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Posted to issues@spark.apache.org by "Hyukjin Kwon (JIRA)" <ji...@apache.org> on 2019/05/21 04:12:40 UTC

[jira] [Resolved] (SPARK-20158) crash in Spark sql insert in partitioned hive tables

     [ https://issues.apache.org/jira/browse/SPARK-20158?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Hyukjin Kwon resolved SPARK-20158.
----------------------------------
    Resolution: Incomplete

> crash in Spark sql insert in partitioned hive tables
> ----------------------------------------------------
>
>                 Key: SPARK-20158
>                 URL: https://issues.apache.org/jira/browse/SPARK-20158
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 2.0.0, 2.1.0
>         Environment: hive 1.2.1 on parquet file table
>            Reporter: Paride Casulli
>            Priority: Major
>              Labels: bulk-closed
>
> Hi, I have this exception while inserting data on a parquet partitioned table in hive from a temp view
> Job aborted due to stage failure: Task 3 in stage 177.0 failed 4 times, most recent failure: Lost task 3.3 in stage 177.0 (TID 3833, XXX.XXX.XXX.XXX, executor 1008): org.apache.spark.SparkException: Task failed while writing rows.
> 	at org.apache.spark.sql.hive.SparkHiveDynamicPartitionWriterContainer.writeToFile(hiveWriterContainers.scala:328)
> 	at org.apache.spark.sql.hive.execution.InsertIntoHiveTable$$anonfun$saveAsHiveFile$3.apply(InsertIntoHiveTable.scala:159)
> 	at org.apache.spark.sql.hive.execution.InsertIntoHiveTable$$anonfun$saveAsHiveFile$3.apply(InsertIntoHiveTable.scala:159)
> 	at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
> 	at org.apache.spark.scheduler.Task.run(Task.scala:99)
> 	at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:282)
> 	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.lang.ArrayIndexOutOfBoundsException



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