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.getThreadStatisti >>> cs()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$$anonfun$1.apply$ >>> mcJ$sp(SparkHadoopUtil.scala:149) >>> at org.apache.spark.deploy.SparkHadoopUtil.getFSBytesReadOnThre >>> adCallback(SparkHadoopUtil.scala:150) >>> at org.apache.spark.sql.execution.datasources.FileScanRDD$$ >>> anon$1.<init>(FileScanRDD.scala:78) >>> at org.apache.spark.sql.execution.datasources.FileScanRDD. >>> compute(FileScanRDD.scala:71) >>> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) >>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) >>> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsR >>> DD.scala:38) >>> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) >>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) >>> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsR >>> DD.scala:38) >>> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) >>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) >>> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87) >>> at org.apache.spark.scheduler.Task.run(Task.scala:108) >>> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:335) >>> at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPool >>> Executor.java:1149) >>> at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoo >>> lExecutor.java:624) >>> at java.lang.Thread.run(Thread.java:748) >>> Driver stacktrace: >>> at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$sch >>> eduler$DAGScheduler$$failJobAndIndependentStages(DAGSchedule >>> r.scala:1499) >>> at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$ >>> 1.apply(DAGScheduler.scala:1487) >>> at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$ >>> 1.apply(DAGScheduler.scala:1486) >>> at scala.collection.mutable.ResizableArray$class.foreach(Resiza >>> bleArray.scala:59) >>> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48) >>> at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGSchedu >>> ler.scala:1486) >>> at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskS >>> etFailed$1.apply(DAGScheduler.scala:814) >>> at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskS >>> etFailed$1.apply(DAGScheduler.scala:814) >>> at scala.Option.foreach(Option.scala:257) >>> at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed( >>> DAGScheduler.scala:814) >>> at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOn >>> Receive(DAGScheduler.scala:1714) >>> at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onRe >>> ceive(DAGScheduler.scala:1669) >>> at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onRe >>> ceive(DAGScheduler.scala:1658) >>> at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) >>> at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler. >>> scala:630) >>> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2022) >>> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2043) >>> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2062) >>> at org.apache.spark.sql.execution.SparkPlan.executeTake( >>> SparkPlan.scala:336) >>> at org.apache.spark.sql.execution.CollectLimitExec.executeColle >>> ct(limit.scala:38) >>> at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$c >>> ollectFromPlan(Dataset.scala:2853) >>> at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.s >>> cala:2153) >>> at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.s >>> cala:2153) >>> at org.apache.spark.sql.Dataset$$anonfun$55.apply(Dataset.scala:2837) >>> at org.apache.spark.sql.execution.SQLExecution$.withNewExecutio >>> nId(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.FileSyste >>> m$Statistics.getThreadStatistics()Lorg/apache/hadoop/fs/ >>> FileSystem$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$$anonfun$1.apply$ >>> mcJ$sp(SparkHadoopUtil.scala:149) >>> at org.apache.spark.deploy.SparkHadoopUtil.getFSBytesReadOnThre >>> adCallback(SparkHadoopUtil.scala:150) >>> at org.apache.spark.sql.execution.datasources.FileScanRDD$$ >>> anon$1.<init>(FileScanRDD.scala:78) >>> at org.apache.spark.sql.execution.datasources.FileScanRDD. >>> compute(FileScanRDD.scala:71) >>> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) >>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) >>> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsR >>> DD.scala:38) >>> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) >>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) >>> at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsR >>> DD.scala:38) >>> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) >>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) >>> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87) >>> at org.apache.spark.scheduler.Task.run(Task.scala:108) >>> at org.apache.spark.executor.Executor$TaskRunner.run(Executor. >>> scala:335) >>> ... 3 more >> >> >>
