[SPARK-19459] ORC tables cannot be read when they contain char/varchar columns

• Type: Bug
• Status: Resolved
• Priority: Major
• Resolution: Fixed
• Affects Version/s: 2.0.2, 2.1.0
• Fix Version/s: 2.1.1, 2.2.0
• Component/s: SQL
• Target Version/s: 2.0.3, 2.1.1, 2.2.0
• Assignee: Herman van Hövell
• Reporter: Herman van Hövell
• Created: 04/Feb/17 10:45
• Updated: 11/Jan/19 00:37
• Resolved: 10/Feb/17 19:07

Description

Reading from an ORC table which contains char/varchar columns can fail if the table has been created using Spark. This is caused by the fact that spark internally replaces char and varchar columns with a string column, this causes the ORC reader to use the wrong reader, and that eventually causes a ClassCastException.

Issue Links

• is duplicated by: SPARK-19430 Cannot read external tables with VARCHAR columns if they're backed by ORC files written by Hive 1.2.1
• is duplicated by: SPARK-20515 Issue with reading Hive ORC tables having char/varchar columns in Spark SQL
• is related to: SPARK-21997 Spark shows different results on char/varchar columns on Parquet
• is related to: SPARK-23774 `Cast` to CHAR/VARCHAR should truncate the values
• relates to: SPARK-20901 Feature parity for ORC with Parquet
• links to: [Github] Pull Request #16804 (hvanhovell)
• links to: [Github] Pull Request #17030 (hvanhovell)
• links to: [Github] Pull Request #17041 (hvanhovell)
• links to: [Github] Pull Request #19235 (dongjoon-hyun)
• links to: GitHub Pull Request #16804