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https://issues.apache.org/jira/browse/SPARK-27504?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Wenchen Fan resolved SPARK-27504.
---------------------------------
Resolution: Fixed
Fix Version/s: 3.0.0
Issue resolved by pull request 24401
[https://github.com/apache/spark/pull/24401]
> File source V2: support refreshing metadata cache
> -------------------------------------------------
>
> Key: SPARK-27504
> URL: https://issues.apache.org/jira/browse/SPARK-27504
> Project: Spark
> Issue Type: Task
> Components: SQL
> Affects Versions: 3.0.0
> Reporter: Gengliang Wang
> Assignee: Gengliang Wang
> Priority: Major
> Fix For: 3.0.0
>
>
> In file source V1, if some file is deleted manually, reading the
> DataFrame/Table will throws an exception with suggestion message "It is
> possible the underlying files have been updated. You can explicitly
> invalidate the cache in Spark by running 'REFRESH TABLE tableName' command in
> SQL or by recreating the Dataset/DataFrame involved.".
> After refreshing the table/DataFrame, the reads should return correct results.
> We should follow it in file source V2 as well.
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