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https://issues.apache.org/jira/browse/SPARK-33844?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Wenchen Fan resolved SPARK-33844.
---------------------------------
Fix Version/s: 3.2.0
Resolution: Fixed
Issue resolved by pull request 30850
[https://github.com/apache/spark/pull/30850]
> 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
> Assignee: angerszhu
> Priority: Major
> Fix For: 3.2.0
>
>
>
> 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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