[
https://issues.apache.org/jira/browse/OOZIE-2482?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15301134#comment-15301134
]
Satish Subhashrao Saley commented on OOZIE-2482:
------------------------------------------------
Hi [~rkanter] and [~gezapeti],
Setting {{SPARK_HOME}} approach is nice and saves us from passing zip files
through --py-files option.
But I am worried about [copying over the zip files again
|https://github.com/apache/spark/blob/master/yarn/src/main/scala/org/apache/spark/deploy/yarn/Client.scala#L323-L327]
by spark since they reside on local file system. Also we are copying them over
from lib/ to python/lib/.
If we mention those using --py-files option with hdfs paths to pyspark.zip and
py4j-0.9-src.zip then this copy could be avoided (i.e.if these files are part
of sharelib, we can pass in that path). And for local mode, we just use the
files which are available under local directory of launcher job.
I think its between -- simpler code with extra copying Vs some involved code to
avoid copying.
with SPARK_HOME in yarn-cluster
{code}
2016-05-25 15:44:22,873 INFO [uber-SubtaskRunner]
org.apache.spark.deploy.yarn.Client: Uploading resource
file:/private/tmp/hadoop-saley/nm-local-dir/usercache/saley/appcache/application_1464215511846_0003/container_1464215511846_0003_01_000001/python/lib/pyspark.zip
->
hdfs://localhost:8020/user/saley/.sparkStaging/application_1464215511846_0004/pyspark.zip
2016-05-25 15:44:22,880 INFO [uber-SubtaskRunner]
org.apache.spark.deploy.yarn.Client: Uploading resource
file:/private/tmp/hadoop-saley/nm-local-dir/usercache/saley/appcache/application_1464215511846_0003/container_1464215511846_0003_01_000001/python/lib/py4j-0.9-src.zip
->
hdfs://localhost:8020/user/saley/.sparkStaging/application_1464215511846_0004/py4j-0.9-src.zip
{code}
with PYSPARK_ARCHIVES_PATH in yarn-cluster mode. I have setup zip files inside
sharelib:
{code}
2016-05-25 23:35:43,440 INFO [uber-SubtaskRunner]
org.apache.spark.deploy.yarn.Client: Source and destination file systems are
the same. Not copying
hdfs:/tmp/sharelib_dir/spark_yarn/share/spark/python/lib/pyspark.zip
2016-05-25 23:35:43,460 INFO [uber-SubtaskRunner]
org.apache.spark.deploy.yarn.Client: Source and destination file systems are
the same. Not copying
hdfs:/tmp/sharelib_dir/spark_yarn/share/spark/python/lib/py4j-0.9-src.zip
{code}
> 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, OOZIE-2482-2.patch,
> OOZIE-2482-3.patch, OOZIE-2482-4.patch, OOZIE-2482-5.patch,
> OOZIE-2482-6.patch, OOZIE-2482-zip.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]
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