I have the same issue... Il giorno mar 3 lug 2018 alle 23:18 Adamantios Corais < adamantios.cor...@gmail.com> ha scritto:
> Hi Jeff, I am using the embedded Spark. > > FYI, this is how I start the dockerized (yet old) version of Zeppelin that > works as expected. > > #!/bin/bash >> docker run --rm \ >> --name zepelin \ >> -p 127.0.0.1:9090:8080 \ >> -p 127.0.0.1:5050:4040 \ >> -v $(pwd):/zeppelin/notebook \ >> apache/zeppelin:0.7.3 > > > And this is how I start the binarized (yet stable) version of Zeppelin that > is supposed to work (but it doesn't). > > #!/bin/bash >> wget >> http://www-eu.apache.org/dist/zeppelin/zeppelin-0.8.0/zeppelin-0.8.0-bin-all.tgz >> tar zxvf zeppelin-0.8.0-bin-all.tgz >> cd ./zeppelin-0.8.0-bin-all/ >> bash ./bin/zeppelin.sh > > > Thanks. > > > > > *// **Adamantios Corais* > > On Tue, Jul 3, 2018 at 2:24 AM, Jeff Zhang <zjf...@gmail.com> wrote: > >> >> Do you use the embeded spark or specify SPARK_HOME ? If you set >> SPARK_HOME, which spark version and hadoop version do you use ? >> >> >> >> Adamantios Corais <adamantios.cor...@gmail.com>于2018年7月3日周二 上午12:32写道： >> >>> Hi, >>> >>> I have downloaded the latest binary package of Zeppelin (ver. 0.8.0), >>> extracted, and started as follows: `./bin/zeppelin.sh` >>> >>> Next, I tried a very simple example: >>> >>> `spark.read.parquet("./bin/userdata1.parquet").show()` >>> >>> Which unfortunately returns the following error. Note that the same >>> example works fine with the official docker version of Zeppelin (ver. >>> 0.7.3). Any ideas? >>> >>> org.apache.spark.SparkException: Job aborted due to stage failure: Task >>>> 0 in stage 7.0 failed 1 times, most recent failure: Lost task 0.0 in stage >>>> 7.0 (TID 7, localhost, executor driver): java.lang.NoSuchMethodError: >>>> org.apache.hadoop.fs.FileSystem$Statistics.getThreadStatistics()Lorg/apache/hadoop/fs/FileSystem$Statistics$StatisticsData; >>>> at >>>> org.apache.spark.deploy.SparkHadoopUtil$$anonfun$1$$anonfun$apply$mcJ$sp$1.apply(SparkHadoopUtil.scala:149) >>>> at >>>> org.apache.spark.deploy.SparkHadoopUtil$$anonfun$1$$anonfun$apply$mcJ$sp$1.apply(SparkHadoopUtil.scala:149) >>>> at >>>> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234) >>>> at >>>> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234) >>>> at scala.collection.Iterator$class.foreach(Iterator.scala:893) >>>> at scala.collection.AbstractIterator.foreach(Iterator.scala:1336) >>>> at scala.collection.IterableLike$class.foreach(IterableLike.scala:72) >>>> at scala.collection.AbstractIterable.foreach(Iterable.scala:54) >>>> at scala.collection.TraversableLike$class.map(TraversableLike.scala:234) >>>> at scala.collection.AbstractTraversable.map(Traversable.scala:104) >>>> at >>>> org.apache.spark.deploy.SparkHadoopUtil$$anonfun$1.apply$mcJ$sp(SparkHadoopUtil.scala:149) >>>> at >>>> org.apache.spark.deploy.SparkHadoopUtil.getFSBytesReadOnThreadCallback(SparkHadoopUtil.scala:150) >>>> at >>>> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.<init>(FileScanRDD.scala:78) >>>> at >>>> org.apache.spark.sql.execution.datasources.FileScanRDD.compute(FileScanRDD.scala:71) >>>> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) >>>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) >>>> at >>>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) >>>> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) >>>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) >>>> at >>>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) >>>> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) >>>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) >>>> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87) >>>> at org.apache.spark.scheduler.Task.run(Task.scala:108) >>>> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:335) >>>> at >>>> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) >>>> at >>>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) >>>> at java.lang.Thread.run(Thread.java:748) >>>> Driver stacktrace: >>>> at org.apache.spark.scheduler.DAGScheduler.org >>>> $apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1499) >>>> at >>>> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1487) >>>> at >>>> org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1486) >>>> at >>>> scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) >>>> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48) >>>> at >>>> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1486) >>>> at >>>> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:814) >>>> at >>>> org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:814) >>>> at scala.Option.foreach(Option.scala:257) >>>> at >>>> org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:814) >>>> at >>>> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1714) >>>> at >>>> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1669) >>>> at >>>> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1658) >>>> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) >>>> at >>>> org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:630) >>>> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2022) >>>> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2043) >>>> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2062) >>>> at >>>> org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:336) >>>> at >>>> org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38) >>>> at org.apache.spark.sql.Dataset.org >>>> $apache$spark$sql$Dataset$$collectFromPlan(Dataset.scala:2853) >>>> at >>>> org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2153) >>>> at >>>> org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2153) >>>> at org.apache.spark.sql.Dataset$$anonfun$55.apply(Dataset.scala:2837) >>>> at >>>> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:65) >>>> at org.apache.spark.sql.Dataset.withAction(Dataset.scala:2836) >>>> at org.apache.spark.sql.Dataset.head(Dataset.scala:2153) >>>> at org.apache.spark.sql.Dataset.take(Dataset.scala:2366) >>>> at org.apache.spark.sql.Dataset.showString(Dataset.scala:245) >>>> at org.apache.spark.sql.Dataset.show(Dataset.scala:644) >>>> at org.apache.spark.sql.Dataset.show(Dataset.scala:603) >>>> at org.apache.spark.sql.Dataset.show(Dataset.scala:612) >>>> ... 52 elided >>>> Caused by: java.lang.NoSuchMethodError: >>>> org.apache.hadoop.fs.FileSystem$Statistics.getThreadStatistics()Lorg/apache/hadoop/fs/FileSystem$Statistics$StatisticsData; >>>> at >>>> org.apache.spark.deploy.SparkHadoopUtil$$anonfun$1$$anonfun$apply$mcJ$sp$1.apply(SparkHadoopUtil.scala:149) >>>> at >>>> org.apache.spark.deploy.SparkHadoopUtil$$anonfun$1$$anonfun$apply$mcJ$sp$1.apply(SparkHadoopUtil.scala:149) >>>> at >>>> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234) >>>> at >>>> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234) >>>> at scala.collection.Iterator$class.foreach(Iterator.scala:893) >>>> at scala.collection.AbstractIterator.foreach(Iterator.scala:1336) >>>> at scala.collection.IterableLike$class.foreach(IterableLike.scala:72) >>>> at scala.collection.AbstractIterable.foreach(Iterable.scala:54) >>>> at >>>> scala.collection.TraversableLike$class.map(TraversableLike.scala:234) >>>> at scala.collection.AbstractTraversable.map(Traversable.scala:104) >>>> at >>>> org.apache.spark.deploy.SparkHadoopUtil$$anonfun$1.apply$mcJ$sp(SparkHadoopUtil.scala:149) >>>> at >>>> org.apache.spark.deploy.SparkHadoopUtil.getFSBytesReadOnThreadCallback(SparkHadoopUtil.scala:150) >>>> at >>>> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.<init>(FileScanRDD.scala:78) >>>> at >>>> org.apache.spark.sql.execution.datasources.FileScanRDD.compute(FileScanRDD.scala:71) >>>> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) >>>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) >>>> at >>>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) >>>> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) >>>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) >>>> at >>>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) >>>> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) >>>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) >>>> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87) >>>> at org.apache.spark.scheduler.Task.run(Task.scala:108) >>>> at >>>> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:335) >>>> ... 3 more >>> >>> >>> >
