[jira] [Resolved] (SPARK-24733) Dataframe saved to parquet can have different metadata then the resulting parquet file

["Hyukjin Kwon (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-24733?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Hyukjin Kwon resolved SPARK-24733.
----------------------------------
    Resolution: Incomplete

> Dataframe saved to parquet can have different metadata then the resulting parquet file
> --------------------------------------------------------------------------------------
>
>                 Key: SPARK-24733
>                 URL: https://issues.apache.org/jira/browse/SPARK-24733
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 2.3.0
>            Reporter: David Herskovics
>            Priority: Minor
>              Labels: bulk-closed
>
> See the repro using spark-shell below:
> Let's say that we have a dataframe called *df_with_metadata* which has column *name* with metadata.
>  
> {code:scala}
> scala> df_with_metadata.schema.json // Check that we have the metadata here.
> scala> df_with_metadata.createOrReplaceTempView("input")
> scala> val df2 = spark.sql("select case when true then name else null end as name from input")
> scala> df2.schema.json // We don't have the metadata anymore.
> scala> df2.write.parquet("no_metadata_expected")
> scala> val df3 = spark.read.parquet("no_metadata_expected")
> scala> df3.schema.json // And the metadata is there again so the no_metadata_expected does have metadata.
> {code}



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