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https://issues.apache.org/jira/browse/SPARK-16334?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15363438#comment-15363438
 ] 

Vladimir Ivanov commented on SPARK-16334:
-----------------------------------------

Hi, we discovered problem with the same stacktrace in Spark 2.0. In our case 
it's thrown during {code}DataFrame.rdd{code} call. Moreover it somehow depends 
on volume of data, because it is not thrown when we change filter criteria 
accordingly. We used SparkSQL to write these parquet files and didn't 
explicitly specify {code}WriterVersion{code} option so I believe whatever 
version is set by default was used.

> [SQL] SQL query on parquet table java.lang.ArrayIndexOutOfBoundsException
> -------------------------------------------------------------------------
>
>                 Key: SPARK-16334
>                 URL: https://issues.apache.org/jira/browse/SPARK-16334
>             Project: Spark
>          Issue Type: Bug
>    Affects Versions: 2.0.0
>            Reporter: Egor Pahomov
>            Priority: Critical
>              Labels: sql
>
> Query:
> {code}
> select * from blabla where user_id = 415706251
> {code}
> Error:
> {code}
> 16/06/30 14:07:27 WARN scheduler.TaskSetManager: Lost task 11.0 in stage 0.0 
> (TID 3, hadoop6): java.lang.ArrayIndexOutOfBoundsException: 6934
>         at 
> org.apache.parquet.column.values.dictionary.PlainValuesDictionary$PlainBinaryDictionary.decodeToBinary(PlainValuesDictionary.java:119)
>         at 
> org.apache.spark.sql.execution.datasources.parquet.VectorizedColumnReader.decodeDictionaryIds(VectorizedColumnReader.java:273)
>         at 
> org.apache.spark.sql.execution.datasources.parquet.VectorizedColumnReader.readBatch(VectorizedColumnReader.java:170)
>         at 
> org.apache.spark.sql.execution.datasources.parquet.VectorizedParquetRecordReader.nextBatch(VectorizedParquetRecordReader.java:230)
>         at 
> org.apache.spark.sql.execution.datasources.parquet.VectorizedParquetRecordReader.nextKeyValue(VectorizedParquetRecordReader.java:137)
>         at 
> org.apache.spark.sql.execution.datasources.RecordReaderIterator.hasNext(RecordReaderIterator.scala:36)
>         at 
> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:91)
>         at 
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.scan_nextBatch$(Unknown
>  Source)
>         at 
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown
>  Source)
>         at 
> org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
>         at 
> org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:370)
>         at 
> org.apache.spark.sql.execution.SparkPlan$$anonfun$4.apply(SparkPlan.scala:246)
>         at 
> org.apache.spark.sql.execution.SparkPlan$$anonfun$4.apply(SparkPlan.scala:240)
>         at 
> org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:780)
>         at 
> org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$24.apply(RDD.scala:780)
>         at 
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
>         at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:319)
>         at org.apache.spark.rdd.RDD.iterator(RDD.scala:283)
>         at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
>         at org.apache.spark.scheduler.Task.run(Task.scala:85)
>         at 
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
>         at 
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
>         at 
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
>         at java.lang.Thread.run(Thread.java:745)
> {code}
> Work on 1.6.1



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