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Posted to issues@spark.apache.org by "Gengliang Wang (JIRA)" <ji...@apache.org> on 2019/04/18 09:13:00 UTC

[jira] [Created] (SPARK-27504) File source V2: support refreshing metadata cache

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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