You are viewing a plain text version of this content. The canonical link for it is here.
Posted to dev@oozie.apache.org by "Robert Kanter (JIRA)" <ji...@apache.org> on 2016/05/16 23:00:16 UTC

[jira] [Comment Edited] (OOZIE-2482) Pyspark job fails with Oozie

    [ https://issues.apache.org/jira/browse/OOZIE-2482?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15285594#comment-15285594 ] 

Robert Kanter edited comment on OOZIE-2482 at 5/16/16 10:59 PM:
----------------------------------------------------------------

I suppose the other option is to make it so that the user has to manually add the two zip files into the Spark sharelib.  Given the complexities here, and how Spark keeps changing their packaging, we're probably best off just leaving that up to the user.  We can make it clear in the Oozie setup docs; and also if the user specifies a a python file but the zips are not there, the Spark Action(Executor?) could fail fast with a specific message about adding those zips.  We might even be able to have Oozie reject the workflow at submission time if the requirements are not met (though that might require Spark Action-related code outside of the SparkActionExecutor and SparkMain classes, so maybe we shouldn't do it at submission time).

[~satishsaley], [~gezapeti], what do you think?


was (Author: rkanter):
I suppose the other option is to make it so that the user has to manually add the two zip files into the Spark sharelib.  Given the complexities here, and how Spark keeps changing their packaging, we're probably best off just leaving that up to the user.  We can make it clear in the Oozie setup docs; and also if the user specifies a a python file but the zips are not there, the Spark Action(Executor?) could fail fast with a specific message about adding those zips.  We might even be able to have Oozie reject the workflow at submission time if the requirements are not met.

> Pyspark job fails with Oozie
> ----------------------------
>
>                 Key: OOZIE-2482
>                 URL: https://issues.apache.org/jira/browse/OOZIE-2482
>             Project: Oozie
>          Issue Type: Bug
>          Components: core, workflow
>    Affects Versions: 4.2.0
>         Environment: Hadoop 2.7.2, Spark 1.6.0 on Yarn, Oozie 4.2.0
> Cluster secured with Kerberos
>            Reporter: Alexandre Linte
>            Assignee: Satish Subhashrao Saley
>         Attachments: OOZIE-2482-1.patch, py4j-0.9-src.zip, pyspark.zip
>
>
> Hello,
> I'm trying to run pi.py example in a pyspark job with Oozie. Every try I made failed for the same reason: key not found: SPARK_HOME.
> Note: A scala job works well in the environment with Oozie.
> The logs on the executors are:
> {noformat}
> SLF4J: Class path contains multiple SLF4J bindings.
> SLF4J: Found binding in [jar:file:/mnt/hd4/hadoop/yarn/local/filecache/145/slf4j-log4j12-1.6.6.jar!/org/slf4j/impl/StaticLoggerBinder.class]
> SLF4J: Found binding in [jar:file:/mnt/hd2/hadoop/yarn/local/filecache/155/spark-assembly-1.6.0-hadoop2.7.1.jar!/org/slf4j/impl/StaticLoggerBinder.class]
> SLF4J: Found binding in [jar:file:/opt/application/Hadoop/hadoop-2.7.2/share/hadoop/common/lib/slf4j-log4j12-1.7.10.jar!/org/slf4j/impl/StaticLoggerBinder.class]
> SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
> SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]
> log4j:ERROR setFile(null,true) call failed.
> java.io.FileNotFoundException: /mnt/hd7/hadoop/yarn/log/application_1454673025841_13136/container_1454673025841_13136_01_000001 (Is a directory)
>         at java.io.FileOutputStream.open(Native Method)
>         at java.io.FileOutputStream.<init>(FileOutputStream.java:221)
>         at java.io.FileOutputStream.<init>(FileOutputStream.java:142)
>         at org.apache.log4j.FileAppender.setFile(FileAppender.java:294)
>         at org.apache.log4j.FileAppender.activateOptions(FileAppender.java:165)
>         at org.apache.hadoop.yarn.ContainerLogAppender.activateOptions(ContainerLogAppender.java:55)
>         at org.apache.log4j.config.PropertySetter.activate(PropertySetter.java:307)
>         at org.apache.log4j.config.PropertySetter.setProperties(PropertySetter.java:172)
>         at org.apache.log4j.config.PropertySetter.setProperties(PropertySetter.java:104)
>         at org.apache.log4j.PropertyConfigurator.parseAppender(PropertyConfigurator.java:809)
>         at org.apache.log4j.PropertyConfigurator.parseCategory(PropertyConfigurator.java:735)
>         at org.apache.log4j.PropertyConfigurator.configureRootCategory(PropertyConfigurator.java:615)
>         at org.apache.log4j.PropertyConfigurator.doConfigure(PropertyConfigurator.java:502)
>         at org.apache.log4j.PropertyConfigurator.doConfigure(PropertyConfigurator.java:547)
>         at org.apache.log4j.helpers.OptionConverter.selectAndConfigure(OptionConverter.java:483)
>         at org.apache.log4j.LogManager.<clinit>(LogManager.java:127)
>         at org.slf4j.impl.Log4jLoggerFactory.getLogger(Log4jLoggerFactory.java:64)
>         at org.slf4j.LoggerFactory.getLogger(LoggerFactory.java:285)
>         at org.apache.commons.logging.impl.SLF4JLogFactory.getInstance(SLF4JLogFactory.java:155)
>         at org.apache.commons.logging.impl.SLF4JLogFactory.getInstance(SLF4JLogFactory.java:132)
>         at org.apache.commons.logging.LogFactory.getLog(LogFactory.java:275)
>         at org.apache.hadoop.service.AbstractService.<clinit>(AbstractService.java:43)
> Using properties file: null
> Parsed arguments:
>   master                  yarn-master
>   deployMode              cluster
>   executorMemory          null
>   executorCores           null
>   totalExecutorCores      null
>   propertiesFile          null
>   driverMemory            null
>   driverCores             null
>   driverExtraClassPath    null
>   driverExtraLibraryPath  null
>   driverExtraJavaOptions  null
>   supervise               false
>   queue                   null
>   numExecutors            null
>   files                   null
>   pyFiles                 null
>   archives                null
>   mainClass               null
>   primaryResource         hdfs://hadoopsandbox/User/toto/WORK/Oozie/pyspark/lib/pi.py
>   name                    Pysparkpi example
>   childArgs               [100]
>   jars                    null
>   packages                null
>   packagesExclusions      null
>   repositories            null
>   verbose                 true
> Spark properties used, including those specified through
>  --conf and those from the properties file null:
>   spark.executorEnv.SPARK_HOME -> /opt/application/Spark/current
>   spark.executorEnv.PYTHONPATH -> /opt/application/Spark/current/python
>   spark.yarn.appMasterEnv.SPARK_HOME -> /opt/application/Spark/current
> Main class:
> org.apache.spark.deploy.yarn.Client
> Arguments:
> --name
> Pysparkpi example
> --primary-py-file
> hdfs://hadoopsandbox/User/toto/WORK/Oozie/pyspark/lib/pi.py
> --class
> org.apache.spark.deploy.PythonRunner
> --arg
> 100
> System properties:
> spark.executorEnv.SPARK_HOME -> /opt/application/Spark/current
> spark.executorEnv.PYTHONPATH -> /opt/application/Spark/current/python
> SPARK_SUBMIT -> true
> spark.app.name -> Pysparkpi example
> spark.submit.deployMode -> cluster
> spark.yarn.appMasterEnv.SPARK_HOME -> /opt/application/Spark/current
> spark.yarn.isPython -> true
> spark.master -> yarn-cluster
> Classpath elements:
> Failing Oozie Launcher, Main class [org.apache.oozie.action.hadoop.SparkMain], main() threw exception, key not found: SPARK_HOME
> java.util.NoSuchElementException: key not found: SPARK_HOME
>         at scala.collection.MapLike$class.default(MapLike.scala:228)
>         at scala.collection.AbstractMap.default(Map.scala:58)
>         at scala.collection.MapLike$class.apply(MapLike.scala:141)
>         at scala.collection.AbstractMap.apply(Map.scala:58)
>         at org.apache.spark.deploy.yarn.Client$$anonfun$findPySparkArchives$2.apply(Client.scala:1045)
>         at org.apache.spark.deploy.yarn.Client$$anonfun$findPySparkArchives$2.apply(Client.scala:1044)
>         at scala.Option.getOrElse(Option.scala:120)
>         at org.apache.spark.deploy.yarn.Client.findPySparkArchives(Client.scala:1044)
>         at org.apache.spark.deploy.yarn.Client.createContainerLaunchContext(Client.scala:717)
>         at org.apache.spark.deploy.yarn.Client.submitApplication(Client.scala:142)
>         at org.apache.spark.deploy.yarn.Client.run(Client.scala:1016)
>         at org.apache.spark.deploy.yarn.Client$.main(Client.scala:1076)
>         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:731)
>         at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:181)
>         at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:206)
>         at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:121)
>         at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
>         at org.apache.oozie.action.hadoop.SparkMain.runSpark(SparkMain.java:104)
>         at org.apache.oozie.action.hadoop.SparkMain.run(SparkMain.java:95)
>         at org.apache.oozie.action.hadoop.LauncherMain.run(LauncherMain.java:47)
>         at org.apache.oozie.action.hadoop.SparkMain.main(SparkMain.java:38)
>         at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
>         at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
>         at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
>         at java.lang.reflect.Method.invoke(Method.java:606)
>         at org.apache.oozie.action.hadoop.LauncherMapper.map(LauncherMapper.java:236)
>         at org.apache.hadoop.mapred.MapRunner.run(MapRunner.java:54)
>         at org.apache.hadoop.mapred.MapTask.runOldMapper(MapTask.java:453)
>         at org.apache.hadoop.mapred.MapTask.run(MapTask.java:343)
>         at org.apache.hadoop.mapred.LocalContainerLauncher$EventHandler.runSubtask(LocalContainerLauncher.java:380)
>         at org.apache.hadoop.mapred.LocalContainerLauncher$EventHandler.runTask(LocalContainerLauncher.java:301)
>         at org.apache.hadoop.mapred.LocalContainerLauncher$EventHandler.access$200(LocalContainerLauncher.java:187)
>         at org.apache.hadoop.mapred.LocalContainerLauncher$EventHandler$1.run(LocalContainerLauncher.java:230)
>         at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:471)
>         at java.util.concurrent.FutureTask.run(FutureTask.java:262)
>         at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
>         at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
>         at java.lang.Thread.run(Thread.java:745)
> log4j:WARN No appenders could be found for logger (org.apache.hadoop.mapreduce.v2.app.MRAppMaster).
> log4j:WARN Please initialize the log4j system properly.
> log4j:WARN See http://logging.apache.org/log4j/1.2/faq.html#noconfig for more info.
> {noformat}
> The workflow used for Oozie is the following:
> {noformat}
> <workflow-app xmlns='uri:oozie:workflow:0.5' name='PysparkPi-test'>
>         <start to='spark-node' />
>         <action name='spark-node'>
>                 <spark xmlns="uri:oozie:spark-action:0.1">
>                         <job-tracker>${jobTracker}</job-tracker>
>                         <name-node>${nameNode}</name-node>
>                         <master>${master}</master>
>                         <mode>${mode}</mode>
>                         <name>Pysparkpi example</name>
>                         <class></class>
>                         <jar>${nameNode}/User/toto/WORK/Oozie/pyspark/lib/pi.py</jar>
>                         <spark-opts>--conf spark.yarn.appMasterEnv.SPARK_HOME=/opt/application/Spark/current --conf spark.executorEnv.SPARK_HOME=/opt/application/Spark/current --conf spark.executorEnv.PYTHONPATH=/opt/application/Spark/current/python</spark-opts>
>                         <arg>100</arg>
>                 </spark>
>                 <ok to="end" />
>                 <error to="fail" />
>         </action>
>         <kill name="fail">
>                 <message>Workflow failed, error message[${wf:errorMessage(wf:lastErrorNode())}]</message>
>         </kill>
>         <end name='end' />
> </workflow-app>
> {noformat}
> I also created a JIRA for Spark: [https://issues.apache.org/jira/browse/SPARK-13679]



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)