Amer Sheikh created ZEPPELIN-3601:
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Summary: Zeppelin 0.8 error whilst trying to read a csv file.
Key: ZEPPELIN-3601
URL: https://issues.apache.org/jira/browse/ZEPPELIN-3601
Project: Zeppelin
Issue Type: Bug
Components: zeppelin-interpreter
Affects Versions: 0.8.0
Environment: Windows
Reporter: Amer Sheikh
Whilst trying to do a simple csv read using
var df = sqlContext.read.format("com.databricks.spark.csv").option("header",
"true").option("inferSchema", "true").option("delimiter",
"|").load("C:\\VodafoneData\\Customer\\TEMP\\TOTAL_AMDOCS_POS_MOVIL.TXT")
I get the following error in Windows. This is using the packaged SPARK 2.2
binaries.
On Stack Overflow the same issue has been seen on Linux. I'm also unable to
set up my local SPARK 2.3.1 version on Zeppelin 0.8.
I tried setting the SPARK_HOME variable as my environment variable and that
didn't work at all.
So I tried setting it in zeppelin-env.cmd, but it was ignored. Why is Zeppelin
so complicated to set up ???
Job aborted due to stage failure: Task 0 in stage 0.0 failed 1 times, most
recent failure: Lost task 0.0 in stage 0.0 (TID 0, 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:
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