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[SPARK-27504][SQL] File source V2: support refreshing metadata cache
## What changes were proposed in this pull request? 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. ## How was this patch tested? Unit test Closes apache#24401 from gengliangwang/refreshFileTable. Authored-by: Gengliang Wang <[email protected]> Signed-off-by: Wenchen Fan <[email protected]>
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