Gengliang Wang created SPARK-27504:
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Summary: 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
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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