Spark on Yarn: Max number of executor failures reached - scala

Question

When I am running spark job on cluster mode I am facing following issue:
6/05/25 12:42:55 INFO Client: Application report for application_1464166348026_0025 (state: RUNNING)
16/05/25 12:42:56 INFO Client: Application report for application_1464166348026_0025 (state: FINISHED)
16/05/25 12:42:56 INFO Client:
client token: N/A
diagnostics: N/A
ApplicationMaster host: 10.255.8.181
ApplicationMaster RPC port: 0
queue: root.pimuser
start time: 1464172925289
final status: FAILED
tracking URL: http://test-hadoop-001.localdomain:8088/proxy/application_1464166348026_0025/history/application_1464166348026_0025/2
user: pimuser
Exception in thread "main" org.apache.spark.SparkException: Application application_1464166348026_0025 finished with failed status
at org.apache.spark.deploy.yarn.Client.run(Client.scala:927)
at org.apache.spark.deploy.yarn.Client$.main(Client.scala:973)
at org.apache.spark.deploy.yarn.Client.main(Client.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:672)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:180)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:205)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:120)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
16/05/25 12:42:56 INFO ShutdownHookManager: Shutdown hook called
Following Command I am using to run the job.
spark-submit --driver-java-options -XX:MaxPermSize=2048m --driver-memory 4g --deploy-mode cluster --master yarn --files cluster.xls --class com.app.test.Matching target/test-0.0.1-SNAPSHOT-jar-with-dependencies.jar
Even I tried --master yarn-cluster also but I got same error.
I am using cloudera 5.5 ,Hadoop 2.6.0-cdh5.5.1 and Spark 1.5 versions.