[jira] [Commented] (SPARK-1719) spark.executor.extraLibraryPath isn't applied on yarn
[ https://issues.apache.org/jira/browse/SPARK-1719?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14163484#comment-14163484 ] Apache Spark commented on SPARK-1719: - User 'witgo' has created a pull request for this issue: https://github.com/apache/spark/pull/2711 > spark.executor.extraLibraryPath isn't applied on yarn > - > > Key: SPARK-1719 > URL: https://issues.apache.org/jira/browse/SPARK-1719 > Project: Spark > Issue Type: Sub-task > Components: YARN >Affects Versions: 1.0.0 >Reporter: Thomas Graves >Assignee: Guoqiang Li > Fix For: 1.2.0 > > > Looking through the code for spark on yarn I don't see that > spark.executor.extraLibraryPath is being properly applied when it launches > executors. It is using the spark.driver.libraryPath in the ClientBase. > Note I didn't actually test it so its possible I missed something. > I also think better to use LD_LIBRARY_PATH rather then -Djava.library.path. > once java.library.path is set, it doesn't search LD_LIBRARY_PATH. In Hadoop > we switched to use LD_LIBRARY_PATH instead of java.library.path. See > https://issues.apache.org/jira/browse/MAPREDUCE-4072. I'll split this into > separate jira. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-1719) spark.executor.extraLibraryPath isn't applied on yarn
[ https://issues.apache.org/jira/browse/SPARK-1719?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14137176#comment-14137176 ] Wilfred Spiegelenburg commented on SPARK-1719: -- oops, not sure how I missed that last file change :-( > spark.executor.extraLibraryPath isn't applied on yarn > - > > Key: SPARK-1719 > URL: https://issues.apache.org/jira/browse/SPARK-1719 > Project: Spark > Issue Type: Sub-task > Components: YARN >Affects Versions: 1.0.0 >Reporter: Thomas Graves >Assignee: Guoqiang Li > Fix For: 1.2.0 > > > Looking through the code for spark on yarn I don't see that > spark.executor.extraLibraryPath is being properly applied when it launches > executors. It is using the spark.driver.libraryPath in the ClientBase. > Note I didn't actually test it so its possible I missed something. > I also think better to use LD_LIBRARY_PATH rather then -Djava.library.path. > once java.library.path is set, it doesn't search LD_LIBRARY_PATH. In Hadoop > we switched to use LD_LIBRARY_PATH instead of java.library.path. See > https://issues.apache.org/jira/browse/MAPREDUCE-4072. I'll split this into > separate jira. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-1719) spark.executor.extraLibraryPath isn't applied on yarn
[
https://issues.apache.org/jira/browse/SPARK-1719?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14129740#comment-14129740
]
Guoqiang Li commented on SPARK-1719:
[~wilfreds]
The relevant code in
[ExecutorRunnableUtil.scala#L62|https://github.com/witgo/spark/blob/SPARK-1720/yarn/common/src/main/scala/org/apache/spark/deploy/yarn/ExecutorRunnableUtil.scala#L62]
{code}
sys.props.get("spark.executor.extraLibraryPath").foreach { p =>
val libraryPath = Seq(p, Utils.libraryPath$).mkString(File.pathSeparator)
javaOpts += s"-Djava.library.path=$libraryPath"
}
{code}
eg: In linux
spark-defaults.conf =>
{noformat}
spark.executor.extraLibraryPath /usr/local/hadoop/lib
{noformat}
ExecutorRunnableUtil generated command line =>
{noformat}
java -server ... -Djava.library.path=/usr/local/hadoop/lib:$LD_LIBRARY_PATH
... org.apache.spark.executor.CoarseGrainedExecutorBackend
{noformat}
> spark.executor.extraLibraryPath isn't applied on yarn
> -
>
> Key: SPARK-1719
> URL: https://issues.apache.org/jira/browse/SPARK-1719
> Project: Spark
> Issue Type: Sub-task
> Components: YARN
>Affects Versions: 1.0.0
>Reporter: Thomas Graves
>Assignee: Guoqiang Li
> Fix For: 1.1.0
>
>
> Looking through the code for spark on yarn I don't see that
> spark.executor.extraLibraryPath is being properly applied when it launches
> executors. It is using the spark.driver.libraryPath in the ClientBase.
> Note I didn't actually test it so its possible I missed something.
> I also think better to use LD_LIBRARY_PATH rather then -Djava.library.path.
> once java.library.path is set, it doesn't search LD_LIBRARY_PATH. In Hadoop
> we switched to use LD_LIBRARY_PATH instead of java.library.path. See
> https://issues.apache.org/jira/browse/MAPREDUCE-4072. I'll split this into
> separate jira.
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[jira] [Commented] (SPARK-1719) spark.executor.extraLibraryPath isn't applied on yarn
[ https://issues.apache.org/jira/browse/SPARK-1719?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14129644#comment-14129644 ] Wilfred Spiegelenburg commented on SPARK-1719: -- I looked through the pull request linked here and the pull request that closed the linked one and I can not see any reference to the spark.executor.extraLibraryPath. I went through the trunk and the only place I can see it is in the mesos code. Can you explain how the change in https://github.com/apache/spark/pull/1031 fixes the issue reported without referencing the setting at all? > spark.executor.extraLibraryPath isn't applied on yarn > - > > Key: SPARK-1719 > URL: https://issues.apache.org/jira/browse/SPARK-1719 > Project: Spark > Issue Type: Sub-task > Components: YARN >Affects Versions: 1.0.0 >Reporter: Thomas Graves >Assignee: Guoqiang Li > Fix For: 1.1.0 > > > Looking through the code for spark on yarn I don't see that > spark.executor.extraLibraryPath is being properly applied when it launches > executors. It is using the spark.driver.libraryPath in the ClientBase. > Note I didn't actually test it so its possible I missed something. > I also think better to use LD_LIBRARY_PATH rather then -Djava.library.path. > once java.library.path is set, it doesn't search LD_LIBRARY_PATH. In Hadoop > we switched to use LD_LIBRARY_PATH instead of java.library.path. See > https://issues.apache.org/jira/browse/MAPREDUCE-4072. I'll split this into > separate jira. -- This message was sent by Atlassian JIRA (v6.3.4#6332) - To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Commented] (SPARK-1719) spark.executor.extraLibraryPath isn't applied on yarn
[ https://issues.apache.org/jira/browse/SPARK-1719?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14074026#comment-14074026 ] Guoqiang Li commented on SPARK-1719: Seems to be related. > spark.executor.extraLibraryPath isn't applied on yarn > - > > Key: SPARK-1719 > URL: https://issues.apache.org/jira/browse/SPARK-1719 > Project: Spark > Issue Type: Sub-task > Components: YARN >Affects Versions: 1.0.0 >Reporter: Thomas Graves >Assignee: Guoqiang Li > Fix For: 1.1.0 > > > Looking through the code for spark on yarn I don't see that > spark.executor.extraLibraryPath is being properly applied when it launches > executors. It is using the spark.driver.libraryPath in the ClientBase. > Note I didn't actually test it so its possible I missed something. > I also think better to use LD_LIBRARY_PATH rather then -Djava.library.path. > once java.library.path is set, it doesn't search LD_LIBRARY_PATH. In Hadoop > we switched to use LD_LIBRARY_PATH instead of java.library.path. See > https://issues.apache.org/jira/browse/MAPREDUCE-4072. I'll split this into > separate jira. -- This message was sent by Atlassian JIRA (v6.2#6252)
[jira] [Commented] (SPARK-1719) spark.executor.extraLibraryPath isn't applied on yarn
[
https://issues.apache.org/jira/browse/SPARK-1719?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14074021#comment-14074021
]
Xuri Nagarin commented on SPARK-1719:
-
Is this related? When I run spark-shell with "--master yarn
--driver-library-path /opt/cloudera/parcels/GPLEXTRAS/lib/hadoop/lib/native/",
then I can load a lzo file as:
val textFile = sc.textFile("/some/lzo/file.lzo")
textFile.first()
textFile.count()
org.apache.spark.SparkException: Job aborted due to stage failure: Task 3.0:0
failed 4 times, most recent failure: Exception failure in TID 7 on host
node1-9-ops.abc.net: java.lang.RuntimeException: native-lzo library not
available
com.hadoop.compression.lzo.LzopCodec.getDecompressorType(LzopCodec.java:96)
org.apache.hadoop.io.compress.CodecPool.getDecompressor(CodecPool.java:176)
org.apache.hadoop.mapred.LineRecordReader.(LineRecordReader.java:110)
org.apache.hadoop.mapred.TextInputFormat.getRecordReader(TextInputFormat.java:67)
org.apache.spark.rdd.HadoopRDD$$anon$1.(HadoopRDD.scala:193)
org.apache.spark.rdd.HadoopRDD.compute(HadoopRDD.scala:184)
org.apache.spark.rdd.HadoopRDD.compute(HadoopRDD.scala:93)
org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
org.apache.spark.rdd.MappedRDD.compute(MappedRDD.scala:31)
org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:111)
org.apache.spark.scheduler.Task.run(Task.scala:51)
org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:187)
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
java.lang.Thread.run(Thread.java:745)
Driver stacktrace:
at
org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1033)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1017)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1015)
at
scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at
org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1015)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:633)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:633)
at scala.Option.foreach(Option.scala:236)
at
org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:633)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessActor$$anonfun$receive$2.applyOrElse(DAGScheduler.scala:1207)
at akka.actor.ActorCell.receiveMessage(ActorCell.scala:498)
at akka.actor.ActorCell.invoke(ActorCell.scala:456)
at akka.dispatch.Mailbox.processMailbox(Mailbox.scala:237)
at akka.dispatch.Mailbox.run(Mailbox.scala:219)
at
akka.dispatch.ForkJoinExecutorConfigurator$AkkaForkJoinTask.exec(AbstractDispatcher.scala:386)
at scala.concurrent.forkjoin.ForkJoinTask.doExec(ForkJoinTask.java:260)
at
scala.concurrent.forkjoin.ForkJoinPool$WorkQueue.runTask(ForkJoinPool.java:1339)
at
scala.concurrent.forkjoin.ForkJoinPool.runWorker(ForkJoinPool.java:1979)
at
scala.concurrent.forkjoin.ForkJoinWorkerThread.run(ForkJoinWorkerThread.java:107)
> spark.executor.extraLibraryPath isn't applied on yarn
> -
>
> Key: SPARK-1719
> URL: https://issues.apache.org/jira/browse/SPARK-1719
> Project: Spark
> Issue Type: Sub-task
> Components: YARN
>Affects Versions: 1.0.0
>Reporter: Thomas Graves
>Assignee: Guoqiang Li
> Fix For: 1.1.0
>
>
> Looking through the code for spark on yarn I don't see that
> spark.executor.extraLibraryPath is being properly applied when it launches
> executors. It is using the spark.driver.libraryPath in the ClientBase.
> Note I didn't actually test it so its possible I missed something.
> I also think better to use LD_LIBRARY_PATH rather then -Djava.library.path.
> once java.library.path is set, it doesn't search LD_LIBRARY_PATH. In Hadoop
> we switched to use LD_LIBRARY_PATH instead of java.library.path. See
> https://issues.apache.org/jira/browse/MAPREDUCE-4072. I'll split this into
> separate jira.
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