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From "Hadoop QA (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (AMBARI-17639) Spark Interpreter fails with "HiveException: org.apache.thrift.transport.TTransportException"
Date Sun, 10 Jul 2016 02:18:10 GMT

    [ https://issues.apache.org/jira/browse/AMBARI-17639?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15369390#comment-15369390
] 

Hadoop QA commented on AMBARI-17639:
------------------------------------

{color:red}-1 overall{color}.  Here are the results of testing the latest attachment 
  http://issues.apache.org/jira/secure/attachment/12816998/AMBARI-17639_trunk%2Bbranch-2.4_v1.patch
  against trunk revision .

    {color:green}+1 @author{color}.  The patch does not contain any @author tags.

    {color:red}-1 tests included{color}.  The patch doesn't appear to include any new or modified
tests.
                        Please justify why no new tests are needed for this patch.
                        Also please list what manual steps were performed to verify this patch.

    {color:green}+1 javac{color}.  The applied patch does not increase the total number of
javac compiler warnings.

    {color:green}+1 release audit{color}.  The applied patch does not increase the total number
of release audit warnings.

    {color:red}-1 core tests{color}.  The test build failed in ambari-server 

Test results: https://builds.apache.org/job/Ambari-trunk-test-patch/7763//testReport/
Console output: https://builds.apache.org/job/Ambari-trunk-test-patch/7763//console

This message is automatically generated.

> Spark Interpreter fails with "HiveException: org.apache.thrift.transport.TTransportException"
> ---------------------------------------------------------------------------------------------
>
>                 Key: AMBARI-17639
>                 URL: https://issues.apache.org/jira/browse/AMBARI-17639
>             Project: Ambari
>          Issue Type: Bug
>    Affects Versions: 2.4.0
>            Reporter: Yesha Vora
>            Assignee: Renjith Kamath
>             Fix For: 2.4.0
>
>         Attachments: AMBARI-17639_trunk+branch-2.4_v1.patch
>
>
> Scenario:
> * Create a new notebook 
> * Run below paragraph
> {code}
> %sh
> hdfs dfs -copyFromLocal /etc/hadoop//conf/core-site.xml /tmp{code}
> {code}
> %spark 
> val file = sc.textFile("/tmp/core-site.xml")
> val counts = file.flatMap(line => line.split(" ")).map(word => (word, 1)).reduceByKey(_
+ _)
> counts.saveAsTextFile("/tmp/wordcount1"){code}
> {code:title=output from zeppelin notebook}
> org.apache.thrift.transport.TTransportException
> 	at org.apache.thrift.transport.TIOStreamTransport.read(TIOStreamTransport.java:132)
> 	at org.apache.thrift.transport.TTransport.readAll(TTransport.java:86)
> 	at org.apache.thrift.protocol.TBinaryProtocol.readAll(TBinaryProtocol.java:429)
> 	at org.apache.thrift.protocol.TBinaryProtocol.readI32(TBinaryProtocol.java:318)
> 	at org.apache.thrift.protocol.TBinaryProtocol.readMessageBegin(TBinaryProtocol.java:219)
> 	at org.apache.thrift.TServiceClient.receiveBase(TServiceClient.java:69)
> 	at org.apache.hadoop.hive.metastore.api.ThriftHiveMetastore$Client.recv_get_delegation_token(ThriftHiveMetastore.java:3715)
> 	at org.apache.hadoop.hive.metastore.api.ThriftHiveMetastore$Client.get_delegation_token(ThriftHiveMetastore.java:3701)
> 	at org.apache.hadoop.hive.metastore.HiveMetaStoreClient.getDelegationToken(HiveMetaStoreClient.java:1796)
> 	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.hadoop.hive.metastore.RetryingMetaStoreClient.invoke(RetryingMetaStoreClient.java:156)
> 	at com.sun.proxy.$Proxy29.getDelegationToken(Unknown Source)
> 	at org.apache.hadoop.hive.ql.metadata.Hive.getDelegationToken(Hive.java:3150)
> 	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.yarn.YarnSparkHadoopUtil$$anonfun$obtainTokenForHiveMetastoreInner$4.apply(YarnSparkHadoopUtil.scala:251)
> 	at org.apache.spark.deploy.yarn.YarnSparkHadoopUtil$$anonfun$obtainTokenForHiveMetastoreInner$4.apply(YarnSparkHadoopUtil.scala:249)
> 	at org.apache.spark.deploy.yarn.YarnSparkHadoopUtil$$anon$1.run(YarnSparkHadoopUtil.scala:340)
> 	at java.security.AccessController.doPrivileged(Native Method)
> 	at javax.security.auth.Subject.doAs(Subject.java:415)
> 	at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1724)
> 	at org.apache.spark.deploy.yarn.YarnSparkHadoopUtil.doAsRealUser(YarnSparkHadoopUtil.scala:339)
> 	at org.apache.spark.deploy.yarn.YarnSparkHadoopUtil.obtainTokenForHiveMetastoreInner(YarnSparkHadoopUtil.scala:249)
> 	at org.apache.spark.deploy.yarn.YarnSparkHadoopUtil.obtainTokenForHiveMetastore(YarnSparkHadoopUtil.scala:204)
> 	at org.apache.spark.deploy.yarn.YarnSparkHadoopUtil.obtainTokenForHiveMetastore(YarnSparkHadoopUtil.scala:151)
> 	at org.apache.spark.deploy.yarn.Client.prepareLocalResources(Client.scala:348)
> 	at org.apache.spark.deploy.yarn.Client.createContainerLaunchContext(Client.scala:733)
> 	at org.apache.spark.deploy.yarn.Client.submitApplication(Client.scala:143)
> 	at org.apache.spark.scheduler.cluster.YarnClientSchedulerBackend.start(YarnClientSchedulerBackend.scala:56)
> 	at org.apache.spark.scheduler.TaskSchedulerImpl.start(TaskSchedulerImpl.scala:144)
> 	at org.apache.spark.SparkContext.<init>(SparkContext.scala:530)
> 	at org.apache.zeppelin.spark.SparkInterpreter.createSparkContext(SparkInterpreter.java:338)
> 	at org.apache.zeppelin.spark.SparkInterpreter.getSparkContext(SparkInterpreter.java:122)
> 	at org.apache.zeppelin.spark.SparkInterpreter.open(SparkInterpreter.java:513)
> 	at org.apache.zeppelin.interpreter.LazyOpenInterpreter.open(LazyOpenInterpreter.java:69)
> 	at org.apache.zeppelin.interpreter.LazyOpenInterpreter.interpret(LazyOpenInterpreter.java:93)
> 	at org.apache.zeppelin.interpreter.remote.RemoteInterpreterServer$InterpretJob.jobRun(RemoteInterpreterServer.java:341)
> 	at org.apache.zeppelin.scheduler.Job.run(Job.java:176)
> 	at org.apache.zeppelin.scheduler.FIFOScheduler$1.run(FIFOScheduler.java:139)
> 	at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:471)
> 	at java.util.concurrent.FutureTask.run(FutureTask.java:262)
> 	at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$201(ScheduledThreadPoolExecutor.java:178)
> 	at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:292)
> 	at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
> 	at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
> 	at java.lang.Thread.run(Thread.java:745)
> {code}
> The same spark wordcount example works fine directly using spark-shell. It fails only
via Zeppelin. 



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