[ 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()
<returns a string from the file>
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.<init>(LineRecordReader.java:110)
org.apache.hadoop.mapred.TextInputFormat.getRecordReader(TextInputFormat.java:67)
org.apache.spark.rdd.HadoopRDD$$anon$1.<init>(HadoopRDD.scala:193)
org.apache.spark.rdd.HadoopRDD.compute(HadoopRDD.scala:184)
org.apache.spark.rdd.HadoopRDD.compute(HadoopRDD.scala:93)
org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
org.apache.spark.rdd.MappedRDD.compute(MappedRDD.scala:31)
org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:262)
org.apache.spark.rdd.RDD.iterator(RDD.scala:229)
org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:111)
org.apache.spark.scheduler.Task.run(Task.scala:51)
org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:187)
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
java.lang.Thread.run(Thread.java:745)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$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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