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