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From "Apache Spark (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-19809) NullPointerException on zero-size ORC file
Date Wed, 13 Dec 2017 02:31:02 GMT

    [ https://issues.apache.org/jira/browse/SPARK-19809?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16288622#comment-16288622
] 

Apache Spark commented on SPARK-19809:
--------------------------------------

User 'dongjoon-hyun' has created a pull request for this issue:
https://github.com/apache/spark/pull/19960

> NullPointerException on zero-size ORC file
> ------------------------------------------
>
>                 Key: SPARK-19809
>                 URL: https://issues.apache.org/jira/browse/SPARK-19809
>             Project: Spark
>          Issue Type: Bug
>          Components: Input/Output
>    Affects Versions: 1.6.3, 2.0.2, 2.1.1, 2.2.1
>            Reporter: MichaƂ Dawid
>            Assignee: Dongjoon Hyun
>             Fix For: 2.3.0
>
>
> When reading from hive ORC table if there are some 0 byte files we get NullPointerException:
> {code}java.lang.NullPointerException
> 	at org.apache.hadoop.hive.ql.io.orc.OrcInputFormat$BISplitStrategy.getSplits(OrcInputFormat.java:560)
> 	at org.apache.hadoop.hive.ql.io.orc.OrcInputFormat.generateSplitsInfo(OrcInputFormat.java:1010)
> 	at org.apache.hadoop.hive.ql.io.orc.OrcInputFormat.getSplits(OrcInputFormat.java:1048)
> 	at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:199)
> 	at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:242)
> 	at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:240)
> 	at scala.Option.getOrElse(Option.scala:120)
> 	at org.apache.spark.rdd.RDD.partitions(RDD.scala:240)
> 	at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
> 	at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:242)
> 	at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:240)
> 	at scala.Option.getOrElse(Option.scala:120)
> 	at org.apache.spark.rdd.RDD.partitions(RDD.scala:240)
> 	at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
> 	at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:242)
> 	at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:240)
> 	at scala.Option.getOrElse(Option.scala:120)
> 	at org.apache.spark.rdd.RDD.partitions(RDD.scala:240)
> 	at org.apache.spark.rdd.UnionRDD$$anonfun$1.apply(UnionRDD.scala:66)
> 	at org.apache.spark.rdd.UnionRDD$$anonfun$1.apply(UnionRDD.scala:66)
> 	at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> 	at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
> 	at scala.collection.immutable.List.foreach(List.scala:318)
> 	at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
> 	at scala.collection.AbstractTraversable.map(Traversable.scala:105)
> 	at org.apache.spark.rdd.UnionRDD.getPartitions(UnionRDD.scala:66)
> 	at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:242)
> 	at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:240)
> 	at scala.Option.getOrElse(Option.scala:120)
> 	at org.apache.spark.rdd.RDD.partitions(RDD.scala:240)
> 	at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
> 	at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:242)
> 	at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:240)
> 	at scala.Option.getOrElse(Option.scala:120)
> 	at org.apache.spark.rdd.RDD.partitions(RDD.scala:240)
> 	at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:190)
> 	at org.apache.spark.sql.execution.Limit.executeCollect(basicOperators.scala:165)
> 	at org.apache.spark.sql.execution.SparkPlan.executeCollectPublic(SparkPlan.scala:174)
> 	at org.apache.spark.sql.DataFrame$$anonfun$org$apache$spark$sql$DataFrame$$execute$1$1.apply(DataFrame.scala:1499)
> 	at org.apache.spark.sql.DataFrame$$anonfun$org$apache$spark$sql$DataFrame$$execute$1$1.apply(DataFrame.scala:1499)
> 	at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:56)
> 	at org.apache.spark.sql.DataFrame.withNewExecutionId(DataFrame.scala:2086)
> 	at org.apache.spark.sql.DataFrame.org$apache$spark$sql$DataFrame$$execute$1(DataFrame.scala:1498)
> 	at org.apache.spark.sql.DataFrame.org$apache$spark$sql$DataFrame$$collect(DataFrame.scala:1505)
> 	at org.apache.spark.sql.DataFrame$$anonfun$head$1.apply(DataFrame.scala:1375)
> 	at org.apache.spark.sql.DataFrame$$anonfun$head$1.apply(DataFrame.scala:1374)
> 	at org.apache.spark.sql.DataFrame.withCallback(DataFrame.scala:2099)
> 	at org.apache.spark.sql.DataFrame.head(DataFrame.scala:1374)
> 	at org.apache.spark.sql.DataFrame.take(DataFrame.scala:1456)
> 	at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> 	at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> 	at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> 	at java.lang.reflect.Method.invoke(Method.java:497)
> 	at org.apache.zeppelin.spark.ZeppelinContext.showDF(ZeppelinContext.java:209)
> 	at org.apache.zeppelin.spark.SparkSqlInterpreter.interpret(SparkSqlInterpreter.java:129)
> 	at org.apache.zeppelin.interpreter.LazyOpenInterpreter.interpret(LazyOpenInterpreter.java:94)
> 	at org.apache.zeppelin.interpreter.remote.RemoteInterpreterServer$InterpretJob.jobRun(RemoteInterpreterServer.java:341)
> 	at org.apache.zeppelin.scheduler.Job.run(Job.java:176)
> 	at org.apache.zeppelin.scheduler.FIFOScheduler$1.run(FIFOScheduler.java:139)
> 	at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
> 	at java.util.concurrent.FutureTask.run(FutureTask.java:266)
> 	at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$201(ScheduledThreadPoolExecutor.java:180)
> 	at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:293)
> 	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){code}



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