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Posted to issues@spark.apache.org by "Apache Spark (Jira)" <ji...@apache.org> on 2021/08/26 04:00:11 UTC
[jira] [Commented] (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:comment-tabpanel&focusedCommentId=17404895#comment-17404895 ]
Apache Spark commented on SPARK-36594:
--------------------------------------
User 'c21' has created a pull request for this issue:
https://github.com/apache/spark/pull/33842
> 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
> Priority: Major
>
> 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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