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Posted to issues@spark.apache.org by "Zhan Zhang (JIRA)" <ji...@apache.org> on 2015/09/01 00:02:46 UTC
[jira] [Commented] (SPARK-10304) Partition discovery does not throw
an exception if the dir structure is valid
[ https://issues.apache.org/jira/browse/SPARK-10304?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14724122#comment-14724122 ]
Zhan Zhang commented on SPARK-10304:
------------------------------------
[~lian cheng] forget about my question. From the code, it is not allowed. Here it happens because the directory has nonPartitionedTableX, and the validation check does not handle this case.
> Partition discovery does not throw an exception if the dir structure is valid
> -----------------------------------------------------------------------------
>
> Key: SPARK-10304
> URL: https://issues.apache.org/jira/browse/SPARK-10304
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Reporter: Yin Huai
> Assignee: Zhan Zhang
> Priority: Critical
>
> I have a dir structure like {{/path/table1/partition_column=1/}}. When I try to use {{load("/path/")}}, it works and I get a DF. When I query this DF, if it is stored as ORC, there will be the following NPE. But, if it is Parquet, we even can return rows. We should complain to users about the dir struct because {{table1}} does not meet our format.
> {code}
> org.apache.spark.SparkException: Job aborted due to stage failure: Task 26 in stage 57.0 failed 4 times, most recent failure: Lost task 26.3 in stage 57.0 (TID 3504, 10.0.195.227): java.lang.NullPointerException
> at org.apache.spark.sql.hive.HiveInspectors$class.unwrapperFor(HiveInspectors.scala:466)
> at org.apache.spark.sql.hive.orc.OrcTableScan.unwrapperFor(OrcRelation.scala:224)
> at org.apache.spark.sql.hive.orc.OrcTableScan$$anonfun$org$apache$spark$sql$hive$orc$OrcTableScan$$fillObject$1$$anonfun$9.apply(OrcRelation.scala:261)
> at org.apache.spark.sql.hive.orc.OrcTableScan$$anonfun$org$apache$spark$sql$hive$orc$OrcTableScan$$fillObject$1$$anonfun$9.apply(OrcRelation.scala:261)
> 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.sql.hive.orc.OrcTableScan$$anonfun$org$apache$spark$sql$hive$orc$OrcTableScan$$fillObject$1.apply(OrcRelation.scala:261)
> at org.apache.spark.sql.hive.orc.OrcTableScan$$anonfun$org$apache$spark$sql$hive$orc$OrcTableScan$$fillObject$1.apply(OrcRelation.scala:256)
> at scala.Option.map(Option.scala:145)
> at org.apache.spark.sql.hive.orc.OrcTableScan.org$apache$spark$sql$hive$orc$OrcTableScan$$fillObject(OrcRelation.scala:256)
> at org.apache.spark.sql.hive.orc.OrcTableScan$$anonfun$execute$3.apply(OrcRelation.scala:318)
> at org.apache.spark.sql.hive.orc.OrcTableScan$$anonfun$execute$3.apply(OrcRelation.scala:316)
> at org.apache.spark.rdd.HadoopRDD$HadoopMapPartitionsWithSplitRDD.compute(HadoopRDD.scala:380)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
> 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.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
> {code}
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