This is due to hadoop version used in embedded spark is 2.3 which is too lower. I created https://issues.apache.org/jira/browse/ZEPPELIN-3586 for this issue. Suppose it will be fixed in o.8.1
Andrea Santurbano <sant...@gmail.com>于2018年7月5日周四 下午3:35写道： > I agree that is not for production, but if want to do a simple blog post > (and that's what I'm doing) I think it's a well suited solution. > Is it possible to fix this? > Thanks > Andrea > > Il giorno gio 5 lug 2018 alle ore 02:29 Jeff Zhang <zjf...@gmail.com> ha > scritto: > >> >> 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 >>>>>> >>>>>> >>>>>> >>>>
