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Posted to issues@spark.apache.org by "Wenchen Fan (Jira)" <ji...@apache.org> on 2021/08/26 06:56:00 UTC
[jira] [Resolved] (SPARK-36594) ORC vectorized reader should
properly check maximal number of fields
[ https://issues.apache.org/jira/browse/SPARK-36594?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Wenchen Fan resolved SPARK-36594.
---------------------------------
Fix Version/s: 3.2.0
Resolution: Fixed
Issue resolved by pull request 33843
[https://github.com/apache/spark/pull/33843]
> ORC vectorized reader should properly check maximal number of fields
> --------------------------------------------------------------------
>
> Key: SPARK-36594
> URL: https://issues.apache.org/jira/browse/SPARK-36594
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 3.2.0, 3.3.0
> Reporter: Cheng Su
> Assignee: Cheng Su
> Priority: Major
> Fix For: 3.2.0
>
>
> Debugged internally and found a bug where we should disable vectorized reader now based on schema recursively. Currently we check `schema.length` to be no more than `wholeStageMaxNumFields` to enable vectorization. `schema.length` does not take nested columns sub-fields into condition (i.e. view nested column same as primitive column). This check will be wrong when enabling vectorization for nested columns. We should follow same check from `WholeStageCodegenExec` to check sub-fields recursively. This will not cause correctness issue but will cause performance issue where we may enable vectorization for nested columns by mistake when nested column has a lot of sub-fields.
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