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Posted to issues@spark.apache.org by "Apache Spark (Jira)" <ji...@apache.org> on 2020/12/19 04:19:00 UTC
[jira] [Assigned] (SPARK-33844) InsertIntoDir failed since query
column name contains ',' cause column type and column names size not equal
[ https://issues.apache.org/jira/browse/SPARK-33844?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Apache Spark reassigned SPARK-33844:
------------------------------------
Assignee: (was: Apache Spark)
> InsertIntoDir failed since query column name contains ',' cause column type and column names size not equal
> -----------------------------------------------------------------------------------------------------------
>
> Key: SPARK-33844
> URL: https://issues.apache.org/jira/browse/SPARK-33844
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 2.4.0
> Reporter: angerszhu
> Priority: Major
>
>
> After hive-2.3 we will set COLUMN_NAME_DELIMITER to special char when col name cntains ','since column list and column types in serde is splited by COLUMN_NAME_DELIMITER.
> In spark-2.4.0 + hive-1.2.1 we will failed when INSERT OVERWRITE DIR when query result schema columan name contains ','as
> {code:java}
> org.apache.hadoop.hive.serde2.SerDeException: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe: columns has 14 elements while columns.types has 11 elements! at org.apache.hadoop.hive.serde2.lazy.LazySerDeParameters.extractColumnInfo(LazySerDeParameters.java:146) at org.apache.hadoop.hive.serde2.lazy.LazySerDeParameters.<init>(LazySerDeParameters.java:85) at org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe.initialize(LazySimpleSerDe.java:125) at org.apache.spark.sql.hive.execution.HiveOutputWriter.<init>(HiveFileFormat.scala:119) at org.apache.spark.sql.hive.execution.HiveFileFormat$$anon$1.newInstance(HiveFileFormat.scala:103) at org.apache.spark.sql.execution.datasources.SingleDirectoryDataWriter.newOutputWriter(FileFormatDataWriter.scala:120) at org.apache.spark.sql.execution.datasources.SingleDirectoryDataWriter.<init>(FileFormatDataWriter.scala:108) at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:287) at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:219) at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:218) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) at org.apache.spark.scheduler.Task.run(Task.scala:121) at org.apache.spark.executor.Executor$TaskRunner$$anonfun$12.apply(Executor.scala:461) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:467) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at java.lang.Thread.run(Thread.java:748){code}
> Since this problem has been solved by [https://github.com/apache/hive/blob/6f4c35c9e904d226451c465effdc5bfd31d395a0/metastore/src/java/org/apache/hadoop/hive/metastore/MetaStoreUtils.java#L1044-L1075]
> But I think we can do this in Spark side to make all version work well.
>
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