DataFrame.write.parquet() throws NPE

DataFrame.write.parquet() throws NPE - apache-spark

source DataFrame: a csv with spark-csv,which comes from maven
sqlctx.read.format("com.databricks.spark.csv")
.option("header", "true")
.option("inferSchema", "true")
.load(FileName)
After read it i tried DataFrame.printSchema() which shows good
And when doing DataFrame.write.parquet(path), it crashed with NPE throwed, messages are following:
16/02/01 15:43:59 ERROR Executor: Exception in task 0.0 in stage 4.0 (TID 59)
java.lang.NullPointerException
at java.lang.ProcessBuilder.start(ProcessBuilder.java:1012)
at org.apache.hadoop.util.Shell.runCommand(Shell.java:482)
at org.apache.hadoop.util.Shell.run(Shell.java:455)
at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:715)
at org.apache.hadoop.util.Shell.execCommand(Shell.java:808)
at org.apache.hadoop.util.Shell.execCommand(Shell.java:791)
at org.apache.hadoop.fs.RawLocalFileSystem.setPermission(RawLocalFileSystem.java:656)
at org.apache.hadoop.fs.FilterFileSystem.setPermission(FilterFileSystem.java:490)
at org.apache.hadoop.fs.ChecksumFileSystem.create(ChecksumFileSystem.java:462)
at org.apache.hadoop.fs.ChecksumFileSystem.create(ChecksumFileSystem.java:428)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:908)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:889)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:786)
at org.apache.parquet.hadoop.ParquetFileWriter.<init>(ParquetFileWriter.java:176)
at org.apache.parquet.hadoop.ParquetFileWriter.<init>(ParquetFileWriter.java:160)
at org.apache.parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:289)
at org.apache.parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:262)
at org.apache.spark.sql.execution.datasources.parquet.ParquetOutputWriter.<init>(ParquetRelation.scala:94)
at org.apache.spark.sql.execution.datasources.parquet.ParquetRelation$$anon$3.newInstance(ParquetRelation.scala:286)
at org.apache.spark.sql.execution.datasources.BaseWriterContainer.newOutputWriter(WriterContainer.scala:129)
at org.apache.spark.sql.execution.datasources.DefaultWriterContainer.writeRows(WriterContainer.scala:255)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation$$anonfun$run$1$$anonfun$apply$mcV$sp$3.apply(InsertIntoHadoopFsRelation.scala:150)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation$$anonfun$run$1$$anonfun$apply$mcV$sp$3.apply(InsertIntoHadoopFsRelation.scala:150)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
16/02/01 15:43:59 WARN TaskSetManager: Lost task 0.0 in stage 4.0 (TID 59, localhost): java.lang.NullPointerException
at java.lang.ProcessBuilder.start(ProcessBuilder.java:1012)
at org.apache.hadoop.util.Shell.runCommand(Shell.java:482)
at org.apache.hadoop.util.Shell.run(Shell.java:455)
at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:715)
at org.apache.hadoop.util.Shell.execCommand(Shell.java:808)
at org.apache.hadoop.util.Shell.execCommand(Shell.java:791)
at org.apache.hadoop.fs.RawLocalFileSystem.setPermission(RawLocalFileSystem.java:656)
at org.apache.hadoop.fs.FilterFileSystem.setPermission(FilterFileSystem.java:490)
at org.apache.hadoop.fs.ChecksumFileSystem.create(ChecksumFileSystem.java:462)
at org.apache.hadoop.fs.ChecksumFileSystem.create(ChecksumFileSystem.java:428)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:908)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:889)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:786)
at org.apache.parquet.hadoop.ParquetFileWriter.<init>(ParquetFileWriter.java:176)
at org.apache.parquet.hadoop.ParquetFileWriter.<init>(ParquetFileWriter.java:160)
at org.apache.parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:289)
at org.apache.parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:262)
at org.apache.spark.sql.execution.datasources.parquet.ParquetOutputWriter.<init>(ParquetRelation.scala:94)
at org.apache.spark.sql.execution.datasources.parquet.ParquetRelation$$anon$3.newInstance(ParquetRelation.scala:286)
at org.apache.spark.sql.execution.datasources.BaseWriterContainer.newOutputWriter(WriterContainer.scala:129)
at org.apache.spark.sql.execution.datasources.DefaultWriterContainer.writeRows(WriterContainer.scala:255)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation$$anonfun$run$1$$anonfun$apply$mcV$sp$3.apply(InsertIntoHadoopFsRelation.scala:150)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelation$$anonfun$run$1$$anonfun$apply$mcV$sp$3.apply(InsertIntoHadoopFsRelation.scala:150)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Environment:NPE only happens in windows, all codes runs fine in linux
P.S: DataFrame.write.save() shows the same NPE, is this a win spec problem?

You have to install winutils.exe in the hadoop installation mentioned in $HADOOP_HOME. You can obtain this installation from https://www.barik.net/archive/2015/01/19/172716/ which is a hadoop build with the winutils.exe in the bin folder. This resolves the NPE problem.

Related

KafkaConsumer is not safe for multi-threaded access while creating and dropping globalTempView in spark

I am running the below code and after reading couple of RDDs from Kafka I get this Kafka multithreding access error. Not sure what is causing this. Basically what code does is that it reads CDRs from kafka and tries to put that in a globaltempview. In short, all the RDDs / dataframes must be stored in global view. I am using Kafka 0.10 and spark 2.1.1
val schema_string = "subscriberNumber, originNodeType, originHostName, originOperatorID, originTimeStamp, currentServiceClass, voucherBasedRefill, transactionAmount, refillProfileID, voucherGroupID, externalData1, externalData2"
val schema_rdd = StructType(schema_string.split(",").map(fieldName => StructField(fieldName, StringType, true)) )
val init_df= sqlContext.createDataFrame(sc.emptyRDD[Row], schema_rdd)
println("initial count of initial RDD is " +init_df.count())
init_df.createGlobalTempView("AIRGLOBAL")
AirDRStream.foreachRDD(foreachFunc = rdd => {
System.out.println("--- New RDD with " + rdd.count() + " records");
if (rdd.count() == 0) {
println("--- No logs received in this time interval=================")
} else {
rdd.toDF().createOrReplaceTempView("AIR")
val FilteredDR = sqlContext.sql("select * from AIR ")
val globalview= sqlContext.sql("SELECT * FROM global_temp.AIRGLOBAL ")
println("RESULTS FROM GLOBAL VIEW before union"+ globalview.count() )
globalview.union(FilteredDR).createOrReplaceTempView("TempView")
sqlContext.catalog.dropGlobalTempView("AIRGLOBAL")
println("global view dropped" )
val tempview =sqlContext.sql("SELECT * FROM TempView ")
println("Results from tempView" + tempview.count() )
tempview.createGlobalTempView("AIRGLOBAL")
println("global view created after dropping" )
//val globalviewfinal= sqlContext.sql("SELECT count(*) FROM global_temp.AIRGLOBAL ")
//println("RESULTS FROM GLOBAL VIEW after union"+ globalviewfinal.count() )
}
})
streamingContext.start()
streamingContext.awaitTermination()
Below is full trace of errors. As you can see it runs fine for couple of RDDs and then throws error.
---creating Empty RDD
initial count of initial RDD is 0
--- New RDD with 0 records
--- No logs received in this time interval=================
--- New RDD with 1741 records
RESULTS FROM GLOBAL VIEW before union0
global view dropped
Results from tempView1741
global view created after dropping
RESULTS FROM GLOBAL VIEW after union1
--- New RDD with 4692 records
RESULTS FROM GLOBAL VIEW before union1741
global view dropped
Results from tempView6433
global view created after dropping
18/05/06 11:04:00 ERROR Executor: Exception in task 0.0 in stage 18.0 (TID 17)
java.util.ConcurrentModificationException: KafkaConsumer is not safe for multi-threaded access
at org.apache.kafka.clients.consumer.KafkaConsumer.acquire(KafkaConsumer.java:1431)
at org.apache.kafka.clients.consumer.KafkaConsumer.seek(KafkaConsumer.java:1132)
at org.apache.spark.streaming.kafka010.CachedKafkaConsumer.seek(CachedKafkaConsumer.scala:95)
at org.apache.spark.streaming.kafka010.CachedKafkaConsumer.get(CachedKafkaConsumer.scala:69)
at org.apache.spark.streaming.kafka010.KafkaRDD$KafkaRDDIterator.next(KafkaRDD.scala:228)
at org.apache.spark.streaming.kafka010.KafkaRDD$KafkaRDDIterator.next(KafkaRDD.scala:194)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:377)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.agg_doAggregateWithoutKey$(Unknown Source)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:377)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:126)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
at org.apache.spark.scheduler.Task.run(Task.scala:99)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:322)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
18/05/06 11:04:00 ERROR TaskSetManager: Task 0 in stage 18.0 failed 1 times; aborting job
18/05/06 11:04:00 ERROR JobScheduler: Error running job streaming job 1525593840000 ms.0
org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 18.0 failed 1 times, most recent failure: Lost task 0.0 in stage 18.0 (TID 17, localhost, executor driver): java.util.ConcurrentModificationException: KafkaConsumer is not safe for multi-threaded access
at org.apache.kafka.clients.consumer.KafkaConsumer.acquire(KafkaConsumer.java:1431)
at org.apache.kafka.clients.consumer.KafkaConsumer.seek(KafkaConsumer.java:1132)
at org.apache.spark.streaming.kafka010.CachedKafkaConsumer.seek(CachedKafkaConsumer.scala:95)
at org.apache.spark.streaming.kafka010.CachedKafkaConsumer.get(CachedKafkaConsumer.scala:69)
at org.apache.spark.streaming.kafka010.KafkaRDD$KafkaRDDIterator.next(KafkaRDD.scala:228)
at org.apache.spark.streaming.kafka010.KafkaRDD$KafkaRDDIterator.next(KafkaRDD.scala:194)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:377)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.agg_doAggregateWithoutKey$(Unknown Source)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:377)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:126)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
at org.apache.spark.scheduler.Task.run(Task.scala:99)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:322)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1435)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1423)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1422)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1422)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:802)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1650)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1605)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1594)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:628)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1925)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1938)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1951)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1965)
at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:936)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:362)
at org.apache.spark.rdd.RDD.collect(RDD.scala:935)
at org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:275)
at org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$execute$1$1.apply(Dataset.scala:2386)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57)
at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2788)
at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$execute$1(Dataset.scala:2385)
at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collect(Dataset.scala:2392)
at org.apache.spark.sql.Dataset$$anonfun$count$1.apply(Dataset.scala:2420)
at org.apache.spark.sql.Dataset$$anonfun$count$1.apply(Dataset.scala:2419)
at org.apache.spark.sql.Dataset.withCallback(Dataset.scala:2801)
at org.apache.spark.sql.Dataset.count(Dataset.scala:2419)
at com.asiacell.spark.KafkaAirDRsProcess$$anonfun$main$1.apply(KafkaAirDRsProcess.scala:113)
at com.asiacell.spark.KafkaAirDRsProcess$$anonfun$main$1.apply(KafkaAirDRsProcess.scala:81)
at org.apache.spark.streaming.dstream.DStream$$anonfun$foreachRDD$1$$anonfun$apply$mcV$sp$3.apply(DStream.scala:627)
at org.apache.spark.streaming.dstream.DStream$$anonfun$foreachRDD$1$$anonfun$apply$mcV$sp$3.apply(DStream.scala:627)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(ForEachDStream.scala:51)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply(ForEachDStream.scala:51)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply(ForEachDStream.scala:51)
at org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:415)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply$mcV$sp(ForEachDStream.scala:50)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:50)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:50)
at scala.util.Try$.apply(Try.scala:192)
at org.apache.spark.streaming.scheduler.Job.run(Job.scala:39)
at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply$mcV$sp(JobScheduler.scala:256)
at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply(JobScheduler.scala:256)
at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply(JobScheduler.scala:256)
at scala.util.DynamicVariable.withValue(DynamicVariable.scala:58)
at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler.run(JobScheduler.scala:255)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.util.ConcurrentModificationException: KafkaConsumer is not safe for multi-threaded access
at org.apache.kafka.clients.consumer.KafkaConsumer.acquire(KafkaConsumer.java:1431)
at org.apache.kafka.clients.consumer.KafkaConsumer.seek(KafkaConsumer.java:1132)
at org.apache.spark.streaming.kafka010.CachedKafkaConsumer.seek(CachedKafkaConsumer.scala:95)
at org.apache.spark.streaming.kafka010.CachedKafkaConsumer.get(CachedKafkaConsumer.scala:69)
at org.apache.spark.streaming.kafka010.KafkaRDD$KafkaRDDIterator.next(KafkaRDD.scala:228)
at org.apache.spark.streaming.kafka010.KafkaRDD$KafkaRDDIterator.next(KafkaRDD.scala:194)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:377)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.agg_doAggregateWithoutKey$(Unknown Source)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:377)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:126)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
at org.apache.spark.scheduler.Task.run(Task.scala:99)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:322)
... 3 more
Exception in thread "main" org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 18.0 failed 1 times, most recent failure: Lost task 0.0 in stage 18.0 (TID 17, localhost, executor driver): java.util.ConcurrentModificationException: KafkaConsumer is not safe for multi-threaded access
at org.apache.kafka.clients.consumer.KafkaConsumer.acquire(KafkaConsumer.java:1431)
at org.apache.kafka.clients.consumer.KafkaConsumer.seek(KafkaConsumer.java:1132)
at org.apache.spark.streaming.kafka010.CachedKafkaConsumer.seek(CachedKafkaConsumer.scala:95)
at org.apache.spark.streaming.kafka010.CachedKafkaConsumer.get(CachedKafkaConsumer.scala:69)
at org.apache.spark.streaming.kafka010.KafkaRDD$KafkaRDDIterator.next(KafkaRDD.scala:228)
at org.apache.spark.streaming.kafka010.KafkaRDD$KafkaRDDIterator.next(KafkaRDD.scala:194)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:377)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.agg_doAggregateWithoutKey$(Unknown Source)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:377)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:126)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
at org.apache.spark.scheduler.Task.run(Task.scala:99)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:322)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1435)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1423)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1422)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1422)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:802)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1650)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1605)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1594)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:628)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1925)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1938)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1951)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1965)
at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:936)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:362)
at org.apache.spark.rdd.RDD.collect(RDD.scala:935)
at org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:275)
at org.apache.spark.sql.Dataset$$anonfun$org$apache$spark$sql$Dataset$$execute$1$1.apply(Dataset.scala:2386)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57)
at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2788)
at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$execute$1(Dataset.scala:2385)
at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collect(Dataset.scala:2392)
at org.apache.spark.sql.Dataset$$anonfun$count$1.apply(Dataset.scala:2420)
at org.apache.spark.sql.Dataset$$anonfun$count$1.apply(Dataset.scala:2419)
at org.apache.spark.sql.Dataset.withCallback(Dataset.scala:2801)
at org.apache.spark.sql.Dataset.count(Dataset.scala:2419)
at com.asiacell.spark.KafkaAirDRsProcess$$anonfun$main$1.apply(KafkaAirDRsProcess.scala:113)
at com.asiacell.spark.KafkaAirDRsProcess$$anonfun$main$1.apply(KafkaAirDRsProcess.scala:81)
at org.apache.spark.streaming.dstream.DStream$$anonfun$foreachRDD$1$$anonfun$apply$mcV$sp$3.apply(DStream.scala:627)
at org.apache.spark.streaming.dstream.DStream$$anonfun$foreachRDD$1$$anonfun$apply$mcV$sp$3.apply(DStream.scala:627)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(ForEachDStream.scala:51)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply(ForEachDStream.scala:51)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply(ForEachDStream.scala:51)
at org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:415)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply$mcV$sp(ForEachDStream.scala:50)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:50)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:50)
at scala.util.Try$.apply(Try.scala:192)
at org.apache.spark.streaming.scheduler.Job.run(Job.scala:39)
at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply$mcV$sp(JobScheduler.scala:256)
at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply(JobScheduler.scala:256)
at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply(JobScheduler.scala:256)
at scala.util.DynamicVariable.withValue(DynamicVariable.scala:58)
at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler.run(JobScheduler.scala:255)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.util.ConcurrentModificationException: KafkaConsumer is not safe for multi-threaded access
at org.apache.kafka.clients.consumer.KafkaConsumer.acquire(KafkaConsumer.java:1431)
at org.apache.kafka.clients.consumer.KafkaConsumer.seek(KafkaConsumer.java:1132)
at org.apache.spark.streaming.kafka010.CachedKafkaConsumer.seek(CachedKafkaConsumer.scala:95)
at org.apache.spark.streaming.kafka010.CachedKafkaConsumer.get(CachedKafkaConsumer.scala:69)
at org.apache.spark.streaming.kafka010.KafkaRDD$KafkaRDDIterator.next(KafkaRDD.scala:228)
at org.apache.spark.streaming.kafka010.KafkaRDD$KafkaRDDIterator.next(KafkaRDD.scala:194)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:409)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:377)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.agg_doAggregateWithoutKey$(Unknown Source)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:377)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:126)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
at org.apache.spark.scheduler.Task.run(Task.scala:99)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:322)

KafkaConsumer has never intended to be thread-safe contrary to the producer.
Actually AFAIK most MQ consumers are not thread safe.
Anyway if you want to avoid the burden of writing Kafka Consumer specific code I have create a lib to avoid this :
https://www.github.com/jaubin/gojulmq4j-api
Hope it helps.

H2O sparkling water error from large Spark Dataframe to H2O Dataframe

When I try to convert from spark dataframe to H2O data frame I get the error below. This seems to have to do with the size of the dataframe because when I make it smaller the converter between spark and H2O works well.
Are there any configurations that need to be changed in order to convert large spark dataframes to H2O using sparkling water? In my configuration I am allowing max memory to the driver and executor so this is not a memory issue.
I am using R here the code is:
training<-as_h2o_frame(sc, final1, strict_version_check = FALSE)
Error:
Error: org.apache.spark.SparkException: Job aborted due to stage failure: Task 4 in stage 95.1 failed 4 times, most recent failure: Lost task 4.3 in stage 95.1 (TID 4050, 10.0.0.9): java.lang.ArrayIndexOutOfBoundsException: 65535
at water.DKV.get(DKV.java:202)
at water.DKV.get(DKV.java:175)
at water.Key.get(Key.java:83)
at water.fvec.Frame.createNewChunks(Frame.java:896)
at water.fvec.FrameUtils$class.createNewChunks(FrameUtils.scala:43)
at water.fvec.FrameUtils$.createNewChunks(FrameUtils.scala:70)
at org.apache.spark.h2o.backends.internal.InternalWriteConverterCtx.createChunks(InternalWriteConverterCtx.scala:29)
at org.apache.spark.h2o.converters.SparkDataFrameConverter$.org$apache$spark$h2o$converters$SparkDataFrameConverter$$perSQLPartition(SparkDataFrameConverter.scala:95)
at org.apache.spark.h2o.converters.SparkDataFrameConverter$$anonfun$toH2OFrame$1$$anonfun$apply$2.apply(SparkDataFrameConverter.scala:74)
at org.apache.spark.h2o.converters.SparkDataFrameConverter$$anonfun$toH2OFrame$1$$anonfun$apply$2.apply(SparkDataFrameConverter.scala:74)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
at org.apache.spark.scheduler.Task.run(Task.scala:86)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:748)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1454)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1442)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1441)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1441)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:811)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:811)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:811)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1667)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1622)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1611)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:632)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1873)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1886)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1906)
at org.apache.spark.h2o.converters.WriteConverterCtxUtils$.convert(WriteConverterCtxUtils.scala:83)
at org.apache.spark.h2o.converters.SparkDataFrameConverter$.toH2OFrame(SparkDataFrameConverter.scala:74)
at org.apache.spark.h2o.H2OContext.asH2OFrame(H2OContext.scala:145)
at org.apache.spark.h2o.H2OContext.asH2OFrame(H2OContext.scala:143)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at sparklyr.Invoke$.invoke(invoke.scala:102)
at sparklyr.StreamHandler$.handleMethodCall(stream.scala:89)
at sparklyr.StreamHandler$.read(stream.scala:54)
at sparklyr.BackendHandler.channelRead0(handler.scala:49)
at sparklyr.BackendHandler.channelRead0(handler.scala:14)
at io.netty.channel.SimpleChannelInboundHandler.channelRead(SimpleChannelInboundHandler.java:105)
at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:308)
at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:294)
at io.netty.handler.codec.MessageToMessageDecoder.channelRead(MessageToMessageDecoder.java:103)
at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:308)
at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:294)
at io.netty.handler.codec.ByteToMessageDecoder.channelRead(ByteToMessageDecoder.java:244)
at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:308)
at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:294)
at io.netty.channel.DefaultChannelPipeline.fireChannelRead(DefaultChannelPipeline.java:846)
at io.netty.channel.nio.AbstractNioByteChannel$NioByteUnsafe.read(AbstractNioByteChannel.java:131)
at io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:511)
at io.netty.channel.nio.NioEventLoop.processSelectedKeysOptimized(NioEventLoop.java:468)
at io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:382)
at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:354)
at io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:111)
at io.netty.util.concurrent.DefaultThreadFactory$DefaultRunnableDecorator.run(DefaultThreadFactory.java:137)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.lang.ArrayIndexOutOfBoundsException: 65535
at water.DKV.get(DKV.java:202)
at water.DKV.get(DKV.java:175)
at water.Key.get(Key.java:83)
at water.fvec.Frame.createNewChunks(Frame.java:896)
at water.fvec.FrameUtils$class.createNewChunks(FrameUtils.scala:43)
at water.fvec.FrameUtils$.createNewChunks(FrameUtils.scala:70)
at org.apache.spark.h2o.backends.internal.InternalWriteConverterCtx.createChunks(InternalWriteConverterCtx.scala:29)
at org.apache.spark.h2o.converters.SparkDataFrameConverter$.org$apache$spark$h2o$converters$SparkDataFrameConverter$$perSQLPartition(SparkDataFrameConverter.scala:95)
at org.apache.spark.h2o.converters.SparkDataFrameConverter$$anonfun$toH2OFrame$1$$anonfun$apply$2.apply(SparkDataFrameConverter.scala:74)
at org.apache.spark.h2o.converters.SparkDataFrameConverter$$anonfun$toH2OFrame$1$$anonfun$apply$2.apply(SparkDataFrameConverter.scala:74)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
at org.apache.spark.scheduler.Task.run(Task.scala:86)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
... 1 more

going to repost Jakub's comment so it is more easily found:
It seems like your H2O cloud is not properly initialized. Please check the readme here github.com/h2oai/rsparkling#spark-connection

Spark com.databricks.spark.csv is not able to load a snappy compressed file using node-snappy

I have some csv files on S3 that are compressed using the snappy compression algorithm (using node-snappy package). I like to process those files in spark using com.databricks.spark.csv but I am consistently getting an invalid file input error.
code:
file_df = sqlContext.read.format('com.databricks.spark.csv').options(header='true', inferschema='true', codec='snappy', mode='FAILFAST').load('s3://sample.csv.snappy')
error message:
16/09/24 21:57:25 WARN TaskSetManager: Lost task 0.0 in stage 0.0 (TID 0, ip-10-0-32-5.ec2.internal): java.lang.InternalError: Could not decompress data. Input is invalid.
at org.apache.hadoop.io.compress.snappy.SnappyDecompressor.decompressBytesDirect(Native Method)
at org.apache.hadoop.io.compress.snappy.SnappyDecompressor.decompress(SnappyDecompressor.java:239)
at org.apache.hadoop.io.compress.BlockDecompressorStream.decompress(BlockDecompressorStream.java:88)
at org.apache.hadoop.io.compress.DecompressorStream.read(DecompressorStream.java:85)
at java.io.InputStream.read(InputStream.java:101)
at org.apache.hadoop.util.LineReader.fillBuffer(LineReader.java:180)
at org.apache.hadoop.util.LineReader.readDefaultLine(LineReader.java:216)
at org.apache.hadoop.util.LineReader.readLine(LineReader.java:174)
at org.apache.hadoop.mapred.LineRecordReader.skipUtfByteOrderMark(LineRecordReader.java:208)
at org.apache.hadoop.mapred.LineRecordReader.next(LineRecordReader.java:246)
at org.apache.hadoop.mapred.LineRecordReader.next(LineRecordReader.java:48)
at org.apache.spark.rdd.HadoopRDD$$anon$1.getNext(HadoopRDD.scala:255)
at org.apache.spark.rdd.HadoopRDD$$anon$1.getNext(HadoopRDD.scala:209)
at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:39)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:461)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:389)
at scala.collection.Iterator$class.foreach(Iterator.scala:893)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1336)
at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48)
at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310)
at scala.collection.AbstractIterator.to(Iterator.scala:1336)
at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:302)
at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1336)
at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:289)
at scala.collection.AbstractIterator.toArray(Iterator.scala:1336)
at org.apache.spark.rdd.RDD$$anonfun$take$1$$anonfun$29.apply(RDD.scala:1305)
at org.apache.spark.rdd.RDD$$anonfun$take$1$$anonfun$29.apply(RDD.scala:1305)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1897)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1897)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
at org.apache.spark.scheduler.Task.run(Task.scala:85)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)

Looks like the same problem that is answered here - basically python snappy isn't compatible with Hadoop snappy.

How to deal with categoricalFeaturesInfo?

How do I deal with categoricalFeaturesInfo in RandomForest?
I created a list of variables like this:
alllist = listdouble + listint + listcategorielfeatures
But when I create LabeledPoint I lose this order.
How can I keep type of my variable like int for categorial features that I had StringIndexer before.
Error :
Py4JJavaError: An error occurred while calling o20271.trainRandomForestModel.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 29 in stage 1898.0 failed 4 times, most recent failure: Lost task 29.3 in stage 1898.0 (TID 748788, prbigdata1s013.bigplay.bigdata.intraxa): java.lang.IllegalArgumentException: DecisionTree given invalid data: Feature 517 is categorical with values in {0,...,16, but a data point gives it value 48940.0.
Bad data point: (1.0,(825,[0,1,2,4,8,17,19,21,27,31,32,50,52,56,57,75,77,78,79,80,83,89,96,97,98,99,101,103,104,105,108,114,121,122,123,124,126,128,129,130,132,133,134,135,136,138,139,140,141,142,156,157,160,161,163,164,165,166,167,181,182,185,186,187,190,191,202,203,204,205,206,207,208,209,210,213,220,221,222,223,224,225,226,227,228,229,230,231,232,233,234,235,238,245,246,247,248,249,250,251,260,262,263,264,265,266,269,270,271,272,273,275,276,277,278,279,280,281,282,283,284,293,294,295,298,308,309,312,328,350,368,371,379,384,385,388,389,390,391,392,393,394,395,396,397,398,402,403,404,405,406,407,408,409,410,411,412,416,417,418,419,420,421,422,423,424,425,426,428,429,430,431,432,433,434,435,436,437,438,439,440,447,448,449,450,451,452,453,454,455,456,457,460,464,465,466,470,473,477,481,482,483,484,485,486,487,488,489,490,491,492,493,496,497,498,499,500,501,502,503,504,505,506,507,508,511,512,513,514,515,516,517,518,519,520,521,522,523,526,527,528,529,530,531,532,533,534,535,536,537,538,541,542,550,554,556,562,564,565,566,567,568,569,570,571,572,573,574,575,576,644,646,647,648,649,651,654,655,656,657,663,664,666,667,668,669,670,671,672,673,675,677,678,679,680,681,682,683,684,685,687,688,689,690,691,692,693,694,695,696,697,698,699,700,704,709,710,711,712,713,714,715,716,717,718,729,734,735,737,738,739,740,741,742,743,744,745,747,748,749,750,751,752,753,754,755,756,758,760,761,764,765,766,767,768,769,774,776,777,779,780,781,782,783,784,786,787,788,789,790,791,793,794,796,797,798,799,800,801,802,803,804,805,808,809,810,811,814,816,817,824],[10.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,200.0,2000.0,2000.0,460.0,305.0,2000.0,2000.0,460.0,305.0,81.76,69.8,31.66,5.28,18.8,162.06,20.6,51.96,27.6,108.74,77.5,66.16,30.0,5.0,17.82,153.62,19.52,49.24,26.18,103.08,1.23456789E9,1.23456789E9,1.23456789E9,0.01,2.0,14.0,14.0,63.0,3.0,1.0,1.0,1.0,1.0,2.0,1.0,1.0,3.0,3.0,1.0,1.0,1.0,1.0,3.0,2.0,2.0,3.0,1.0,400.0,1.0,1.0,13.0,15.0,19.0,20.0,25.0,1.23456789E9,1.23456789E9,1.23456789E9,3.0,5.0,6.0,7.0,8.0,9.0,10.0,12.0,1.0,13.0,15.0,19.0,20.0,25.0,1.23456789E9,1.23456789E9,1.23456789E9,3.0,5.0,6.0,7.0,8.0,9.0,10.0,12.0,1210.0,8.0,121112.0,130912.0,28.0,1.0,17450.0,1.0,8.0,1.0,1.0,8508.0,8508.0,10550.0,10000.0,8889.0,8426.0,8889.0,8426.0,8889.0,8426.0,8889.0,8426.0,2.0,1.0,100.0,100.0,4.0,1.0,1.0,1.0,1.0,3.0,1.0,1.0,4.0,5.0,3.0,4.0,10.0,11.0,12.0,10.0,10.0,7.0,4.0,4.0,4.0,3.0,4.0,10.0,11.0,12.0,10.0,10.0,7.0,4.0,4.0,4.0,3.0,4.0,10.0,11.0,13.0,10.0,9.0,7.0,5.0,1.0,1.0,4.0,4.0,3.0,4.0,10.0,11.0,14.0,10.0,9.0,7.0,5.0,4.0,5.0,3.0,4.0,10.0,11.0,12.0,10.0,10.0,7.0,4.0,2.0,1.0,1.0,1.0,15.0,1.0,1.0,38335.0,8815.0,78408.0,44160.0,37187.0,1079.0,51630.0,11873.0,17102.0,11839.0,10126.0,22676.0,7000.0,39303.0,9037.0,81842.0,48036.0,37187.0,1116.0,51630.0,11873.0,17102.0,11839.0,10126.0,22676.0,7000.0,40971.0,9422.0,80086.0,44257.0,37000.0,1064.0,48940.0,11255.0,16212.0,11224.0,9598.0,18600.0,7948.0,40971.0,9422.0,80086.0,44257.0,37000.0,1064.0,48940.0,11255.0,16212.0,11224.0,9598.0,18600.0,7948.0,1.2345678901234567E9,1.2345678901234567E9,1381780.0,1183365.0,1.23456789E9,1.0,1400.0,1400.0,1400.0,1400.0,1400.0,800.0,1400.0,1400.0,1400.0,1400.0,1400.0,1400.0,1400.0,462191.0,462191.0,677785.0,694715.0,729570.0,8.0,2.0,16.0,6.0,1.0,4.0,1.0,1.23456789E9,1.0,1.23456789E9,1.23456789E9,1.23456789E9,1.23456789E9,1.23456789E9,68.0,3304.0,24.0,54.0,34.0,2654.0,84.0,2494.0,2504.0,2534.0,44.0,6908.9,766.7,176.3,1568.16,883.2,743.74,21.58,1032.6,237.46,342.04,236.78,202.52,453.52,140.0,1.0,3.0,1.0,3.0,3.0,5.0,6.0,3.0,2.0,1.0,1.0,13.0,16.0,1.23456789E9,1.0,743.74,1595.08,342.52,21.58,1910.2,413.76,453.52,1119.98,1799.3,6804.6,2.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,4621.91,1.0,2533.0,2940.49,2940.49,-1242.0,64.0,8832.67,1.0,2.0,1.0,101.0,1398.0,1581.0,1581.0,2281.0,1145.0,5.0,1.23456789E9,1070.0,4.0,50.0,1.2345678901234567E9,3000.0,1.23456789E9,5499.0,66240.0,66.0,1.23456789E9,1.23456789E9,1.0,1.0,1.23456789E9,3.0,1.23456789E9,1.23456789E9,1.23456789E9,3.0,3.0,1.0,6.0,1.23456789E9,1.23456789E9]))
at org.apache.spark.mllib.tree.impl.TreePoint$.findBin(TreePoint.scala:140)
at org.apache.spark.mllib.tree.impl.TreePoint$.org$apache$spark$mllib$tree$impl$TreePoint$$labeledPointToTreePoint(TreePoint.scala:84)
at org.apache.spark.mllib.tree.impl.TreePoint$$anonfun$convertToTreeRDD$2.apply(TreePoint.scala:66)
at org.apache.spark.mllib.tree.impl.TreePoint$$anonfun$convertToTreeRDD$2.apply(TreePoint.scala:65)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at org.apache.spark.storage.MemoryStore.unrollSafely(MemoryStore.scala:278)
at org.apache.spark.CacheManager.putInBlockManager(CacheManager.scala:171)
at org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:78)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:262)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:88)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1294)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1282)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1281)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1281)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:697)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:697)
at scala.Option.foreach(Option.scala:236)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:697)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1507)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1469)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1458)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:567)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1824)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1837)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1850)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1921)
at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:905)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:108)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:306)
at org.apache.spark.rdd.RDD.collect(RDD.scala:904)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$collectAsMap$1.apply(PairRDDFunctions.scala:686)
at org.apache.spark.rdd.PairRDDFunctions$$anonfun$collectAsMap$1.apply(PairRDDFunctions.scala:685)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:108)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:306)
at org.apache.spark.rdd.PairRDDFunctions.collectAsMap(PairRDDFunctions.scala:685)
at org.apache.spark.mllib.tree.DecisionTree$.findBestSplits(DecisionTree.scala:654)
at org.apache.spark.mllib.tree.RandomForest.run(RandomForest.scala:235)
at org.apache.spark.mllib.tree.RandomForest$.trainClassifier(RandomForest.scala:291)
at org.apache.spark.mllib.api.python.PythonMLLibAPI.trainRandomForestModel(PythonMLLibAPI.scala:742)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:379)
at py4j.Gateway.invoke(Gateway.java:259)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:207)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.IllegalArgumentException: DecisionTree given invalid data: Feature 517 is categorical with values in {0,...,16, but a data point gives it value 48940.0.

exception thrown on worker gets "Task exception could not be deserialized" ClassNotFoundException error

When an exception defined in my application is thrown on a worker, for example in a map:
sc.parallelize(0 until 10000).map(x =>
if (x == 7938)
throw new FatalException("oops")
else
x).sum()
I get a error of the form:
16/04/06 15:07:55 WARN ThrowableSerializationWrapper: Task exception could not be deserialized
java.lang.ClassNotFoundException: $line15.$read$$iwC$$iwC$FatalException
which is propagated to the driver as a SparkException: ReasonUnknown:
org.apache.spark.SparkException: Job aborted due to stage failure: Task 6 in stage 0.0 failed 1 times, most recent failure: Lost task 6.0 in stage 0.0 (TID 6, localhost): UnknownReason
This is a serious problem since I can't diagnose errors in the driver or report them meaningfully to the application user.
If I throw a SparkException, on the other hand, I get a nice:
org.apache.spark.SparkException: Job aborted due to stage failure: Task 6 in stage 1.0 failed 1 times, most recent failure: Lost task 6.0 in stage 1.0 (TID 14, localhost): org.apache.spark.SparkException: oops
I'm guess the class loader deserializing the propagated exception isn't seeing my application jar (or in this case, the class defined in spark-shell), but I haven't been able to find a workaround. Any ideas?
I'm seeing this in an application run through spark-submit, but here's a full example through spark-shell:
$ /usr/local/spark-1.5.2-bin-hadoop2.6/bin/spark-shell
log4j:WARN No appenders could be found for logger (org.apache.hadoop.metrics2.lib.MutableMetricsFactory).
log4j:WARN Please initialize the log4j system properly.
log4j:WARN See http://logging.apache.org/log4j/1.2/faq.html#noconfig for more info.
Using Spark's repl log4j profile: org/apache/spark/log4j-defaults-repl.properties
To adjust logging level use sc.setLogLevel("INFO")
Welcome to
____ __
/ __/__ ___ _____/ /__
_\ \/ _ \/ _ `/ __/ '_/
/___/ .__/\_,_/_/ /_/\_\ version 1.5.2
/_/
Using Scala version 2.10.4 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_45)
Type in expressions to have them evaluated.
Type :help for more information.
16/04/06 15:07:38 WARN MetricsSystem: Using default name DAGScheduler for source because spark.app.id is not set.
Spark context available as sc.
16/04/06 15:07:39 WARN Connection: BoneCP specified but not present in CLASSPATH (or one of dependencies)
16/04/06 15:07:39 WARN Connection: BoneCP specified but not present in CLASSPATH (or one of dependencies)
16/04/06 15:07:41 WARN ObjectStore: Version information not found in metastore. hive.metastore.schema.verification is not enabled so recording the schema version 1.2.0
16/04/06 15:07:41 WARN ObjectStore: Failed to get database default, returning NoSuchObjectException
16/04/06 15:07:42 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
16/04/06 15:07:42 WARN Connection: BoneCP specified but not present in CLASSPATH (or one of dependencies)
16/04/06 15:07:42 WARN Connection: BoneCP specified but not present in CLASSPATH (or one of dependencies)
SQL context available as sqlContext.
scala> class FatalException(msg: String) extends RuntimeException(msg)
defined class FatalException
scala> sc.parallelize(0 until 10000).map(x => if (x == 7938) throw new FatalException("oops") else x).sum()
[Stage 0:> (0 + 0) / 8]16/04/06 15:07:55 ERROR Executor: Exception in task 6.0 in stage 0.0 (TID 6)
$line15.$read$$iwC$$iwC$FatalException: oops
at $line19.$read$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$anonfun$1.apply$mcII$sp(<console>:23)
at $line19.$read$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$anonfun$1.apply(<console>:23)
at $line19.$read$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$anonfun$1.apply(<console>:23)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at scala.collection.Iterator$class.foreach(Iterator.scala:727)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
at scala.collection.TraversableOnce$class.foldLeft(TraversableOnce.scala:144)
at scala.collection.AbstractIterator.foldLeft(Iterator.scala:1157)
at scala.collection.TraversableOnce$class.fold(TraversableOnce.scala:199)
at scala.collection.AbstractIterator.fold(Iterator.scala:1157)
at org.apache.spark.rdd.RDD$$anonfun$fold$1$$anonfun$19.apply(RDD.scala:1061)
at org.apache.spark.rdd.RDD$$anonfun$fold$1$$anonfun$19.apply(RDD.scala:1061)
at org.apache.spark.SparkContext$$anonfun$36.apply(SparkContext.scala:1943)
at org.apache.spark.SparkContext$$anonfun$36.apply(SparkContext.scala:1943)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:88)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
16/04/06 15:07:55 WARN ThrowableSerializationWrapper: Task exception could not be deserialized
java.lang.ClassNotFoundException: $line15.$read$$iwC$$iwC$FatalException
at java.net.URLClassLoader.findClass(URLClassLoader.java:381)
at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:331)
at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
at java.lang.Class.forName0(Native Method)
at java.lang.Class.forName(Class.java:348)
at org.apache.spark.serializer.JavaDeserializationStream$$anon$1.resolveClass(JavaSerializer.scala:67)
at java.io.ObjectInputStream.readNonProxyDesc(ObjectInputStream.java:1613)
at java.io.ObjectInputStream.readClassDesc(ObjectInputStream.java:1518)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1774)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.readObject(ObjectInputStream.java:371)
at org.apache.spark.ThrowableSerializationWrapper.readObject(TaskEndReason.scala:167)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:497)
at java.io.ObjectStreamClass.invokeReadObject(ObjectStreamClass.java:1017)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1896)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1993)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1918)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.defaultReadFields(ObjectInputStream.java:1993)
at java.io.ObjectInputStream.readSerialData(ObjectInputStream.java:1918)
at java.io.ObjectInputStream.readOrdinaryObject(ObjectInputStream.java:1801)
at java.io.ObjectInputStream.readObject0(ObjectInputStream.java:1351)
at java.io.ObjectInputStream.readObject(ObjectInputStream.java:371)
at org.apache.spark.serializer.JavaDeserializationStream.readObject(JavaSerializer.scala:72)
at org.apache.spark.serializer.JavaSerializerInstance.deserialize(JavaSerializer.scala:98)
at org.apache.spark.scheduler.TaskResultGetter$$anon$3$$anonfun$run$2.apply$mcV$sp(TaskResultGetter.scala:108)
at org.apache.spark.scheduler.TaskResultGetter$$anon$3$$anonfun$run$2.apply(TaskResultGetter.scala:105)
at org.apache.spark.scheduler.TaskResultGetter$$anon$3$$anonfun$run$2.apply(TaskResultGetter.scala:105)
at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1699)
at org.apache.spark.scheduler.TaskResultGetter$$anon$3.run(TaskResultGetter.scala:105)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
16/04/06 15:07:55 ERROR TaskResultGetter: Could not deserialize TaskEndReason: ClassNotFound with classloader org.apache.spark.repl.SparkIMain$TranslatingClassLoader#4538856f
16/04/06 15:07:55 WARN TaskSetManager: Lost task 6.0 in stage 0.0 (TID 6, localhost): UnknownReason
16/04/06 15:07:55 ERROR TaskSetManager: Task 6 in stage 0.0 failed 1 times; aborting job
org.apache.spark.SparkException: Job aborted due to stage failure: Task 6 in stage 0.0 failed 1 times, most recent failure: Lost task 6.0 in stage 0.0 (TID 6, localhost): UnknownReason
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1283)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1271)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1270)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1270)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:697)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:697)
at scala.Option.foreach(Option.scala:236)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:697)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1496)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1458)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1447)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:567)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1824)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1944)
at org.apache.spark.rdd.RDD$$anonfun$fold$1.apply(RDD.scala:1063)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:108)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:310)
at org.apache.spark.rdd.RDD.fold(RDD.scala:1057)
at org.apache.spark.rdd.DoubleRDDFunctions$$anonfun$sum$1.apply$mcD$sp(DoubleRDDFunctions.scala:34)
at org.apache.spark.rdd.DoubleRDDFunctions$$anonfun$sum$1.apply(DoubleRDDFunctions.scala:34)
at org.apache.spark.rdd.DoubleRDDFunctions$$anonfun$sum$1.apply(DoubleRDDFunctions.scala:34)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:108)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:310)
at org.apache.spark.rdd.DoubleRDDFunctions.sum(DoubleRDDFunctions.scala:33)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:23)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:28)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:30)
at $iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:32)
at $iwC$$iwC$$iwC$$iwC.<init>(<console>:34)
at $iwC$$iwC$$iwC.<init>(<console>:36)
at $iwC$$iwC.<init>(<console>:38)
at $iwC.<init>(<console>:40)
at <init>(<console>:42)
at .<init>(<console>:46)
at .<clinit>(<console>)
at .<init>(<console>:7)
at .<clinit>(<console>)
at $print(<console>)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:497)
at org.apache.spark.repl.SparkIMain$ReadEvalPrint.call(SparkIMain.scala:1065)
at org.apache.spark.repl.SparkIMain$Request.loadAndRun(SparkIMain.scala:1340)
at org.apache.spark.repl.SparkIMain.loadAndRunReq$1(SparkIMain.scala:840)
at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:871)
at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:819)
at org.apache.spark.repl.SparkILoop.reallyInterpret$1(SparkILoop.scala:857)
at org.apache.spark.repl.SparkILoop.interpretStartingWith(SparkILoop.scala:902)
at org.apache.spark.repl.SparkILoop.command(SparkILoop.scala:814)
at org.apache.spark.repl.SparkILoop.processLine$1(SparkILoop.scala:657)
at org.apache.spark.repl.SparkILoop.innerLoop$1(SparkILoop.scala:665)
at org.apache.spark.repl.SparkILoop.org$apache$spark$repl$SparkILoop$$loop(SparkILoop.scala:670)
at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply$mcZ$sp(SparkILoop.scala:997)
at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:945)
at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:945)
at scala.tools.nsc.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:135)
at org.apache.spark.repl.SparkILoop.org$apache$spark$repl$SparkILoop$$process(SparkILoop.scala:945)
at org.apache.spark.repl.SparkILoop.process(SparkILoop.scala:1059)
at org.apache.spark.repl.Main$.main(Main.scala:31)
at org.apache.spark.repl.Main.main(Main.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:497)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:674)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:180)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:205)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:120)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
scala> import org.apache.spark._
import org.apache.spark._
scala> sc.parallelize(0 until 10000).map(x => if (x == 7938) throw new SparkException("oops") else x).sum()
16/04/06 15:08:05 ERROR Executor: Exception in task 6.0 in stage 1.0 (TID 14)
org.apache.spark.SparkException: oops
at $line23.$read$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$anonfun$1.apply$mcII$sp(<console>:25)
at $line23.$read$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$anonfun$1.apply(<console>:25)
at $line23.$read$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$anonfun$1.apply(<console>:25)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at scala.collection.Iterator$class.foreach(Iterator.scala:727)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
at scala.collection.TraversableOnce$class.foldLeft(TraversableOnce.scala:144)
at scala.collection.AbstractIterator.foldLeft(Iterator.scala:1157)
at scala.collection.TraversableOnce$class.fold(TraversableOnce.scala:199)
at scala.collection.AbstractIterator.fold(Iterator.scala:1157)
at org.apache.spark.rdd.RDD$$anonfun$fold$1$$anonfun$19.apply(RDD.scala:1061)
at org.apache.spark.rdd.RDD$$anonfun$fold$1$$anonfun$19.apply(RDD.scala:1061)
at org.apache.spark.SparkContext$$anonfun$36.apply(SparkContext.scala:1943)
at org.apache.spark.SparkContext$$anonfun$36.apply(SparkContext.scala:1943)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:88)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
16/04/06 15:08:05 WARN TaskSetManager: Lost task 6.0 in stage 1.0 (TID 14, localhost): org.apache.spark.SparkException: oops
at $line23.$read$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$anonfun$1.apply$mcII$sp(<console>:25)
at $line23.$read$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$anonfun$1.apply(<console>:25)
at $line23.$read$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$anonfun$1.apply(<console>:25)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at scala.collection.Iterator$class.foreach(Iterator.scala:727)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
at scala.collection.TraversableOnce$class.foldLeft(TraversableOnce.scala:144)
at scala.collection.AbstractIterator.foldLeft(Iterator.scala:1157)
at scala.collection.TraversableOnce$class.fold(TraversableOnce.scala:199)
at scala.collection.AbstractIterator.fold(Iterator.scala:1157)
at org.apache.spark.rdd.RDD$$anonfun$fold$1$$anonfun$19.apply(RDD.scala:1061)
at org.apache.spark.rdd.RDD$$anonfun$fold$1$$anonfun$19.apply(RDD.scala:1061)
at org.apache.spark.SparkContext$$anonfun$36.apply(SparkContext.scala:1943)
at org.apache.spark.SparkContext$$anonfun$36.apply(SparkContext.scala:1943)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:88)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
16/04/06 15:08:05 ERROR TaskSetManager: Task 6 in stage 1.0 failed 1 times; aborting job
org.apache.spark.SparkException: Job aborted due to stage failure: Task 6 in stage 1.0 failed 1 times, most recent failure: Lost task 6.0 in stage 1.0 (TID 14, localhost): org.apache.spark.SparkException: oops
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$anonfun$1.apply$mcII$sp(<console>:25)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$anonfun$1.apply(<console>:25)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$anonfun$1.apply(<console>:25)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at scala.collection.Iterator$class.foreach(Iterator.scala:727)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
at scala.collection.TraversableOnce$class.foldLeft(TraversableOnce.scala:144)
at scala.collection.AbstractIterator.foldLeft(Iterator.scala:1157)
at scala.collection.TraversableOnce$class.fold(TraversableOnce.scala:199)
at scala.collection.AbstractIterator.fold(Iterator.scala:1157)
at org.apache.spark.rdd.RDD$$anonfun$fold$1$$anonfun$19.apply(RDD.scala:1061)
at org.apache.spark.rdd.RDD$$anonfun$fold$1$$anonfun$19.apply(RDD.scala:1061)
at org.apache.spark.SparkContext$$anonfun$36.apply(SparkContext.scala:1943)
at org.apache.spark.SparkContext$$anonfun$36.apply(SparkContext.scala:1943)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:88)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1283)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1271)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1270)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1270)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:697)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:697)
at scala.Option.foreach(Option.scala:236)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:697)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1496)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1458)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1447)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:567)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1824)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1944)
at org.apache.spark.rdd.RDD$$anonfun$fold$1.apply(RDD.scala:1063)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:108)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:310)
at org.apache.spark.rdd.RDD.fold(RDD.scala:1057)
at org.apache.spark.rdd.DoubleRDDFunctions$$anonfun$sum$1.apply$mcD$sp(DoubleRDDFunctions.scala:34)
at org.apache.spark.rdd.DoubleRDDFunctions$$anonfun$sum$1.apply(DoubleRDDFunctions.scala:34)
at org.apache.spark.rdd.DoubleRDDFunctions$$anonfun$sum$1.apply(DoubleRDDFunctions.scala:34)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:147)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:108)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:310)
at org.apache.spark.rdd.DoubleRDDFunctions.sum(DoubleRDDFunctions.scala:33)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:25)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:30)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:32)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:34)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:36)
at $iwC$$iwC$$iwC$$iwC$$iwC.<init>(<console>:38)
at $iwC$$iwC$$iwC$$iwC.<init>(<console>:40)
at $iwC$$iwC$$iwC.<init>(<console>:42)
at $iwC$$iwC.<init>(<console>:44)
at $iwC.<init>(<console>:46)
at <init>(<console>:48)
at .<init>(<console>:52)
at .<clinit>(<console>)
at .<init>(<console>:7)
at .<clinit>(<console>)
at $print(<console>)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:497)
at org.apache.spark.repl.SparkIMain$ReadEvalPrint.call(SparkIMain.scala:1065)
at org.apache.spark.repl.SparkIMain$Request.loadAndRun(SparkIMain.scala:1340)
at org.apache.spark.repl.SparkIMain.loadAndRunReq$1(SparkIMain.scala:840)
at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:871)
at org.apache.spark.repl.SparkIMain.interpret(SparkIMain.scala:819)
at org.apache.spark.repl.SparkILoop.reallyInterpret$1(SparkILoop.scala:857)
at org.apache.spark.repl.SparkILoop.interpretStartingWith(SparkILoop.scala:902)
at org.apache.spark.repl.SparkILoop.command(SparkILoop.scala:814)
at org.apache.spark.repl.SparkILoop.processLine$1(SparkILoop.scala:657)
at org.apache.spark.repl.SparkILoop.innerLoop$1(SparkILoop.scala:665)
at org.apache.spark.repl.SparkILoop.org$apache$spark$repl$SparkILoop$$loop(SparkILoop.scala:670)
at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply$mcZ$sp(SparkILoop.scala:997)
at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:945)
at org.apache.spark.repl.SparkILoop$$anonfun$org$apache$spark$repl$SparkILoop$$process$1.apply(SparkILoop.scala:945)
at scala.tools.nsc.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:135)
at org.apache.spark.repl.SparkILoop.org$apache$spark$repl$SparkILoop$$process(SparkILoop.scala:945)
at org.apache.spark.repl.SparkILoop.process(SparkILoop.scala:1059)
at org.apache.spark.repl.Main$.main(Main.scala:31)
at org.apache.spark.repl.Main.main(Main.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:497)
at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:674)
at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:180)
at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:205)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:120)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: org.apache.spark.SparkException: oops
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$anonfun$1.apply$mcII$sp(<console>:25)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$anonfun$1.apply(<console>:25)
at $iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$iwC$$anonfun$1.apply(<console>:25)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
at scala.collection.Iterator$class.foreach(Iterator.scala:727)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
at scala.collection.TraversableOnce$class.foldLeft(TraversableOnce.scala:144)
at scala.collection.AbstractIterator.foldLeft(Iterator.scala:1157)
at scala.collection.TraversableOnce$class.fold(TraversableOnce.scala:199)
at scala.collection.AbstractIterator.fold(Iterator.scala:1157)
at org.apache.spark.rdd.RDD$$anonfun$fold$1$$anonfun$19.apply(RDD.scala:1061)
at org.apache.spark.rdd.RDD$$anonfun$fold$1$$anonfun$19.apply(RDD.scala:1061)
at org.apache.spark.SparkContext$$anonfun$36.apply(SparkContext.scala:1943)
at org.apache.spark.SparkContext$$anonfun$36.apply(SparkContext.scala:1943)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:88)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:214)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
scala>
Any ideas?
edit 1:
The relevant code in Spark is in TaskResultGetter.scala:
try {
if (serializedData != null && serializedData.limit() > 0) {
reason = serializer.get().deserialize[TaskEndReason](
serializedData, Utils.getSparkClassLoader)
}
} catch {
case cnd: ClassNotFoundException =>
// Log an error but keep going here -- the task failed, so not catastrophic
// if we can't deserialize the reason.
val loader = Utils.getContextOrSparkClassLoader
logError(
"Could not deserialize TaskEndReason: ClassNotFound with classloader " + loader)
case ex: Exception => {}
}
which calls spark.util.Utils.getSparkClassLoader:
def getSparkClassLoader: ClassLoader = getClass.getClassLoader
which is using the class loader which loaded the Spark jar.

This is a known issue: SPARK-11195. You need to upgrade your Spark to 1.6.0 or 1.6.1.

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