcher.yarn.app.mapreduce.am.env</name>
<value>SPARK_HOME=/usr/hdp/2.5.3.0-37/spark</value>
</property>
<property>
<name>oozie.launcher.mapred.child.env</name>
<value>SPARK_HOME=/usr/hdp/2.5.3.0-37/spark</value>
</property>
</configuration>
</global>
<start to='spark-node' />
<action name='spark-node'>
<spark xmlns="uri:oozie:spark-action:0.1">
<job-tracker>${jobTracker}</job-tracker>
<name-node>${nameNode}</name-node>
<prepare>
<delete path="${nameNode}/user/${wf:user()}/${examplesRoot}/output-data/spark"/>
</prepare>
<master>${master}</master>
<name>SparkR</name>
<jar>${nameNode}/user/${wf:user()}/spark.R</jar>
<spark-opts>--driver-memory 512m --conf spark.driver.extraJavaOptions=-Dhdp.version=2.5.3.0</spark-opts>
</spark>
<ok to="end" />
<error to="fail" />
</action>
<kill name="fail">
<message>Workflow failed, error
message[${wf:errorMessage(wf:lastErrorNode())}]
</message>
</kill>
<end name='end' />
</workflow-app> .
4. Make sure that you don't have sparkr.zip in workflow/lib directory or Oozie sharelib or in <file> tag in the workflow, or else it will cause conflicts.
.
Upload workflow to hdfs and run it. It should work. This has been successfully tested on HDP-2.5.X & HDP-2.6.X
.
Please comment if you have any feedback/questions/suggestions.
Happy Hadooping!! 
Reference - https://developer.ibm.com/hadoop/2017/06/30/scheduling-spark-job-written-pyspark-sparkr-yarn-oozie
