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https://issues.apache.org/jira/browse/SPARK-16628?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Wenchen Fan resolved SPARK-16628.
---------------------------------
Resolution: Fixed
Fix Version/s: 2.3.0
2.2.1
Issue resolved by pull request 19470
[https://github.com/apache/spark/pull/19470]
> OrcConversions should not convert an ORC table represented by
> MetastoreRelation to HadoopFsRelation if metastore schema does not match
> schema stored in ORC files
> -----------------------------------------------------------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-16628
> URL: https://issues.apache.org/jira/browse/SPARK-16628
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Reporter: Yin Huai
> Fix For: 2.2.1, 2.3.0
>
>
> When {{spark.sql.hive.convertMetastoreOrc}} is enabled, we will convert a ORC
> table represented by a MetastoreRelation to HadoopFsRelation that uses
> Spark's OrcFileFormat internally. This conversion aims to make table scanning
> have a better performance since at runtime, the code path to scan
> HadoopFsRelation's performance is better. However, OrcFileFormat's
> implementation is based on the assumption that ORC files store their schema
> with correct column names. However, before Hive 2.0, an ORC table created by
> Hive does not store column name correctly in the ORC files (HIVE-4243). So,
> for this kind of ORC datasets, we cannot really convert the code path.
> Right now, if ORC tables are created by Hive 1.x or 0.x, enabling
> {{spark.sql.hive.convertMetastoreOrc}} will introduce a runtime exception for
> non-partitioned ORC tables and drop the metastore schema for partitioned ORC
> tables.
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