hi, all
  I notice that jenkins may also throw this error when running 
tests(https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/18688/consoleFull).


This is because in Utils.executeAndGetOutput our progress exitCode is not 0, 
may be we should logWarning here rather than throw a exception?

Utils.executeAndGetOutput {
    val exitCode = process.waitFor()
    stdoutThread.join()   // Wait for it to finish reading output
    if (exitCode != 0) {
      throw new SparkException("Process " + command + " exited with code " + 
exitCode)
    }
}

any idea?


On 2014/8/15 11:01, scwf wrote:
env: ubuntu 14.04 + spark master buranch

mvn -Pyarn -Phive -Phadoop-2.4 -Dhadoop.version=2.4.0 -DskipTests clean package

mvn -Pyarn -Phadoop-2.4 -Phive test

test error:

DriverSuite:
Spark assembly has been built with Hive, including Datanucleus jars on classpath
- driver should exit after finishing *** FAILED ***
   SparkException was thrown during property evaluation. (DriverSuite.scala:40)
     Message: Process List(./bin/spark-class, 
org.apache.spark.DriverWithoutCleanup, local) exited with code 1
     Occurred at table row 0 (zero based, not counting headings), which had 
values (
       master = local
     )

SparkSubmitSuite:
Spark assembly has been built with Hive, including Datanucleus jars on classpath
- launch simple application with spark-submit *** FAILED ***
   org.apache.spark.SparkException: Process List(./bin/spark-submit, --class, 
org.apache.spark.deploy.SimpleApplicationTest, --name, testApp, --master, 
local, file:/tmp/1408015655220-0/testJar-1408015655220.jar) exited with code 1

   at org.apache.spark.util.Utils$.executeAndGetOutput(Utils.scala:810)
   at 
org.apache.spark.deploy.SparkSubmitSuite.runSparkSubmit(SparkSubmitSuite.scala:311)
   at 
org.apache.spark.deploy.SparkSubmitSuite$$anonfun$14.apply$mcV$sp(SparkSubmitSuite.scala:291)
   at 
org.apache.spark.deploy.SparkSubmitSuite$$anonfun$14.apply(SparkSubmitSuite.scala:284)
   at 
org.apache.spark.deploy.SparkSubmitSuite$$anonfun$14.apply(SparkSubmitSuite.scala:284)
   at org.scalatest.Transformer$$anonfun$apply$1.apply(Transformer.scala:22)
   at org.scalatest.Transformer$$anonfun$apply$1.apply(Transformer.scala:22)
   at org.scalatest.OutcomeOf$class.outcomeOf(OutcomeOf.scala:85)
   at org.scalatest.OutcomeOf$.outcomeOf(OutcomeOf.scala:104)
   at org.scalatest.Transformer.apply(Transformer.scala:22)
   ...
Spark assembly has been built with Hive, including Datanucleus jars on classpath
- spark submit includes jars passed in through --jar *** FAILED ***
   org.apache.spark.SparkException: Process List(./bin/spark-submit, --class, 
org.apache.spark.deploy.JarCreationTest, --name, testApp, --master, 
local-cluster[2,1,512], --jars, 
file:/tmp/1408015659416-0/testJar-1408015659471.jar,fi
le:/tmp/1408015659472-0/testJar-1408015659513.jar, 
file:/tmp/1408015659415-0/testJar-1408015659416.jar) exited with code 1
   at org.apache.spark.util.Utils$.executeAndGetOutput(Utils.scala:810)
   at 
org.apache.spark.deploy.SparkSubmitSuite.runSparkSubmit(SparkSubmitSuite.scala:311)
   at 
org.apache.spark.deploy.SparkSubmitSuite$$anonfun$15.apply$mcV$sp(SparkSubmitSuite.scala:305)
   at 
org.apache.spark.deploy.SparkSubmitSuite$$anonfun$15.apply(SparkSubmitSuite.scala:294)
   at 
org.apache.spark.deploy.SparkSubmitSuite$$anonfun$15.apply(SparkSubmitSuite.scala:294)
   at org.scalatest.Transformer$$anonfun$apply$1.apply(Transformer.scala:22)
   at org.scalatest.Transformer$$anonfun$apply$1.apply(Transformer.scala:22)
   at org.scalatest.OutcomeOf$class.outcomeOf(OutcomeOf.scala:85)
   at org.scalatest.OutcomeOf$.outcomeOf(OutcomeOf.scala:104)
   at org.scalatest.Transformer.apply(Transformer.scala:22)
   ...


but only test the specific suite as follows will be ok:
mvn -Pyarn -Phadoop-2.4 -Phive -DwildcardSuites=org.apache.spark.DriverSuite 
test

it seems when run with "mvn -Pyarn -Phadoop-2.4 -Phive test",the process with 
Utils.executeAndGetOutput started can not exited successfully (exitcode is not zero)

anyone has idea for this?






--

Best Regards
Fei Wang

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