[jira] [Created] (SPARK-34805) PySpark loses metadata in DataFrame fields when selecting nested columns

["Mark Ressler (Jira)" <ji...@apache.org>]

Mark Ressler created SPARK-34805:
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             Summary: PySpark loses metadata in DataFrame fields when selecting nested columns
                 Key: SPARK-34805
                 URL: https://issues.apache.org/jira/browse/SPARK-34805
             Project: Spark
          Issue Type: Bug
          Components: PySpark
    Affects Versions: 3.1.1, 3.0.1
            Reporter: Mark Ressler


For a DataFrame schema with nested StructTypes, where metadata is set for fields in the schema, that metadata is lost when a DataFrame selects nested fields.  For example, suppose
{code:java}
df.schema.fields[0].dataType.fields[0].metadata
{code}
returns a non-empty dictionary, then
{code:java}
df.select('Field0.SubField0').schema.fields[0].metadata{code}
returns an empty dictionary, where "Field0" is the name of the first field in the DataFrame and "SubField0" is the name of the first nested field under "Field0".

 



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