This might be due to the embedded spark version. I would recommend you to specify SPARK_HOME instead of using the embedded spark, the embedded spark is not for production.
Andrea Santurbano <sant...@gmail.com>于2018年7月5日周四 上午12:07写道： > 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 >>>> >>>> >>>> >>
