How to fix "Connection refused error" when running a cluster mode spark job - apache-spark

Question

I am running terasort benchmark with spark on the uni cluster which uses SLURM job management system. It works fine when I use --master local[8], however when I set the master as my current node I get connection refused error.
I run this command to launch the app on local without problem:
> spark-submit \
--class com.github.ehiggs.spark.terasort.TeraGen \
--master local[8] \
target/spark-terasort-1.1-SNAPSHOT-jar-with-dependencies.jar 1g \
data/terasort_in
When I use cluster mode I get the following error:
> spark-submit \
--class com.github.ehiggs.spark.terasort.TeraGen \
--master spark://iris-055:7077 \ #name of the cluster-node in use
--deploy-mode cluster \
--executor-memory 20G \
--total-executor-cores 24 \
target/spark-terasort-1.1-SNAPSHOT-jar-with-dependencies.jar 5g \
data/terasort_in
Output:
WARN NativeCodeLoader:62 - Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Exception in thread "main" org.apache.spark.SparkException: Exception thrown in awaitResult:
at
org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:226)
at
.
.
./*many lines of timeout logs etc.*/
.
.
.
Caused by: java.net.ConnectException: Connection refused
... 11 more
I expect the command to run smooth and terminate, but I cannot get over this connection error.

Answer 1

The problem could be not defining --conf variables. This could work out:
spark-submit \
--class com.github.ehiggs.spark.terasort.TeraGen \
--master spark://iris-055:7077 \
--conf spark.driver.memory=4g \
--conf spark.executor.memory=20g \
--executor-memory 20g \
--total-executor-cores 24 \
target/spark-terasort-1.1-SNAPSHOT-jar-with-dependencies.jar 5g \
data/terasort_in