Running Workflows

Getting Exception : ‘User: ec2-user is not allowed to impersonate ec2-user

Sparkflows impersonates the logged in user when submitting the jobs onto the Cluster.

So, the user with which Sparkflows is running has to be configured on HDFS as a proxy user.

Details for allowing the sparkflows user to impersonate other users is available at:

  • ../installation-upgrading/connecting-spark-cluster

When running the workflows on my Spark Cluster, results are not showing up in the Browser

This is probably because there is some configuration error. Sparkflows uses spark-submit to submit the jobs to the cluster. The driver of the spark job posts back results to the Fire server.

  • Check out the log for spark-submit for the workflow in /tmp/fire/workflowlogs to find the root cause. Maybe the spark job is just failing.
  • It is also useful to ensure Spark jobs can be submitted to the Cluster from the machine on which Sparkflows is running with spark-submit. Submit the SparkPi job from spark-examples.jar to test it.
    • SparkPi can be run with a command like : spark-submit --class org.apache.spark.examples.SparkPi --master yarn --deploy-mode client spark-examples.jar 10
    • spark-examples.jar is in your Apache Spark install direction on the machine.
  • If the Spark job is running successfully (according to the logs), but the results are still not showing up in the Browser, it could be because the fire spark job is unable to post results back to the Fire web server. You should see these failures in the logs.
    • Under Administration/Configuration, there is the config app.postMessageURL. It determines the Fire URL to which the results from the spark driver are posted back to the fire server. Ensure that it is set up correctly.

Getting Exception: Permission:denied : user=admin

When running on the Cluster, you are running into the exception below: Permission denied: user=admin, access=WRITE, inode="/user":hdfs:supergroup:drwxr-xr-x
  • If the above exception is coming up when running the workflow, then it means that the logged in user does not exist on HDFS.
  • In the above case, the user is logged into Fire as admin. So the jobs submitted by Fire on the cluster is as the user admin. But the user ‘admin’ does not exist on HDFS.
  • Please make sure to log into Fire as a user which exists on HDFS.

When running the example workflows on the Spark Cluster it is not able to find the input files

The example workflows read in input files.

  • They have to be on HDFS in the home directory of the logged in user.
  • The data directory which comes with Sparkflows has to be uploaded onto HDFS.
  • For example, if the logged in user is john, then the data directory would be on HDFS in the directory /user/john

Getting Exception : Server returned HTTP response code: 405 for URL: messageFromSparkJob

When submitting jobs to the cluster from Fire, you are running into the exception below:

Sending 'POST' request to URL :

Response Code : 405 Server returned HTTP response code: 405 for URL:

at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)

at sun.reflect.NativeConstructorAccessorImpl.newInstance(

at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(

at java.lang.reflect.Constructor.newInstance(



Fire submits Spark jobs to the cluster. The spark driver, posts certain results back to the Fire server to be displayed to the user.

The cause of this error is that the postback-url has not been set correctly -

There could be following issues with the URL:

The machine name/IP is wrong. It has to be the machine on which Fire is running.

The port number is wrong. Fire server is running on another port on the machine.

Getting Exception : java.lang.ClassNotFoundException: fire.execute.WorkflowExecuteFromFile

When running the jobs on the cluster, you are running into the exception below.

  • The reason for it is that the app.sparkSubmitJar is not set up correctly. Fire comes with a jar file which gets submitted to the cluster with spark-submit. app.sparkSubmitJar has to correctly point to this jar file.
  • You can go under Administration/Configuration to set it up correctly.


Warning: Local jar /home/ec2-user/fire-2.1.0/fire-lib/fire-spark_1_6-core-2.1.0-jar-with-dependencies.jar does not exist, skipping.
java.lang.ClassNotFoundException: fire.execute.WorkflowExecuteFromFile at at
java.lang.ClassLoader.loadClass( at java.lang.ClassLoader.loadClass( at
java.lang.Class.forName0(Native Method) at java.lang.Class.forName( at
org.apache.spark.util.Utils$.classForName(Utils.scala:177) at
org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:688) at
org.apache.spark.deploy.SparkSubmit$$anon$ at
org.apache.spark.deploy.SparkSubmit$$anon$ at Method) at at at
org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:161) at
org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:206) at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:121) at

Getting Exception on HDInsight : No FileSystem for scheme: wasbs

When running the jobs on the cluster, you are running into the exception below.

  • The reason for it is that it is not understanding the scheme wasb. In order to fix it, run ./ start instead of ./ start.
  • This enables getting the distribution libraries into the executable.


Error : No FileSystem for scheme: wasbs at
org.apache.hadoop.fs.FileSystem.getFileSystemClass( at
org.apache.hadoop.fs.FileSystem.createFileSystem( at
org.apache.hadoop.fs.FileSystem.access$200( at